Research ArticleDevelopment of a Correlation between the Resilient Modulus andCBR Value for Granular Blends Containing Natural Aggregatesand RAPRCA Materials

Muhammad Arshad 12

1Department of Geological Engineering University of Engineering amp Technology Lahore Pakistan2Department of Civil Engineering McMaster University Hamilton Canada

Correspondence should be addressed to Muhammad Arshad arshadmtcdie

Received 4 December 2018 Accepted 14 February 2019 Published 1 April 2019

Academic Editor Claudio Pettinari

Copyright copy 2019 Muhammad Arshad is is an open access article distributed under the Creative Commons AttributionLicense which permits unrestricted use distribution and reproduction in any medium provided the original work isproperly cited

Limited supplies of natural aggregates for highway construction in addition to increasing processing costs time and environmentalconcerns have led to the use of various reclaimedrecycled materials Reclaimed asphalt pavement (RAP) and recycled concreteaggregate (RCA) have prospective uses in substantial amounts in base and subbase layers of flexible pavement in order to overcomethe increasing issue of a shortage of natural aggregates is research presents the development of an empirical model for theestimation of resilient modulus value (MR) on the basis of CBR values using experimental results obtained for 52 remoulded granularsamples containing natural aggregates RCA and RAP samples Statistical analysis of the suggested model shows promising results interms of its strength and significance when t-test was applied Additionally experimental results also show thatMR value increases inconjunction with an increase in RAP contents while the trend for the CBR value is the opposite Statistical analysis of simulationresults using PerRoad and KenPave demonstrates that addition of RAP contents in the subbase layer of flexible pavements sig-nificantly improves its performance when considering resistance against rutting and fatigue However results of repeated load triaxialtests show that residual accumulative strain under a certain range of loading conditions increases substantially due to the addition ofRAP materials which may be disadvantageous to the serviceable life of the whole pavement structure

1 Introduction

e highway construction industry is responsible for almost30 of global air pollution and greenhouse gas emissionsand contributes roughly a quarter of the total fossil fuelconsumption across the world [1] Replacing natural orvirgin aggregates with high-quality recycled materials hasconsiderable potential to reduce the carbon footprint of theroadpavement construction industry e overall financialand environmental savings due to the replacement of naturalaggregates with recycled materials can rationalise the sta-bilisation cost in pavement applications Hence low-carbonand low-cost substitutes for conventional aggregates areactively being sought by researchers worldwide [2]Reclaimed asphalt pavement (RAP) [3 4] and recycledconcrete aggregate (RCA) [5ndash7] have been reported as the

most commonly recycled materials used in different layers offlexible pavements while use of recycled bricks [8] recycledglass [9ndash11] and fly ash [12] has also been documented bymany researchers and institutions

In general RAP materials are a blend of coarse and fineaggregates and bitumen obtained from aged or expiredasphalt pavementsroughout the world major use of RAPmaterial in a surfacing layer is commonly termed as hot mixasphalt (HMA) RAP has been used in the surface layer offlexible pavements in combination with natural aggregatesin different percentages extending up to 80 in some cases[13] Most of the researchers suggest a typical range of20ndash50 [12 14 15] is shows that RAP materials shouldalso be used in basesubbase layers of pavement in additionto using them to make blends with natural granular ma-terial in HMA applications RCA can be obtained from the

HindawiAdvances in Materials Science and EngineeringVolume 2019 Article ID 8238904 16 pageshttpsdoiorg10115520198238904

revamping or demolition of different types of structuresincluding commercial and residential buildings or other civilengineering structures [16ndash18] Many researchers havefound that the engineering properties of RCA are eithercomparable to or even better than typical natural aggregatesused in road construction [19 20] is implies that RCAproducts have potentially suitable applications in subbase orbase course It should also be noted that RCA can be used aspremium base course materials [21]

Conventional pavement design usually depends on theldquoCalifornia bearing ratiordquo (CBR) of the soilaggregate used inpavement structure while the resilient modulus value (MR) ofunbound aggregates is the fundamental input parameterrequired in the mechanistic empirical designanalysis ofpavement structures e most reliable and hence mostdesirable way to determine the resilient moduli is throughrepeated triaxial load testing However because of the diffi-culties encountered with the test procedure including timeconsumption and the economy of the project other labo-ratory tests such as CBR would also be considered if a reliablecorrelation could be established for the estimation of the MRvalue In the existing literature there are many studies tocorrelate resilient modulus values to those with CBR valuesdetermined for the natural granular materials Howeverstudies incorporating RAPRCA instead of natural materialsare very limited Furthermore a rational or coherentmechanism of the correlation development could probablynot be identified owing to the fact that the mechanics of bothof these tests are starkly different from each other

e specific objectives of this paper are as follows

(1) To develop a rational model for the prediction of aresilient modulus value of unbound granular ma-terials containing RAPRCA as a major componenton the basis of CBR values

(2) To evaluate the performance of blended samplesused in subbase layers through the computer soft-ware packages PerRoad and KenPave

(3) To evaluate the long-term performance of blendedsamples under a range of cyclic loading conditions

Furthermore a brief literature review on correlations forthe estimation of MR values with major emphasis on thedevelopment of a correlation between CBR value and re-silient modulus is presented in the next section of thisresearch paper

2 Existing Regression Models for thePrediction of MR Value

From the existing literature regression models for theprediction of MR value for granular material can be cate-gorically divided into four types

Class I In this category the models are based on singlestrength or stiffness parameter of soil such as

(i) CBR values [22ndash26](ii) R-value [27ndash31]

(iii) Unconfined compressive strength [32](iv) Undrained compressive strength [33]

Class II In this category the models are based on soilproperties and stress state for instance

(i) Bulk stress and index properties of the soil [34](ii) Unconfined compressive strength and index

properties of the soil [35](iii) R-value and index properties of the soil [36]

Regression models based on this methodology havemarkedly varying intricacy and acceptability in the researchcommunity [32 37ndash39]

Class III In this approach resilient modulus value for acertain soil is obtained by considering a certain type of stressinvariant or set of stress invariants for instance

(i) Bulk stress [27](ii) Confining pressure and deviator stress [40] and

bulk stress and atmospheric pressure [41](iii) Bulk stress atmospheric pressure and deviator

stress [42](iv) Bulk stress atmospheric pressure and octahedral

shear stress [43](v) Atmospheric pressure octahedral normal stress

and octahedral shear stress [44]

In this category the model parameters are given simplenumerical values

Class IV ere are also certain constitutive equations for theestimation of resilient modulus values derived from con-sidering soilrsquos physical properties incorporated in modelparameters in addition to stress invariant [45ndash48]

Since this research is focused on the establishment of acorrelation between CBR value and resilient modulus valueit is logical to further explain such attempts in a historicalperspective

A number of researchers including Porter [49 50]Hight and Stevens [51] and Fleming and Rogers [52]pointed out that the CBR tends to be a bearing value (moreof a parameter in terms of strength) rather than a supportvalue (in terms of recoverable behaviour) of materialsompson and Robnett [53] could not find a suitablecorrelation between CBR and MR Hight and Stevens [51]stated that the CBR does not correlate consistently witheither strength or stiffness and Sukumaran et al [54] opinedthat there is an apparent wide variation in theMR value thatcan be obtained using the CBR which depends on manyfactors On the other hand Lister and Powell [55] feltpositive that the CBR can be related within reasonablelimits to subgrade stiffness Hossain [56] believed that theCBR test is still one of the most widely used tests forevaluating the competency of pavement subgrade howeverthere are variations in the procedure followed by differentagencies (eg in terms of size of mould compaction

2 Advances in Materials Science and Engineering

techniques and efforts) and it was found that [56] corre-lations between resilient modulus values and all test results(including the CBR) were not statistically significant Garget al [57] opined that the CBR value can be converted to aresilient modulus a strong trend is apparent in the corre-lation but there is a lot of scatter A few of the existingcorrelations based on CBR values are given in Table 1

3 Material Characterisation

For this research four different types of RAP samples(designated as ldquoRAP(1)rdquo ldquoRAP(2)rdquo ldquoRAP(3)rdquo andldquoRAP(4)rdquo) three different types of natural aggregates(designated as ldquoArdquo ldquoFrdquo and ldquoWrdquo) and one RCA samplewere used Based on the gradation curves natural ag-gregate A is finer than other natural aggregate (F and W)while natural aggregate W is the most coarser amongthem Each of the natural aggregate samples as well as theRAP and RCA materials contained crushed limestone ofsubangular to angular shape Elongated and flat particlesin the samplesmaterials were not more than 6 as perASTM D 4791

A summary of material characterisations in terms ofdetailed gradation properties (D10D30D50 grain size di-ameter corresponding to 103050 percent finer by mass Cccoefficient of curvature Cu coefficient of uniformity)compaction characteristics effective shear strength param-eters and physical properties of recovered bitumen bindershas been presented in Table 2 Further detail on materialcharacterisation can be found in Arshad and Ahmed [60]and Arshad [61] Since focus of the testing campaign consistsof the CBR test and the resilient modulus test the same hasbeen briefly explained in the following subsections

Table 3 shows the matrix of the testing program in-cluding the resilient modulus tests the CBR tests and therepeated load tests

31 CBR Test In conventional pavement design the CBRvalue is an important parameter used to determine thethickness of various layers of the pavement structureUsually the higher the CBR value the better the perfor-mance of the pavement is with regard to both stiffness andstrength is implies that the CBR value can be used as aparameter to evaluate the suitability of a soil for use aspavement construction material For this study standard 3-point CBR tests were performed on the naturalRAPs andblended samples under unsoaked conditions to simulate themoisture content at which the resilient modulus tests wereperformed A schematic diagram of the CBR test is shown inFigure 1

e test equipment primarily consisted of a

(1) cylindrical mould having an inner diameter of150mm and a height of 175mm

(2) spacer disc of 148mm in diameter and 477mm inheight

(3) special surcharge weights

(4) metallic penetration piston of 50mm diameter andminimum of 100mm in length

(5) loading machine with a capacity of at least 50 kN andequipped with a movable head or base that travels ata uniform rate of 125mmmin

e CBR value is defined as the ratio of stress requiredfor the circular piston to penetrate at the rate of 125mmmin the soil mass in the cylinder to the standard stress that isrequired for the corresponding penetration of a standardmaterial ie like limestone found in California Furtherprocedural details on the CBR value calculations can befound in AASHTO T 193

32 Resilient Modulus Test Resilient modulus (MR) is de-fined as the ratio of cyclic axial stress to recoverable axialstrain (ΔσcΔεa) e cylindrical test specimen is compactedat a desired density and is subjected to cyclic axial stress at agiven confining pressure within a conventional triaxial cellResilient modulus tests for this research were conducted asper the guidelines specified in AASHTO T 307-99(2004) forwhich a haversine-shaped loading waveform is mandatory tosimulate traffic loading Each load cycle of this waveformessentially consists of 01 seconds load duration and a09 second rest period Figure 2 shows a typical repetitiveloadstress pulse along with the generated residual de-formation curve in the time domain e regular loadingsequence in AASHTO T 307-99 consists of 15 differentstages each one having 100 load cycles following the ex-ecution of the conditioning stage of 750 load cycles Each ofthe loading stages has a particular combination of confiningstress maximum axial stress and cyclic deviator stress asshown in Table 4 Further procedural details of the testincluding sample preparation and installation techniqueelectromechanics of the loading system (servo-controlledelectrohydraulic MTS testing machine) specification of theused load cells and LVDTs and particulars of the data ac-quisition system can be found in several works [60ndash62]

4 Test Results and Discussion

is section presents a discussion on trends obtained for theCBR tests and the resilient modulus tests performed on anumber of reconstituted granular samples as identified inTable 2

41 SampleResults of theCBRTest Sample results of the CBRtest in terms of compaction effort and the percentage of RAPcontent on the CBR values are presented in Figure 3 Fromthis figure it can be inferred that the CBR value decreases

Table 1 Existing models for the estimation of resilient modulusbased on CBR value

MR 1033CBR [23]MR 38(CBR)0711 [22]MR 18(CBR)064 [55]MR 21(CBR)065 [58]MR 176(CBR)064 [59]

Advances in Materials Science and Engineering 3

noticeably in correspondence to the increasing content inthe blended samples incorporating granular (A) and RAP(1)For instance the blend containing 25RAP(1) achieves only74 of the CBR value achieved by the aggregate (A) (naturalmaterial) at the same level of compaction eort ie 65blows Similarly the corresponding value for blends con-taining 50 RAP(1) 75 RAP(1) and 100 RAP(1) islimited to 5625 325 and 225 respectively Likewise

the trend can also be observed for the other two compactioneorts consisting of 10 and 30 blows

42 Eect of RAP Contents on Resilient Modulus (MR)Forty-eight blended samples were prepared by mixing thefour types of RAPmaterials with natural granular samplesAF W and RCA in proportion with RAP contents of 25

Table 2 Characterisation of the tested materials

MaterialCompaction characteristics (AASHTO T180)

Maximum dry density (kNm3) Optimum moisture content ()Natural aggregates 219ndash233 55ndash71RAPs 197ndash214 64ndash91RCA 207 75

Gradation characteristics (AASHTO T27-99)D10 (mm) D30 (mm) D50 (mm) Cu Cc Sand size (mm) (475ndash95) mm

Natural aggregate A 015 045 1 117 077 70 10Natural aggregate F 015 15 9 1000 100 35 10Natural aggregate W 06 5 15 333 208 25 12RAP(1) 03 12 275 133 120 64 22RAP(2) 03 12 275 133 120 60 30RAP(3) 15 5 65 50 222 27 50RAP(4) 03 12 2 92 175 82 10RCA 025 15 65 400 09 40 18

Flat and elongated particles (ASTM D 4791)Natural aggregatesRAPsRCA Limited to 6

Shear strength parameters under quick shear testNatural aggregatesRAPsRCA Friction angle Cohesion

36degndash43deg 20‒30 kPaPhysical properties of recovered bitumen binder

RAPs 60degC viscosity (poise)(ASTM D4402)

25degC penetration (dmm)(ASTM D5-06) Softening point (degC) (ASTM D36-76)

23500ndash46700 20ndash52 62ndash67

Table 3 Matrix of the testing program

Natural aggregateRCA RAP Minimum number ofresilient modulus tests

Minimum numberof CBR tests

Minimum number ofrepeated load triaxial tests

Natural aggregate A F W mdash 3 3 2RCA mdash 1 1 mdashBlends of natural aggregates with RAPs 4times 3lowast 3times 3times 4 36 3times 3times 4 36 7Blends of RCA with RAPs 4times 3lowast 3times 412 3times 412 mdashTotal 52 52 9lowastBlended samples were prepared by mixing 25 50 and 75 (by weight) of each RAP type with the natural aggregates and RCA

Transducer to measurepenetration

Annular weights

Sample

Standard mould

Applied load

Standard plunger

Figure 1 A schematic diagram of the CBR test

Stre

sss

trai

n le

vel

Time

Deformation vs time

Stress vs time

Figure 2 Typical shape of applied repeated load cycles and thegenerated deformation curve

4 Advances in Materials Science and Engineering

50 and 75 for each Figures 4(a)ndash4(d) show the eects ofthe addition of these RAPs on themeasuredMR values over arange of bulk stresses as specied in AASHTOT 307-99 (68)Variation ofMR values with bulk stress can be approximatedthrough trend lines based on a power function having thecoecient of determination (R2) in the range of 095ndash099From these trend lines it is evident that MR values increasenot only due to the increase in bulk stress but also incombination with the addition of RAP contents ie blendedsamples give higher MR values when compared to thoseobtained from the natural samples of granular A F W andRCA More specically for instance at a bulk stress ofsim673 kPa MR value for the 100 granular W is 320MPawhile the corresponding values for blended samples in-corporating 25 50 and 75 of RAP(1) are 340MPa360MPa and 390MPa respectively

A similar trend in MR values was observed at lowerlevels of bulk stress or more precisely over the entirerange of bulk stresses considered during the testing

campaign In some cases sim50 increase in MR values wasobserved for the blends containing 75 RAP contents Ingeneral for most of the blended samples containing 25and 50 RAP contents the corresponding increase in MRvalues was in the range of 5ndash15 and 10ndash20 respectivelyAn important point is that the addition of RAPs to RCAinduced the most signicant increase in the resilientmoduli when compared with the increase inMR when RAPwas added to granular samples Similar observations havealso been documented by many researchers including Kimand Labuz [12] MacGregor et al [63] Alam et al [64] andBennert and Maher [65]

5 Development of Correlation betweenResilient Modulus and CBR Values

51 Proposed Correlation and eoretical BackgroundFor this study an attempt has been made to correlate theMR values with the CBR values on the basis of a commonvalue of bulk stress identied during both types of testsyenis should be emphasize that CBR values tend to decreasewith addition of RAP contents while reverse is the situationin case of resilient modulus values Such trends are pri-marily due to the fact that loading for the resilient modulustest is dynamic in nature while in the case of the CBR test itis virtually static

Fundamentally axial stress is applied during the CBRtests through a plunger (σpa) in addition to an axial sur-charge weight (σsa) as shown in Figure 5 However lateralstress on the walls of the CBRmould can be estimated on thebasis of the lateral earth pressure coecient (Ka) as describedin classical soil mechanics such that

σpl Kaσpa

σsl Kaσsa

Ka 1minus sin(ϕ)

(1)

where ϕ is the eective angle of internal friction of the soilsample (blend) under consideration

Table 4 Loading sequence for the resilient modulus test as per AASHTO T 307 protocol

Seq No No of load applied Conning stress Max axial stress Cyclic axial stress Contact stress Total axial stress (kPa)σ3 (kPa) σmax (kPa) σcyclic (kPa) 01σmax (kPa)0 750 1034 1034 931 103 20681 100 207 207 186 21 4142 100 207 414 373 41 6213 100 207 621 559 62 8284 100 345 345 31 35 695 100 345 689 62 69 10346 100 345 1034 931 103 13797 100 689 689 62 69 13788 100 689 1379 1241 138 20689 100 689 2068 1861 207 275710 100 1034 689 62 69 172311 100 1034 1034 931 103 206812 100 1034 2068 1861 207 310213 100 1379 1034 931 103 241314 100 1379 1379 1241 138 275815 100 1379 2758 2482 276 4137

0

10

20

30

40

50

60

70

80

90

1950 2000 2050 2100 2150 2200 2250

Uns

oake

d CB

R (

)

Unit weight (kNm3)

A75 A + 25 RAP(1)50 A + 50 RAP(1)

25 A + 75 RAP(1)RAP(1)

Figure 3 Eect of RAP contents on CBR values

Advances in Materials Science and Engineering 5

It is interesting to note that the 3-point CBR test en-compasses a wide range of dry and bulk density in thesample while on the other hand each resilient modulus

test uses a unique value of the samplersquos dry and bulkdensity To estimate a unique value of the bulk stress duringthe CBR test which is analogous to the bulk stress valueidentied from resilient modulus test the following pro-cedure was adopted

(1) Determine the dry density of the resilient modulussample

(2) Estimate the CBR value corresponding to that drydensity value

(3) Determine the axial stress (σpa) value correspondingto the CBR value

(4) Calculate the bulk stress using the following relation

σbulk θ σ1 + σ2 + σ3 σpa + σsa( ) + 2Ka σpa + σsa( ) (2)

Using a unique value of bulk stress on the basis ofequation (2) the corresponding resilient modulus valuefrom the actual experimental data (MR test) was matchedand then a correlation between CBR value (point 2)and the resilient modulus value in terms of the power

y = 52x064

R2 = 099

y = 88x056

R2 = 098

y = 136x051

R2 = 095

y = 101x056

R2 = 098

0

50

100

150

200

250

300

350

400

450

0 200 400 600 800

MR (

MPa

)

Bulk stress (kPa)

100 A75 A + 25 RAP(2)

50 A + 50 RAP(2)25 A + 75 RAP(2)

(a)

100 F75 F + 25 RAP(3)

50 F + 50 RAP(3)25 F + 75 RAP(3)

y = 517x064

R2 = 099

y = 745x058

R2 = 099

y = 101x054

R2 = 097

y = 972x057

R2 = 096

0

50

100

150

200

250

300

350

400

450

0 200 400 600 800

MR (

MPa

)

Bulk stress (kPa)

(b)

y = 517x064

R2 = 099

y = 745x058

R2 = 099

y = 101x054

R2 = 097

y = 972x057

R2 = 096

0

50

100

150

200

250

300

350

400

450

0 200 400 600 800

MR (

MPa

)

Bulk stress (kPa)

100 W75 W + 25 RAP(1)

50 W + 50 RAP(1)25 W + 75 RAP(1)

(c)

y = 517x064

R2 = 099

y = 745x058

R2 = 099

y = 101x054

R2 = 097

y = 972x057

R2 = 096

0

50

100

150

200

250

300

350

400

450

0 100 200 300 400 500 600 700 800

MR (

MPa

)

Bulk stress (kPa)

100 RCA25 RCA + 75 RAP(4)

50 RCA + 50 RAP(4)75 RCA + 25 RAP(4)

(d)

Figure 4 Variation ofMR value with bulk stress and percentage of RAP contents for (a) naturalA (b) natural F (c) naturalW and (d) RCA

Plunger

Surchargeweight

Soil sample

Lateral stress due toloading of plunger (σpl)

Lateral stress due tosurcharge loading (σsl)

Figure 5 An assumed conguration of axial and lateral stressesduring CBR test

6 Advances in Materials Science and Engineering

function having a coefficient of determination sim081 canbe given as

MR 4937(CBR)059

(3)

Table 5 shows the experimental data and the estimatedvalues of MR based on the four steps explained above andequation (3)

Figure 6 shows the capabilities of the proposed regressionmodel on the basis of the distribution of the data pointswhich in fact involves the experimentally determined andestimated MR values along the unity line giving a 95prediction and confidence interval is figure illustrates thatthere is an almost equal distribution of the data points on bothsides of the unity line Additionally the entire set of the datapoints is confined within the 95 prediction interval which isdefined as the interval around the linear regression line suchthat 95 of the predicted values will fall in this intervalFurther details on the mathematical framework of the pre-diction and the confidence interval can be found in standardtextbooks dealing with statistics and probability analysis suchas those authored by Wonnacott and Ronald [66] Penny andRoberts [67] and Dybowski and Roberts [68]

52 Statistical Analysis of the Proposed Model A Pearsonrsquoscorrelation coefficient (r) as given by equation (4) is ameasure of the strength and direction of linear associationthat exists between two continuous variables More specif-ically for the drawn line of best fit for sample data points oftwo variables Pearsonrsquos correlation indicates how well thedata points fit this new modelline of best fit and its nu-merical value indicates how far away all these data points areto the line of best fit (ie how well the data points fit this newmodelline of best fit) [69 70]

r 1113936

ni1 ui minus ui( 1113857 ti minusti( 1113857

1113936ni1 ui minus ui( 1113857

2ti minus ti( 1113857

21113960 1113961

1113969 (4)

where ui and ti experimental and predicted values re-spectively for the ith output ui average of experimentaloutputs and n size of sample

e statistical value of r may range from minus1 for a perfectnegative linear relationship (inversely related) to +1 for aperfect positive linear relationship (directly related) In gen-eral from theoretical point of view the strength of the linearrelationship can be categorised as ldquovery strongrdquo ldquomoderatelystrongrdquo and ldquofairly strongrdquo for the corresponding numericalvalues of r in the range 08ndash10 06ndash08 and 03ndash05 [71] Itshould be emphasized that if r 00 it does not necessarilymean that the two variables have no relationship In order tolook into the real strength of the correlation usually a sta-tistical test of significance is performed as discussed in [72]For this study three different types of statistical tests wereapplied to assess the significance of the developed correlationpresented in equation (3) and Table 5

Case 1 t-Test for the assessment of the implication of co-efficient of correlation (r) at a specific degree of freedom andlevel of significance [73]

is provides the researcher with some idea of how largea correlation coefficient must be before it can be consideredas demonstrating that there really is a relationship betweentwo variables (in our case the (MR)measured and CBR values)It may be the situation that two variables are related bychance and a hypothesis test for r allows the researcher todecide whether the observed r could have emerged by chanceor not e null hypothesis is that there is no relationshipbetween the two variables at is if ρ is the true correlationcoefficient for the two variables and when all populationvalues have been observed then the null hypothesis can begiven as

H0 ρ 0 (5)

e alternative hypothesis could be written as

HA ρne 0 (6)

whereas the standardised t-test for the null hypothesis that ris equal to zero can be written as

t r

nminus 21minus r2

1113970

(7)

where n is the number of paired observations in the givensample

e null hypothesis is evaluated by comparing the t-statistic of equation (7) with t-critical (201) obtained from tdistribution having the nminus 2 degree of freedom

Case 2 Direct comparison of the coefficient of correlationvalue (09) with the r-critical value (027) obtained from astatistical table corresponding to a specific degree of freedomand level of significance [61 74]

Case 3 It often becomes mandatory to statistically evaluatethe difference between two datasets obtained by two dif-ferent sources As in our case one set of MR values wasobtained experimentally using the AASHTOT 307-99(2004)protocol and the other set of MR values was obtained usingthe proposed correlation A standard t-test was performed toevaluate the difference between the paired values of(MR)measured and (MR)estimated at a specific degree of freedomand level of significance [74 75]

Table 6 summarises the statistical analysis of the abovethree cases

6 Assessment of Pavement PerformanceContaining RAPContent in Its Subbase Layer

To examine the performance of the pavement containingnatural aggregates mixed with RAP and used as subbasematerials the following analyses were performed usingcomputer software simulation

(1) To access the likelihood that critical pavement re-sponses exceed predefined thresholds using com-puter program PerRoad [76]

Advances in Materials Science and Engineering 7

(2) To determine the stresses and strains at critical lo-cations in the pavement structure using computerprogram KenPave developed by the University ofKentucky [77]

PerRoad is a Monte Carlo-based simulation softwareused to develop probability-based analysis for flexiblepavement is software can easily demonstrate the influ-ence of the MR values of the pavement material on the

Table 5 A comparison of measured and estimated MR values along with CBR values

MaterialBlend Dry unit weightachieved (kNm3) CBR () Total axial

stress (kPa)

Estimatedbulk stress

in CBR test (kPa)

MR values measuredprojected (MPa)

MR valuesestimated(MPa)

100 A 211 65 9780 1663 550 584100 F 221 74 11130 1892 600 631100 W 224 85 12780 2173 670 685100 RCA 192 53 7980 1357 410 51875 A+ 25 RAP(1) 207 47 7080 1204 470 48250 A+ 50 RAP(1) 205 31 4680 796 300 37725 A+ 75 RAP(1) 202 22 3330 566 280 30875 A+ 25 RAP(2) 203 55 8280 1408 505 52950 A+ 50 RAP(2) 208 39 5880 1000 410 43225 A+ 75 RAP(2) 213 17 2580 439 260 26475 A+ 25 RAP(3) 201 51 7680 1306 490 50650 A+ 50 RAP(3) 205 30 4530 770 315 37025 A+ 75 RAP(3) 199 19 2880 490 310 28275 A+ 25 RAP(4) 197 55 8280 1408 505 52950 A+ 50 RAP(4) 198 43 6480 1102 402 45825 A+ 75 RAP(4) 192 27 4080 694 252 34775 F+ 25 RAP(1) 208 52 7830 1331 538 51250 F+ 50 RAP(1) 213 41 6180 1051 455 44525 F+ 75 RAP(1) 201 14 2130 362 356 23575 F+ 25 RAP(2) 205 59 8880 1510 525 55250 F+ 50 RAP(2) 199 48 7230 1229 407 48825 F+ 75 RAP(2) 197 31 4680 796 408 37775 F+ 25 RAP(3) 201 62 9330 1586 667 56850 F+ 50 RAP(3) 192 41 6180 1051 516 44525 F+ 75 RAP(3) 208 19 2880 490 343 28275 F+ 25 RAP(4) 213 43 6480 1102 515 45850 F+ 50 RAP(4) 201 32 4830 821 490 38425 F+ 75 RAP(4) 213 13 1980 337 278 22575 W+25 RAP(1) 208 51 7680 1306 510 50650 W+50 RAP(1) 205 44 6630 1127 500 46425 W+75 RAP(1) 199 16 2430 413 240 25575 W+25 RAP(2) 197 55 8280 1408 502 52950 W+50 RAP(2) 199 31 4680 796 438 37725 W+75 RAP(2) 213 12 1830 311 265 21575 W+25 RAP(3) 201 48 7230 1229 520 48850 W+50 RAP(3) 213 35 5280 898 447 40525 W+75 RAP(3) 207 21 3180 541 255 29975 W+25 RAP(4) 205 45 6780 1153 480 47050 W+50 RAP(4) 199 34 5130 872 473 39825 W+75 RAP(4) 192 9 1380 235 213 18175 RCA+ 25 RAP(1) 208 38 5730 974 486 42550 RCA+ 50 RAP(1) 213 23 3480 592 330 31625 RCA+ 75 RAP(1) 201 12 1830 311 187 21575 RCA+ 25 RAP(2) 213 38 5730 974 525 42550 RCA+ 50 RAP(2) 201 31 4680 796 356 37725 RCA+ 75 RAP(2) 214 14 2130 362 200 23575 RCA+ 25 RAP(3) 201 32 4830 821 447 38450 RCA+ 50 RAP(3) 205 15 2280 388 226 24525 RCA+ 75 RAP(3) 199 9 1380 235 148 18175 RCA+ 25 RAP(4) 192 39 5880 1000 473 43250 RCA+ 50 RAP(4) 201 13 1980 337 200 22525 RCA+ 75 RAP(4) 202 18 2730 464 161 273

8 Advances in Materials Science and Engineering

cumulative damage factor (CDF) It also demonstrates thelikelihood that critical pavement responses could exceedpredened thresholds which are the horizontal tensile strainof 70 microns at the bottom of the asphalt concrete (which islinked with fatigue cracking) and the vertical compressivestrain of 200 microns at the top of the subgrade (which isassociated with the structural rutting) [78]

61 Pavement Structure and Material CharacteristicsFigure 7 shows a typical cross section of copyexible pavementswhich consists of a hot mix asphalt layer supported by theunbound base unbound subbase and compacted subgradeyene thickness of each layer generally depends on the tracload or more specically the equivalent single axle load(ESAL) during the proposed life cycle of the road

In this parametric study the focus is placed on how theproperties of granular subbase materials are changed by theaddition of a certain amount of RAP and their eect on thepavementrsquos performance As such the resilient modulus ofthe granular base and the asphalt concrete is xed yenestructure of the pavement to be simulated and the propertiesof materials in dierent layers are summarised in Table 7 Inthis particular study the subbase material will be one of theaggregates or aggregateRAP blends tested during the ex-perimental studies of this research

yene properties of the dierent pavement layers used inthe analysis are shown in Table 7 yene bulk stresses at the top

and bottom of the granular subbase layer were determinedusing the computer program KenPave For the selectedHMA resilient moduli (MR 5000MPa) the bulk stresseswere found in the range of 27 kPa to 30 kPa and 14 kPa to18 kPa at the top and bottom of the subbase layers re-spectively for the wheel load of 40 kN In the simulationsvalues of MR are used corresponding to the bulk stress of100 kPa

62 Trac Load For this parametric study the trac datafor urban interstate highways as recommended byAASHTO were used In the case of the PerRoad softwaretrac is separated by axle type single axle tandem axletridem axle and steer axle After determining the percentageof each axle type in the total trac trac is then subdividedinto weight classes in 2 kip intervals yene following is thesummary of the trac data the average annual daily trac(AADT) is 1000 vehicles with 10 being trucks annualgrowth rate of trac is 4 the directional distribution is50 and the percentages of single tandem and tridem axlesare 5573 4266 and 161 respectively yene rest of thetrac loading characteristics in terms of the distribution ofvehicle types and axle weights are described in Figure 8yenese values were used as input in PerRoad 35 Axle weightswere used to evaluate the response of the pavement layers interms of stresses strains and deformations at critical lo-cations of certain layers of the copyexible pavement

Table 6 Summary of the statistical analysis of the proposed model at an alpha value of 005 which matches to 95 condence level

Case Comments

1 t-Critical 20 t-Statistic 1459Since t-statisticgt t-critical which implies that value of the correlation coecient is not dueto sampling error the null hypothesis is rejected and it is concluded that there is a

signicant correlation between (MR)measured and CBR value in the population

2 r-Pearson 09 r-Critical 027

Since r-Pearsongt r-critical which implies that the null hypothesis is rejectedit is quite realistic to accept the ldquoalternative hypothesisrdquo that is the value of r that

we have obtained from our sample represents a real relationship between (MR)measuredand CBR value in the population

3 t-Critical 20 t-Statistic 052Since t-statisticlt t-critical which implies that the null hypothesis is accepted

it is concluded that there is an insignicant dierence between(MR)measured and (MR)correlated values in the population

0

100

200

300

400

500

600

700

800

0 200 400 600 800

MR

(esti

mat

ed)

MR (measured)

1 1 line

95confidence

interval

95prediction

interval

Figure 6 A comparison of estimated and measured MR values along the unity line

Advances in Materials Science and Engineering 9

63 Pavement Performance Criteria In the design ofconventional flexible pavements pavement sectionsare designed corresponding to a cumulative damagefactor (CDF) of 10 which corresponds to a terminallevel of pavement damage For perpetual pavementshowever it is recommended that the CDF is equal to 01at the end of its design life [76] e fatigue and ruttingalgorithms developed at MnROAD [79] for the cali-bration of flexible pavement performance equations wereused to predict pavement damage in cases where pave-ment responses exceeded these thresholds ese corre-lations are as follows

Nf 283lowast 10minus61εt

1113888 1113889

3148

(fatigue)

Nr 6026lowast 10minus81εv

1113888 1113889

387

(ritting)

(8)

where Nf number of load repetitions when fatigue failureoccurs Nr number of load repetition when rutting failureoccurs εt the horizontal tensile strain at the bottom of theHMA and εv the vertical compressive strain at the top ofthe subgrade

It should be noted that the damage of rutting estimatedby PerRoad only takes into account the permanent de-formation in the subgrade Any rutting associated with thedeformation of granular subbase materials is not consideredAccording to the test results in this study use of RAP ingranular subbase layers may induce substantial residualdeformation Further investigation should be performed toget a better understanding of its influence on the rutting offlexible pavements

64 Simulation Results and Discussion Simulation resultsare obtained and discussed in terms of

(1) e likelihood of the tensile strain at the bottom ofthe HMA exceeding 70 με

(2) e likelihood of the vertical strain at the top of thesubgrade soil exceeding 200 με

(3) e number of years it could take to reach a CDF of01 (the threshold level) for fatigue damage

(4) e number of years it could take to reach a CDF of01 for damage induced by rutting

Figure 9 illustrates the concept frequency distributionfor strain both within and outside the threshold limits

We first examine the likelihood of critical pavementresponses exceeding the predefined thresholds when theresilient modulus of the asphalt concrete is 5000MPa anddifferent aggregates or aggregate-RAP blends are used inthe granular subbase layer Figure 10 summarises (1) thelikelihood of the tensile strain at the bottom of the HMAremaining within the critical value of 70 με and (2) thelikelihood of the vertical strain at the top of the subgradesoil exceeding 200 με From this figure it can be inter-preted that all of the blends result in better pavementperformance than the natural aggregate both in terms ofthe tensile strains at the bottom of the HMA and thevertical compressive strains at the top of the subgrade soilFor instance the natural aggregates and RCA on averagehave an 813 likelihood that horizontal strain at thebottom of the HMA will remain within the critical limit of70 με

On the other hand the likelihood for blended ma-terials containing 25 50 and 75 of RAP materials inthe blended samples may reach (on average) 85758937 and 9377 (respectively) chance of remainingwithin the limit Similarly the likelihood that the com-pressive strain at the top of the subgrade will not exceedthe critical value of 200 microns is 8828 (naturalsamples) 9346 (25 RAP material blends) 9557(50 RAP material blends) and 982 (75 RAP ma-terial blends)

Figure 11 shows the number of years required to reacha CDF of 01 when fatigue is controlled by the horizontaltensile strain at the bottom of the subgrade and the HMAand vertical structural rutting are controlled by the verticalcompressive strain at the top of the subgrade e numberof years required to reach a CDF of 01 in general in-creases in line with the increase in the quantity of RAP inthe blend For example the number of years required toreach a CDF of 01 in terms of fatigue damage at thebottom of HMA is 4033 years for natural samples whilethe corresponding figure for the blends containing 75RAP is 5168 years on average A similar trend regarding anincrease in the number of years required to reach a CDF of01 in terms of structural damage at the top of the subgradewas also observed Furthermore for all the cases thenumber of years to reach a CDF of 01 was more than40 years but it is clear that fatigue will be the predominantpavement failure mode

Asphalt concrete

Unbound base

Unbound subbase

Compacted subgrade

Natural subgrade

Figure 7 A typical cross section of flexible pavement

Table 7 Material properties and pavement layer thicknesses

Parameters HMA Base course Subbasecourse Subgrade

MR (MPa) 5000 350 Variable 35Coefficient ofvariation for MR () 25 30 35 45

ickness ofthe layer (mm) 250 200 300 mdash

icknessVariability () 5 8 15 mdash

Poisson ratio 03 03 03 04

10 Advances in Materials Science and Engineering

7 Long-Term Effect of Cyclic Loading onBlended Samples

In order to explore the long-term eects of cyclic loading 9repeated load triaxial tests were performed under a range ofcyclic loading conditions and varying percentages of RAPcontents Figure 12 presents the variation of the residual strainof the tested samples subjected to 20000 load cycles under twodierent values of conning pressures of 345 kPa and1379 kPa each while the corresponding cyclic deviator stresswas maintained at 3105 kPa and 372 kPa From this gure itcan be inferred that the presence of RAP contents increases theresidual strain considerably for both of the conning pressurescenarios For instance for the repeated load test conducted atthe conning pressure of 345 kPa the residual strain for 100natural aggregate F is 012 after 20000 load cycles while forthe blend containing 50 RAP(2) and 75 RAP(2) thecorresponding gures reach 022 and 060 ie an additionof 50 RAP increases the residual strain by amargin of almost83 while the addition of 75 RAP increases the residualstrain by almost 400 Similarly for the repeated load testsconducted at a conning pressure of 1379 kPa on samples

containing natural aggregateW and the blends with RAP(1) at50 and 75 the residual strain after 20000 load cycles is 55and 300 higher when compared with the correspondingvalue for the 100 natural aggregate W Furthermore it isevident from the gures that almost 60 of the total residualstrain occurred during the rst 2000 load cycles out of the20000 total load cycles applied across all the cases

However it should be emphasized that there is a ten-dency for the elastic shakedown to be less pronounced forblended samples when compared to pure natural aggregatesFor instance for the blended sample 50 W and 50RAP(1) the rate of increase of strain becomes 0000154 forthe load cycles in the range of 2000ndash20000 On the otherhand this gure remained limited to 0000056 for thesample containing 100 natural aggregate W under thesame loading condition

Figure 13 shows the eect of the ratio of ldquocyclic deviatorstress to the conning stress (σdσc)rdquo on the residual strain forthe blended sample containing 50 A and 50 RAP(3)From this gure it can be inferred that the ratio σdσc has asubstantial eect on the residual strain generated undercyclic loading For instance at (σdσc) 09 the residualstrain after 6000 load cycles is limited to 006 however thisvalue reaches 011 and 021 at (σdσc) 18 and(σdσc) 27 respectively yene samples tend to stabilisemore quickly under a lower value of (σdσc) 09 whencompared to the stabilising tendency at the higher values of(σdσc) 18 and (σdσc) 27 which were also in-vestigated in this research A 50ndash60 residual strain occursduring the rst 1000 load cycles out of the total 6000 loadcycles applied during the experimental campaign irre-spective of the σdσc value

8 Summary and Conclusions

(1) yene blended samples (ie RAP combined withnatural granular materials) result in higher MRvalues than those obtained for natural granular

Figure 8 Vehicular load classication used in PerRoad 35

Area outside the threshold limit

Stra

in fr

eque

ncy

Figure 9 Example of frequency distribution of strain within andoutside the threshold limits

Advances in Materials Science and Engineering 11

samples under the same loading conditions whilevariations between MR values and the applied bulkstresses during the resilient modulus tests can beapproximated through power law having coecientof correlation (r) value in the range of 097ndash099

(2) yene CBR values of blended samples decrease withthe addition of RAP contents however a clear

decreasing trend in conjunction with an increasingpercentage of RAP contents could not be found

(3) yene new model for the estimation of MR values in-cludes the stress state through the experimentallydetermined CBR having a coecient of correlation ldquorrdquoequal to approximately 09 with fair distribution of thedata points (MR measured and MR estimated) about

Perc

enta

ge o

f are

a

70

75

80

85

90

95

100

100

A10

0 F

100

W10

0 R

CA75

A

+ 2

5 R

AP(

1)75

A

+ 2

5 R

AP(

2)75

A

+ 2

5 R

AP(

3)75

A

+ 2

5 R

AP(

4)75

F

+ 2

5 R

AP(

1)75

F

+ 2

5 R

AP(

2)75

F

+ 2

5 R

AP(

3)75

F

+ 2

5 R

AP(

4)75

W

+ 2

5 R

AP(

1)75

W

+ 2

5 R

AP(

2)75

W

+ 2

5 R

AP(

3)75

W

+ 2

5 R

AP(

4)75

R

CA +

25

RA

P(1)

75

RCA

+ 2

5 R

AP(

2)75

R

CA +

25

RA

P(3)

75

RCA

+ 2

5 R

AP(

4)50

A

+ 5

0 R

AP(

1)50

A

+ 5

0 R

AP(

2)50

A

+ 5

0 R

AP(

3)50

A

+ 5

0 R

AP(

4)50

F

+ 5

0 R

AP(

1)50

F

+ 5

0 R

AP(

2)50

F

+ 5

0 R

AP(

3)50

F

+ 5

0 R

AP(

4)50

W

+ 5

0 R

AP(

1)50

W

+ 5

0 R

AP(

2)50

W

+ 5

0 R

AP(

3)50

W

+ 5

0 R

AP(

4)50

R

CA +

50

RA

P(1)

50

RCA

+ 5

0 R

AP(

2)50

R

CA +

50

RA

P(3)

50

RCA

+ 5

0 R

AP(

4)25

A

+ 7

5 R

AP(

1)25

A

+ 7

5 R

AP(

2)25

A

+ 7

5 R

AP(

3)25

A

+ 7

5 R

AP(

4)25

F

+ 7

5 R

AP(

1)25

F

+ 7

5 R

AP(

2)25

F

+ 7

5 R

AP(

3)25

F

+ 7

5 R

AP(

4)25

W

+ 7

5 R

AP(

1)25

W

+ 7

5 R

AP(

2)25

W

+ 7

5 R

AP(

3)25

W

+ 7

5 R

AP(

4)25

R

CA +

75

RA

P(1)

25

RCA

+ 7

5 R

AP(

2)25

R

CA +

75

RA

P(3)

25

RCA

+ 7

5 R

AP(

4)

Percentage of area within the critical limit of horizontal strain at the bottom of HMAPercentage of area within the critical limit of vertical strain at the top of subgrade

Figure 10 Percentage of area within the critical limits for horizontal strain at the bottom of HMA and vertical strain at the top of subgrade

30

35

40

45

50

55

60

65

70

100

A10

0 F

100

W10

0 R

CA75

A

+ 2

5 R

AP(

1)75

A

+ 2

5 R

AP(

2)75

A

+ 2

5 R

AP(

3)75

A

+ 2

5 R

AP(

4)75

F

+ 2

5 R

AP(

1)75

F

+ 2

5 R

AP(

2)75

F

+ 2

5 R

AP(

3)75

F

+ 2

5 R

AP(

4)75

W

+ 2

5 R

AP(

1)75

W

+ 2

5 R

AP(

2)75

W

+ 2

5 R

AP(

3)75

W

+ 2

5 R

AP(

4)75

R

CA +

25

RA

P(1)

75

RCA

+ 2

5 R

AP(

2)75

R

CA +

25

RA

P(3)

75

RCA

+ 2

5 R

AP(

4)50

A

+ 5

0 R

AP(

1)50

A

+ 5

0 R

AP(

2)50

A

+ 5

0 R

AP(

3)50

A

+ 5

0 R

AP(

4)50

F

+ 5

0 R

AP(

1)50

F

+ 5

0 R

AP(

2)50

F

+ 5

0 R

AP(

3)50

F

+ 5

0 R

AP(

4)50

W

+ 5

0 R

AP(

1)50

W

+ 5

0 R

AP(

2)50

W

+ 5

0 R

AP(

3)50

W

+ 5

0 R

AP(

4)50

R

CA +

50

RA

P(1)

50

RCA

+ 5

0 R

AP(

2)50

R

CA +

50

RA

P(3)

50

RCA

+ 5

0 R

AP(

4)25

A

+ 7

5 R

AP(

1)25

A

+ 7

5 R

AP(

2)25

A

+ 7

5 R

AP(

3)25

A

+ 7

5 R

AP(

4)25

F

+ 7

5 R

AP(

1)25

F

+ 7

5 R

AP(

2)25

F

+ 7

5 R

AP(

3)25

F

+ 7

5 R

AP(

4)25

W

+ 7

5 R

AP(

1)25

W

+ 7

5 R

AP(

2)25

W

+ 7

5 R

AP(

3)25

W

+ 7

5 R

AP(

4)25

R

CA +

75

RA

P(1)

25

RCA

+ 7

5 R

AP(

2)25

R

CA +

75

RA

P(3)

25

RCA

+ 7

5 R

AP(

4)

Year

s

Number of years required to reach CDF = 01 in terms of horizontal strain at the bottom of HMANumber of years required to reach CDF = 01 in terms of vertical strain at the top of subgrade

Figure 11 Number of years required to reach CDF 01 in terms of horizontal strain at the bottom of HMA and vertical strain at the top ofsubgrade

12 Advances in Materials Science and Engineering

the unity line indicating that the proposed regressionmodel has a moderate to strong correlation

(4) Statistical analysis of simulation results based onPerRoad and KenPave software demonstrates thatthe addition of RAP contents in the subbase layer ofthe copyexible pavement signicantly improves itsperformance against rutting and fatigue

(5) Residual strain during the long-term repeated loadtriaxial test was found to increase in line with anincrease in the ratio of ldquocyclic deviator stress to theconning stress (σdσc)rdquo in correlation to an increasein the percentage of RAP contents in the blendedsample

(6) From the authorrsquos perspective the addition of RAPcontents beyond a certain limit (sim50) may prove tobe detrimental for the overall performance of copyexiblepavement structure

Data Availability

yene experimental data used to support the ndings of thisstudy are included within the article in the form of graphsand tables

Conflicts of Interest

yene author declares that there are no concopyicts of interestregarding the publication of this paper

References

[1] R B Mallick and A Veeraragavan ldquoSustainable pavements inIndia-the time to start is nowrdquo New Building Materials andConstruction World (NBMampCW) Magazine vol 16 no 3pp 128ndash140 2010

[2] A Mohammadinia A Arulrajah S Horpibulsuk andA Chinkulkijniwat ldquoEect of copyy ash on properties of crushedbrick and reclaimed asphalt in pavement basesubbase

000

050

100

150

200

250

300

350

400

450

500

0 2000 4000 6000 8000 10000 12000 14000 16000 18000 20000

Axi

al st

rain

()

Number of load cycles

100 W50 W + 50 RAP(1)25 W + 75 RAP(1)100 F50 F + 50 RAP(2)25 F + 75 RAP(2)

σc = 1379kPa σd = 372kPa

Figure 12 Eect of RAP contents on residual strain under long-term repeated loading

000

005

010

015

020

025

0 1000 2000 3000 4000 5000 6000

Axi

al st

rain

()

Number of load cycles

091827

odoc

Figure 13 Eect of ratio of ldquocyclic deviator stress to the conningstress (σdσc)rdquo on the residual strain under long-term repeatedloading

Advances in Materials Science and Engineering 13

applicationsrdquo Journal of Hazardous Materials vol 321pp 547ndash556 2017

[3] L R Hoyos A J Puppala and C A Ordonez ldquoCharacter-ization of cement-fiber-treated reclaimed asphalt pavementaggregates preliminary investigationrdquo Journal of Materials inCivil Engineering vol 23 no 7 pp 977ndash989 2011

[4] R Taha A Al-Harthy K Al-Shamsi and M Al-ZubeidildquoCement stabilization of reclaimed asphalt pavement aggre-gate for road bases and subbasesrdquo Journal of Materials in CivilEngineering vol 14 no 3 pp 239ndash245 2002

[5] A M Azam and D A Cameron ldquoGeotechnical properties ofblends of recycled clay masonry and recycled concrete ag-gregates in unbound pavement constructionrdquo Journal ofMaterials in Civil Engineering vol 25 no 6 pp 788ndash7982013

[6] A Gabor and D Cameron ldquoProperties of recycled concreteaggregate for unbound pavement constructionrdquo Journal ofMaterials in Civil Engineering vol 24 no 6 pp 754ndash7642012

[7] C S Poon and D Chan ldquoFeasible use of recycled concreteaggregates and crushed clay brick as unbound road sub-baserdquoConstruction and Building Materials vol 20 no 8 pp 578ndash585 2006

[8] A Arulrajah M M Y Ali M M Disfani J Piratheepan andM W Bo ldquoGeotechnical performance of recycled glass-wasterock blends in footpath basesrdquo Journal of Materials in CivilEngineering vol 25 no 5 pp 653ndash661 2013

[9] L T Lee Jr ldquoRecycled glass and dredged materialsrdquo ReportNo ERDC TNDOER-T8 US Army Corps of EngineersEngineer Research and Development Center Mississippi MSUSA 2007

[10] M Ali A Arulrajah M Disfani and J Piratheepan ldquoSuit-ability of using recycled glassmdashcrushed rock blends forpavement subbase applicationsrdquo in Proceedings of the Geo-Frontiers 2011 Conference on Geotechnical Foundation Designpp 1325ndash1334 ASCE Reston VA USA 2011

[11] J Wartman D G Grubb and A S M Nasim ldquoSelectengineering characteristics of crushed glassrdquo Journal ofMaterials in Civil Engineering vol 16 no 6 pp 526ndash5392004

[12] W Kim and J Labuz Resilient Modulus and Strength of BaseCourse with Recycled Bituminous Material Minnesota De-partment of Transportation Research Services Section MNUSA 2007

[13] D Bloomquist G Diamond M Oden B Ruth and M TiaEngineering and Environmental Aspects of Recycled Materialsfor Highway Construction Appendix 1 Final Report 1993

[14] A Hussain and Q Yanjun ldquoEvaluation of asphalt mixescontaining reclaimed asphalt pavement for wearing cour-sesrdquo in Proceedings of the International Conference onTraffic and Transportation Engineering School of CivilEngineering Southwest Jiaotong University ChengduChina 2012

[15] M Solaimanian and M Tahmoressi ldquoVariability analysis ofhot-mix asphalt concrete containing high percentage ofreclaimed asphalt pavementrdquo Transportation Research Re-cord Journal of the Transportation Research Board vol 1543no 1 pp 89ndash96 1996

[16] A Gabr and D A Cameron ldquoProperties of recycled concreteaggregate for unbound pavement constructionrdquo Journal ofMaterials in Civil Engineering vol 24 no 6 pp 754ndash7642011

[17] W-L Huang D-H Lin N-B Chang and K-S LinldquoRecycling of construction and demolition waste via a

mechanical sorting processrdquo Resources Conservation andRecycling vol 37 no 1 pp 23ndash37 2002

[18] A R Pasandın and I Perez ldquoOverview of bituminous mix-tures made with recycled concrete Aggregatesrdquo Constructionand Building Materials vol 74 pp 151ndash161 2015

[19] P Jitsangiam H Nikraz and K Siripun ldquoConstruction anddemolition (CampD) waste as a road base material for WesternAustralia roadsrdquo Australian Geomechanics vol 44 no 3pp 57ndash62 2009

[20] A Nataatmadja and Y L Tan ldquoResilient response of recycledconcrete road aggregatesrdquo Journal of Transportation Engi-neering vol 127 no 5 pp 450ndash453 2001

[21] C Leek and K Siripun ldquoSpecification and performance ofrecycled materials in road pavementsrdquo Contract Rep (01119-1)2010

[22] J Green and J Hall Nondistructive Vibratory Testing ofAirport Pavement 1975

[23] W Heukelom and A Klomp ldquoDynamic testing as a means ofcontrolling pavements during and after constructionrdquo inProceedings of the International Conference on the StructuralDesign of Asphalt Pavements University of Michigan AnnArbor MI USA 1962

[24] Ohio Department of Transportation Pavement DesignManual Ohio Department of Transportation Office ofPavement Engineering OH USA 2008

[25] W D Powell H C Mayhew and M M Nunn ldquoestructural design of bituminous roadsrdquo Laboratory Report1132 Transport and Road Research Laboratory CrowthorneUK 1984

[26] M W Witczak X Qi and M W Mirza ldquoUse of nonlinearsubgrade modulus in AASHTO design procedurerdquo Journal ofTransportation Engineering vol 121 no 3 1995

[27] AASHTO Guide for Design of Pavement Structures Wash-ington DC USA 1993

[28] Asphalt Institute Research and Development of 5e AsphaltInstitutersquos 5ickness Design Manual (MS-1) 9th edition 1982

[29] T Buu Correlation of Resistance R-value and ResilientModulus of Idaho Subgrade Soil Idaho Department ofTransportation Division of Highways ID USA 1980

[30] S Muench J Mahoney and L Pierce WSDOT PavementGuide Washington State Department of TransportationInternet Module Washington DC USA 2009

[31] S Yeh and C Su ldquoResilient properties of Colorado soilsrdquoReport No CDOH-DH-SM-89-9 Colorado Department ofHighways Denver CO USA 1989

[32] M R ompson and Q L Robnett ldquoResilient properties ofsubgrade soilsrdquo Transportation Engineering Journal of ASCEvol 105 pp 71ndash89 1979

[33] W Lee N C Bohra A G Altschaeffl and T D WhiteldquoResilient modulus of cohesive soilsrdquo Journal of Geotechnicaland Geoenvironmental Engineering vol 123 no 2 pp 131ndash136 1997

[34] R Carmichael III and E Stuart ldquoPredicting resilient modulusa study to determine the mechanical properties of subgradesoilsrdquo Transportation Research Record vol 1043 pp 145ndash1481986

[35] E C Drumm Y Boateng-Poku and T Johnson PierceldquoEstimation of subgrade resilient modulus from standardtestsrdquo Journal of Geotechnical Engineering vol 116 no 5pp 774ndash789 1990

[36] M J Farrar and J P Turner Resilient Modulus of WyomingSubgrade Soils 1991

14 Advances in Materials Science and Engineering

[37] M P Jones and M W Witczak ldquoSubgrade modulus on thesan diego test roadrdquo Transportation Research Record Journalof the Transportation Research Board vol 641 pp 1ndash6 1977

[38] A M Rahim and K P George ldquoSubgrade soil indexproperties to estimate resilient modulusrdquo in Proceedings ofthe 83th Annual Meeting of the Transportation ResearchBoard National Research Council Washington DC USA2004

[39] M R ompson and T G LaGrow A Proposed ConventionalFlexible Pavement 5ickness Design Procedure University ofIllinois Peoria IL USA 1988

[40] R Pezo ldquoA general method of reporting resilient modulustests of soils a pavement engineerrsquos point of viewrdquo in Pro-ceedings of the 72nd Annual Meeting of Transportation Re-search Board Washington DC USA 1993

[41] R G Hicks and C L Monismith ldquoResilient properties ofgranular materialrdquo Transportation Research Record vol 345pp 15ndash31 1971

[42] J Uzan ldquoCharacterization of granular materialsrdquo Trans-portation Research Record Journal of the Transportation Re-search Board vol 1022 pp 52ndash59 1985

[43] National Cooperative Highway Research Program ldquoGuide formechanistic-empirical design of new and rehabilitatedpavement structuresrdquo NCHRP 1-37A NCHRP WashingtonDC USA 2004

[44] N M Louay H T Hani and H Ananda ldquoEvaluation ofresilient modulus of subgrade soil by cone penetration testrdquoTransportation Research Record Journal of the TransportationResearch Board vol 1652 pp 236ndash245 1999

[45] S Dai and J Zollars ldquoResilient modulus of Minnesota roadresearch project subgrade soilrdquo Transportation Research Re-cord Journal of the Transportation Research Board vol 1786no 1 pp 20ndash28 2002

[46] L Mohammad B Huang A Puppala and A Allen ldquoRe-gression model for resilient modulus of subgrade soilsrdquoTransportation Research Record Journal of the TransportationResearch Board vol 1687 no 1 pp 47ndash54 1999

[47] B Santa ldquoResilient modulus of subgrade soils comparison oftwo constitutive equationsrdquo Transportation Research RecordJournal of the Transportation Research Board vol 1462pp 79ndash90 1994

[48] H Von Quintus and B Killingsworth Analyses Relating toPavement Material Characterizations and their Effects onPavement Performance 1998

[49] O Porter ldquoe preparation of subgradesrdquo in Proceedings ofthe Nineteenth Annual Meeting Highway Research BoardWashington DC USA December 1939

[50] O J Porter ldquoDevelopment of the original method for highwaydesignrdquo Transactions of the American Society of Civil Engi-neers vol 115 pp 461ndash467 1950

[51] D W Hight and M G H Stevens ldquoAn analysis of theCalifornia Bearing Ratio test in saturated claysrdquoGeotechnique vol 32 no 4 pp 315ndash322 1982

[52] P R Fleming and C D F Rogers ldquoAssessment of pavementfoundations during constructionrdquo Proceedings of the In-stitution of Civil Engineers-Transport vol 111 no 2pp 105ndash115 1995

[53] M R ompson R Marshall and Q L Robnett ldquoResilientproperties of subgrade soilsrdquo Final Report No FHWA-IL-UI-160 University of Illinois Urbana IL USA 1976

[54] B Sukumaran V Kyatham A Shah and D Sheth ldquoSuit-ability of using California bearing ratio test to predict resilientmodulusrdquo in Proceedings Federal Aviation Administration

Airport Technology Transfer Conference Atlantic City NJUSA 2002

[55] N W Lister and D Powell ldquoDesign practices for pavementsin the United Kingdomrdquo in Proceedings of the 6th In-ternational Conference on the Structural Design of AsphaltPavements Ann Arbor MI USA July 1987

[56] S Hossain G Dickerson and C Weaver Comparative Studyof VTM and AASHTO Test Method for CBR Co MaterialsDivision VDOT 2005

[57] N Garg A Larkin and H Brar ldquoA comparative subgradeevaluation using CBR vane shear light weight deflectometerand resilient modulus testsrdquo in Proceedings of the 8th In-ternational Conference on the Bearing Capacity of RoadsRailways and Airfields CRC Press Champaign IL USA2009

[58] M Ayres Development of a rational probabilistic approach forflexible pavement analysis University of Maryland CollegePark MD USA 1997

[59] AASHTO T 307 Determining the Resilient Modulus of Soilsand Aggregate Materials (2012) American Association ofState Highway and Transportation Officials Washington DCUSA 2004

[60] M Arshad and M F Ahmed ldquoPotential use of reclaimedasphalt pavement and recycled concrete aggregate in basesubbase layers of flexible pavementsrdquo Construction andBuilding Materials vol 151 pp 83ndash97 2017

[61] M Arshad ldquoCorrelation between resilient modulus (MR) andconstrained modulus (Mc) values of granular materialsrdquoConstruction and Building Materials vol 159 pp 440ndash4502018

[62] P Guo and J Emery ldquoImportance of strain level inevaluating resilient modulus of granular materialsrdquo In-ternational Journal of Pavement Engineering vol 12 no 2pp 187ndash199 2011

[63] E J McGarrah ldquoEvaluation of current practices of reclaimedasphalt pavementvirgin aggregate as base course materialrdquoNo WA-RD 7131 Federal Highway AdministrationWashington DC USA 2007

[64] T B Alam M Abdelrahman and S A Schram ldquoLaboratorycharacterisation of recycled asphalt pavement as a base layerrdquoInternational Journal of Pavement Engineering vol 11 no 2pp 123ndash131 2010

[65] T Bennert and A Maher ldquoe development of a performancespecification for granular base and subbase materialrdquo ReportNo FHWA-NJ-2005-003 Department of TransportationEwing Township NJ USA 2005

[66] T H Wonnacott H omas and J Ronald ldquoRegression asecond course in statisticsrdquo No 04 QA2782 W6Wiley NewYork NY USA 1981

[67] W Penny and S Roberts Neural network predictions witherror bars Dept of Electrical and Electronic EngineeringTechnology and Medicine Research Report TR-97-1 ImperialCollege of Science London UK 1997

[68] R Dybowski and S J Roberts ldquoConfidence intervals andprediction intervals for feed-forward neural networksrdquoClinical Applications of Artificial Neural Networks pp 298ndash326 2001

[69] J Hauke and T Kossowski ldquoComparison of values ofPearsonrsquos and Spearmanrsquos correlation coefficients on the samesets of datardquo Quaestiones Geographicae vol 30 no 2pp 87ndash93 2011

[70] K-z Yan H-b Xu and G-h Shen ldquoNovel approach toresilient modulus using routine subgrade soil propertiesrdquo

Advances in Materials Science and Engineering 15

International Journal of Geomechanics vol 14 no 6 article04014025 2013

[71] Y H Chan ldquoBiostatistics 104 correlational analysisrdquoSingapore Medical Journal vol 44 no 12 pp 614ndash6192003

[72] B M Damghani D Welch C OrsquoMalley and S Knights ldquoemisleading value of measured correlationrdquoWilmott vol 2012no 62 pp 64ndash73 2012

[73] L B Christensen B Johnson and L A Turner ldquoResearchmethods design and analysisrdquo 2011

[74] W J Dixon and F J Massey Introduction to StatisticalAnalysis McGraw-Hill New York NY USA 1969

[75] B Colbert and Z You ldquoe determination of mechanicalperformance of laboratory produced hot mix asphalt mixturesusing controlled RAP and virgin aggregate size fractionsrdquoConstruction and Building Materials vol 26 no 1 pp 655ndash662 2012

[76] D H Timm and D E Newcomb ldquoPerpetual pavement designfor flexible pavements in the USrdquo International Journal ofPavement Engineering vol 7 no 2 pp 111ndash119 2006

[77] Y H Huang Pavement Analysis and Design Prentice-HallEnglewood Cliffs NJ USA 2nd edition 1993

[78] L Walubita W Liu and T Scullion Texas perpetualpavements-Experience overview and the way forward Tech-nical Report No 0-4822-3 Texas Transportation InstituteTexas AampM University College Station TX USA 2010

[79] D Timm and D Newcomb ldquoCalibration of flexible pavementperformance equations for Minnesota road research projectrdquoTransportation Research Record Journal of the TransportationResearch Board no 1853 pp 134ndash142 2003

16 Advances in Materials Science and Engineering

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Submit your manuscripts atwwwhindawicom

techniques and efforts) and it was found that [56] corre-lations between resilient modulus values and all test results(including the CBR) were not statistically significant Garget al [57] opined that the CBR value can be converted to aresilient modulus a strong trend is apparent in the corre-lation but there is a lot of scatter A few of the existingcorrelations based on CBR values are given in Table 1

3 Material Characterisation

For this research four different types of RAP samples(designated as ldquoRAP(1)rdquo ldquoRAP(2)rdquo ldquoRAP(3)rdquo andldquoRAP(4)rdquo) three different types of natural aggregates(designated as ldquoArdquo ldquoFrdquo and ldquoWrdquo) and one RCA samplewere used Based on the gradation curves natural ag-gregate A is finer than other natural aggregate (F and W)while natural aggregate W is the most coarser amongthem Each of the natural aggregate samples as well as theRAP and RCA materials contained crushed limestone ofsubangular to angular shape Elongated and flat particlesin the samplesmaterials were not more than 6 as perASTM D 4791

A summary of material characterisations in terms ofdetailed gradation properties (D10D30D50 grain size di-ameter corresponding to 103050 percent finer by mass Cccoefficient of curvature Cu coefficient of uniformity)compaction characteristics effective shear strength param-eters and physical properties of recovered bitumen bindershas been presented in Table 2 Further detail on materialcharacterisation can be found in Arshad and Ahmed [60]and Arshad [61] Since focus of the testing campaign consistsof the CBR test and the resilient modulus test the same hasbeen briefly explained in the following subsections

Table 3 shows the matrix of the testing program in-cluding the resilient modulus tests the CBR tests and therepeated load tests

31 CBR Test In conventional pavement design the CBRvalue is an important parameter used to determine thethickness of various layers of the pavement structureUsually the higher the CBR value the better the perfor-mance of the pavement is with regard to both stiffness andstrength is implies that the CBR value can be used as aparameter to evaluate the suitability of a soil for use aspavement construction material For this study standard 3-point CBR tests were performed on the naturalRAPs andblended samples under unsoaked conditions to simulate themoisture content at which the resilient modulus tests wereperformed A schematic diagram of the CBR test is shown inFigure 1

e test equipment primarily consisted of a

(1) cylindrical mould having an inner diameter of150mm and a height of 175mm

(2) spacer disc of 148mm in diameter and 477mm inheight

(3) special surcharge weights

(4) metallic penetration piston of 50mm diameter andminimum of 100mm in length

(5) loading machine with a capacity of at least 50 kN andequipped with a movable head or base that travels ata uniform rate of 125mmmin

e CBR value is defined as the ratio of stress requiredfor the circular piston to penetrate at the rate of 125mmmin the soil mass in the cylinder to the standard stress that isrequired for the corresponding penetration of a standardmaterial ie like limestone found in California Furtherprocedural details on the CBR value calculations can befound in AASHTO T 193

32 Resilient Modulus Test Resilient modulus (MR) is de-fined as the ratio of cyclic axial stress to recoverable axialstrain (ΔσcΔεa) e cylindrical test specimen is compactedat a desired density and is subjected to cyclic axial stress at agiven confining pressure within a conventional triaxial cellResilient modulus tests for this research were conducted asper the guidelines specified in AASHTO T 307-99(2004) forwhich a haversine-shaped loading waveform is mandatory tosimulate traffic loading Each load cycle of this waveformessentially consists of 01 seconds load duration and a09 second rest period Figure 2 shows a typical repetitiveloadstress pulse along with the generated residual de-formation curve in the time domain e regular loadingsequence in AASHTO T 307-99 consists of 15 differentstages each one having 100 load cycles following the ex-ecution of the conditioning stage of 750 load cycles Each ofthe loading stages has a particular combination of confiningstress maximum axial stress and cyclic deviator stress asshown in Table 4 Further procedural details of the testincluding sample preparation and installation techniqueelectromechanics of the loading system (servo-controlledelectrohydraulic MTS testing machine) specification of theused load cells and LVDTs and particulars of the data ac-quisition system can be found in several works [60ndash62]

4 Test Results and Discussion

is section presents a discussion on trends obtained for theCBR tests and the resilient modulus tests performed on anumber of reconstituted granular samples as identified inTable 2

41 SampleResults of theCBRTest Sample results of the CBRtest in terms of compaction effort and the percentage of RAPcontent on the CBR values are presented in Figure 3 Fromthis figure it can be inferred that the CBR value decreases

Table 1 Existing models for the estimation of resilient modulusbased on CBR value

MR 1033CBR [23]MR 38(CBR)0711 [22]MR 18(CBR)064 [55]MR 21(CBR)065 [58]MR 176(CBR)064 [59]

Advances in Materials Science and Engineering 3

noticeably in correspondence to the increasing content inthe blended samples incorporating granular (A) and RAP(1)For instance the blend containing 25RAP(1) achieves only74 of the CBR value achieved by the aggregate (A) (naturalmaterial) at the same level of compaction eort ie 65blows Similarly the corresponding value for blends con-taining 50 RAP(1) 75 RAP(1) and 100 RAP(1) islimited to 5625 325 and 225 respectively Likewise

the trend can also be observed for the other two compactioneorts consisting of 10 and 30 blows

42 Eect of RAP Contents on Resilient Modulus (MR)Forty-eight blended samples were prepared by mixing thefour types of RAPmaterials with natural granular samplesAF W and RCA in proportion with RAP contents of 25

Table 2 Characterisation of the tested materials

MaterialCompaction characteristics (AASHTO T180)

Maximum dry density (kNm3) Optimum moisture content ()Natural aggregates 219ndash233 55ndash71RAPs 197ndash214 64ndash91RCA 207 75

Gradation characteristics (AASHTO T27-99)D10 (mm) D30 (mm) D50 (mm) Cu Cc Sand size (mm) (475ndash95) mm

Natural aggregate A 015 045 1 117 077 70 10Natural aggregate F 015 15 9 1000 100 35 10Natural aggregate W 06 5 15 333 208 25 12RAP(1) 03 12 275 133 120 64 22RAP(2) 03 12 275 133 120 60 30RAP(3) 15 5 65 50 222 27 50RAP(4) 03 12 2 92 175 82 10RCA 025 15 65 400 09 40 18

Flat and elongated particles (ASTM D 4791)Natural aggregatesRAPsRCA Limited to 6

Shear strength parameters under quick shear testNatural aggregatesRAPsRCA Friction angle Cohesion

36degndash43deg 20‒30 kPaPhysical properties of recovered bitumen binder

RAPs 60degC viscosity (poise)(ASTM D4402)

25degC penetration (dmm)(ASTM D5-06) Softening point (degC) (ASTM D36-76)

23500ndash46700 20ndash52 62ndash67

Table 3 Matrix of the testing program

Natural aggregateRCA RAP Minimum number ofresilient modulus tests

Minimum numberof CBR tests

Minimum number ofrepeated load triaxial tests

Natural aggregate A F W mdash 3 3 2RCA mdash 1 1 mdashBlends of natural aggregates with RAPs 4times 3lowast 3times 3times 4 36 3times 3times 4 36 7Blends of RCA with RAPs 4times 3lowast 3times 412 3times 412 mdashTotal 52 52 9lowastBlended samples were prepared by mixing 25 50 and 75 (by weight) of each RAP type with the natural aggregates and RCA

Transducer to measurepenetration

Annular weights

Sample

Standard mould

Applied load

Standard plunger

Figure 1 A schematic diagram of the CBR test

Stre

sss

trai

n le

vel

Time

Deformation vs time

Stress vs time

Figure 2 Typical shape of applied repeated load cycles and thegenerated deformation curve

4 Advances in Materials Science and Engineering

50 and 75 for each Figures 4(a)ndash4(d) show the eects ofthe addition of these RAPs on themeasuredMR values over arange of bulk stresses as specied in AASHTOT 307-99 (68)Variation ofMR values with bulk stress can be approximatedthrough trend lines based on a power function having thecoecient of determination (R2) in the range of 095ndash099From these trend lines it is evident that MR values increasenot only due to the increase in bulk stress but also incombination with the addition of RAP contents ie blendedsamples give higher MR values when compared to thoseobtained from the natural samples of granular A F W andRCA More specically for instance at a bulk stress ofsim673 kPa MR value for the 100 granular W is 320MPawhile the corresponding values for blended samples in-corporating 25 50 and 75 of RAP(1) are 340MPa360MPa and 390MPa respectively

A similar trend in MR values was observed at lowerlevels of bulk stress or more precisely over the entirerange of bulk stresses considered during the testing

campaign In some cases sim50 increase in MR values wasobserved for the blends containing 75 RAP contents Ingeneral for most of the blended samples containing 25and 50 RAP contents the corresponding increase in MRvalues was in the range of 5ndash15 and 10ndash20 respectivelyAn important point is that the addition of RAPs to RCAinduced the most signicant increase in the resilientmoduli when compared with the increase inMR when RAPwas added to granular samples Similar observations havealso been documented by many researchers including Kimand Labuz [12] MacGregor et al [63] Alam et al [64] andBennert and Maher [65]

5 Development of Correlation betweenResilient Modulus and CBR Values

51 Proposed Correlation and eoretical BackgroundFor this study an attempt has been made to correlate theMR values with the CBR values on the basis of a commonvalue of bulk stress identied during both types of testsyenis should be emphasize that CBR values tend to decreasewith addition of RAP contents while reverse is the situationin case of resilient modulus values Such trends are pri-marily due to the fact that loading for the resilient modulustest is dynamic in nature while in the case of the CBR test itis virtually static

Fundamentally axial stress is applied during the CBRtests through a plunger (σpa) in addition to an axial sur-charge weight (σsa) as shown in Figure 5 However lateralstress on the walls of the CBRmould can be estimated on thebasis of the lateral earth pressure coecient (Ka) as describedin classical soil mechanics such that

σpl Kaσpa

σsl Kaσsa

Ka 1minus sin(ϕ)

(1)

where ϕ is the eective angle of internal friction of the soilsample (blend) under consideration

Table 4 Loading sequence for the resilient modulus test as per AASHTO T 307 protocol

Seq No No of load applied Conning stress Max axial stress Cyclic axial stress Contact stress Total axial stress (kPa)σ3 (kPa) σmax (kPa) σcyclic (kPa) 01σmax (kPa)0 750 1034 1034 931 103 20681 100 207 207 186 21 4142 100 207 414 373 41 6213 100 207 621 559 62 8284 100 345 345 31 35 695 100 345 689 62 69 10346 100 345 1034 931 103 13797 100 689 689 62 69 13788 100 689 1379 1241 138 20689 100 689 2068 1861 207 275710 100 1034 689 62 69 172311 100 1034 1034 931 103 206812 100 1034 2068 1861 207 310213 100 1379 1034 931 103 241314 100 1379 1379 1241 138 275815 100 1379 2758 2482 276 4137

0

10

20

30

40

50

60

70

80

90

1950 2000 2050 2100 2150 2200 2250

Uns

oake

d CB

R (

)

Unit weight (kNm3)

A75 A + 25 RAP(1)50 A + 50 RAP(1)

25 A + 75 RAP(1)RAP(1)

Figure 3 Eect of RAP contents on CBR values

Advances in Materials Science and Engineering 5

It is interesting to note that the 3-point CBR test en-compasses a wide range of dry and bulk density in thesample while on the other hand each resilient modulus

test uses a unique value of the samplersquos dry and bulkdensity To estimate a unique value of the bulk stress duringthe CBR test which is analogous to the bulk stress valueidentied from resilient modulus test the following pro-cedure was adopted

(1) Determine the dry density of the resilient modulussample

(2) Estimate the CBR value corresponding to that drydensity value

(3) Determine the axial stress (σpa) value correspondingto the CBR value

(4) Calculate the bulk stress using the following relation

σbulk θ σ1 + σ2 + σ3 σpa + σsa( ) + 2Ka σpa + σsa( ) (2)

Using a unique value of bulk stress on the basis ofequation (2) the corresponding resilient modulus valuefrom the actual experimental data (MR test) was matchedand then a correlation between CBR value (point 2)and the resilient modulus value in terms of the power

y = 52x064

R2 = 099

y = 88x056

R2 = 098

y = 136x051

R2 = 095

y = 101x056

R2 = 098

0

50

100

150

200

250

300

350

400

450

0 200 400 600 800

MR (

MPa

)

Bulk stress (kPa)

100 A75 A + 25 RAP(2)

50 A + 50 RAP(2)25 A + 75 RAP(2)

(a)

100 F75 F + 25 RAP(3)

50 F + 50 RAP(3)25 F + 75 RAP(3)

y = 517x064

R2 = 099

y = 745x058

R2 = 099

y = 101x054

R2 = 097

y = 972x057

R2 = 096

0

50

100

150

200

250

300

350

400

450

0 200 400 600 800

MR (

MPa

)

Bulk stress (kPa)

(b)

y = 517x064

R2 = 099

y = 745x058

R2 = 099

y = 101x054

R2 = 097

y = 972x057

R2 = 096

0

50

100

150

200

250

300

350

400

450

0 200 400 600 800

MR (

MPa

)

Bulk stress (kPa)

100 W75 W + 25 RAP(1)

50 W + 50 RAP(1)25 W + 75 RAP(1)

(c)

y = 517x064

R2 = 099

y = 745x058

R2 = 099

y = 101x054

R2 = 097

y = 972x057

R2 = 096

0

50

100

150

200

250

300

350

400

450

0 100 200 300 400 500 600 700 800

MR (

MPa

)

Bulk stress (kPa)

100 RCA25 RCA + 75 RAP(4)

50 RCA + 50 RAP(4)75 RCA + 25 RAP(4)

(d)

Figure 4 Variation ofMR value with bulk stress and percentage of RAP contents for (a) naturalA (b) natural F (c) naturalW and (d) RCA

Plunger

Surchargeweight

Soil sample

Lateral stress due toloading of plunger (σpl)

Lateral stress due tosurcharge loading (σsl)

Figure 5 An assumed conguration of axial and lateral stressesduring CBR test

6 Advances in Materials Science and Engineering

function having a coefficient of determination sim081 canbe given as

MR 4937(CBR)059

(3)

Table 5 shows the experimental data and the estimatedvalues of MR based on the four steps explained above andequation (3)

Figure 6 shows the capabilities of the proposed regressionmodel on the basis of the distribution of the data pointswhich in fact involves the experimentally determined andestimated MR values along the unity line giving a 95prediction and confidence interval is figure illustrates thatthere is an almost equal distribution of the data points on bothsides of the unity line Additionally the entire set of the datapoints is confined within the 95 prediction interval which isdefined as the interval around the linear regression line suchthat 95 of the predicted values will fall in this intervalFurther details on the mathematical framework of the pre-diction and the confidence interval can be found in standardtextbooks dealing with statistics and probability analysis suchas those authored by Wonnacott and Ronald [66] Penny andRoberts [67] and Dybowski and Roberts [68]

52 Statistical Analysis of the Proposed Model A Pearsonrsquoscorrelation coefficient (r) as given by equation (4) is ameasure of the strength and direction of linear associationthat exists between two continuous variables More specif-ically for the drawn line of best fit for sample data points oftwo variables Pearsonrsquos correlation indicates how well thedata points fit this new modelline of best fit and its nu-merical value indicates how far away all these data points areto the line of best fit (ie how well the data points fit this newmodelline of best fit) [69 70]

r 1113936

ni1 ui minus ui( 1113857 ti minusti( 1113857

1113936ni1 ui minus ui( 1113857

2ti minus ti( 1113857

21113960 1113961

1113969 (4)

where ui and ti experimental and predicted values re-spectively for the ith output ui average of experimentaloutputs and n size of sample

e statistical value of r may range from minus1 for a perfectnegative linear relationship (inversely related) to +1 for aperfect positive linear relationship (directly related) In gen-eral from theoretical point of view the strength of the linearrelationship can be categorised as ldquovery strongrdquo ldquomoderatelystrongrdquo and ldquofairly strongrdquo for the corresponding numericalvalues of r in the range 08ndash10 06ndash08 and 03ndash05 [71] Itshould be emphasized that if r 00 it does not necessarilymean that the two variables have no relationship In order tolook into the real strength of the correlation usually a sta-tistical test of significance is performed as discussed in [72]For this study three different types of statistical tests wereapplied to assess the significance of the developed correlationpresented in equation (3) and Table 5

Case 1 t-Test for the assessment of the implication of co-efficient of correlation (r) at a specific degree of freedom andlevel of significance [73]

is provides the researcher with some idea of how largea correlation coefficient must be before it can be consideredas demonstrating that there really is a relationship betweentwo variables (in our case the (MR)measured and CBR values)It may be the situation that two variables are related bychance and a hypothesis test for r allows the researcher todecide whether the observed r could have emerged by chanceor not e null hypothesis is that there is no relationshipbetween the two variables at is if ρ is the true correlationcoefficient for the two variables and when all populationvalues have been observed then the null hypothesis can begiven as

H0 ρ 0 (5)

e alternative hypothesis could be written as

HA ρne 0 (6)

whereas the standardised t-test for the null hypothesis that ris equal to zero can be written as

t r

nminus 21minus r2

1113970

(7)

where n is the number of paired observations in the givensample

e null hypothesis is evaluated by comparing the t-statistic of equation (7) with t-critical (201) obtained from tdistribution having the nminus 2 degree of freedom

Case 2 Direct comparison of the coefficient of correlationvalue (09) with the r-critical value (027) obtained from astatistical table corresponding to a specific degree of freedomand level of significance [61 74]

Case 3 It often becomes mandatory to statistically evaluatethe difference between two datasets obtained by two dif-ferent sources As in our case one set of MR values wasobtained experimentally using the AASHTOT 307-99(2004)protocol and the other set of MR values was obtained usingthe proposed correlation A standard t-test was performed toevaluate the difference between the paired values of(MR)measured and (MR)estimated at a specific degree of freedomand level of significance [74 75]

Table 6 summarises the statistical analysis of the abovethree cases

6 Assessment of Pavement PerformanceContaining RAPContent in Its Subbase Layer

To examine the performance of the pavement containingnatural aggregates mixed with RAP and used as subbasematerials the following analyses were performed usingcomputer software simulation

(1) To access the likelihood that critical pavement re-sponses exceed predefined thresholds using com-puter program PerRoad [76]

Advances in Materials Science and Engineering 7

(2) To determine the stresses and strains at critical lo-cations in the pavement structure using computerprogram KenPave developed by the University ofKentucky [77]

PerRoad is a Monte Carlo-based simulation softwareused to develop probability-based analysis for flexiblepavement is software can easily demonstrate the influ-ence of the MR values of the pavement material on the

Table 5 A comparison of measured and estimated MR values along with CBR values

MaterialBlend Dry unit weightachieved (kNm3) CBR () Total axial

stress (kPa)

Estimatedbulk stress

in CBR test (kPa)

MR values measuredprojected (MPa)

MR valuesestimated(MPa)

100 A 211 65 9780 1663 550 584100 F 221 74 11130 1892 600 631100 W 224 85 12780 2173 670 685100 RCA 192 53 7980 1357 410 51875 A+ 25 RAP(1) 207 47 7080 1204 470 48250 A+ 50 RAP(1) 205 31 4680 796 300 37725 A+ 75 RAP(1) 202 22 3330 566 280 30875 A+ 25 RAP(2) 203 55 8280 1408 505 52950 A+ 50 RAP(2) 208 39 5880 1000 410 43225 A+ 75 RAP(2) 213 17 2580 439 260 26475 A+ 25 RAP(3) 201 51 7680 1306 490 50650 A+ 50 RAP(3) 205 30 4530 770 315 37025 A+ 75 RAP(3) 199 19 2880 490 310 28275 A+ 25 RAP(4) 197 55 8280 1408 505 52950 A+ 50 RAP(4) 198 43 6480 1102 402 45825 A+ 75 RAP(4) 192 27 4080 694 252 34775 F+ 25 RAP(1) 208 52 7830 1331 538 51250 F+ 50 RAP(1) 213 41 6180 1051 455 44525 F+ 75 RAP(1) 201 14 2130 362 356 23575 F+ 25 RAP(2) 205 59 8880 1510 525 55250 F+ 50 RAP(2) 199 48 7230 1229 407 48825 F+ 75 RAP(2) 197 31 4680 796 408 37775 F+ 25 RAP(3) 201 62 9330 1586 667 56850 F+ 50 RAP(3) 192 41 6180 1051 516 44525 F+ 75 RAP(3) 208 19 2880 490 343 28275 F+ 25 RAP(4) 213 43 6480 1102 515 45850 F+ 50 RAP(4) 201 32 4830 821 490 38425 F+ 75 RAP(4) 213 13 1980 337 278 22575 W+25 RAP(1) 208 51 7680 1306 510 50650 W+50 RAP(1) 205 44 6630 1127 500 46425 W+75 RAP(1) 199 16 2430 413 240 25575 W+25 RAP(2) 197 55 8280 1408 502 52950 W+50 RAP(2) 199 31 4680 796 438 37725 W+75 RAP(2) 213 12 1830 311 265 21575 W+25 RAP(3) 201 48 7230 1229 520 48850 W+50 RAP(3) 213 35 5280 898 447 40525 W+75 RAP(3) 207 21 3180 541 255 29975 W+25 RAP(4) 205 45 6780 1153 480 47050 W+50 RAP(4) 199 34 5130 872 473 39825 W+75 RAP(4) 192 9 1380 235 213 18175 RCA+ 25 RAP(1) 208 38 5730 974 486 42550 RCA+ 50 RAP(1) 213 23 3480 592 330 31625 RCA+ 75 RAP(1) 201 12 1830 311 187 21575 RCA+ 25 RAP(2) 213 38 5730 974 525 42550 RCA+ 50 RAP(2) 201 31 4680 796 356 37725 RCA+ 75 RAP(2) 214 14 2130 362 200 23575 RCA+ 25 RAP(3) 201 32 4830 821 447 38450 RCA+ 50 RAP(3) 205 15 2280 388 226 24525 RCA+ 75 RAP(3) 199 9 1380 235 148 18175 RCA+ 25 RAP(4) 192 39 5880 1000 473 43250 RCA+ 50 RAP(4) 201 13 1980 337 200 22525 RCA+ 75 RAP(4) 202 18 2730 464 161 273

8 Advances in Materials Science and Engineering

cumulative damage factor (CDF) It also demonstrates thelikelihood that critical pavement responses could exceedpredened thresholds which are the horizontal tensile strainof 70 microns at the bottom of the asphalt concrete (which islinked with fatigue cracking) and the vertical compressivestrain of 200 microns at the top of the subgrade (which isassociated with the structural rutting) [78]

61 Pavement Structure and Material CharacteristicsFigure 7 shows a typical cross section of copyexible pavementswhich consists of a hot mix asphalt layer supported by theunbound base unbound subbase and compacted subgradeyene thickness of each layer generally depends on the tracload or more specically the equivalent single axle load(ESAL) during the proposed life cycle of the road

In this parametric study the focus is placed on how theproperties of granular subbase materials are changed by theaddition of a certain amount of RAP and their eect on thepavementrsquos performance As such the resilient modulus ofthe granular base and the asphalt concrete is xed yenestructure of the pavement to be simulated and the propertiesof materials in dierent layers are summarised in Table 7 Inthis particular study the subbase material will be one of theaggregates or aggregateRAP blends tested during the ex-perimental studies of this research

yene properties of the dierent pavement layers used inthe analysis are shown in Table 7 yene bulk stresses at the top

and bottom of the granular subbase layer were determinedusing the computer program KenPave For the selectedHMA resilient moduli (MR 5000MPa) the bulk stresseswere found in the range of 27 kPa to 30 kPa and 14 kPa to18 kPa at the top and bottom of the subbase layers re-spectively for the wheel load of 40 kN In the simulationsvalues of MR are used corresponding to the bulk stress of100 kPa

62 Trac Load For this parametric study the trac datafor urban interstate highways as recommended byAASHTO were used In the case of the PerRoad softwaretrac is separated by axle type single axle tandem axletridem axle and steer axle After determining the percentageof each axle type in the total trac trac is then subdividedinto weight classes in 2 kip intervals yene following is thesummary of the trac data the average annual daily trac(AADT) is 1000 vehicles with 10 being trucks annualgrowth rate of trac is 4 the directional distribution is50 and the percentages of single tandem and tridem axlesare 5573 4266 and 161 respectively yene rest of thetrac loading characteristics in terms of the distribution ofvehicle types and axle weights are described in Figure 8yenese values were used as input in PerRoad 35 Axle weightswere used to evaluate the response of the pavement layers interms of stresses strains and deformations at critical lo-cations of certain layers of the copyexible pavement

Table 6 Summary of the statistical analysis of the proposed model at an alpha value of 005 which matches to 95 condence level

Case Comments

1 t-Critical 20 t-Statistic 1459Since t-statisticgt t-critical which implies that value of the correlation coecient is not dueto sampling error the null hypothesis is rejected and it is concluded that there is a

signicant correlation between (MR)measured and CBR value in the population

2 r-Pearson 09 r-Critical 027

Since r-Pearsongt r-critical which implies that the null hypothesis is rejectedit is quite realistic to accept the ldquoalternative hypothesisrdquo that is the value of r that

we have obtained from our sample represents a real relationship between (MR)measuredand CBR value in the population

3 t-Critical 20 t-Statistic 052Since t-statisticlt t-critical which implies that the null hypothesis is accepted

it is concluded that there is an insignicant dierence between(MR)measured and (MR)correlated values in the population

0

100

200

300

400

500

600

700

800

0 200 400 600 800

MR

(esti

mat

ed)

MR (measured)

1 1 line

95confidence

interval

95prediction

interval

Figure 6 A comparison of estimated and measured MR values along the unity line

Advances in Materials Science and Engineering 9

63 Pavement Performance Criteria In the design ofconventional flexible pavements pavement sectionsare designed corresponding to a cumulative damagefactor (CDF) of 10 which corresponds to a terminallevel of pavement damage For perpetual pavementshowever it is recommended that the CDF is equal to 01at the end of its design life [76] e fatigue and ruttingalgorithms developed at MnROAD [79] for the cali-bration of flexible pavement performance equations wereused to predict pavement damage in cases where pave-ment responses exceeded these thresholds ese corre-lations are as follows

Nf 283lowast 10minus61εt

1113888 1113889

3148

(fatigue)

Nr 6026lowast 10minus81εv

1113888 1113889

387

(ritting)

(8)

where Nf number of load repetitions when fatigue failureoccurs Nr number of load repetition when rutting failureoccurs εt the horizontal tensile strain at the bottom of theHMA and εv the vertical compressive strain at the top ofthe subgrade

It should be noted that the damage of rutting estimatedby PerRoad only takes into account the permanent de-formation in the subgrade Any rutting associated with thedeformation of granular subbase materials is not consideredAccording to the test results in this study use of RAP ingranular subbase layers may induce substantial residualdeformation Further investigation should be performed toget a better understanding of its influence on the rutting offlexible pavements

64 Simulation Results and Discussion Simulation resultsare obtained and discussed in terms of

(1) e likelihood of the tensile strain at the bottom ofthe HMA exceeding 70 με

(2) e likelihood of the vertical strain at the top of thesubgrade soil exceeding 200 με

(3) e number of years it could take to reach a CDF of01 (the threshold level) for fatigue damage

(4) e number of years it could take to reach a CDF of01 for damage induced by rutting

Figure 9 illustrates the concept frequency distributionfor strain both within and outside the threshold limits

We first examine the likelihood of critical pavementresponses exceeding the predefined thresholds when theresilient modulus of the asphalt concrete is 5000MPa anddifferent aggregates or aggregate-RAP blends are used inthe granular subbase layer Figure 10 summarises (1) thelikelihood of the tensile strain at the bottom of the HMAremaining within the critical value of 70 με and (2) thelikelihood of the vertical strain at the top of the subgradesoil exceeding 200 με From this figure it can be inter-preted that all of the blends result in better pavementperformance than the natural aggregate both in terms ofthe tensile strains at the bottom of the HMA and thevertical compressive strains at the top of the subgrade soilFor instance the natural aggregates and RCA on averagehave an 813 likelihood that horizontal strain at thebottom of the HMA will remain within the critical limit of70 με

On the other hand the likelihood for blended ma-terials containing 25 50 and 75 of RAP materials inthe blended samples may reach (on average) 85758937 and 9377 (respectively) chance of remainingwithin the limit Similarly the likelihood that the com-pressive strain at the top of the subgrade will not exceedthe critical value of 200 microns is 8828 (naturalsamples) 9346 (25 RAP material blends) 9557(50 RAP material blends) and 982 (75 RAP ma-terial blends)

Figure 11 shows the number of years required to reacha CDF of 01 when fatigue is controlled by the horizontaltensile strain at the bottom of the subgrade and the HMAand vertical structural rutting are controlled by the verticalcompressive strain at the top of the subgrade e numberof years required to reach a CDF of 01 in general in-creases in line with the increase in the quantity of RAP inthe blend For example the number of years required toreach a CDF of 01 in terms of fatigue damage at thebottom of HMA is 4033 years for natural samples whilethe corresponding figure for the blends containing 75RAP is 5168 years on average A similar trend regarding anincrease in the number of years required to reach a CDF of01 in terms of structural damage at the top of the subgradewas also observed Furthermore for all the cases thenumber of years to reach a CDF of 01 was more than40 years but it is clear that fatigue will be the predominantpavement failure mode

Asphalt concrete

Unbound base

Unbound subbase

Compacted subgrade

Natural subgrade

Figure 7 A typical cross section of flexible pavement

Table 7 Material properties and pavement layer thicknesses

Parameters HMA Base course Subbasecourse Subgrade

MR (MPa) 5000 350 Variable 35Coefficient ofvariation for MR () 25 30 35 45

ickness ofthe layer (mm) 250 200 300 mdash

icknessVariability () 5 8 15 mdash

Poisson ratio 03 03 03 04

10 Advances in Materials Science and Engineering

7 Long-Term Effect of Cyclic Loading onBlended Samples

In order to explore the long-term eects of cyclic loading 9repeated load triaxial tests were performed under a range ofcyclic loading conditions and varying percentages of RAPcontents Figure 12 presents the variation of the residual strainof the tested samples subjected to 20000 load cycles under twodierent values of conning pressures of 345 kPa and1379 kPa each while the corresponding cyclic deviator stresswas maintained at 3105 kPa and 372 kPa From this gure itcan be inferred that the presence of RAP contents increases theresidual strain considerably for both of the conning pressurescenarios For instance for the repeated load test conducted atthe conning pressure of 345 kPa the residual strain for 100natural aggregate F is 012 after 20000 load cycles while forthe blend containing 50 RAP(2) and 75 RAP(2) thecorresponding gures reach 022 and 060 ie an additionof 50 RAP increases the residual strain by amargin of almost83 while the addition of 75 RAP increases the residualstrain by almost 400 Similarly for the repeated load testsconducted at a conning pressure of 1379 kPa on samples

containing natural aggregateW and the blends with RAP(1) at50 and 75 the residual strain after 20000 load cycles is 55and 300 higher when compared with the correspondingvalue for the 100 natural aggregate W Furthermore it isevident from the gures that almost 60 of the total residualstrain occurred during the rst 2000 load cycles out of the20000 total load cycles applied across all the cases

However it should be emphasized that there is a ten-dency for the elastic shakedown to be less pronounced forblended samples when compared to pure natural aggregatesFor instance for the blended sample 50 W and 50RAP(1) the rate of increase of strain becomes 0000154 forthe load cycles in the range of 2000ndash20000 On the otherhand this gure remained limited to 0000056 for thesample containing 100 natural aggregate W under thesame loading condition

Figure 13 shows the eect of the ratio of ldquocyclic deviatorstress to the conning stress (σdσc)rdquo on the residual strain forthe blended sample containing 50 A and 50 RAP(3)From this gure it can be inferred that the ratio σdσc has asubstantial eect on the residual strain generated undercyclic loading For instance at (σdσc) 09 the residualstrain after 6000 load cycles is limited to 006 however thisvalue reaches 011 and 021 at (σdσc) 18 and(σdσc) 27 respectively yene samples tend to stabilisemore quickly under a lower value of (σdσc) 09 whencompared to the stabilising tendency at the higher values of(σdσc) 18 and (σdσc) 27 which were also in-vestigated in this research A 50ndash60 residual strain occursduring the rst 1000 load cycles out of the total 6000 loadcycles applied during the experimental campaign irre-spective of the σdσc value

8 Summary and Conclusions

(1) yene blended samples (ie RAP combined withnatural granular materials) result in higher MRvalues than those obtained for natural granular

Figure 8 Vehicular load classication used in PerRoad 35

Area outside the threshold limit

Stra

in fr

eque

ncy

Figure 9 Example of frequency distribution of strain within andoutside the threshold limits

Advances in Materials Science and Engineering 11

samples under the same loading conditions whilevariations between MR values and the applied bulkstresses during the resilient modulus tests can beapproximated through power law having coecientof correlation (r) value in the range of 097ndash099

(2) yene CBR values of blended samples decrease withthe addition of RAP contents however a clear

decreasing trend in conjunction with an increasingpercentage of RAP contents could not be found

(3) yene new model for the estimation of MR values in-cludes the stress state through the experimentallydetermined CBR having a coecient of correlation ldquorrdquoequal to approximately 09 with fair distribution of thedata points (MR measured and MR estimated) about

Perc

enta

ge o

f are

a

70

75

80

85

90

95

100

100

A10

0 F

100

W10

0 R

CA75

A

+ 2

5 R

AP(

1)75

A

+ 2

5 R

AP(

2)75

A

+ 2

5 R

AP(

3)75

A

+ 2

5 R

AP(

4)75

F

+ 2

5 R

AP(

1)75

F

+ 2

5 R

AP(

2)75

F

+ 2

5 R

AP(

3)75

F

+ 2

5 R

AP(

4)75

W

+ 2

5 R

AP(

1)75

W

+ 2

5 R

AP(

2)75

W

+ 2

5 R

AP(

3)75

W

+ 2

5 R

AP(

4)75

R

CA +

25

RA

P(1)

75

RCA

+ 2

5 R

AP(

2)75

R

CA +

25

RA

P(3)

75

RCA

+ 2

5 R

AP(

4)50

A

+ 5

0 R

AP(

1)50

A

+ 5

0 R

AP(

2)50

A

+ 5

0 R

AP(

3)50

A

+ 5

0 R

AP(

4)50

F

+ 5

0 R

AP(

1)50

F

+ 5

0 R

AP(

2)50

F

+ 5

0 R

AP(

3)50

F

+ 5

0 R

AP(

4)50

W

+ 5

0 R

AP(

1)50

W

+ 5

0 R

AP(

2)50

W

+ 5

0 R

AP(

3)50

W

+ 5

0 R

AP(

4)50

R

CA +

50

RA

P(1)

50

RCA

+ 5

0 R

AP(

2)50

R

CA +

50

RA

P(3)

50

RCA

+ 5

0 R

AP(

4)25

A

+ 7

5 R

AP(

1)25

A

+ 7

5 R

AP(

2)25

A

+ 7

5 R

AP(

3)25

A

+ 7

5 R

AP(

4)25

F

+ 7

5 R

AP(

1)25

F

+ 7

5 R

AP(

2)25

F

+ 7

5 R

AP(

3)25

F

+ 7

5 R

AP(

4)25

W

+ 7

5 R

AP(

1)25

W

+ 7

5 R

AP(

2)25

W

+ 7

5 R

AP(

3)25

W

+ 7

5 R

AP(

4)25

R

CA +

75

RA

P(1)

25

RCA

+ 7

5 R

AP(

2)25

R

CA +

75

RA

P(3)

25

RCA

+ 7

5 R

AP(

4)

Percentage of area within the critical limit of horizontal strain at the bottom of HMAPercentage of area within the critical limit of vertical strain at the top of subgrade

Figure 10 Percentage of area within the critical limits for horizontal strain at the bottom of HMA and vertical strain at the top of subgrade

30

35

40

45

50

55

60

65

70

100

A10

0 F

100

W10

0 R

CA75

A

+ 2

5 R

AP(

1)75

A

+ 2

5 R

AP(

2)75

A

+ 2

5 R

AP(

3)75

A

+ 2

5 R

AP(

4)75

F

+ 2

5 R

AP(

1)75

F

+ 2

5 R

AP(

2)75

F

+ 2

5 R

AP(

3)75

F

+ 2

5 R

AP(

4)75

W

+ 2

5 R

AP(

1)75

W

+ 2

5 R

AP(

2)75

W

+ 2

5 R

AP(

3)75

W

+ 2

5 R

AP(

4)75

R

CA +

25

RA

P(1)

75

RCA

+ 2

5 R

AP(

2)75

R

CA +

25

RA

P(3)

75

RCA

+ 2

5 R

AP(

4)50

A

+ 5

0 R

AP(

1)50

A

+ 5

0 R

AP(

2)50

A

+ 5

0 R

AP(

3)50

A

+ 5

0 R

AP(

4)50

F

+ 5

0 R

AP(

1)50

F

+ 5

0 R

AP(

2)50

F

+ 5

0 R

AP(

3)50

F

+ 5

0 R

AP(

4)50

W

+ 5

0 R

AP(

1)50

W

+ 5

0 R

AP(

2)50

W

+ 5

0 R

AP(

3)50

W

+ 5

0 R

AP(

4)50

R

CA +

50

RA

P(1)

50

RCA

+ 5

0 R

AP(

2)50

R

CA +

50

RA

P(3)

50

RCA

+ 5

0 R

AP(

4)25

A

+ 7

5 R

AP(

1)25

A

+ 7

5 R

AP(

2)25

A

+ 7

5 R

AP(

3)25

A

+ 7

5 R

AP(

4)25

F

+ 7

5 R

AP(

1)25

F

+ 7

5 R

AP(

2)25

F

+ 7

5 R

AP(

3)25

F

+ 7

5 R

AP(

4)25

W

+ 7

5 R

AP(

1)25

W

+ 7

5 R

AP(

2)25

W

+ 7

5 R

AP(

3)25

W

+ 7

5 R

AP(

4)25

R

CA +

75

RA

P(1)

25

RCA

+ 7

5 R

AP(

2)25

R

CA +

75

RA

P(3)

25

RCA

+ 7

5 R

AP(

4)

Year

s

Number of years required to reach CDF = 01 in terms of horizontal strain at the bottom of HMANumber of years required to reach CDF = 01 in terms of vertical strain at the top of subgrade

Figure 11 Number of years required to reach CDF 01 in terms of horizontal strain at the bottom of HMA and vertical strain at the top ofsubgrade

12 Advances in Materials Science and Engineering

the unity line indicating that the proposed regressionmodel has a moderate to strong correlation

(4) Statistical analysis of simulation results based onPerRoad and KenPave software demonstrates thatthe addition of RAP contents in the subbase layer ofthe copyexible pavement signicantly improves itsperformance against rutting and fatigue

(5) Residual strain during the long-term repeated loadtriaxial test was found to increase in line with anincrease in the ratio of ldquocyclic deviator stress to theconning stress (σdσc)rdquo in correlation to an increasein the percentage of RAP contents in the blendedsample

(6) From the authorrsquos perspective the addition of RAPcontents beyond a certain limit (sim50) may prove tobe detrimental for the overall performance of copyexiblepavement structure

Data Availability

yene experimental data used to support the ndings of thisstudy are included within the article in the form of graphsand tables

Conflicts of Interest

yene author declares that there are no concopyicts of interestregarding the publication of this paper

References

[1] R B Mallick and A Veeraragavan ldquoSustainable pavements inIndia-the time to start is nowrdquo New Building Materials andConstruction World (NBMampCW) Magazine vol 16 no 3pp 128ndash140 2010

[2] A Mohammadinia A Arulrajah S Horpibulsuk andA Chinkulkijniwat ldquoEect of copyy ash on properties of crushedbrick and reclaimed asphalt in pavement basesubbase

000

050

100

150

200

250

300

350

400

450

500

0 2000 4000 6000 8000 10000 12000 14000 16000 18000 20000

Axi

al st

rain

()

Number of load cycles

100 W50 W + 50 RAP(1)25 W + 75 RAP(1)100 F50 F + 50 RAP(2)25 F + 75 RAP(2)

σc = 1379kPa σd = 372kPa

Figure 12 Eect of RAP contents on residual strain under long-term repeated loading

000

005

010

015

020

025

0 1000 2000 3000 4000 5000 6000

Axi

al st

rain

()

Number of load cycles

091827

odoc

Figure 13 Eect of ratio of ldquocyclic deviator stress to the conningstress (σdσc)rdquo on the residual strain under long-term repeatedloading

Advances in Materials Science and Engineering 13

applicationsrdquo Journal of Hazardous Materials vol 321pp 547ndash556 2017

[3] L R Hoyos A J Puppala and C A Ordonez ldquoCharacter-ization of cement-fiber-treated reclaimed asphalt pavementaggregates preliminary investigationrdquo Journal of Materials inCivil Engineering vol 23 no 7 pp 977ndash989 2011

[4] R Taha A Al-Harthy K Al-Shamsi and M Al-ZubeidildquoCement stabilization of reclaimed asphalt pavement aggre-gate for road bases and subbasesrdquo Journal of Materials in CivilEngineering vol 14 no 3 pp 239ndash245 2002

[5] A M Azam and D A Cameron ldquoGeotechnical properties ofblends of recycled clay masonry and recycled concrete ag-gregates in unbound pavement constructionrdquo Journal ofMaterials in Civil Engineering vol 25 no 6 pp 788ndash7982013

[6] A Gabor and D Cameron ldquoProperties of recycled concreteaggregate for unbound pavement constructionrdquo Journal ofMaterials in Civil Engineering vol 24 no 6 pp 754ndash7642012

[7] C S Poon and D Chan ldquoFeasible use of recycled concreteaggregates and crushed clay brick as unbound road sub-baserdquoConstruction and Building Materials vol 20 no 8 pp 578ndash585 2006

[8] A Arulrajah M M Y Ali M M Disfani J Piratheepan andM W Bo ldquoGeotechnical performance of recycled glass-wasterock blends in footpath basesrdquo Journal of Materials in CivilEngineering vol 25 no 5 pp 653ndash661 2013

[9] L T Lee Jr ldquoRecycled glass and dredged materialsrdquo ReportNo ERDC TNDOER-T8 US Army Corps of EngineersEngineer Research and Development Center Mississippi MSUSA 2007

[10] M Ali A Arulrajah M Disfani and J Piratheepan ldquoSuit-ability of using recycled glassmdashcrushed rock blends forpavement subbase applicationsrdquo in Proceedings of the Geo-Frontiers 2011 Conference on Geotechnical Foundation Designpp 1325ndash1334 ASCE Reston VA USA 2011

[11] J Wartman D G Grubb and A S M Nasim ldquoSelectengineering characteristics of crushed glassrdquo Journal ofMaterials in Civil Engineering vol 16 no 6 pp 526ndash5392004

[12] W Kim and J Labuz Resilient Modulus and Strength of BaseCourse with Recycled Bituminous Material Minnesota De-partment of Transportation Research Services Section MNUSA 2007

[13] D Bloomquist G Diamond M Oden B Ruth and M TiaEngineering and Environmental Aspects of Recycled Materialsfor Highway Construction Appendix 1 Final Report 1993

[14] A Hussain and Q Yanjun ldquoEvaluation of asphalt mixescontaining reclaimed asphalt pavement for wearing cour-sesrdquo in Proceedings of the International Conference onTraffic and Transportation Engineering School of CivilEngineering Southwest Jiaotong University ChengduChina 2012

[15] M Solaimanian and M Tahmoressi ldquoVariability analysis ofhot-mix asphalt concrete containing high percentage ofreclaimed asphalt pavementrdquo Transportation Research Re-cord Journal of the Transportation Research Board vol 1543no 1 pp 89ndash96 1996

[16] A Gabr and D A Cameron ldquoProperties of recycled concreteaggregate for unbound pavement constructionrdquo Journal ofMaterials in Civil Engineering vol 24 no 6 pp 754ndash7642011

[17] W-L Huang D-H Lin N-B Chang and K-S LinldquoRecycling of construction and demolition waste via a

mechanical sorting processrdquo Resources Conservation andRecycling vol 37 no 1 pp 23ndash37 2002

[18] A R Pasandın and I Perez ldquoOverview of bituminous mix-tures made with recycled concrete Aggregatesrdquo Constructionand Building Materials vol 74 pp 151ndash161 2015

[19] P Jitsangiam H Nikraz and K Siripun ldquoConstruction anddemolition (CampD) waste as a road base material for WesternAustralia roadsrdquo Australian Geomechanics vol 44 no 3pp 57ndash62 2009

[20] A Nataatmadja and Y L Tan ldquoResilient response of recycledconcrete road aggregatesrdquo Journal of Transportation Engi-neering vol 127 no 5 pp 450ndash453 2001

[21] C Leek and K Siripun ldquoSpecification and performance ofrecycled materials in road pavementsrdquo Contract Rep (01119-1)2010

[22] J Green and J Hall Nondistructive Vibratory Testing ofAirport Pavement 1975

[23] W Heukelom and A Klomp ldquoDynamic testing as a means ofcontrolling pavements during and after constructionrdquo inProceedings of the International Conference on the StructuralDesign of Asphalt Pavements University of Michigan AnnArbor MI USA 1962

[24] Ohio Department of Transportation Pavement DesignManual Ohio Department of Transportation Office ofPavement Engineering OH USA 2008

[25] W D Powell H C Mayhew and M M Nunn ldquoestructural design of bituminous roadsrdquo Laboratory Report1132 Transport and Road Research Laboratory CrowthorneUK 1984

[26] M W Witczak X Qi and M W Mirza ldquoUse of nonlinearsubgrade modulus in AASHTO design procedurerdquo Journal ofTransportation Engineering vol 121 no 3 1995

[27] AASHTO Guide for Design of Pavement Structures Wash-ington DC USA 1993

[28] Asphalt Institute Research and Development of 5e AsphaltInstitutersquos 5ickness Design Manual (MS-1) 9th edition 1982

[29] T Buu Correlation of Resistance R-value and ResilientModulus of Idaho Subgrade Soil Idaho Department ofTransportation Division of Highways ID USA 1980

[30] S Muench J Mahoney and L Pierce WSDOT PavementGuide Washington State Department of TransportationInternet Module Washington DC USA 2009

[31] S Yeh and C Su ldquoResilient properties of Colorado soilsrdquoReport No CDOH-DH-SM-89-9 Colorado Department ofHighways Denver CO USA 1989

[32] M R ompson and Q L Robnett ldquoResilient properties ofsubgrade soilsrdquo Transportation Engineering Journal of ASCEvol 105 pp 71ndash89 1979

[33] W Lee N C Bohra A G Altschaeffl and T D WhiteldquoResilient modulus of cohesive soilsrdquo Journal of Geotechnicaland Geoenvironmental Engineering vol 123 no 2 pp 131ndash136 1997

[34] R Carmichael III and E Stuart ldquoPredicting resilient modulusa study to determine the mechanical properties of subgradesoilsrdquo Transportation Research Record vol 1043 pp 145ndash1481986

[35] E C Drumm Y Boateng-Poku and T Johnson PierceldquoEstimation of subgrade resilient modulus from standardtestsrdquo Journal of Geotechnical Engineering vol 116 no 5pp 774ndash789 1990

[36] M J Farrar and J P Turner Resilient Modulus of WyomingSubgrade Soils 1991

14 Advances in Materials Science and Engineering

[37] M P Jones and M W Witczak ldquoSubgrade modulus on thesan diego test roadrdquo Transportation Research Record Journalof the Transportation Research Board vol 641 pp 1ndash6 1977

[38] A M Rahim and K P George ldquoSubgrade soil indexproperties to estimate resilient modulusrdquo in Proceedings ofthe 83th Annual Meeting of the Transportation ResearchBoard National Research Council Washington DC USA2004

[39] M R ompson and T G LaGrow A Proposed ConventionalFlexible Pavement 5ickness Design Procedure University ofIllinois Peoria IL USA 1988

[40] R Pezo ldquoA general method of reporting resilient modulustests of soils a pavement engineerrsquos point of viewrdquo in Pro-ceedings of the 72nd Annual Meeting of Transportation Re-search Board Washington DC USA 1993

[41] R G Hicks and C L Monismith ldquoResilient properties ofgranular materialrdquo Transportation Research Record vol 345pp 15ndash31 1971

[42] J Uzan ldquoCharacterization of granular materialsrdquo Trans-portation Research Record Journal of the Transportation Re-search Board vol 1022 pp 52ndash59 1985

[43] National Cooperative Highway Research Program ldquoGuide formechanistic-empirical design of new and rehabilitatedpavement structuresrdquo NCHRP 1-37A NCHRP WashingtonDC USA 2004

[44] N M Louay H T Hani and H Ananda ldquoEvaluation ofresilient modulus of subgrade soil by cone penetration testrdquoTransportation Research Record Journal of the TransportationResearch Board vol 1652 pp 236ndash245 1999

[45] S Dai and J Zollars ldquoResilient modulus of Minnesota roadresearch project subgrade soilrdquo Transportation Research Re-cord Journal of the Transportation Research Board vol 1786no 1 pp 20ndash28 2002

[46] L Mohammad B Huang A Puppala and A Allen ldquoRe-gression model for resilient modulus of subgrade soilsrdquoTransportation Research Record Journal of the TransportationResearch Board vol 1687 no 1 pp 47ndash54 1999

[47] B Santa ldquoResilient modulus of subgrade soils comparison oftwo constitutive equationsrdquo Transportation Research RecordJournal of the Transportation Research Board vol 1462pp 79ndash90 1994

[48] H Von Quintus and B Killingsworth Analyses Relating toPavement Material Characterizations and their Effects onPavement Performance 1998

[49] O Porter ldquoe preparation of subgradesrdquo in Proceedings ofthe Nineteenth Annual Meeting Highway Research BoardWashington DC USA December 1939

[50] O J Porter ldquoDevelopment of the original method for highwaydesignrdquo Transactions of the American Society of Civil Engi-neers vol 115 pp 461ndash467 1950

[51] D W Hight and M G H Stevens ldquoAn analysis of theCalifornia Bearing Ratio test in saturated claysrdquoGeotechnique vol 32 no 4 pp 315ndash322 1982

[52] P R Fleming and C D F Rogers ldquoAssessment of pavementfoundations during constructionrdquo Proceedings of the In-stitution of Civil Engineers-Transport vol 111 no 2pp 105ndash115 1995

[53] M R ompson R Marshall and Q L Robnett ldquoResilientproperties of subgrade soilsrdquo Final Report No FHWA-IL-UI-160 University of Illinois Urbana IL USA 1976

[54] B Sukumaran V Kyatham A Shah and D Sheth ldquoSuit-ability of using California bearing ratio test to predict resilientmodulusrdquo in Proceedings Federal Aviation Administration

Airport Technology Transfer Conference Atlantic City NJUSA 2002

[55] N W Lister and D Powell ldquoDesign practices for pavementsin the United Kingdomrdquo in Proceedings of the 6th In-ternational Conference on the Structural Design of AsphaltPavements Ann Arbor MI USA July 1987

[56] S Hossain G Dickerson and C Weaver Comparative Studyof VTM and AASHTO Test Method for CBR Co MaterialsDivision VDOT 2005

[57] N Garg A Larkin and H Brar ldquoA comparative subgradeevaluation using CBR vane shear light weight deflectometerand resilient modulus testsrdquo in Proceedings of the 8th In-ternational Conference on the Bearing Capacity of RoadsRailways and Airfields CRC Press Champaign IL USA2009

[58] M Ayres Development of a rational probabilistic approach forflexible pavement analysis University of Maryland CollegePark MD USA 1997

[59] AASHTO T 307 Determining the Resilient Modulus of Soilsand Aggregate Materials (2012) American Association ofState Highway and Transportation Officials Washington DCUSA 2004

[60] M Arshad and M F Ahmed ldquoPotential use of reclaimedasphalt pavement and recycled concrete aggregate in basesubbase layers of flexible pavementsrdquo Construction andBuilding Materials vol 151 pp 83ndash97 2017

[61] M Arshad ldquoCorrelation between resilient modulus (MR) andconstrained modulus (Mc) values of granular materialsrdquoConstruction and Building Materials vol 159 pp 440ndash4502018

[62] P Guo and J Emery ldquoImportance of strain level inevaluating resilient modulus of granular materialsrdquo In-ternational Journal of Pavement Engineering vol 12 no 2pp 187ndash199 2011

[63] E J McGarrah ldquoEvaluation of current practices of reclaimedasphalt pavementvirgin aggregate as base course materialrdquoNo WA-RD 7131 Federal Highway AdministrationWashington DC USA 2007

[64] T B Alam M Abdelrahman and S A Schram ldquoLaboratorycharacterisation of recycled asphalt pavement as a base layerrdquoInternational Journal of Pavement Engineering vol 11 no 2pp 123ndash131 2010

[65] T Bennert and A Maher ldquoe development of a performancespecification for granular base and subbase materialrdquo ReportNo FHWA-NJ-2005-003 Department of TransportationEwing Township NJ USA 2005

[66] T H Wonnacott H omas and J Ronald ldquoRegression asecond course in statisticsrdquo No 04 QA2782 W6Wiley NewYork NY USA 1981

[67] W Penny and S Roberts Neural network predictions witherror bars Dept of Electrical and Electronic EngineeringTechnology and Medicine Research Report TR-97-1 ImperialCollege of Science London UK 1997

[68] R Dybowski and S J Roberts ldquoConfidence intervals andprediction intervals for feed-forward neural networksrdquoClinical Applications of Artificial Neural Networks pp 298ndash326 2001

[69] J Hauke and T Kossowski ldquoComparison of values ofPearsonrsquos and Spearmanrsquos correlation coefficients on the samesets of datardquo Quaestiones Geographicae vol 30 no 2pp 87ndash93 2011

[70] K-z Yan H-b Xu and G-h Shen ldquoNovel approach toresilient modulus using routine subgrade soil propertiesrdquo

Advances in Materials Science and Engineering 15

International Journal of Geomechanics vol 14 no 6 article04014025 2013

[71] Y H Chan ldquoBiostatistics 104 correlational analysisrdquoSingapore Medical Journal vol 44 no 12 pp 614ndash6192003

[72] B M Damghani D Welch C OrsquoMalley and S Knights ldquoemisleading value of measured correlationrdquoWilmott vol 2012no 62 pp 64ndash73 2012

[73] L B Christensen B Johnson and L A Turner ldquoResearchmethods design and analysisrdquo 2011

[74] W J Dixon and F J Massey Introduction to StatisticalAnalysis McGraw-Hill New York NY USA 1969

[75] B Colbert and Z You ldquoe determination of mechanicalperformance of laboratory produced hot mix asphalt mixturesusing controlled RAP and virgin aggregate size fractionsrdquoConstruction and Building Materials vol 26 no 1 pp 655ndash662 2012

[76] D H Timm and D E Newcomb ldquoPerpetual pavement designfor flexible pavements in the USrdquo International Journal ofPavement Engineering vol 7 no 2 pp 111ndash119 2006

[77] Y H Huang Pavement Analysis and Design Prentice-HallEnglewood Cliffs NJ USA 2nd edition 1993

[78] L Walubita W Liu and T Scullion Texas perpetualpavements-Experience overview and the way forward Tech-nical Report No 0-4822-3 Texas Transportation InstituteTexas AampM University College Station TX USA 2010

[79] D Timm and D Newcomb ldquoCalibration of flexible pavementperformance equations for Minnesota road research projectrdquoTransportation Research Record Journal of the TransportationResearch Board no 1853 pp 134ndash142 2003

16 Advances in Materials Science and Engineering

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Submit your manuscripts atwwwhindawicom

noticeably in correspondence to the increasing content inthe blended samples incorporating granular (A) and RAP(1)For instance the blend containing 25RAP(1) achieves only74 of the CBR value achieved by the aggregate (A) (naturalmaterial) at the same level of compaction eort ie 65blows Similarly the corresponding value for blends con-taining 50 RAP(1) 75 RAP(1) and 100 RAP(1) islimited to 5625 325 and 225 respectively Likewise

the trend can also be observed for the other two compactioneorts consisting of 10 and 30 blows

42 Eect of RAP Contents on Resilient Modulus (MR)Forty-eight blended samples were prepared by mixing thefour types of RAPmaterials with natural granular samplesAF W and RCA in proportion with RAP contents of 25

Table 2 Characterisation of the tested materials

MaterialCompaction characteristics (AASHTO T180)

Maximum dry density (kNm3) Optimum moisture content ()Natural aggregates 219ndash233 55ndash71RAPs 197ndash214 64ndash91RCA 207 75

Gradation characteristics (AASHTO T27-99)D10 (mm) D30 (mm) D50 (mm) Cu Cc Sand size (mm) (475ndash95) mm

Natural aggregate A 015 045 1 117 077 70 10Natural aggregate F 015 15 9 1000 100 35 10Natural aggregate W 06 5 15 333 208 25 12RAP(1) 03 12 275 133 120 64 22RAP(2) 03 12 275 133 120 60 30RAP(3) 15 5 65 50 222 27 50RAP(4) 03 12 2 92 175 82 10RCA 025 15 65 400 09 40 18

Flat and elongated particles (ASTM D 4791)Natural aggregatesRAPsRCA Limited to 6

Shear strength parameters under quick shear testNatural aggregatesRAPsRCA Friction angle Cohesion

36degndash43deg 20‒30 kPaPhysical properties of recovered bitumen binder

RAPs 60degC viscosity (poise)(ASTM D4402)

25degC penetration (dmm)(ASTM D5-06) Softening point (degC) (ASTM D36-76)

23500ndash46700 20ndash52 62ndash67

Table 3 Matrix of the testing program

Natural aggregateRCA RAP Minimum number ofresilient modulus tests

Minimum numberof CBR tests

Minimum number ofrepeated load triaxial tests

Natural aggregate A F W mdash 3 3 2RCA mdash 1 1 mdashBlends of natural aggregates with RAPs 4times 3lowast 3times 3times 4 36 3times 3times 4 36 7Blends of RCA with RAPs 4times 3lowast 3times 412 3times 412 mdashTotal 52 52 9lowastBlended samples were prepared by mixing 25 50 and 75 (by weight) of each RAP type with the natural aggregates and RCA

Transducer to measurepenetration

Annular weights

Sample

Standard mould

Applied load

Standard plunger

Figure 1 A schematic diagram of the CBR test

Stre

sss

trai

n le

vel

Time

Deformation vs time

Stress vs time

Figure 2 Typical shape of applied repeated load cycles and thegenerated deformation curve

4 Advances in Materials Science and Engineering

50 and 75 for each Figures 4(a)ndash4(d) show the eects ofthe addition of these RAPs on themeasuredMR values over arange of bulk stresses as specied in AASHTOT 307-99 (68)Variation ofMR values with bulk stress can be approximatedthrough trend lines based on a power function having thecoecient of determination (R2) in the range of 095ndash099From these trend lines it is evident that MR values increasenot only due to the increase in bulk stress but also incombination with the addition of RAP contents ie blendedsamples give higher MR values when compared to thoseobtained from the natural samples of granular A F W andRCA More specically for instance at a bulk stress ofsim673 kPa MR value for the 100 granular W is 320MPawhile the corresponding values for blended samples in-corporating 25 50 and 75 of RAP(1) are 340MPa360MPa and 390MPa respectively

A similar trend in MR values was observed at lowerlevels of bulk stress or more precisely over the entirerange of bulk stresses considered during the testing

campaign In some cases sim50 increase in MR values wasobserved for the blends containing 75 RAP contents Ingeneral for most of the blended samples containing 25and 50 RAP contents the corresponding increase in MRvalues was in the range of 5ndash15 and 10ndash20 respectivelyAn important point is that the addition of RAPs to RCAinduced the most signicant increase in the resilientmoduli when compared with the increase inMR when RAPwas added to granular samples Similar observations havealso been documented by many researchers including Kimand Labuz [12] MacGregor et al [63] Alam et al [64] andBennert and Maher [65]

5 Development of Correlation betweenResilient Modulus and CBR Values

51 Proposed Correlation and eoretical BackgroundFor this study an attempt has been made to correlate theMR values with the CBR values on the basis of a commonvalue of bulk stress identied during both types of testsyenis should be emphasize that CBR values tend to decreasewith addition of RAP contents while reverse is the situationin case of resilient modulus values Such trends are pri-marily due to the fact that loading for the resilient modulustest is dynamic in nature while in the case of the CBR test itis virtually static

Fundamentally axial stress is applied during the CBRtests through a plunger (σpa) in addition to an axial sur-charge weight (σsa) as shown in Figure 5 However lateralstress on the walls of the CBRmould can be estimated on thebasis of the lateral earth pressure coecient (Ka) as describedin classical soil mechanics such that

σpl Kaσpa

σsl Kaσsa

Ka 1minus sin(ϕ)

(1)

where ϕ is the eective angle of internal friction of the soilsample (blend) under consideration

Table 4 Loading sequence for the resilient modulus test as per AASHTO T 307 protocol

Seq No No of load applied Conning stress Max axial stress Cyclic axial stress Contact stress Total axial stress (kPa)σ3 (kPa) σmax (kPa) σcyclic (kPa) 01σmax (kPa)0 750 1034 1034 931 103 20681 100 207 207 186 21 4142 100 207 414 373 41 6213 100 207 621 559 62 8284 100 345 345 31 35 695 100 345 689 62 69 10346 100 345 1034 931 103 13797 100 689 689 62 69 13788 100 689 1379 1241 138 20689 100 689 2068 1861 207 275710 100 1034 689 62 69 172311 100 1034 1034 931 103 206812 100 1034 2068 1861 207 310213 100 1379 1034 931 103 241314 100 1379 1379 1241 138 275815 100 1379 2758 2482 276 4137

0

10

20

30

40

50

60

70

80

90

1950 2000 2050 2100 2150 2200 2250

Uns

oake

d CB

R (

)

Unit weight (kNm3)

A75 A + 25 RAP(1)50 A + 50 RAP(1)

25 A + 75 RAP(1)RAP(1)

Figure 3 Eect of RAP contents on CBR values

Advances in Materials Science and Engineering 5

It is interesting to note that the 3-point CBR test en-compasses a wide range of dry and bulk density in thesample while on the other hand each resilient modulus

test uses a unique value of the samplersquos dry and bulkdensity To estimate a unique value of the bulk stress duringthe CBR test which is analogous to the bulk stress valueidentied from resilient modulus test the following pro-cedure was adopted

(1) Determine the dry density of the resilient modulussample

(2) Estimate the CBR value corresponding to that drydensity value

(3) Determine the axial stress (σpa) value correspondingto the CBR value

(4) Calculate the bulk stress using the following relation

σbulk θ σ1 + σ2 + σ3 σpa + σsa( ) + 2Ka σpa + σsa( ) (2)

Using a unique value of bulk stress on the basis ofequation (2) the corresponding resilient modulus valuefrom the actual experimental data (MR test) was matchedand then a correlation between CBR value (point 2)and the resilient modulus value in terms of the power

y = 52x064

R2 = 099

y = 88x056

R2 = 098

y = 136x051

R2 = 095

y = 101x056

R2 = 098

0

50

100

150

200

250

300

350

400

450

0 200 400 600 800

MR (

MPa

)

Bulk stress (kPa)

100 A75 A + 25 RAP(2)

50 A + 50 RAP(2)25 A + 75 RAP(2)

(a)

100 F75 F + 25 RAP(3)

50 F + 50 RAP(3)25 F + 75 RAP(3)

y = 517x064

R2 = 099

y = 745x058

R2 = 099

y = 101x054

R2 = 097

y = 972x057

R2 = 096

0

50

100

150

200

250

300

350

400

450

0 200 400 600 800

MR (

MPa

)

Bulk stress (kPa)

(b)

y = 517x064

R2 = 099

y = 745x058

R2 = 099

y = 101x054

R2 = 097

y = 972x057

R2 = 096

0

50

100

150

200

250

300

350

400

450

0 200 400 600 800

MR (

MPa

)

Bulk stress (kPa)

100 W75 W + 25 RAP(1)

50 W + 50 RAP(1)25 W + 75 RAP(1)

(c)

y = 517x064

R2 = 099

y = 745x058

R2 = 099

y = 101x054

R2 = 097

y = 972x057

R2 = 096

0

50

100

150

200

250

300

350

400

450

0 100 200 300 400 500 600 700 800

MR (

MPa

)

Bulk stress (kPa)

100 RCA25 RCA + 75 RAP(4)

50 RCA + 50 RAP(4)75 RCA + 25 RAP(4)

(d)

Figure 4 Variation ofMR value with bulk stress and percentage of RAP contents for (a) naturalA (b) natural F (c) naturalW and (d) RCA

Plunger

Surchargeweight

Soil sample

Lateral stress due toloading of plunger (σpl)

Lateral stress due tosurcharge loading (σsl)

Figure 5 An assumed conguration of axial and lateral stressesduring CBR test

6 Advances in Materials Science and Engineering

function having a coefficient of determination sim081 canbe given as

MR 4937(CBR)059

(3)

Table 5 shows the experimental data and the estimatedvalues of MR based on the four steps explained above andequation (3)

Figure 6 shows the capabilities of the proposed regressionmodel on the basis of the distribution of the data pointswhich in fact involves the experimentally determined andestimated MR values along the unity line giving a 95prediction and confidence interval is figure illustrates thatthere is an almost equal distribution of the data points on bothsides of the unity line Additionally the entire set of the datapoints is confined within the 95 prediction interval which isdefined as the interval around the linear regression line suchthat 95 of the predicted values will fall in this intervalFurther details on the mathematical framework of the pre-diction and the confidence interval can be found in standardtextbooks dealing with statistics and probability analysis suchas those authored by Wonnacott and Ronald [66] Penny andRoberts [67] and Dybowski and Roberts [68]

52 Statistical Analysis of the Proposed Model A Pearsonrsquoscorrelation coefficient (r) as given by equation (4) is ameasure of the strength and direction of linear associationthat exists between two continuous variables More specif-ically for the drawn line of best fit for sample data points oftwo variables Pearsonrsquos correlation indicates how well thedata points fit this new modelline of best fit and its nu-merical value indicates how far away all these data points areto the line of best fit (ie how well the data points fit this newmodelline of best fit) [69 70]

r 1113936

ni1 ui minus ui( 1113857 ti minusti( 1113857

1113936ni1 ui minus ui( 1113857

2ti minus ti( 1113857

21113960 1113961

1113969 (4)

where ui and ti experimental and predicted values re-spectively for the ith output ui average of experimentaloutputs and n size of sample

e statistical value of r may range from minus1 for a perfectnegative linear relationship (inversely related) to +1 for aperfect positive linear relationship (directly related) In gen-eral from theoretical point of view the strength of the linearrelationship can be categorised as ldquovery strongrdquo ldquomoderatelystrongrdquo and ldquofairly strongrdquo for the corresponding numericalvalues of r in the range 08ndash10 06ndash08 and 03ndash05 [71] Itshould be emphasized that if r 00 it does not necessarilymean that the two variables have no relationship In order tolook into the real strength of the correlation usually a sta-tistical test of significance is performed as discussed in [72]For this study three different types of statistical tests wereapplied to assess the significance of the developed correlationpresented in equation (3) and Table 5

Case 1 t-Test for the assessment of the implication of co-efficient of correlation (r) at a specific degree of freedom andlevel of significance [73]

is provides the researcher with some idea of how largea correlation coefficient must be before it can be consideredas demonstrating that there really is a relationship betweentwo variables (in our case the (MR)measured and CBR values)It may be the situation that two variables are related bychance and a hypothesis test for r allows the researcher todecide whether the observed r could have emerged by chanceor not e null hypothesis is that there is no relationshipbetween the two variables at is if ρ is the true correlationcoefficient for the two variables and when all populationvalues have been observed then the null hypothesis can begiven as

H0 ρ 0 (5)

e alternative hypothesis could be written as

HA ρne 0 (6)

whereas the standardised t-test for the null hypothesis that ris equal to zero can be written as

t r

nminus 21minus r2

1113970

(7)

where n is the number of paired observations in the givensample

e null hypothesis is evaluated by comparing the t-statistic of equation (7) with t-critical (201) obtained from tdistribution having the nminus 2 degree of freedom

Case 2 Direct comparison of the coefficient of correlationvalue (09) with the r-critical value (027) obtained from astatistical table corresponding to a specific degree of freedomand level of significance [61 74]

Case 3 It often becomes mandatory to statistically evaluatethe difference between two datasets obtained by two dif-ferent sources As in our case one set of MR values wasobtained experimentally using the AASHTOT 307-99(2004)protocol and the other set of MR values was obtained usingthe proposed correlation A standard t-test was performed toevaluate the difference between the paired values of(MR)measured and (MR)estimated at a specific degree of freedomand level of significance [74 75]

Table 6 summarises the statistical analysis of the abovethree cases

6 Assessment of Pavement PerformanceContaining RAPContent in Its Subbase Layer

To examine the performance of the pavement containingnatural aggregates mixed with RAP and used as subbasematerials the following analyses were performed usingcomputer software simulation

(1) To access the likelihood that critical pavement re-sponses exceed predefined thresholds using com-puter program PerRoad [76]

Advances in Materials Science and Engineering 7

(2) To determine the stresses and strains at critical lo-cations in the pavement structure using computerprogram KenPave developed by the University ofKentucky [77]

PerRoad is a Monte Carlo-based simulation softwareused to develop probability-based analysis for flexiblepavement is software can easily demonstrate the influ-ence of the MR values of the pavement material on the

Table 5 A comparison of measured and estimated MR values along with CBR values

MaterialBlend Dry unit weightachieved (kNm3) CBR () Total axial

stress (kPa)

Estimatedbulk stress

in CBR test (kPa)

MR values measuredprojected (MPa)

MR valuesestimated(MPa)

100 A 211 65 9780 1663 550 584100 F 221 74 11130 1892 600 631100 W 224 85 12780 2173 670 685100 RCA 192 53 7980 1357 410 51875 A+ 25 RAP(1) 207 47 7080 1204 470 48250 A+ 50 RAP(1) 205 31 4680 796 300 37725 A+ 75 RAP(1) 202 22 3330 566 280 30875 A+ 25 RAP(2) 203 55 8280 1408 505 52950 A+ 50 RAP(2) 208 39 5880 1000 410 43225 A+ 75 RAP(2) 213 17 2580 439 260 26475 A+ 25 RAP(3) 201 51 7680 1306 490 50650 A+ 50 RAP(3) 205 30 4530 770 315 37025 A+ 75 RAP(3) 199 19 2880 490 310 28275 A+ 25 RAP(4) 197 55 8280 1408 505 52950 A+ 50 RAP(4) 198 43 6480 1102 402 45825 A+ 75 RAP(4) 192 27 4080 694 252 34775 F+ 25 RAP(1) 208 52 7830 1331 538 51250 F+ 50 RAP(1) 213 41 6180 1051 455 44525 F+ 75 RAP(1) 201 14 2130 362 356 23575 F+ 25 RAP(2) 205 59 8880 1510 525 55250 F+ 50 RAP(2) 199 48 7230 1229 407 48825 F+ 75 RAP(2) 197 31 4680 796 408 37775 F+ 25 RAP(3) 201 62 9330 1586 667 56850 F+ 50 RAP(3) 192 41 6180 1051 516 44525 F+ 75 RAP(3) 208 19 2880 490 343 28275 F+ 25 RAP(4) 213 43 6480 1102 515 45850 F+ 50 RAP(4) 201 32 4830 821 490 38425 F+ 75 RAP(4) 213 13 1980 337 278 22575 W+25 RAP(1) 208 51 7680 1306 510 50650 W+50 RAP(1) 205 44 6630 1127 500 46425 W+75 RAP(1) 199 16 2430 413 240 25575 W+25 RAP(2) 197 55 8280 1408 502 52950 W+50 RAP(2) 199 31 4680 796 438 37725 W+75 RAP(2) 213 12 1830 311 265 21575 W+25 RAP(3) 201 48 7230 1229 520 48850 W+50 RAP(3) 213 35 5280 898 447 40525 W+75 RAP(3) 207 21 3180 541 255 29975 W+25 RAP(4) 205 45 6780 1153 480 47050 W+50 RAP(4) 199 34 5130 872 473 39825 W+75 RAP(4) 192 9 1380 235 213 18175 RCA+ 25 RAP(1) 208 38 5730 974 486 42550 RCA+ 50 RAP(1) 213 23 3480 592 330 31625 RCA+ 75 RAP(1) 201 12 1830 311 187 21575 RCA+ 25 RAP(2) 213 38 5730 974 525 42550 RCA+ 50 RAP(2) 201 31 4680 796 356 37725 RCA+ 75 RAP(2) 214 14 2130 362 200 23575 RCA+ 25 RAP(3) 201 32 4830 821 447 38450 RCA+ 50 RAP(3) 205 15 2280 388 226 24525 RCA+ 75 RAP(3) 199 9 1380 235 148 18175 RCA+ 25 RAP(4) 192 39 5880 1000 473 43250 RCA+ 50 RAP(4) 201 13 1980 337 200 22525 RCA+ 75 RAP(4) 202 18 2730 464 161 273

8 Advances in Materials Science and Engineering

cumulative damage factor (CDF) It also demonstrates thelikelihood that critical pavement responses could exceedpredened thresholds which are the horizontal tensile strainof 70 microns at the bottom of the asphalt concrete (which islinked with fatigue cracking) and the vertical compressivestrain of 200 microns at the top of the subgrade (which isassociated with the structural rutting) [78]

61 Pavement Structure and Material CharacteristicsFigure 7 shows a typical cross section of copyexible pavementswhich consists of a hot mix asphalt layer supported by theunbound base unbound subbase and compacted subgradeyene thickness of each layer generally depends on the tracload or more specically the equivalent single axle load(ESAL) during the proposed life cycle of the road

In this parametric study the focus is placed on how theproperties of granular subbase materials are changed by theaddition of a certain amount of RAP and their eect on thepavementrsquos performance As such the resilient modulus ofthe granular base and the asphalt concrete is xed yenestructure of the pavement to be simulated and the propertiesof materials in dierent layers are summarised in Table 7 Inthis particular study the subbase material will be one of theaggregates or aggregateRAP blends tested during the ex-perimental studies of this research

yene properties of the dierent pavement layers used inthe analysis are shown in Table 7 yene bulk stresses at the top

and bottom of the granular subbase layer were determinedusing the computer program KenPave For the selectedHMA resilient moduli (MR 5000MPa) the bulk stresseswere found in the range of 27 kPa to 30 kPa and 14 kPa to18 kPa at the top and bottom of the subbase layers re-spectively for the wheel load of 40 kN In the simulationsvalues of MR are used corresponding to the bulk stress of100 kPa

62 Trac Load For this parametric study the trac datafor urban interstate highways as recommended byAASHTO were used In the case of the PerRoad softwaretrac is separated by axle type single axle tandem axletridem axle and steer axle After determining the percentageof each axle type in the total trac trac is then subdividedinto weight classes in 2 kip intervals yene following is thesummary of the trac data the average annual daily trac(AADT) is 1000 vehicles with 10 being trucks annualgrowth rate of trac is 4 the directional distribution is50 and the percentages of single tandem and tridem axlesare 5573 4266 and 161 respectively yene rest of thetrac loading characteristics in terms of the distribution ofvehicle types and axle weights are described in Figure 8yenese values were used as input in PerRoad 35 Axle weightswere used to evaluate the response of the pavement layers interms of stresses strains and deformations at critical lo-cations of certain layers of the copyexible pavement

Table 6 Summary of the statistical analysis of the proposed model at an alpha value of 005 which matches to 95 condence level

Case Comments

1 t-Critical 20 t-Statistic 1459Since t-statisticgt t-critical which implies that value of the correlation coecient is not dueto sampling error the null hypothesis is rejected and it is concluded that there is a

signicant correlation between (MR)measured and CBR value in the population

2 r-Pearson 09 r-Critical 027

Since r-Pearsongt r-critical which implies that the null hypothesis is rejectedit is quite realistic to accept the ldquoalternative hypothesisrdquo that is the value of r that

we have obtained from our sample represents a real relationship between (MR)measuredand CBR value in the population

3 t-Critical 20 t-Statistic 052Since t-statisticlt t-critical which implies that the null hypothesis is accepted

it is concluded that there is an insignicant dierence between(MR)measured and (MR)correlated values in the population

0

100

200

300

400

500

600

700

800

0 200 400 600 800

MR

(esti

mat

ed)

MR (measured)

1 1 line

95confidence

interval

95prediction

interval

Figure 6 A comparison of estimated and measured MR values along the unity line

Advances in Materials Science and Engineering 9

63 Pavement Performance Criteria In the design ofconventional flexible pavements pavement sectionsare designed corresponding to a cumulative damagefactor (CDF) of 10 which corresponds to a terminallevel of pavement damage For perpetual pavementshowever it is recommended that the CDF is equal to 01at the end of its design life [76] e fatigue and ruttingalgorithms developed at MnROAD [79] for the cali-bration of flexible pavement performance equations wereused to predict pavement damage in cases where pave-ment responses exceeded these thresholds ese corre-lations are as follows

Nf 283lowast 10minus61εt

1113888 1113889

3148

(fatigue)

Nr 6026lowast 10minus81εv

1113888 1113889

387

(ritting)

(8)

where Nf number of load repetitions when fatigue failureoccurs Nr number of load repetition when rutting failureoccurs εt the horizontal tensile strain at the bottom of theHMA and εv the vertical compressive strain at the top ofthe subgrade

It should be noted that the damage of rutting estimatedby PerRoad only takes into account the permanent de-formation in the subgrade Any rutting associated with thedeformation of granular subbase materials is not consideredAccording to the test results in this study use of RAP ingranular subbase layers may induce substantial residualdeformation Further investigation should be performed toget a better understanding of its influence on the rutting offlexible pavements

64 Simulation Results and Discussion Simulation resultsare obtained and discussed in terms of

(1) e likelihood of the tensile strain at the bottom ofthe HMA exceeding 70 με

(2) e likelihood of the vertical strain at the top of thesubgrade soil exceeding 200 με

(3) e number of years it could take to reach a CDF of01 (the threshold level) for fatigue damage

(4) e number of years it could take to reach a CDF of01 for damage induced by rutting

Figure 9 illustrates the concept frequency distributionfor strain both within and outside the threshold limits

We first examine the likelihood of critical pavementresponses exceeding the predefined thresholds when theresilient modulus of the asphalt concrete is 5000MPa anddifferent aggregates or aggregate-RAP blends are used inthe granular subbase layer Figure 10 summarises (1) thelikelihood of the tensile strain at the bottom of the HMAremaining within the critical value of 70 με and (2) thelikelihood of the vertical strain at the top of the subgradesoil exceeding 200 με From this figure it can be inter-preted that all of the blends result in better pavementperformance than the natural aggregate both in terms ofthe tensile strains at the bottom of the HMA and thevertical compressive strains at the top of the subgrade soilFor instance the natural aggregates and RCA on averagehave an 813 likelihood that horizontal strain at thebottom of the HMA will remain within the critical limit of70 με

On the other hand the likelihood for blended ma-terials containing 25 50 and 75 of RAP materials inthe blended samples may reach (on average) 85758937 and 9377 (respectively) chance of remainingwithin the limit Similarly the likelihood that the com-pressive strain at the top of the subgrade will not exceedthe critical value of 200 microns is 8828 (naturalsamples) 9346 (25 RAP material blends) 9557(50 RAP material blends) and 982 (75 RAP ma-terial blends)

Figure 11 shows the number of years required to reacha CDF of 01 when fatigue is controlled by the horizontaltensile strain at the bottom of the subgrade and the HMAand vertical structural rutting are controlled by the verticalcompressive strain at the top of the subgrade e numberof years required to reach a CDF of 01 in general in-creases in line with the increase in the quantity of RAP inthe blend For example the number of years required toreach a CDF of 01 in terms of fatigue damage at thebottom of HMA is 4033 years for natural samples whilethe corresponding figure for the blends containing 75RAP is 5168 years on average A similar trend regarding anincrease in the number of years required to reach a CDF of01 in terms of structural damage at the top of the subgradewas also observed Furthermore for all the cases thenumber of years to reach a CDF of 01 was more than40 years but it is clear that fatigue will be the predominantpavement failure mode

Asphalt concrete

Unbound base

Unbound subbase

Compacted subgrade

Natural subgrade

Figure 7 A typical cross section of flexible pavement

Table 7 Material properties and pavement layer thicknesses

Parameters HMA Base course Subbasecourse Subgrade

MR (MPa) 5000 350 Variable 35Coefficient ofvariation for MR () 25 30 35 45

ickness ofthe layer (mm) 250 200 300 mdash

icknessVariability () 5 8 15 mdash

Poisson ratio 03 03 03 04

10 Advances in Materials Science and Engineering

7 Long-Term Effect of Cyclic Loading onBlended Samples

In order to explore the long-term eects of cyclic loading 9repeated load triaxial tests were performed under a range ofcyclic loading conditions and varying percentages of RAPcontents Figure 12 presents the variation of the residual strainof the tested samples subjected to 20000 load cycles under twodierent values of conning pressures of 345 kPa and1379 kPa each while the corresponding cyclic deviator stresswas maintained at 3105 kPa and 372 kPa From this gure itcan be inferred that the presence of RAP contents increases theresidual strain considerably for both of the conning pressurescenarios For instance for the repeated load test conducted atthe conning pressure of 345 kPa the residual strain for 100natural aggregate F is 012 after 20000 load cycles while forthe blend containing 50 RAP(2) and 75 RAP(2) thecorresponding gures reach 022 and 060 ie an additionof 50 RAP increases the residual strain by amargin of almost83 while the addition of 75 RAP increases the residualstrain by almost 400 Similarly for the repeated load testsconducted at a conning pressure of 1379 kPa on samples

containing natural aggregateW and the blends with RAP(1) at50 and 75 the residual strain after 20000 load cycles is 55and 300 higher when compared with the correspondingvalue for the 100 natural aggregate W Furthermore it isevident from the gures that almost 60 of the total residualstrain occurred during the rst 2000 load cycles out of the20000 total load cycles applied across all the cases

However it should be emphasized that there is a ten-dency for the elastic shakedown to be less pronounced forblended samples when compared to pure natural aggregatesFor instance for the blended sample 50 W and 50RAP(1) the rate of increase of strain becomes 0000154 forthe load cycles in the range of 2000ndash20000 On the otherhand this gure remained limited to 0000056 for thesample containing 100 natural aggregate W under thesame loading condition

Figure 13 shows the eect of the ratio of ldquocyclic deviatorstress to the conning stress (σdσc)rdquo on the residual strain forthe blended sample containing 50 A and 50 RAP(3)From this gure it can be inferred that the ratio σdσc has asubstantial eect on the residual strain generated undercyclic loading For instance at (σdσc) 09 the residualstrain after 6000 load cycles is limited to 006 however thisvalue reaches 011 and 021 at (σdσc) 18 and(σdσc) 27 respectively yene samples tend to stabilisemore quickly under a lower value of (σdσc) 09 whencompared to the stabilising tendency at the higher values of(σdσc) 18 and (σdσc) 27 which were also in-vestigated in this research A 50ndash60 residual strain occursduring the rst 1000 load cycles out of the total 6000 loadcycles applied during the experimental campaign irre-spective of the σdσc value

8 Summary and Conclusions

(1) yene blended samples (ie RAP combined withnatural granular materials) result in higher MRvalues than those obtained for natural granular

Figure 8 Vehicular load classication used in PerRoad 35

Area outside the threshold limit

Stra

in fr

eque

ncy

Figure 9 Example of frequency distribution of strain within andoutside the threshold limits

Advances in Materials Science and Engineering 11

samples under the same loading conditions whilevariations between MR values and the applied bulkstresses during the resilient modulus tests can beapproximated through power law having coecientof correlation (r) value in the range of 097ndash099

(2) yene CBR values of blended samples decrease withthe addition of RAP contents however a clear

decreasing trend in conjunction with an increasingpercentage of RAP contents could not be found

(3) yene new model for the estimation of MR values in-cludes the stress state through the experimentallydetermined CBR having a coecient of correlation ldquorrdquoequal to approximately 09 with fair distribution of thedata points (MR measured and MR estimated) about

Perc

enta

ge o

f are

a

70

75

80

85

90

95

100

100

A10

0 F

100

W10

0 R

CA75

A

+ 2

5 R

AP(

1)75

A

+ 2

5 R

AP(

2)75

A

+ 2

5 R

AP(

3)75

A

+ 2

5 R

AP(

4)75

F

+ 2

5 R

AP(

1)75

F

+ 2

5 R

AP(

2)75

F

+ 2

5 R

AP(

3)75

F

+ 2

5 R

AP(

4)75

W

+ 2

5 R

AP(

1)75

W

+ 2

5 R

AP(

2)75

W

+ 2

5 R

AP(

3)75

W

+ 2

5 R

AP(

4)75

R

CA +

25

RA

P(1)

75

RCA

+ 2

5 R

AP(

2)75

R

CA +

25

RA

P(3)

75

RCA

+ 2

5 R

AP(

4)50

A

+ 5

0 R

AP(

1)50

A

+ 5

0 R

AP(

2)50

A

+ 5

0 R

AP(

3)50

A

+ 5

0 R

AP(

4)50

F

+ 5

0 R

AP(

1)50

F

+ 5

0 R

AP(

2)50

F

+ 5

0 R

AP(

3)50

F

+ 5

0 R

AP(

4)50

W

+ 5

0 R

AP(

1)50

W

+ 5

0 R

AP(

2)50

W

+ 5

0 R

AP(

3)50

W

+ 5

0 R

AP(

4)50

R

CA +

50

RA

P(1)

50

RCA

+ 5

0 R

AP(

2)50

R

CA +

50

RA

P(3)

50

RCA

+ 5

0 R

AP(

4)25

A

+ 7

5 R

AP(

1)25

A

+ 7

5 R

AP(

2)25

A

+ 7

5 R

AP(

3)25

A

+ 7

5 R

AP(

4)25

F

+ 7

5 R

AP(

1)25

F

+ 7

5 R

AP(

2)25

F

+ 7

5 R

AP(

3)25

F

+ 7

5 R

AP(

4)25

W

+ 7

5 R

AP(

1)25

W

+ 7

5 R

AP(

2)25

W

+ 7

5 R

AP(

3)25

W

+ 7

5 R

AP(

4)25

R

CA +

75

RA

P(1)

25

RCA

+ 7

5 R

AP(

2)25

R

CA +

75

RA

P(3)

25

RCA

+ 7

5 R

AP(

4)

Percentage of area within the critical limit of horizontal strain at the bottom of HMAPercentage of area within the critical limit of vertical strain at the top of subgrade

Figure 10 Percentage of area within the critical limits for horizontal strain at the bottom of HMA and vertical strain at the top of subgrade

30

35

40

45

50

55

60

65

70

100

A10

0 F

100

W10

0 R

CA75

A

+ 2

5 R

AP(

1)75

A

+ 2

5 R

AP(

2)75

A

+ 2

5 R

AP(

3)75

A

+ 2

5 R

AP(

4)75

F

+ 2

5 R

AP(

1)75

F

+ 2

5 R

AP(

2)75

F

+ 2

5 R

AP(

3)75

F

+ 2

5 R

AP(

4)75

W

+ 2

5 R

AP(

1)75

W

+ 2

5 R

AP(

2)75

W

+ 2

5 R

AP(

3)75

W

+ 2

5 R

AP(

4)75

R

CA +

25

RA

P(1)

75

RCA

+ 2

5 R

AP(

2)75

R

CA +

25

RA

P(3)

75

RCA

+ 2

5 R

AP(

4)50

A

+ 5

0 R

AP(

1)50

A

+ 5

0 R

AP(

2)50

A

+ 5

0 R

AP(

3)50

A

+ 5

0 R

AP(

4)50

F

+ 5

0 R

AP(

1)50

F

+ 5

0 R

AP(

2)50

F

+ 5

0 R

AP(

3)50

F

+ 5

0 R

AP(

4)50

W

+ 5

0 R

AP(

1)50

W

+ 5

0 R

AP(

2)50

W

+ 5

0 R

AP(

3)50

W

+ 5

0 R

AP(

4)50

R

CA +

50

RA

P(1)

50

RCA

+ 5

0 R

AP(

2)50

R

CA +

50

RA

P(3)

50

RCA

+ 5

0 R

AP(

4)25

A

+ 7

5 R

AP(

1)25

A

+ 7

5 R

AP(

2)25

A

+ 7

5 R

AP(

3)25

A

+ 7

5 R

AP(

4)25

F

+ 7

5 R

AP(

1)25

F

+ 7

5 R

AP(

2)25

F

+ 7

5 R

AP(

3)25

F

+ 7

5 R

AP(

4)25

W

+ 7

5 R

AP(

1)25

W

+ 7

5 R

AP(

2)25

W

+ 7

5 R

AP(

3)25

W

+ 7

5 R

AP(

4)25

R

CA +

75

RA

P(1)

25

RCA

+ 7

5 R

AP(

2)25

R

CA +

75

RA

P(3)

25

RCA

+ 7

5 R

AP(

4)

Year

s

Number of years required to reach CDF = 01 in terms of horizontal strain at the bottom of HMANumber of years required to reach CDF = 01 in terms of vertical strain at the top of subgrade

Figure 11 Number of years required to reach CDF 01 in terms of horizontal strain at the bottom of HMA and vertical strain at the top ofsubgrade

12 Advances in Materials Science and Engineering

the unity line indicating that the proposed regressionmodel has a moderate to strong correlation

(4) Statistical analysis of simulation results based onPerRoad and KenPave software demonstrates thatthe addition of RAP contents in the subbase layer ofthe copyexible pavement signicantly improves itsperformance against rutting and fatigue

(5) Residual strain during the long-term repeated loadtriaxial test was found to increase in line with anincrease in the ratio of ldquocyclic deviator stress to theconning stress (σdσc)rdquo in correlation to an increasein the percentage of RAP contents in the blendedsample

(6) From the authorrsquos perspective the addition of RAPcontents beyond a certain limit (sim50) may prove tobe detrimental for the overall performance of copyexiblepavement structure

Data Availability

yene experimental data used to support the ndings of thisstudy are included within the article in the form of graphsand tables

Conflicts of Interest

yene author declares that there are no concopyicts of interestregarding the publication of this paper

References

[1] R B Mallick and A Veeraragavan ldquoSustainable pavements inIndia-the time to start is nowrdquo New Building Materials andConstruction World (NBMampCW) Magazine vol 16 no 3pp 128ndash140 2010

[2] A Mohammadinia A Arulrajah S Horpibulsuk andA Chinkulkijniwat ldquoEect of copyy ash on properties of crushedbrick and reclaimed asphalt in pavement basesubbase

000

050

100

150

200

250

300

350

400

450

500

0 2000 4000 6000 8000 10000 12000 14000 16000 18000 20000

Axi

al st

rain

()

Number of load cycles

100 W50 W + 50 RAP(1)25 W + 75 RAP(1)100 F50 F + 50 RAP(2)25 F + 75 RAP(2)

σc = 1379kPa σd = 372kPa

Figure 12 Eect of RAP contents on residual strain under long-term repeated loading

000

005

010

015

020

025

0 1000 2000 3000 4000 5000 6000

Axi

al st

rain

()

Number of load cycles

091827

odoc

Figure 13 Eect of ratio of ldquocyclic deviator stress to the conningstress (σdσc)rdquo on the residual strain under long-term repeatedloading

Advances in Materials Science and Engineering 13

applicationsrdquo Journal of Hazardous Materials vol 321pp 547ndash556 2017

[3] L R Hoyos A J Puppala and C A Ordonez ldquoCharacter-ization of cement-fiber-treated reclaimed asphalt pavementaggregates preliminary investigationrdquo Journal of Materials inCivil Engineering vol 23 no 7 pp 977ndash989 2011

[4] R Taha A Al-Harthy K Al-Shamsi and M Al-ZubeidildquoCement stabilization of reclaimed asphalt pavement aggre-gate for road bases and subbasesrdquo Journal of Materials in CivilEngineering vol 14 no 3 pp 239ndash245 2002

[5] A M Azam and D A Cameron ldquoGeotechnical properties ofblends of recycled clay masonry and recycled concrete ag-gregates in unbound pavement constructionrdquo Journal ofMaterials in Civil Engineering vol 25 no 6 pp 788ndash7982013

[6] A Gabor and D Cameron ldquoProperties of recycled concreteaggregate for unbound pavement constructionrdquo Journal ofMaterials in Civil Engineering vol 24 no 6 pp 754ndash7642012

[7] C S Poon and D Chan ldquoFeasible use of recycled concreteaggregates and crushed clay brick as unbound road sub-baserdquoConstruction and Building Materials vol 20 no 8 pp 578ndash585 2006

[8] A Arulrajah M M Y Ali M M Disfani J Piratheepan andM W Bo ldquoGeotechnical performance of recycled glass-wasterock blends in footpath basesrdquo Journal of Materials in CivilEngineering vol 25 no 5 pp 653ndash661 2013

[9] L T Lee Jr ldquoRecycled glass and dredged materialsrdquo ReportNo ERDC TNDOER-T8 US Army Corps of EngineersEngineer Research and Development Center Mississippi MSUSA 2007

[10] M Ali A Arulrajah M Disfani and J Piratheepan ldquoSuit-ability of using recycled glassmdashcrushed rock blends forpavement subbase applicationsrdquo in Proceedings of the Geo-Frontiers 2011 Conference on Geotechnical Foundation Designpp 1325ndash1334 ASCE Reston VA USA 2011

[11] J Wartman D G Grubb and A S M Nasim ldquoSelectengineering characteristics of crushed glassrdquo Journal ofMaterials in Civil Engineering vol 16 no 6 pp 526ndash5392004

[12] W Kim and J Labuz Resilient Modulus and Strength of BaseCourse with Recycled Bituminous Material Minnesota De-partment of Transportation Research Services Section MNUSA 2007

[13] D Bloomquist G Diamond M Oden B Ruth and M TiaEngineering and Environmental Aspects of Recycled Materialsfor Highway Construction Appendix 1 Final Report 1993

[14] A Hussain and Q Yanjun ldquoEvaluation of asphalt mixescontaining reclaimed asphalt pavement for wearing cour-sesrdquo in Proceedings of the International Conference onTraffic and Transportation Engineering School of CivilEngineering Southwest Jiaotong University ChengduChina 2012

[15] M Solaimanian and M Tahmoressi ldquoVariability analysis ofhot-mix asphalt concrete containing high percentage ofreclaimed asphalt pavementrdquo Transportation Research Re-cord Journal of the Transportation Research Board vol 1543no 1 pp 89ndash96 1996

[16] A Gabr and D A Cameron ldquoProperties of recycled concreteaggregate for unbound pavement constructionrdquo Journal ofMaterials in Civil Engineering vol 24 no 6 pp 754ndash7642011

[17] W-L Huang D-H Lin N-B Chang and K-S LinldquoRecycling of construction and demolition waste via a

mechanical sorting processrdquo Resources Conservation andRecycling vol 37 no 1 pp 23ndash37 2002

[18] A R Pasandın and I Perez ldquoOverview of bituminous mix-tures made with recycled concrete Aggregatesrdquo Constructionand Building Materials vol 74 pp 151ndash161 2015

[19] P Jitsangiam H Nikraz and K Siripun ldquoConstruction anddemolition (CampD) waste as a road base material for WesternAustralia roadsrdquo Australian Geomechanics vol 44 no 3pp 57ndash62 2009

[20] A Nataatmadja and Y L Tan ldquoResilient response of recycledconcrete road aggregatesrdquo Journal of Transportation Engi-neering vol 127 no 5 pp 450ndash453 2001

[21] C Leek and K Siripun ldquoSpecification and performance ofrecycled materials in road pavementsrdquo Contract Rep (01119-1)2010

[22] J Green and J Hall Nondistructive Vibratory Testing ofAirport Pavement 1975

[23] W Heukelom and A Klomp ldquoDynamic testing as a means ofcontrolling pavements during and after constructionrdquo inProceedings of the International Conference on the StructuralDesign of Asphalt Pavements University of Michigan AnnArbor MI USA 1962

[24] Ohio Department of Transportation Pavement DesignManual Ohio Department of Transportation Office ofPavement Engineering OH USA 2008

[25] W D Powell H C Mayhew and M M Nunn ldquoestructural design of bituminous roadsrdquo Laboratory Report1132 Transport and Road Research Laboratory CrowthorneUK 1984

[26] M W Witczak X Qi and M W Mirza ldquoUse of nonlinearsubgrade modulus in AASHTO design procedurerdquo Journal ofTransportation Engineering vol 121 no 3 1995

[27] AASHTO Guide for Design of Pavement Structures Wash-ington DC USA 1993

[28] Asphalt Institute Research and Development of 5e AsphaltInstitutersquos 5ickness Design Manual (MS-1) 9th edition 1982

[29] T Buu Correlation of Resistance R-value and ResilientModulus of Idaho Subgrade Soil Idaho Department ofTransportation Division of Highways ID USA 1980

[30] S Muench J Mahoney and L Pierce WSDOT PavementGuide Washington State Department of TransportationInternet Module Washington DC USA 2009

[31] S Yeh and C Su ldquoResilient properties of Colorado soilsrdquoReport No CDOH-DH-SM-89-9 Colorado Department ofHighways Denver CO USA 1989

[32] M R ompson and Q L Robnett ldquoResilient properties ofsubgrade soilsrdquo Transportation Engineering Journal of ASCEvol 105 pp 71ndash89 1979

[33] W Lee N C Bohra A G Altschaeffl and T D WhiteldquoResilient modulus of cohesive soilsrdquo Journal of Geotechnicaland Geoenvironmental Engineering vol 123 no 2 pp 131ndash136 1997

[34] R Carmichael III and E Stuart ldquoPredicting resilient modulusa study to determine the mechanical properties of subgradesoilsrdquo Transportation Research Record vol 1043 pp 145ndash1481986

[35] E C Drumm Y Boateng-Poku and T Johnson PierceldquoEstimation of subgrade resilient modulus from standardtestsrdquo Journal of Geotechnical Engineering vol 116 no 5pp 774ndash789 1990

[36] M J Farrar and J P Turner Resilient Modulus of WyomingSubgrade Soils 1991

14 Advances in Materials Science and Engineering

[37] M P Jones and M W Witczak ldquoSubgrade modulus on thesan diego test roadrdquo Transportation Research Record Journalof the Transportation Research Board vol 641 pp 1ndash6 1977

[38] A M Rahim and K P George ldquoSubgrade soil indexproperties to estimate resilient modulusrdquo in Proceedings ofthe 83th Annual Meeting of the Transportation ResearchBoard National Research Council Washington DC USA2004

[39] M R ompson and T G LaGrow A Proposed ConventionalFlexible Pavement 5ickness Design Procedure University ofIllinois Peoria IL USA 1988

[40] R Pezo ldquoA general method of reporting resilient modulustests of soils a pavement engineerrsquos point of viewrdquo in Pro-ceedings of the 72nd Annual Meeting of Transportation Re-search Board Washington DC USA 1993

[41] R G Hicks and C L Monismith ldquoResilient properties ofgranular materialrdquo Transportation Research Record vol 345pp 15ndash31 1971

[42] J Uzan ldquoCharacterization of granular materialsrdquo Trans-portation Research Record Journal of the Transportation Re-search Board vol 1022 pp 52ndash59 1985

[43] National Cooperative Highway Research Program ldquoGuide formechanistic-empirical design of new and rehabilitatedpavement structuresrdquo NCHRP 1-37A NCHRP WashingtonDC USA 2004

[44] N M Louay H T Hani and H Ananda ldquoEvaluation ofresilient modulus of subgrade soil by cone penetration testrdquoTransportation Research Record Journal of the TransportationResearch Board vol 1652 pp 236ndash245 1999

[45] S Dai and J Zollars ldquoResilient modulus of Minnesota roadresearch project subgrade soilrdquo Transportation Research Re-cord Journal of the Transportation Research Board vol 1786no 1 pp 20ndash28 2002

[46] L Mohammad B Huang A Puppala and A Allen ldquoRe-gression model for resilient modulus of subgrade soilsrdquoTransportation Research Record Journal of the TransportationResearch Board vol 1687 no 1 pp 47ndash54 1999

[47] B Santa ldquoResilient modulus of subgrade soils comparison oftwo constitutive equationsrdquo Transportation Research RecordJournal of the Transportation Research Board vol 1462pp 79ndash90 1994

[48] H Von Quintus and B Killingsworth Analyses Relating toPavement Material Characterizations and their Effects onPavement Performance 1998

[49] O Porter ldquoe preparation of subgradesrdquo in Proceedings ofthe Nineteenth Annual Meeting Highway Research BoardWashington DC USA December 1939

[50] O J Porter ldquoDevelopment of the original method for highwaydesignrdquo Transactions of the American Society of Civil Engi-neers vol 115 pp 461ndash467 1950

[51] D W Hight and M G H Stevens ldquoAn analysis of theCalifornia Bearing Ratio test in saturated claysrdquoGeotechnique vol 32 no 4 pp 315ndash322 1982

[52] P R Fleming and C D F Rogers ldquoAssessment of pavementfoundations during constructionrdquo Proceedings of the In-stitution of Civil Engineers-Transport vol 111 no 2pp 105ndash115 1995

[53] M R ompson R Marshall and Q L Robnett ldquoResilientproperties of subgrade soilsrdquo Final Report No FHWA-IL-UI-160 University of Illinois Urbana IL USA 1976

[54] B Sukumaran V Kyatham A Shah and D Sheth ldquoSuit-ability of using California bearing ratio test to predict resilientmodulusrdquo in Proceedings Federal Aviation Administration

Airport Technology Transfer Conference Atlantic City NJUSA 2002

[55] N W Lister and D Powell ldquoDesign practices for pavementsin the United Kingdomrdquo in Proceedings of the 6th In-ternational Conference on the Structural Design of AsphaltPavements Ann Arbor MI USA July 1987

[56] S Hossain G Dickerson and C Weaver Comparative Studyof VTM and AASHTO Test Method for CBR Co MaterialsDivision VDOT 2005

[57] N Garg A Larkin and H Brar ldquoA comparative subgradeevaluation using CBR vane shear light weight deflectometerand resilient modulus testsrdquo in Proceedings of the 8th In-ternational Conference on the Bearing Capacity of RoadsRailways and Airfields CRC Press Champaign IL USA2009

[58] M Ayres Development of a rational probabilistic approach forflexible pavement analysis University of Maryland CollegePark MD USA 1997

[59] AASHTO T 307 Determining the Resilient Modulus of Soilsand Aggregate Materials (2012) American Association ofState Highway and Transportation Officials Washington DCUSA 2004

[60] M Arshad and M F Ahmed ldquoPotential use of reclaimedasphalt pavement and recycled concrete aggregate in basesubbase layers of flexible pavementsrdquo Construction andBuilding Materials vol 151 pp 83ndash97 2017

[61] M Arshad ldquoCorrelation between resilient modulus (MR) andconstrained modulus (Mc) values of granular materialsrdquoConstruction and Building Materials vol 159 pp 440ndash4502018

[62] P Guo and J Emery ldquoImportance of strain level inevaluating resilient modulus of granular materialsrdquo In-ternational Journal of Pavement Engineering vol 12 no 2pp 187ndash199 2011

[63] E J McGarrah ldquoEvaluation of current practices of reclaimedasphalt pavementvirgin aggregate as base course materialrdquoNo WA-RD 7131 Federal Highway AdministrationWashington DC USA 2007

[64] T B Alam M Abdelrahman and S A Schram ldquoLaboratorycharacterisation of recycled asphalt pavement as a base layerrdquoInternational Journal of Pavement Engineering vol 11 no 2pp 123ndash131 2010

[65] T Bennert and A Maher ldquoe development of a performancespecification for granular base and subbase materialrdquo ReportNo FHWA-NJ-2005-003 Department of TransportationEwing Township NJ USA 2005

[66] T H Wonnacott H omas and J Ronald ldquoRegression asecond course in statisticsrdquo No 04 QA2782 W6Wiley NewYork NY USA 1981

[67] W Penny and S Roberts Neural network predictions witherror bars Dept of Electrical and Electronic EngineeringTechnology and Medicine Research Report TR-97-1 ImperialCollege of Science London UK 1997

[68] R Dybowski and S J Roberts ldquoConfidence intervals andprediction intervals for feed-forward neural networksrdquoClinical Applications of Artificial Neural Networks pp 298ndash326 2001

[69] J Hauke and T Kossowski ldquoComparison of values ofPearsonrsquos and Spearmanrsquos correlation coefficients on the samesets of datardquo Quaestiones Geographicae vol 30 no 2pp 87ndash93 2011

[70] K-z Yan H-b Xu and G-h Shen ldquoNovel approach toresilient modulus using routine subgrade soil propertiesrdquo

Advances in Materials Science and Engineering 15

International Journal of Geomechanics vol 14 no 6 article04014025 2013

[71] Y H Chan ldquoBiostatistics 104 correlational analysisrdquoSingapore Medical Journal vol 44 no 12 pp 614ndash6192003

[72] B M Damghani D Welch C OrsquoMalley and S Knights ldquoemisleading value of measured correlationrdquoWilmott vol 2012no 62 pp 64ndash73 2012

[73] L B Christensen B Johnson and L A Turner ldquoResearchmethods design and analysisrdquo 2011

[74] W J Dixon and F J Massey Introduction to StatisticalAnalysis McGraw-Hill New York NY USA 1969

[75] B Colbert and Z You ldquoe determination of mechanicalperformance of laboratory produced hot mix asphalt mixturesusing controlled RAP and virgin aggregate size fractionsrdquoConstruction and Building Materials vol 26 no 1 pp 655ndash662 2012

[76] D H Timm and D E Newcomb ldquoPerpetual pavement designfor flexible pavements in the USrdquo International Journal ofPavement Engineering vol 7 no 2 pp 111ndash119 2006

[77] Y H Huang Pavement Analysis and Design Prentice-HallEnglewood Cliffs NJ USA 2nd edition 1993

[78] L Walubita W Liu and T Scullion Texas perpetualpavements-Experience overview and the way forward Tech-nical Report No 0-4822-3 Texas Transportation InstituteTexas AampM University College Station TX USA 2010

[79] D Timm and D Newcomb ldquoCalibration of flexible pavementperformance equations for Minnesota road research projectrdquoTransportation Research Record Journal of the TransportationResearch Board no 1853 pp 134ndash142 2003

16 Advances in Materials Science and Engineering

CorrosionInternational Journal of

Hindawiwwwhindawicom Volume 2018

Advances in

Materials Science and EngineeringHindawiwwwhindawicom Volume 2018

Hindawiwwwhindawicom Volume 2018

Journal of

Chemistry

Analytical ChemistryInternational Journal of

Hindawiwwwhindawicom Volume 2018

ScienticaHindawiwwwhindawicom Volume 2018

Polymer ScienceInternational Journal of

Hindawiwwwhindawicom Volume 2018

Hindawiwwwhindawicom Volume 2018

Advances in Condensed Matter Physics

Hindawiwwwhindawicom Volume 2018

International Journal of

BiomaterialsHindawiwwwhindawicom

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Applied ChemistryJournal of

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50 and 75 for each Figures 4(a)ndash4(d) show the eects ofthe addition of these RAPs on themeasuredMR values over arange of bulk stresses as specied in AASHTOT 307-99 (68)Variation ofMR values with bulk stress can be approximatedthrough trend lines based on a power function having thecoecient of determination (R2) in the range of 095ndash099From these trend lines it is evident that MR values increasenot only due to the increase in bulk stress but also incombination with the addition of RAP contents ie blendedsamples give higher MR values when compared to thoseobtained from the natural samples of granular A F W andRCA More specically for instance at a bulk stress ofsim673 kPa MR value for the 100 granular W is 320MPawhile the corresponding values for blended samples in-corporating 25 50 and 75 of RAP(1) are 340MPa360MPa and 390MPa respectively

A similar trend in MR values was observed at lowerlevels of bulk stress or more precisely over the entirerange of bulk stresses considered during the testing

campaign In some cases sim50 increase in MR values wasobserved for the blends containing 75 RAP contents Ingeneral for most of the blended samples containing 25and 50 RAP contents the corresponding increase in MRvalues was in the range of 5ndash15 and 10ndash20 respectivelyAn important point is that the addition of RAPs to RCAinduced the most signicant increase in the resilientmoduli when compared with the increase inMR when RAPwas added to granular samples Similar observations havealso been documented by many researchers including Kimand Labuz [12] MacGregor et al [63] Alam et al [64] andBennert and Maher [65]

5 Development of Correlation betweenResilient Modulus and CBR Values

51 Proposed Correlation and eoretical BackgroundFor this study an attempt has been made to correlate theMR values with the CBR values on the basis of a commonvalue of bulk stress identied during both types of testsyenis should be emphasize that CBR values tend to decreasewith addition of RAP contents while reverse is the situationin case of resilient modulus values Such trends are pri-marily due to the fact that loading for the resilient modulustest is dynamic in nature while in the case of the CBR test itis virtually static

Fundamentally axial stress is applied during the CBRtests through a plunger (σpa) in addition to an axial sur-charge weight (σsa) as shown in Figure 5 However lateralstress on the walls of the CBRmould can be estimated on thebasis of the lateral earth pressure coecient (Ka) as describedin classical soil mechanics such that

σpl Kaσpa

σsl Kaσsa

Ka 1minus sin(ϕ)

(1)

where ϕ is the eective angle of internal friction of the soilsample (blend) under consideration

Table 4 Loading sequence for the resilient modulus test as per AASHTO T 307 protocol

Seq No No of load applied Conning stress Max axial stress Cyclic axial stress Contact stress Total axial stress (kPa)σ3 (kPa) σmax (kPa) σcyclic (kPa) 01σmax (kPa)0 750 1034 1034 931 103 20681 100 207 207 186 21 4142 100 207 414 373 41 6213 100 207 621 559 62 8284 100 345 345 31 35 695 100 345 689 62 69 10346 100 345 1034 931 103 13797 100 689 689 62 69 13788 100 689 1379 1241 138 20689 100 689 2068 1861 207 275710 100 1034 689 62 69 172311 100 1034 1034 931 103 206812 100 1034 2068 1861 207 310213 100 1379 1034 931 103 241314 100 1379 1379 1241 138 275815 100 1379 2758 2482 276 4137

0

10

20

30

40

50

60

70

80

90

1950 2000 2050 2100 2150 2200 2250

Uns

oake

d CB

R (

)

Unit weight (kNm3)

A75 A + 25 RAP(1)50 A + 50 RAP(1)

25 A + 75 RAP(1)RAP(1)

Figure 3 Eect of RAP contents on CBR values

Advances in Materials Science and Engineering 5

It is interesting to note that the 3-point CBR test en-compasses a wide range of dry and bulk density in thesample while on the other hand each resilient modulus

test uses a unique value of the samplersquos dry and bulkdensity To estimate a unique value of the bulk stress duringthe CBR test which is analogous to the bulk stress valueidentied from resilient modulus test the following pro-cedure was adopted

(1) Determine the dry density of the resilient modulussample

(2) Estimate the CBR value corresponding to that drydensity value

(3) Determine the axial stress (σpa) value correspondingto the CBR value

(4) Calculate the bulk stress using the following relation

σbulk θ σ1 + σ2 + σ3 σpa + σsa( ) + 2Ka σpa + σsa( ) (2)

Using a unique value of bulk stress on the basis ofequation (2) the corresponding resilient modulus valuefrom the actual experimental data (MR test) was matchedand then a correlation between CBR value (point 2)and the resilient modulus value in terms of the power

y = 52x064

R2 = 099

y = 88x056

R2 = 098

y = 136x051

R2 = 095

y = 101x056

R2 = 098

0

50

100

150

200

250

300

350

400

450

0 200 400 600 800

MR (

MPa

)

Bulk stress (kPa)

100 A75 A + 25 RAP(2)

50 A + 50 RAP(2)25 A + 75 RAP(2)

(a)

100 F75 F + 25 RAP(3)

50 F + 50 RAP(3)25 F + 75 RAP(3)

y = 517x064

R2 = 099

y = 745x058

R2 = 099

y = 101x054

R2 = 097

y = 972x057

R2 = 096

0

50

100

150

200

250

300

350

400

450

0 200 400 600 800

MR (

MPa

)

Bulk stress (kPa)

(b)

y = 517x064

R2 = 099

y = 745x058

R2 = 099

y = 101x054

R2 = 097

y = 972x057

R2 = 096

0

50

100

150

200

250

300

350

400

450

0 200 400 600 800

MR (

MPa

)

Bulk stress (kPa)

100 W75 W + 25 RAP(1)

50 W + 50 RAP(1)25 W + 75 RAP(1)

(c)

y = 517x064

R2 = 099

y = 745x058

R2 = 099

y = 101x054

R2 = 097

y = 972x057

R2 = 096

0

50

100

150

200

250

300

350

400

450

0 100 200 300 400 500 600 700 800

MR (

MPa

)

Bulk stress (kPa)

100 RCA25 RCA + 75 RAP(4)

50 RCA + 50 RAP(4)75 RCA + 25 RAP(4)

(d)

Figure 4 Variation ofMR value with bulk stress and percentage of RAP contents for (a) naturalA (b) natural F (c) naturalW and (d) RCA

Plunger

Surchargeweight

Soil sample

Lateral stress due toloading of plunger (σpl)

Lateral stress due tosurcharge loading (σsl)

Figure 5 An assumed conguration of axial and lateral stressesduring CBR test

6 Advances in Materials Science and Engineering

function having a coefficient of determination sim081 canbe given as

MR 4937(CBR)059

(3)

Table 5 shows the experimental data and the estimatedvalues of MR based on the four steps explained above andequation (3)

Figure 6 shows the capabilities of the proposed regressionmodel on the basis of the distribution of the data pointswhich in fact involves the experimentally determined andestimated MR values along the unity line giving a 95prediction and confidence interval is figure illustrates thatthere is an almost equal distribution of the data points on bothsides of the unity line Additionally the entire set of the datapoints is confined within the 95 prediction interval which isdefined as the interval around the linear regression line suchthat 95 of the predicted values will fall in this intervalFurther details on the mathematical framework of the pre-diction and the confidence interval can be found in standardtextbooks dealing with statistics and probability analysis suchas those authored by Wonnacott and Ronald [66] Penny andRoberts [67] and Dybowski and Roberts [68]

52 Statistical Analysis of the Proposed Model A Pearsonrsquoscorrelation coefficient (r) as given by equation (4) is ameasure of the strength and direction of linear associationthat exists between two continuous variables More specif-ically for the drawn line of best fit for sample data points oftwo variables Pearsonrsquos correlation indicates how well thedata points fit this new modelline of best fit and its nu-merical value indicates how far away all these data points areto the line of best fit (ie how well the data points fit this newmodelline of best fit) [69 70]

r 1113936

ni1 ui minus ui( 1113857 ti minusti( 1113857

1113936ni1 ui minus ui( 1113857

2ti minus ti( 1113857

21113960 1113961

1113969 (4)

where ui and ti experimental and predicted values re-spectively for the ith output ui average of experimentaloutputs and n size of sample

e statistical value of r may range from minus1 for a perfectnegative linear relationship (inversely related) to +1 for aperfect positive linear relationship (directly related) In gen-eral from theoretical point of view the strength of the linearrelationship can be categorised as ldquovery strongrdquo ldquomoderatelystrongrdquo and ldquofairly strongrdquo for the corresponding numericalvalues of r in the range 08ndash10 06ndash08 and 03ndash05 [71] Itshould be emphasized that if r 00 it does not necessarilymean that the two variables have no relationship In order tolook into the real strength of the correlation usually a sta-tistical test of significance is performed as discussed in [72]For this study three different types of statistical tests wereapplied to assess the significance of the developed correlationpresented in equation (3) and Table 5

Case 1 t-Test for the assessment of the implication of co-efficient of correlation (r) at a specific degree of freedom andlevel of significance [73]

is provides the researcher with some idea of how largea correlation coefficient must be before it can be consideredas demonstrating that there really is a relationship betweentwo variables (in our case the (MR)measured and CBR values)It may be the situation that two variables are related bychance and a hypothesis test for r allows the researcher todecide whether the observed r could have emerged by chanceor not e null hypothesis is that there is no relationshipbetween the two variables at is if ρ is the true correlationcoefficient for the two variables and when all populationvalues have been observed then the null hypothesis can begiven as

H0 ρ 0 (5)

e alternative hypothesis could be written as

HA ρne 0 (6)

whereas the standardised t-test for the null hypothesis that ris equal to zero can be written as

t r

nminus 21minus r2

1113970

(7)

where n is the number of paired observations in the givensample

e null hypothesis is evaluated by comparing the t-statistic of equation (7) with t-critical (201) obtained from tdistribution having the nminus 2 degree of freedom

Case 2 Direct comparison of the coefficient of correlationvalue (09) with the r-critical value (027) obtained from astatistical table corresponding to a specific degree of freedomand level of significance [61 74]

Case 3 It often becomes mandatory to statistically evaluatethe difference between two datasets obtained by two dif-ferent sources As in our case one set of MR values wasobtained experimentally using the AASHTOT 307-99(2004)protocol and the other set of MR values was obtained usingthe proposed correlation A standard t-test was performed toevaluate the difference between the paired values of(MR)measured and (MR)estimated at a specific degree of freedomand level of significance [74 75]

Table 6 summarises the statistical analysis of the abovethree cases

6 Assessment of Pavement PerformanceContaining RAPContent in Its Subbase Layer

To examine the performance of the pavement containingnatural aggregates mixed with RAP and used as subbasematerials the following analyses were performed usingcomputer software simulation

(1) To access the likelihood that critical pavement re-sponses exceed predefined thresholds using com-puter program PerRoad [76]

Advances in Materials Science and Engineering 7

(2) To determine the stresses and strains at critical lo-cations in the pavement structure using computerprogram KenPave developed by the University ofKentucky [77]

PerRoad is a Monte Carlo-based simulation softwareused to develop probability-based analysis for flexiblepavement is software can easily demonstrate the influ-ence of the MR values of the pavement material on the

Table 5 A comparison of measured and estimated MR values along with CBR values

MaterialBlend Dry unit weightachieved (kNm3) CBR () Total axial

stress (kPa)

Estimatedbulk stress

in CBR test (kPa)

MR values measuredprojected (MPa)

MR valuesestimated(MPa)

100 A 211 65 9780 1663 550 584100 F 221 74 11130 1892 600 631100 W 224 85 12780 2173 670 685100 RCA 192 53 7980 1357 410 51875 A+ 25 RAP(1) 207 47 7080 1204 470 48250 A+ 50 RAP(1) 205 31 4680 796 300 37725 A+ 75 RAP(1) 202 22 3330 566 280 30875 A+ 25 RAP(2) 203 55 8280 1408 505 52950 A+ 50 RAP(2) 208 39 5880 1000 410 43225 A+ 75 RAP(2) 213 17 2580 439 260 26475 A+ 25 RAP(3) 201 51 7680 1306 490 50650 A+ 50 RAP(3) 205 30 4530 770 315 37025 A+ 75 RAP(3) 199 19 2880 490 310 28275 A+ 25 RAP(4) 197 55 8280 1408 505 52950 A+ 50 RAP(4) 198 43 6480 1102 402 45825 A+ 75 RAP(4) 192 27 4080 694 252 34775 F+ 25 RAP(1) 208 52 7830 1331 538 51250 F+ 50 RAP(1) 213 41 6180 1051 455 44525 F+ 75 RAP(1) 201 14 2130 362 356 23575 F+ 25 RAP(2) 205 59 8880 1510 525 55250 F+ 50 RAP(2) 199 48 7230 1229 407 48825 F+ 75 RAP(2) 197 31 4680 796 408 37775 F+ 25 RAP(3) 201 62 9330 1586 667 56850 F+ 50 RAP(3) 192 41 6180 1051 516 44525 F+ 75 RAP(3) 208 19 2880 490 343 28275 F+ 25 RAP(4) 213 43 6480 1102 515 45850 F+ 50 RAP(4) 201 32 4830 821 490 38425 F+ 75 RAP(4) 213 13 1980 337 278 22575 W+25 RAP(1) 208 51 7680 1306 510 50650 W+50 RAP(1) 205 44 6630 1127 500 46425 W+75 RAP(1) 199 16 2430 413 240 25575 W+25 RAP(2) 197 55 8280 1408 502 52950 W+50 RAP(2) 199 31 4680 796 438 37725 W+75 RAP(2) 213 12 1830 311 265 21575 W+25 RAP(3) 201 48 7230 1229 520 48850 W+50 RAP(3) 213 35 5280 898 447 40525 W+75 RAP(3) 207 21 3180 541 255 29975 W+25 RAP(4) 205 45 6780 1153 480 47050 W+50 RAP(4) 199 34 5130 872 473 39825 W+75 RAP(4) 192 9 1380 235 213 18175 RCA+ 25 RAP(1) 208 38 5730 974 486 42550 RCA+ 50 RAP(1) 213 23 3480 592 330 31625 RCA+ 75 RAP(1) 201 12 1830 311 187 21575 RCA+ 25 RAP(2) 213 38 5730 974 525 42550 RCA+ 50 RAP(2) 201 31 4680 796 356 37725 RCA+ 75 RAP(2) 214 14 2130 362 200 23575 RCA+ 25 RAP(3) 201 32 4830 821 447 38450 RCA+ 50 RAP(3) 205 15 2280 388 226 24525 RCA+ 75 RAP(3) 199 9 1380 235 148 18175 RCA+ 25 RAP(4) 192 39 5880 1000 473 43250 RCA+ 50 RAP(4) 201 13 1980 337 200 22525 RCA+ 75 RAP(4) 202 18 2730 464 161 273

8 Advances in Materials Science and Engineering

cumulative damage factor (CDF) It also demonstrates thelikelihood that critical pavement responses could exceedpredened thresholds which are the horizontal tensile strainof 70 microns at the bottom of the asphalt concrete (which islinked with fatigue cracking) and the vertical compressivestrain of 200 microns at the top of the subgrade (which isassociated with the structural rutting) [78]

61 Pavement Structure and Material CharacteristicsFigure 7 shows a typical cross section of copyexible pavementswhich consists of a hot mix asphalt layer supported by theunbound base unbound subbase and compacted subgradeyene thickness of each layer generally depends on the tracload or more specically the equivalent single axle load(ESAL) during the proposed life cycle of the road

In this parametric study the focus is placed on how theproperties of granular subbase materials are changed by theaddition of a certain amount of RAP and their eect on thepavementrsquos performance As such the resilient modulus ofthe granular base and the asphalt concrete is xed yenestructure of the pavement to be simulated and the propertiesof materials in dierent layers are summarised in Table 7 Inthis particular study the subbase material will be one of theaggregates or aggregateRAP blends tested during the ex-perimental studies of this research

yene properties of the dierent pavement layers used inthe analysis are shown in Table 7 yene bulk stresses at the top

and bottom of the granular subbase layer were determinedusing the computer program KenPave For the selectedHMA resilient moduli (MR 5000MPa) the bulk stresseswere found in the range of 27 kPa to 30 kPa and 14 kPa to18 kPa at the top and bottom of the subbase layers re-spectively for the wheel load of 40 kN In the simulationsvalues of MR are used corresponding to the bulk stress of100 kPa

62 Trac Load For this parametric study the trac datafor urban interstate highways as recommended byAASHTO were used In the case of the PerRoad softwaretrac is separated by axle type single axle tandem axletridem axle and steer axle After determining the percentageof each axle type in the total trac trac is then subdividedinto weight classes in 2 kip intervals yene following is thesummary of the trac data the average annual daily trac(AADT) is 1000 vehicles with 10 being trucks annualgrowth rate of trac is 4 the directional distribution is50 and the percentages of single tandem and tridem axlesare 5573 4266 and 161 respectively yene rest of thetrac loading characteristics in terms of the distribution ofvehicle types and axle weights are described in Figure 8yenese values were used as input in PerRoad 35 Axle weightswere used to evaluate the response of the pavement layers interms of stresses strains and deformations at critical lo-cations of certain layers of the copyexible pavement

Table 6 Summary of the statistical analysis of the proposed model at an alpha value of 005 which matches to 95 condence level

Case Comments

1 t-Critical 20 t-Statistic 1459Since t-statisticgt t-critical which implies that value of the correlation coecient is not dueto sampling error the null hypothesis is rejected and it is concluded that there is a

signicant correlation between (MR)measured and CBR value in the population

2 r-Pearson 09 r-Critical 027

Since r-Pearsongt r-critical which implies that the null hypothesis is rejectedit is quite realistic to accept the ldquoalternative hypothesisrdquo that is the value of r that

we have obtained from our sample represents a real relationship between (MR)measuredand CBR value in the population

3 t-Critical 20 t-Statistic 052Since t-statisticlt t-critical which implies that the null hypothesis is accepted

it is concluded that there is an insignicant dierence between(MR)measured and (MR)correlated values in the population

0

100

200

300

400

500

600

700

800

0 200 400 600 800

MR

(esti

mat

ed)

MR (measured)

1 1 line

95confidence

interval

95prediction

interval

Figure 6 A comparison of estimated and measured MR values along the unity line

Advances in Materials Science and Engineering 9

63 Pavement Performance Criteria In the design ofconventional flexible pavements pavement sectionsare designed corresponding to a cumulative damagefactor (CDF) of 10 which corresponds to a terminallevel of pavement damage For perpetual pavementshowever it is recommended that the CDF is equal to 01at the end of its design life [76] e fatigue and ruttingalgorithms developed at MnROAD [79] for the cali-bration of flexible pavement performance equations wereused to predict pavement damage in cases where pave-ment responses exceeded these thresholds ese corre-lations are as follows

Nf 283lowast 10minus61εt

1113888 1113889

3148

(fatigue)

Nr 6026lowast 10minus81εv

1113888 1113889

387

(ritting)

(8)

where Nf number of load repetitions when fatigue failureoccurs Nr number of load repetition when rutting failureoccurs εt the horizontal tensile strain at the bottom of theHMA and εv the vertical compressive strain at the top ofthe subgrade

It should be noted that the damage of rutting estimatedby PerRoad only takes into account the permanent de-formation in the subgrade Any rutting associated with thedeformation of granular subbase materials is not consideredAccording to the test results in this study use of RAP ingranular subbase layers may induce substantial residualdeformation Further investigation should be performed toget a better understanding of its influence on the rutting offlexible pavements

64 Simulation Results and Discussion Simulation resultsare obtained and discussed in terms of

(1) e likelihood of the tensile strain at the bottom ofthe HMA exceeding 70 με

(2) e likelihood of the vertical strain at the top of thesubgrade soil exceeding 200 με

(3) e number of years it could take to reach a CDF of01 (the threshold level) for fatigue damage

(4) e number of years it could take to reach a CDF of01 for damage induced by rutting

Figure 9 illustrates the concept frequency distributionfor strain both within and outside the threshold limits

We first examine the likelihood of critical pavementresponses exceeding the predefined thresholds when theresilient modulus of the asphalt concrete is 5000MPa anddifferent aggregates or aggregate-RAP blends are used inthe granular subbase layer Figure 10 summarises (1) thelikelihood of the tensile strain at the bottom of the HMAremaining within the critical value of 70 με and (2) thelikelihood of the vertical strain at the top of the subgradesoil exceeding 200 με From this figure it can be inter-preted that all of the blends result in better pavementperformance than the natural aggregate both in terms ofthe tensile strains at the bottom of the HMA and thevertical compressive strains at the top of the subgrade soilFor instance the natural aggregates and RCA on averagehave an 813 likelihood that horizontal strain at thebottom of the HMA will remain within the critical limit of70 με

On the other hand the likelihood for blended ma-terials containing 25 50 and 75 of RAP materials inthe blended samples may reach (on average) 85758937 and 9377 (respectively) chance of remainingwithin the limit Similarly the likelihood that the com-pressive strain at the top of the subgrade will not exceedthe critical value of 200 microns is 8828 (naturalsamples) 9346 (25 RAP material blends) 9557(50 RAP material blends) and 982 (75 RAP ma-terial blends)

Figure 11 shows the number of years required to reacha CDF of 01 when fatigue is controlled by the horizontaltensile strain at the bottom of the subgrade and the HMAand vertical structural rutting are controlled by the verticalcompressive strain at the top of the subgrade e numberof years required to reach a CDF of 01 in general in-creases in line with the increase in the quantity of RAP inthe blend For example the number of years required toreach a CDF of 01 in terms of fatigue damage at thebottom of HMA is 4033 years for natural samples whilethe corresponding figure for the blends containing 75RAP is 5168 years on average A similar trend regarding anincrease in the number of years required to reach a CDF of01 in terms of structural damage at the top of the subgradewas also observed Furthermore for all the cases thenumber of years to reach a CDF of 01 was more than40 years but it is clear that fatigue will be the predominantpavement failure mode

Asphalt concrete

Unbound base

Unbound subbase

Compacted subgrade

Natural subgrade

Figure 7 A typical cross section of flexible pavement

Table 7 Material properties and pavement layer thicknesses

Parameters HMA Base course Subbasecourse Subgrade

MR (MPa) 5000 350 Variable 35Coefficient ofvariation for MR () 25 30 35 45

ickness ofthe layer (mm) 250 200 300 mdash

icknessVariability () 5 8 15 mdash

Poisson ratio 03 03 03 04

10 Advances in Materials Science and Engineering

7 Long-Term Effect of Cyclic Loading onBlended Samples

In order to explore the long-term eects of cyclic loading 9repeated load triaxial tests were performed under a range ofcyclic loading conditions and varying percentages of RAPcontents Figure 12 presents the variation of the residual strainof the tested samples subjected to 20000 load cycles under twodierent values of conning pressures of 345 kPa and1379 kPa each while the corresponding cyclic deviator stresswas maintained at 3105 kPa and 372 kPa From this gure itcan be inferred that the presence of RAP contents increases theresidual strain considerably for both of the conning pressurescenarios For instance for the repeated load test conducted atthe conning pressure of 345 kPa the residual strain for 100natural aggregate F is 012 after 20000 load cycles while forthe blend containing 50 RAP(2) and 75 RAP(2) thecorresponding gures reach 022 and 060 ie an additionof 50 RAP increases the residual strain by amargin of almost83 while the addition of 75 RAP increases the residualstrain by almost 400 Similarly for the repeated load testsconducted at a conning pressure of 1379 kPa on samples

containing natural aggregateW and the blends with RAP(1) at50 and 75 the residual strain after 20000 load cycles is 55and 300 higher when compared with the correspondingvalue for the 100 natural aggregate W Furthermore it isevident from the gures that almost 60 of the total residualstrain occurred during the rst 2000 load cycles out of the20000 total load cycles applied across all the cases

However it should be emphasized that there is a ten-dency for the elastic shakedown to be less pronounced forblended samples when compared to pure natural aggregatesFor instance for the blended sample 50 W and 50RAP(1) the rate of increase of strain becomes 0000154 forthe load cycles in the range of 2000ndash20000 On the otherhand this gure remained limited to 0000056 for thesample containing 100 natural aggregate W under thesame loading condition

Figure 13 shows the eect of the ratio of ldquocyclic deviatorstress to the conning stress (σdσc)rdquo on the residual strain forthe blended sample containing 50 A and 50 RAP(3)From this gure it can be inferred that the ratio σdσc has asubstantial eect on the residual strain generated undercyclic loading For instance at (σdσc) 09 the residualstrain after 6000 load cycles is limited to 006 however thisvalue reaches 011 and 021 at (σdσc) 18 and(σdσc) 27 respectively yene samples tend to stabilisemore quickly under a lower value of (σdσc) 09 whencompared to the stabilising tendency at the higher values of(σdσc) 18 and (σdσc) 27 which were also in-vestigated in this research A 50ndash60 residual strain occursduring the rst 1000 load cycles out of the total 6000 loadcycles applied during the experimental campaign irre-spective of the σdσc value

8 Summary and Conclusions

(1) yene blended samples (ie RAP combined withnatural granular materials) result in higher MRvalues than those obtained for natural granular

Figure 8 Vehicular load classication used in PerRoad 35

Area outside the threshold limit

Stra

in fr

eque

ncy

Figure 9 Example of frequency distribution of strain within andoutside the threshold limits

Advances in Materials Science and Engineering 11

samples under the same loading conditions whilevariations between MR values and the applied bulkstresses during the resilient modulus tests can beapproximated through power law having coecientof correlation (r) value in the range of 097ndash099

(2) yene CBR values of blended samples decrease withthe addition of RAP contents however a clear

decreasing trend in conjunction with an increasingpercentage of RAP contents could not be found

(3) yene new model for the estimation of MR values in-cludes the stress state through the experimentallydetermined CBR having a coecient of correlation ldquorrdquoequal to approximately 09 with fair distribution of thedata points (MR measured and MR estimated) about

Perc

enta

ge o

f are

a

70

75

80

85

90

95

100

100

A10

0 F

100

W10

0 R

CA75

A

+ 2

5 R

AP(

1)75

A

+ 2

5 R

AP(

2)75

A

+ 2

5 R

AP(

3)75

A

+ 2

5 R

AP(

4)75

F

+ 2

5 R

AP(

1)75

F

+ 2

5 R

AP(

2)75

F

+ 2

5 R

AP(

3)75

F

+ 2

5 R

AP(

4)75

W

+ 2

5 R

AP(

1)75

W

+ 2

5 R

AP(

2)75

W

+ 2

5 R

AP(

3)75

W

+ 2

5 R

AP(

4)75

R

CA +

25

RA

P(1)

75

RCA

+ 2

5 R

AP(

2)75

R

CA +

25

RA

P(3)

75

RCA

+ 2

5 R

AP(

4)50

A

+ 5

0 R

AP(

1)50

A

+ 5

0 R

AP(

2)50

A

+ 5

0 R

AP(

3)50

A

+ 5

0 R

AP(

4)50

F

+ 5

0 R

AP(

1)50

F

+ 5

0 R

AP(

2)50

F

+ 5

0 R

AP(

3)50

F

+ 5

0 R

AP(

4)50

W

+ 5

0 R

AP(

1)50

W

+ 5

0 R

AP(

2)50

W

+ 5

0 R

AP(

3)50

W

+ 5

0 R

AP(

4)50

R

CA +

50

RA

P(1)

50

RCA

+ 5

0 R

AP(

2)50

R

CA +

50

RA

P(3)

50

RCA

+ 5

0 R

AP(

4)25

A

+ 7

5 R

AP(

1)25

A

+ 7

5 R

AP(

2)25

A

+ 7

5 R

AP(

3)25

A

+ 7

5 R

AP(

4)25

F

+ 7

5 R

AP(

1)25

F

+ 7

5 R

AP(

2)25

F

+ 7

5 R

AP(

3)25

F

+ 7

5 R

AP(

4)25

W

+ 7

5 R

AP(

1)25

W

+ 7

5 R

AP(

2)25

W

+ 7

5 R

AP(

3)25

W

+ 7

5 R

AP(

4)25

R

CA +

75

RA

P(1)

25

RCA

+ 7

5 R

AP(

2)25

R

CA +

75

RA

P(3)

25

RCA

+ 7

5 R

AP(

4)

Percentage of area within the critical limit of horizontal strain at the bottom of HMAPercentage of area within the critical limit of vertical strain at the top of subgrade

Figure 10 Percentage of area within the critical limits for horizontal strain at the bottom of HMA and vertical strain at the top of subgrade

30

35

40

45

50

55

60

65

70

100

A10

0 F

100

W10

0 R

CA75

A

+ 2

5 R

AP(

1)75

A

+ 2

5 R

AP(

2)75

A

+ 2

5 R

AP(

3)75

A

+ 2

5 R

AP(

4)75

F

+ 2

5 R

AP(

1)75

F

+ 2

5 R

AP(

2)75

F

+ 2

5 R

AP(

3)75

F

+ 2

5 R

AP(

4)75

W

+ 2

5 R

AP(

1)75

W

+ 2

5 R

AP(

2)75

W

+ 2

5 R

AP(

3)75

W

+ 2

5 R

AP(

4)75

R

CA +

25

RA

P(1)

75

RCA

+ 2

5 R

AP(

2)75

R

CA +

25

RA

P(3)

75

RCA

+ 2

5 R

AP(

4)50

A

+ 5

0 R

AP(

1)50

A

+ 5

0 R

AP(

2)50

A

+ 5

0 R

AP(

3)50

A

+ 5

0 R

AP(

4)50

F

+ 5

0 R

AP(

1)50

F

+ 5

0 R

AP(

2)50

F

+ 5

0 R

AP(

3)50

F

+ 5

0 R

AP(

4)50

W

+ 5

0 R

AP(

1)50

W

+ 5

0 R

AP(

2)50

W

+ 5

0 R

AP(

3)50

W

+ 5

0 R

AP(

4)50

R

CA +

50

RA

P(1)

50

RCA

+ 5

0 R

AP(

2)50

R

CA +

50

RA

P(3)

50

RCA

+ 5

0 R

AP(

4)25

A

+ 7

5 R

AP(

1)25

A

+ 7

5 R

AP(

2)25

A

+ 7

5 R

AP(

3)25

A

+ 7

5 R

AP(

4)25

F

+ 7

5 R

AP(

1)25

F

+ 7

5 R

AP(

2)25

F

+ 7

5 R

AP(

3)25

F

+ 7

5 R

AP(

4)25

W

+ 7

5 R

AP(

1)25

W

+ 7

5 R

AP(

2)25

W

+ 7

5 R

AP(

3)25

W

+ 7

5 R

AP(

4)25

R

CA +

75

RA

P(1)

25

RCA

+ 7

5 R

AP(

2)25

R

CA +

75

RA

P(3)

25

RCA

+ 7

5 R

AP(

4)

Year

s

Number of years required to reach CDF = 01 in terms of horizontal strain at the bottom of HMANumber of years required to reach CDF = 01 in terms of vertical strain at the top of subgrade

Figure 11 Number of years required to reach CDF 01 in terms of horizontal strain at the bottom of HMA and vertical strain at the top ofsubgrade

12 Advances in Materials Science and Engineering

the unity line indicating that the proposed regressionmodel has a moderate to strong correlation

(4) Statistical analysis of simulation results based onPerRoad and KenPave software demonstrates thatthe addition of RAP contents in the subbase layer ofthe copyexible pavement signicantly improves itsperformance against rutting and fatigue

(5) Residual strain during the long-term repeated loadtriaxial test was found to increase in line with anincrease in the ratio of ldquocyclic deviator stress to theconning stress (σdσc)rdquo in correlation to an increasein the percentage of RAP contents in the blendedsample

(6) From the authorrsquos perspective the addition of RAPcontents beyond a certain limit (sim50) may prove tobe detrimental for the overall performance of copyexiblepavement structure

Data Availability

yene experimental data used to support the ndings of thisstudy are included within the article in the form of graphsand tables

Conflicts of Interest

yene author declares that there are no concopyicts of interestregarding the publication of this paper

References

[1] R B Mallick and A Veeraragavan ldquoSustainable pavements inIndia-the time to start is nowrdquo New Building Materials andConstruction World (NBMampCW) Magazine vol 16 no 3pp 128ndash140 2010

[2] A Mohammadinia A Arulrajah S Horpibulsuk andA Chinkulkijniwat ldquoEect of copyy ash on properties of crushedbrick and reclaimed asphalt in pavement basesubbase

000

050

100

150

200

250

300

350

400

450

500

0 2000 4000 6000 8000 10000 12000 14000 16000 18000 20000

Axi

al st

rain

()

Number of load cycles

100 W50 W + 50 RAP(1)25 W + 75 RAP(1)100 F50 F + 50 RAP(2)25 F + 75 RAP(2)

σc = 1379kPa σd = 372kPa

Figure 12 Eect of RAP contents on residual strain under long-term repeated loading

000

005

010

015

020

025

0 1000 2000 3000 4000 5000 6000

Axi

al st

rain

()

Number of load cycles

091827

odoc

Figure 13 Eect of ratio of ldquocyclic deviator stress to the conningstress (σdσc)rdquo on the residual strain under long-term repeatedloading

Advances in Materials Science and Engineering 13

applicationsrdquo Journal of Hazardous Materials vol 321pp 547ndash556 2017

[3] L R Hoyos A J Puppala and C A Ordonez ldquoCharacter-ization of cement-fiber-treated reclaimed asphalt pavementaggregates preliminary investigationrdquo Journal of Materials inCivil Engineering vol 23 no 7 pp 977ndash989 2011

[4] R Taha A Al-Harthy K Al-Shamsi and M Al-ZubeidildquoCement stabilization of reclaimed asphalt pavement aggre-gate for road bases and subbasesrdquo Journal of Materials in CivilEngineering vol 14 no 3 pp 239ndash245 2002

[5] A M Azam and D A Cameron ldquoGeotechnical properties ofblends of recycled clay masonry and recycled concrete ag-gregates in unbound pavement constructionrdquo Journal ofMaterials in Civil Engineering vol 25 no 6 pp 788ndash7982013

[6] A Gabor and D Cameron ldquoProperties of recycled concreteaggregate for unbound pavement constructionrdquo Journal ofMaterials in Civil Engineering vol 24 no 6 pp 754ndash7642012

[7] C S Poon and D Chan ldquoFeasible use of recycled concreteaggregates and crushed clay brick as unbound road sub-baserdquoConstruction and Building Materials vol 20 no 8 pp 578ndash585 2006

[8] A Arulrajah M M Y Ali M M Disfani J Piratheepan andM W Bo ldquoGeotechnical performance of recycled glass-wasterock blends in footpath basesrdquo Journal of Materials in CivilEngineering vol 25 no 5 pp 653ndash661 2013

[9] L T Lee Jr ldquoRecycled glass and dredged materialsrdquo ReportNo ERDC TNDOER-T8 US Army Corps of EngineersEngineer Research and Development Center Mississippi MSUSA 2007

[10] M Ali A Arulrajah M Disfani and J Piratheepan ldquoSuit-ability of using recycled glassmdashcrushed rock blends forpavement subbase applicationsrdquo in Proceedings of the Geo-Frontiers 2011 Conference on Geotechnical Foundation Designpp 1325ndash1334 ASCE Reston VA USA 2011

[11] J Wartman D G Grubb and A S M Nasim ldquoSelectengineering characteristics of crushed glassrdquo Journal ofMaterials in Civil Engineering vol 16 no 6 pp 526ndash5392004

[12] W Kim and J Labuz Resilient Modulus and Strength of BaseCourse with Recycled Bituminous Material Minnesota De-partment of Transportation Research Services Section MNUSA 2007

[13] D Bloomquist G Diamond M Oden B Ruth and M TiaEngineering and Environmental Aspects of Recycled Materialsfor Highway Construction Appendix 1 Final Report 1993

[14] A Hussain and Q Yanjun ldquoEvaluation of asphalt mixescontaining reclaimed asphalt pavement for wearing cour-sesrdquo in Proceedings of the International Conference onTraffic and Transportation Engineering School of CivilEngineering Southwest Jiaotong University ChengduChina 2012

[15] M Solaimanian and M Tahmoressi ldquoVariability analysis ofhot-mix asphalt concrete containing high percentage ofreclaimed asphalt pavementrdquo Transportation Research Re-cord Journal of the Transportation Research Board vol 1543no 1 pp 89ndash96 1996

[16] A Gabr and D A Cameron ldquoProperties of recycled concreteaggregate for unbound pavement constructionrdquo Journal ofMaterials in Civil Engineering vol 24 no 6 pp 754ndash7642011

[17] W-L Huang D-H Lin N-B Chang and K-S LinldquoRecycling of construction and demolition waste via a

mechanical sorting processrdquo Resources Conservation andRecycling vol 37 no 1 pp 23ndash37 2002

[18] A R Pasandın and I Perez ldquoOverview of bituminous mix-tures made with recycled concrete Aggregatesrdquo Constructionand Building Materials vol 74 pp 151ndash161 2015

[19] P Jitsangiam H Nikraz and K Siripun ldquoConstruction anddemolition (CampD) waste as a road base material for WesternAustralia roadsrdquo Australian Geomechanics vol 44 no 3pp 57ndash62 2009

[20] A Nataatmadja and Y L Tan ldquoResilient response of recycledconcrete road aggregatesrdquo Journal of Transportation Engi-neering vol 127 no 5 pp 450ndash453 2001

[21] C Leek and K Siripun ldquoSpecification and performance ofrecycled materials in road pavementsrdquo Contract Rep (01119-1)2010

[22] J Green and J Hall Nondistructive Vibratory Testing ofAirport Pavement 1975

[23] W Heukelom and A Klomp ldquoDynamic testing as a means ofcontrolling pavements during and after constructionrdquo inProceedings of the International Conference on the StructuralDesign of Asphalt Pavements University of Michigan AnnArbor MI USA 1962

[24] Ohio Department of Transportation Pavement DesignManual Ohio Department of Transportation Office ofPavement Engineering OH USA 2008

[25] W D Powell H C Mayhew and M M Nunn ldquoestructural design of bituminous roadsrdquo Laboratory Report1132 Transport and Road Research Laboratory CrowthorneUK 1984

[26] M W Witczak X Qi and M W Mirza ldquoUse of nonlinearsubgrade modulus in AASHTO design procedurerdquo Journal ofTransportation Engineering vol 121 no 3 1995

[27] AASHTO Guide for Design of Pavement Structures Wash-ington DC USA 1993

[28] Asphalt Institute Research and Development of 5e AsphaltInstitutersquos 5ickness Design Manual (MS-1) 9th edition 1982

[29] T Buu Correlation of Resistance R-value and ResilientModulus of Idaho Subgrade Soil Idaho Department ofTransportation Division of Highways ID USA 1980

[30] S Muench J Mahoney and L Pierce WSDOT PavementGuide Washington State Department of TransportationInternet Module Washington DC USA 2009

[31] S Yeh and C Su ldquoResilient properties of Colorado soilsrdquoReport No CDOH-DH-SM-89-9 Colorado Department ofHighways Denver CO USA 1989

[32] M R ompson and Q L Robnett ldquoResilient properties ofsubgrade soilsrdquo Transportation Engineering Journal of ASCEvol 105 pp 71ndash89 1979

[33] W Lee N C Bohra A G Altschaeffl and T D WhiteldquoResilient modulus of cohesive soilsrdquo Journal of Geotechnicaland Geoenvironmental Engineering vol 123 no 2 pp 131ndash136 1997

[34] R Carmichael III and E Stuart ldquoPredicting resilient modulusa study to determine the mechanical properties of subgradesoilsrdquo Transportation Research Record vol 1043 pp 145ndash1481986

[35] E C Drumm Y Boateng-Poku and T Johnson PierceldquoEstimation of subgrade resilient modulus from standardtestsrdquo Journal of Geotechnical Engineering vol 116 no 5pp 774ndash789 1990

[36] M J Farrar and J P Turner Resilient Modulus of WyomingSubgrade Soils 1991

14 Advances in Materials Science and Engineering

[37] M P Jones and M W Witczak ldquoSubgrade modulus on thesan diego test roadrdquo Transportation Research Record Journalof the Transportation Research Board vol 641 pp 1ndash6 1977

[38] A M Rahim and K P George ldquoSubgrade soil indexproperties to estimate resilient modulusrdquo in Proceedings ofthe 83th Annual Meeting of the Transportation ResearchBoard National Research Council Washington DC USA2004

[39] M R ompson and T G LaGrow A Proposed ConventionalFlexible Pavement 5ickness Design Procedure University ofIllinois Peoria IL USA 1988

[40] R Pezo ldquoA general method of reporting resilient modulustests of soils a pavement engineerrsquos point of viewrdquo in Pro-ceedings of the 72nd Annual Meeting of Transportation Re-search Board Washington DC USA 1993

[41] R G Hicks and C L Monismith ldquoResilient properties ofgranular materialrdquo Transportation Research Record vol 345pp 15ndash31 1971

[42] J Uzan ldquoCharacterization of granular materialsrdquo Trans-portation Research Record Journal of the Transportation Re-search Board vol 1022 pp 52ndash59 1985

[43] National Cooperative Highway Research Program ldquoGuide formechanistic-empirical design of new and rehabilitatedpavement structuresrdquo NCHRP 1-37A NCHRP WashingtonDC USA 2004

[44] N M Louay H T Hani and H Ananda ldquoEvaluation ofresilient modulus of subgrade soil by cone penetration testrdquoTransportation Research Record Journal of the TransportationResearch Board vol 1652 pp 236ndash245 1999

[45] S Dai and J Zollars ldquoResilient modulus of Minnesota roadresearch project subgrade soilrdquo Transportation Research Re-cord Journal of the Transportation Research Board vol 1786no 1 pp 20ndash28 2002

[46] L Mohammad B Huang A Puppala and A Allen ldquoRe-gression model for resilient modulus of subgrade soilsrdquoTransportation Research Record Journal of the TransportationResearch Board vol 1687 no 1 pp 47ndash54 1999

[47] B Santa ldquoResilient modulus of subgrade soils comparison oftwo constitutive equationsrdquo Transportation Research RecordJournal of the Transportation Research Board vol 1462pp 79ndash90 1994

[48] H Von Quintus and B Killingsworth Analyses Relating toPavement Material Characterizations and their Effects onPavement Performance 1998

[49] O Porter ldquoe preparation of subgradesrdquo in Proceedings ofthe Nineteenth Annual Meeting Highway Research BoardWashington DC USA December 1939

[50] O J Porter ldquoDevelopment of the original method for highwaydesignrdquo Transactions of the American Society of Civil Engi-neers vol 115 pp 461ndash467 1950

[51] D W Hight and M G H Stevens ldquoAn analysis of theCalifornia Bearing Ratio test in saturated claysrdquoGeotechnique vol 32 no 4 pp 315ndash322 1982

[52] P R Fleming and C D F Rogers ldquoAssessment of pavementfoundations during constructionrdquo Proceedings of the In-stitution of Civil Engineers-Transport vol 111 no 2pp 105ndash115 1995

[53] M R ompson R Marshall and Q L Robnett ldquoResilientproperties of subgrade soilsrdquo Final Report No FHWA-IL-UI-160 University of Illinois Urbana IL USA 1976

[54] B Sukumaran V Kyatham A Shah and D Sheth ldquoSuit-ability of using California bearing ratio test to predict resilientmodulusrdquo in Proceedings Federal Aviation Administration

Airport Technology Transfer Conference Atlantic City NJUSA 2002

[55] N W Lister and D Powell ldquoDesign practices for pavementsin the United Kingdomrdquo in Proceedings of the 6th In-ternational Conference on the Structural Design of AsphaltPavements Ann Arbor MI USA July 1987

[56] S Hossain G Dickerson and C Weaver Comparative Studyof VTM and AASHTO Test Method for CBR Co MaterialsDivision VDOT 2005

[57] N Garg A Larkin and H Brar ldquoA comparative subgradeevaluation using CBR vane shear light weight deflectometerand resilient modulus testsrdquo in Proceedings of the 8th In-ternational Conference on the Bearing Capacity of RoadsRailways and Airfields CRC Press Champaign IL USA2009

[58] M Ayres Development of a rational probabilistic approach forflexible pavement analysis University of Maryland CollegePark MD USA 1997

[59] AASHTO T 307 Determining the Resilient Modulus of Soilsand Aggregate Materials (2012) American Association ofState Highway and Transportation Officials Washington DCUSA 2004

[60] M Arshad and M F Ahmed ldquoPotential use of reclaimedasphalt pavement and recycled concrete aggregate in basesubbase layers of flexible pavementsrdquo Construction andBuilding Materials vol 151 pp 83ndash97 2017

[61] M Arshad ldquoCorrelation between resilient modulus (MR) andconstrained modulus (Mc) values of granular materialsrdquoConstruction and Building Materials vol 159 pp 440ndash4502018

[62] P Guo and J Emery ldquoImportance of strain level inevaluating resilient modulus of granular materialsrdquo In-ternational Journal of Pavement Engineering vol 12 no 2pp 187ndash199 2011

[63] E J McGarrah ldquoEvaluation of current practices of reclaimedasphalt pavementvirgin aggregate as base course materialrdquoNo WA-RD 7131 Federal Highway AdministrationWashington DC USA 2007

[64] T B Alam M Abdelrahman and S A Schram ldquoLaboratorycharacterisation of recycled asphalt pavement as a base layerrdquoInternational Journal of Pavement Engineering vol 11 no 2pp 123ndash131 2010

[65] T Bennert and A Maher ldquoe development of a performancespecification for granular base and subbase materialrdquo ReportNo FHWA-NJ-2005-003 Department of TransportationEwing Township NJ USA 2005

[66] T H Wonnacott H omas and J Ronald ldquoRegression asecond course in statisticsrdquo No 04 QA2782 W6Wiley NewYork NY USA 1981

[67] W Penny and S Roberts Neural network predictions witherror bars Dept of Electrical and Electronic EngineeringTechnology and Medicine Research Report TR-97-1 ImperialCollege of Science London UK 1997

[68] R Dybowski and S J Roberts ldquoConfidence intervals andprediction intervals for feed-forward neural networksrdquoClinical Applications of Artificial Neural Networks pp 298ndash326 2001

[69] J Hauke and T Kossowski ldquoComparison of values ofPearsonrsquos and Spearmanrsquos correlation coefficients on the samesets of datardquo Quaestiones Geographicae vol 30 no 2pp 87ndash93 2011

[70] K-z Yan H-b Xu and G-h Shen ldquoNovel approach toresilient modulus using routine subgrade soil propertiesrdquo

Advances in Materials Science and Engineering 15

International Journal of Geomechanics vol 14 no 6 article04014025 2013

[71] Y H Chan ldquoBiostatistics 104 correlational analysisrdquoSingapore Medical Journal vol 44 no 12 pp 614ndash6192003

[72] B M Damghani D Welch C OrsquoMalley and S Knights ldquoemisleading value of measured correlationrdquoWilmott vol 2012no 62 pp 64ndash73 2012

[73] L B Christensen B Johnson and L A Turner ldquoResearchmethods design and analysisrdquo 2011

[74] W J Dixon and F J Massey Introduction to StatisticalAnalysis McGraw-Hill New York NY USA 1969

[75] B Colbert and Z You ldquoe determination of mechanicalperformance of laboratory produced hot mix asphalt mixturesusing controlled RAP and virgin aggregate size fractionsrdquoConstruction and Building Materials vol 26 no 1 pp 655ndash662 2012

[76] D H Timm and D E Newcomb ldquoPerpetual pavement designfor flexible pavements in the USrdquo International Journal ofPavement Engineering vol 7 no 2 pp 111ndash119 2006

[77] Y H Huang Pavement Analysis and Design Prentice-HallEnglewood Cliffs NJ USA 2nd edition 1993

[78] L Walubita W Liu and T Scullion Texas perpetualpavements-Experience overview and the way forward Tech-nical Report No 0-4822-3 Texas Transportation InstituteTexas AampM University College Station TX USA 2010

[79] D Timm and D Newcomb ldquoCalibration of flexible pavementperformance equations for Minnesota road research projectrdquoTransportation Research Record Journal of the TransportationResearch Board no 1853 pp 134ndash142 2003

16 Advances in Materials Science and Engineering

CorrosionInternational Journal of

Hindawiwwwhindawicom Volume 2018

Advances in

Materials Science and EngineeringHindawiwwwhindawicom Volume 2018

Hindawiwwwhindawicom Volume 2018

Journal of

Chemistry

Analytical ChemistryInternational Journal of

Hindawiwwwhindawicom Volume 2018

ScienticaHindawiwwwhindawicom Volume 2018

Polymer ScienceInternational Journal of

Hindawiwwwhindawicom Volume 2018

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Advances in Condensed Matter Physics

Hindawiwwwhindawicom Volume 2018

International Journal of

BiomaterialsHindawiwwwhindawicom

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Hindawiwwwhindawicom Volume 2018

NanotechnologyHindawiwwwhindawicom Volume 2018

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Hindawiwwwhindawicom Volume 2018

High Energy PhysicsAdvances in

Hindawi Publishing Corporation httpwwwhindawicom Volume 2013Hindawiwwwhindawicom

The Scientific World Journal

Volume 2018

TribologyAdvances in

Hindawiwwwhindawicom Volume 2018

Hindawiwwwhindawicom Volume 2018

ChemistryAdvances in

Hindawiwwwhindawicom Volume 2018

Advances inPhysical Chemistry

Hindawiwwwhindawicom Volume 2018

BioMed Research InternationalMaterials

Journal of

Hindawiwwwhindawicom Volume 2018

Na

nom

ate

ria

ls

Hindawiwwwhindawicom Volume 2018

Journal ofNanomaterials

Submit your manuscripts atwwwhindawicom

It is interesting to note that the 3-point CBR test en-compasses a wide range of dry and bulk density in thesample while on the other hand each resilient modulus

test uses a unique value of the samplersquos dry and bulkdensity To estimate a unique value of the bulk stress duringthe CBR test which is analogous to the bulk stress valueidentied from resilient modulus test the following pro-cedure was adopted

(1) Determine the dry density of the resilient modulussample

(2) Estimate the CBR value corresponding to that drydensity value

(3) Determine the axial stress (σpa) value correspondingto the CBR value

(4) Calculate the bulk stress using the following relation

σbulk θ σ1 + σ2 + σ3 σpa + σsa( ) + 2Ka σpa + σsa( ) (2)

Using a unique value of bulk stress on the basis ofequation (2) the corresponding resilient modulus valuefrom the actual experimental data (MR test) was matchedand then a correlation between CBR value (point 2)and the resilient modulus value in terms of the power

y = 52x064

R2 = 099

y = 88x056

R2 = 098

y = 136x051

R2 = 095

y = 101x056

R2 = 098

0

50

100

150

200

250

300

350

400

450

0 200 400 600 800

MR (

MPa

)

Bulk stress (kPa)

100 A75 A + 25 RAP(2)

50 A + 50 RAP(2)25 A + 75 RAP(2)

(a)

100 F75 F + 25 RAP(3)

50 F + 50 RAP(3)25 F + 75 RAP(3)

y = 517x064

R2 = 099

y = 745x058

R2 = 099

y = 101x054

R2 = 097

y = 972x057

R2 = 096

0

50

100

150

200

250

300

350

400

450

0 200 400 600 800

MR (

MPa

)

Bulk stress (kPa)

(b)

y = 517x064

R2 = 099

y = 745x058

R2 = 099

y = 101x054

R2 = 097

y = 972x057

R2 = 096

0

50

100

150

200

250

300

350

400

450

0 200 400 600 800

MR (

MPa

)

Bulk stress (kPa)

100 W75 W + 25 RAP(1)

50 W + 50 RAP(1)25 W + 75 RAP(1)

(c)

y = 517x064

R2 = 099

y = 745x058

R2 = 099

y = 101x054

R2 = 097

y = 972x057

R2 = 096

0

50

100

150

200

250

300

350

400

450

0 100 200 300 400 500 600 700 800

MR (

MPa

)

Bulk stress (kPa)

100 RCA25 RCA + 75 RAP(4)

50 RCA + 50 RAP(4)75 RCA + 25 RAP(4)

(d)

Figure 4 Variation ofMR value with bulk stress and percentage of RAP contents for (a) naturalA (b) natural F (c) naturalW and (d) RCA

Plunger

Surchargeweight

Soil sample

Lateral stress due toloading of plunger (σpl)

Lateral stress due tosurcharge loading (σsl)

Figure 5 An assumed conguration of axial and lateral stressesduring CBR test

6 Advances in Materials Science and Engineering

function having a coefficient of determination sim081 canbe given as

MR 4937(CBR)059

(3)

Table 5 shows the experimental data and the estimatedvalues of MR based on the four steps explained above andequation (3)

Figure 6 shows the capabilities of the proposed regressionmodel on the basis of the distribution of the data pointswhich in fact involves the experimentally determined andestimated MR values along the unity line giving a 95prediction and confidence interval is figure illustrates thatthere is an almost equal distribution of the data points on bothsides of the unity line Additionally the entire set of the datapoints is confined within the 95 prediction interval which isdefined as the interval around the linear regression line suchthat 95 of the predicted values will fall in this intervalFurther details on the mathematical framework of the pre-diction and the confidence interval can be found in standardtextbooks dealing with statistics and probability analysis suchas those authored by Wonnacott and Ronald [66] Penny andRoberts [67] and Dybowski and Roberts [68]

52 Statistical Analysis of the Proposed Model A Pearsonrsquoscorrelation coefficient (r) as given by equation (4) is ameasure of the strength and direction of linear associationthat exists between two continuous variables More specif-ically for the drawn line of best fit for sample data points oftwo variables Pearsonrsquos correlation indicates how well thedata points fit this new modelline of best fit and its nu-merical value indicates how far away all these data points areto the line of best fit (ie how well the data points fit this newmodelline of best fit) [69 70]

r 1113936

ni1 ui minus ui( 1113857 ti minusti( 1113857

1113936ni1 ui minus ui( 1113857

2ti minus ti( 1113857

21113960 1113961

1113969 (4)

where ui and ti experimental and predicted values re-spectively for the ith output ui average of experimentaloutputs and n size of sample

e statistical value of r may range from minus1 for a perfectnegative linear relationship (inversely related) to +1 for aperfect positive linear relationship (directly related) In gen-eral from theoretical point of view the strength of the linearrelationship can be categorised as ldquovery strongrdquo ldquomoderatelystrongrdquo and ldquofairly strongrdquo for the corresponding numericalvalues of r in the range 08ndash10 06ndash08 and 03ndash05 [71] Itshould be emphasized that if r 00 it does not necessarilymean that the two variables have no relationship In order tolook into the real strength of the correlation usually a sta-tistical test of significance is performed as discussed in [72]For this study three different types of statistical tests wereapplied to assess the significance of the developed correlationpresented in equation (3) and Table 5

Case 1 t-Test for the assessment of the implication of co-efficient of correlation (r) at a specific degree of freedom andlevel of significance [73]

is provides the researcher with some idea of how largea correlation coefficient must be before it can be consideredas demonstrating that there really is a relationship betweentwo variables (in our case the (MR)measured and CBR values)It may be the situation that two variables are related bychance and a hypothesis test for r allows the researcher todecide whether the observed r could have emerged by chanceor not e null hypothesis is that there is no relationshipbetween the two variables at is if ρ is the true correlationcoefficient for the two variables and when all populationvalues have been observed then the null hypothesis can begiven as

H0 ρ 0 (5)

e alternative hypothesis could be written as

HA ρne 0 (6)

whereas the standardised t-test for the null hypothesis that ris equal to zero can be written as

t r

nminus 21minus r2

1113970

(7)

where n is the number of paired observations in the givensample

e null hypothesis is evaluated by comparing the t-statistic of equation (7) with t-critical (201) obtained from tdistribution having the nminus 2 degree of freedom

Case 2 Direct comparison of the coefficient of correlationvalue (09) with the r-critical value (027) obtained from astatistical table corresponding to a specific degree of freedomand level of significance [61 74]

Case 3 It often becomes mandatory to statistically evaluatethe difference between two datasets obtained by two dif-ferent sources As in our case one set of MR values wasobtained experimentally using the AASHTOT 307-99(2004)protocol and the other set of MR values was obtained usingthe proposed correlation A standard t-test was performed toevaluate the difference between the paired values of(MR)measured and (MR)estimated at a specific degree of freedomand level of significance [74 75]

Table 6 summarises the statistical analysis of the abovethree cases

6 Assessment of Pavement PerformanceContaining RAPContent in Its Subbase Layer

To examine the performance of the pavement containingnatural aggregates mixed with RAP and used as subbasematerials the following analyses were performed usingcomputer software simulation

(1) To access the likelihood that critical pavement re-sponses exceed predefined thresholds using com-puter program PerRoad [76]

Advances in Materials Science and Engineering 7

(2) To determine the stresses and strains at critical lo-cations in the pavement structure using computerprogram KenPave developed by the University ofKentucky [77]

PerRoad is a Monte Carlo-based simulation softwareused to develop probability-based analysis for flexiblepavement is software can easily demonstrate the influ-ence of the MR values of the pavement material on the

Table 5 A comparison of measured and estimated MR values along with CBR values

MaterialBlend Dry unit weightachieved (kNm3) CBR () Total axial

stress (kPa)

Estimatedbulk stress

in CBR test (kPa)

MR values measuredprojected (MPa)

MR valuesestimated(MPa)

100 A 211 65 9780 1663 550 584100 F 221 74 11130 1892 600 631100 W 224 85 12780 2173 670 685100 RCA 192 53 7980 1357 410 51875 A+ 25 RAP(1) 207 47 7080 1204 470 48250 A+ 50 RAP(1) 205 31 4680 796 300 37725 A+ 75 RAP(1) 202 22 3330 566 280 30875 A+ 25 RAP(2) 203 55 8280 1408 505 52950 A+ 50 RAP(2) 208 39 5880 1000 410 43225 A+ 75 RAP(2) 213 17 2580 439 260 26475 A+ 25 RAP(3) 201 51 7680 1306 490 50650 A+ 50 RAP(3) 205 30 4530 770 315 37025 A+ 75 RAP(3) 199 19 2880 490 310 28275 A+ 25 RAP(4) 197 55 8280 1408 505 52950 A+ 50 RAP(4) 198 43 6480 1102 402 45825 A+ 75 RAP(4) 192 27 4080 694 252 34775 F+ 25 RAP(1) 208 52 7830 1331 538 51250 F+ 50 RAP(1) 213 41 6180 1051 455 44525 F+ 75 RAP(1) 201 14 2130 362 356 23575 F+ 25 RAP(2) 205 59 8880 1510 525 55250 F+ 50 RAP(2) 199 48 7230 1229 407 48825 F+ 75 RAP(2) 197 31 4680 796 408 37775 F+ 25 RAP(3) 201 62 9330 1586 667 56850 F+ 50 RAP(3) 192 41 6180 1051 516 44525 F+ 75 RAP(3) 208 19 2880 490 343 28275 F+ 25 RAP(4) 213 43 6480 1102 515 45850 F+ 50 RAP(4) 201 32 4830 821 490 38425 F+ 75 RAP(4) 213 13 1980 337 278 22575 W+25 RAP(1) 208 51 7680 1306 510 50650 W+50 RAP(1) 205 44 6630 1127 500 46425 W+75 RAP(1) 199 16 2430 413 240 25575 W+25 RAP(2) 197 55 8280 1408 502 52950 W+50 RAP(2) 199 31 4680 796 438 37725 W+75 RAP(2) 213 12 1830 311 265 21575 W+25 RAP(3) 201 48 7230 1229 520 48850 W+50 RAP(3) 213 35 5280 898 447 40525 W+75 RAP(3) 207 21 3180 541 255 29975 W+25 RAP(4) 205 45 6780 1153 480 47050 W+50 RAP(4) 199 34 5130 872 473 39825 W+75 RAP(4) 192 9 1380 235 213 18175 RCA+ 25 RAP(1) 208 38 5730 974 486 42550 RCA+ 50 RAP(1) 213 23 3480 592 330 31625 RCA+ 75 RAP(1) 201 12 1830 311 187 21575 RCA+ 25 RAP(2) 213 38 5730 974 525 42550 RCA+ 50 RAP(2) 201 31 4680 796 356 37725 RCA+ 75 RAP(2) 214 14 2130 362 200 23575 RCA+ 25 RAP(3) 201 32 4830 821 447 38450 RCA+ 50 RAP(3) 205 15 2280 388 226 24525 RCA+ 75 RAP(3) 199 9 1380 235 148 18175 RCA+ 25 RAP(4) 192 39 5880 1000 473 43250 RCA+ 50 RAP(4) 201 13 1980 337 200 22525 RCA+ 75 RAP(4) 202 18 2730 464 161 273

8 Advances in Materials Science and Engineering

cumulative damage factor (CDF) It also demonstrates thelikelihood that critical pavement responses could exceedpredened thresholds which are the horizontal tensile strainof 70 microns at the bottom of the asphalt concrete (which islinked with fatigue cracking) and the vertical compressivestrain of 200 microns at the top of the subgrade (which isassociated with the structural rutting) [78]

61 Pavement Structure and Material CharacteristicsFigure 7 shows a typical cross section of copyexible pavementswhich consists of a hot mix asphalt layer supported by theunbound base unbound subbase and compacted subgradeyene thickness of each layer generally depends on the tracload or more specically the equivalent single axle load(ESAL) during the proposed life cycle of the road

In this parametric study the focus is placed on how theproperties of granular subbase materials are changed by theaddition of a certain amount of RAP and their eect on thepavementrsquos performance As such the resilient modulus ofthe granular base and the asphalt concrete is xed yenestructure of the pavement to be simulated and the propertiesof materials in dierent layers are summarised in Table 7 Inthis particular study the subbase material will be one of theaggregates or aggregateRAP blends tested during the ex-perimental studies of this research

yene properties of the dierent pavement layers used inthe analysis are shown in Table 7 yene bulk stresses at the top

and bottom of the granular subbase layer were determinedusing the computer program KenPave For the selectedHMA resilient moduli (MR 5000MPa) the bulk stresseswere found in the range of 27 kPa to 30 kPa and 14 kPa to18 kPa at the top and bottom of the subbase layers re-spectively for the wheel load of 40 kN In the simulationsvalues of MR are used corresponding to the bulk stress of100 kPa

62 Trac Load For this parametric study the trac datafor urban interstate highways as recommended byAASHTO were used In the case of the PerRoad softwaretrac is separated by axle type single axle tandem axletridem axle and steer axle After determining the percentageof each axle type in the total trac trac is then subdividedinto weight classes in 2 kip intervals yene following is thesummary of the trac data the average annual daily trac(AADT) is 1000 vehicles with 10 being trucks annualgrowth rate of trac is 4 the directional distribution is50 and the percentages of single tandem and tridem axlesare 5573 4266 and 161 respectively yene rest of thetrac loading characteristics in terms of the distribution ofvehicle types and axle weights are described in Figure 8yenese values were used as input in PerRoad 35 Axle weightswere used to evaluate the response of the pavement layers interms of stresses strains and deformations at critical lo-cations of certain layers of the copyexible pavement

Table 6 Summary of the statistical analysis of the proposed model at an alpha value of 005 which matches to 95 condence level

Case Comments

1 t-Critical 20 t-Statistic 1459Since t-statisticgt t-critical which implies that value of the correlation coecient is not dueto sampling error the null hypothesis is rejected and it is concluded that there is a

signicant correlation between (MR)measured and CBR value in the population

2 r-Pearson 09 r-Critical 027

Since r-Pearsongt r-critical which implies that the null hypothesis is rejectedit is quite realistic to accept the ldquoalternative hypothesisrdquo that is the value of r that

we have obtained from our sample represents a real relationship between (MR)measuredand CBR value in the population

3 t-Critical 20 t-Statistic 052Since t-statisticlt t-critical which implies that the null hypothesis is accepted

it is concluded that there is an insignicant dierence between(MR)measured and (MR)correlated values in the population

0

100

200

300

400

500

600

700

800

0 200 400 600 800

MR

(esti

mat

ed)

MR (measured)

1 1 line

95confidence

interval

95prediction

interval

Figure 6 A comparison of estimated and measured MR values along the unity line

Advances in Materials Science and Engineering 9

63 Pavement Performance Criteria In the design ofconventional flexible pavements pavement sectionsare designed corresponding to a cumulative damagefactor (CDF) of 10 which corresponds to a terminallevel of pavement damage For perpetual pavementshowever it is recommended that the CDF is equal to 01at the end of its design life [76] e fatigue and ruttingalgorithms developed at MnROAD [79] for the cali-bration of flexible pavement performance equations wereused to predict pavement damage in cases where pave-ment responses exceeded these thresholds ese corre-lations are as follows

Nf 283lowast 10minus61εt

1113888 1113889

3148

(fatigue)

Nr 6026lowast 10minus81εv

1113888 1113889

387

(ritting)

(8)

where Nf number of load repetitions when fatigue failureoccurs Nr number of load repetition when rutting failureoccurs εt the horizontal tensile strain at the bottom of theHMA and εv the vertical compressive strain at the top ofthe subgrade

It should be noted that the damage of rutting estimatedby PerRoad only takes into account the permanent de-formation in the subgrade Any rutting associated with thedeformation of granular subbase materials is not consideredAccording to the test results in this study use of RAP ingranular subbase layers may induce substantial residualdeformation Further investigation should be performed toget a better understanding of its influence on the rutting offlexible pavements

64 Simulation Results and Discussion Simulation resultsare obtained and discussed in terms of

(1) e likelihood of the tensile strain at the bottom ofthe HMA exceeding 70 με

(2) e likelihood of the vertical strain at the top of thesubgrade soil exceeding 200 με

(3) e number of years it could take to reach a CDF of01 (the threshold level) for fatigue damage

(4) e number of years it could take to reach a CDF of01 for damage induced by rutting

Figure 9 illustrates the concept frequency distributionfor strain both within and outside the threshold limits

We first examine the likelihood of critical pavementresponses exceeding the predefined thresholds when theresilient modulus of the asphalt concrete is 5000MPa anddifferent aggregates or aggregate-RAP blends are used inthe granular subbase layer Figure 10 summarises (1) thelikelihood of the tensile strain at the bottom of the HMAremaining within the critical value of 70 με and (2) thelikelihood of the vertical strain at the top of the subgradesoil exceeding 200 με From this figure it can be inter-preted that all of the blends result in better pavementperformance than the natural aggregate both in terms ofthe tensile strains at the bottom of the HMA and thevertical compressive strains at the top of the subgrade soilFor instance the natural aggregates and RCA on averagehave an 813 likelihood that horizontal strain at thebottom of the HMA will remain within the critical limit of70 με

On the other hand the likelihood for blended ma-terials containing 25 50 and 75 of RAP materials inthe blended samples may reach (on average) 85758937 and 9377 (respectively) chance of remainingwithin the limit Similarly the likelihood that the com-pressive strain at the top of the subgrade will not exceedthe critical value of 200 microns is 8828 (naturalsamples) 9346 (25 RAP material blends) 9557(50 RAP material blends) and 982 (75 RAP ma-terial blends)

Figure 11 shows the number of years required to reacha CDF of 01 when fatigue is controlled by the horizontaltensile strain at the bottom of the subgrade and the HMAand vertical structural rutting are controlled by the verticalcompressive strain at the top of the subgrade e numberof years required to reach a CDF of 01 in general in-creases in line with the increase in the quantity of RAP inthe blend For example the number of years required toreach a CDF of 01 in terms of fatigue damage at thebottom of HMA is 4033 years for natural samples whilethe corresponding figure for the blends containing 75RAP is 5168 years on average A similar trend regarding anincrease in the number of years required to reach a CDF of01 in terms of structural damage at the top of the subgradewas also observed Furthermore for all the cases thenumber of years to reach a CDF of 01 was more than40 years but it is clear that fatigue will be the predominantpavement failure mode

Asphalt concrete

Unbound base

Unbound subbase

Compacted subgrade

Natural subgrade

Figure 7 A typical cross section of flexible pavement

Table 7 Material properties and pavement layer thicknesses

Parameters HMA Base course Subbasecourse Subgrade

MR (MPa) 5000 350 Variable 35Coefficient ofvariation for MR () 25 30 35 45

ickness ofthe layer (mm) 250 200 300 mdash

icknessVariability () 5 8 15 mdash

Poisson ratio 03 03 03 04

10 Advances in Materials Science and Engineering

7 Long-Term Effect of Cyclic Loading onBlended Samples

In order to explore the long-term eects of cyclic loading 9repeated load triaxial tests were performed under a range ofcyclic loading conditions and varying percentages of RAPcontents Figure 12 presents the variation of the residual strainof the tested samples subjected to 20000 load cycles under twodierent values of conning pressures of 345 kPa and1379 kPa each while the corresponding cyclic deviator stresswas maintained at 3105 kPa and 372 kPa From this gure itcan be inferred that the presence of RAP contents increases theresidual strain considerably for both of the conning pressurescenarios For instance for the repeated load test conducted atthe conning pressure of 345 kPa the residual strain for 100natural aggregate F is 012 after 20000 load cycles while forthe blend containing 50 RAP(2) and 75 RAP(2) thecorresponding gures reach 022 and 060 ie an additionof 50 RAP increases the residual strain by amargin of almost83 while the addition of 75 RAP increases the residualstrain by almost 400 Similarly for the repeated load testsconducted at a conning pressure of 1379 kPa on samples

containing natural aggregateW and the blends with RAP(1) at50 and 75 the residual strain after 20000 load cycles is 55and 300 higher when compared with the correspondingvalue for the 100 natural aggregate W Furthermore it isevident from the gures that almost 60 of the total residualstrain occurred during the rst 2000 load cycles out of the20000 total load cycles applied across all the cases

However it should be emphasized that there is a ten-dency for the elastic shakedown to be less pronounced forblended samples when compared to pure natural aggregatesFor instance for the blended sample 50 W and 50RAP(1) the rate of increase of strain becomes 0000154 forthe load cycles in the range of 2000ndash20000 On the otherhand this gure remained limited to 0000056 for thesample containing 100 natural aggregate W under thesame loading condition

Figure 13 shows the eect of the ratio of ldquocyclic deviatorstress to the conning stress (σdσc)rdquo on the residual strain forthe blended sample containing 50 A and 50 RAP(3)From this gure it can be inferred that the ratio σdσc has asubstantial eect on the residual strain generated undercyclic loading For instance at (σdσc) 09 the residualstrain after 6000 load cycles is limited to 006 however thisvalue reaches 011 and 021 at (σdσc) 18 and(σdσc) 27 respectively yene samples tend to stabilisemore quickly under a lower value of (σdσc) 09 whencompared to the stabilising tendency at the higher values of(σdσc) 18 and (σdσc) 27 which were also in-vestigated in this research A 50ndash60 residual strain occursduring the rst 1000 load cycles out of the total 6000 loadcycles applied during the experimental campaign irre-spective of the σdσc value

8 Summary and Conclusions

(1) yene blended samples (ie RAP combined withnatural granular materials) result in higher MRvalues than those obtained for natural granular

Figure 8 Vehicular load classication used in PerRoad 35

Area outside the threshold limit

Stra

in fr

eque

ncy

Figure 9 Example of frequency distribution of strain within andoutside the threshold limits

Advances in Materials Science and Engineering 11

samples under the same loading conditions whilevariations between MR values and the applied bulkstresses during the resilient modulus tests can beapproximated through power law having coecientof correlation (r) value in the range of 097ndash099

(2) yene CBR values of blended samples decrease withthe addition of RAP contents however a clear

decreasing trend in conjunction with an increasingpercentage of RAP contents could not be found

(3) yene new model for the estimation of MR values in-cludes the stress state through the experimentallydetermined CBR having a coecient of correlation ldquorrdquoequal to approximately 09 with fair distribution of thedata points (MR measured and MR estimated) about

Perc

enta

ge o

f are

a

70

75

80

85

90

95

100

100

A10

0 F

100

W10

0 R

CA75

A

+ 2

5 R

AP(

1)75

A

+ 2

5 R

AP(

2)75

A

+ 2

5 R

AP(

3)75

A

+ 2

5 R

AP(

4)75

F

+ 2

5 R

AP(

1)75

F

+ 2

5 R

AP(

2)75

F

+ 2

5 R

AP(

3)75

F

+ 2

5 R

AP(

4)75

W

+ 2

5 R

AP(

1)75

W

+ 2

5 R

AP(

2)75

W

+ 2

5 R

AP(

3)75

W

+ 2

5 R

AP(

4)75

R

CA +

25

RA

P(1)

75

RCA

+ 2

5 R

AP(

2)75

R

CA +

25

RA

P(3)

75

RCA

+ 2

5 R

AP(

4)50

A

+ 5

0 R

AP(

1)50

A

+ 5

0 R

AP(

2)50

A

+ 5

0 R

AP(

3)50

A

+ 5

0 R

AP(

4)50

F

+ 5

0 R

AP(

1)50

F

+ 5

0 R

AP(

2)50

F

+ 5

0 R

AP(

3)50

F

+ 5

0 R

AP(

4)50

W

+ 5

0 R

AP(

1)50

W

+ 5

0 R

AP(

2)50

W

+ 5

0 R

AP(

3)50

W

+ 5

0 R

AP(

4)50

R

CA +

50

RA

P(1)

50

RCA

+ 5

0 R

AP(

2)50

R

CA +

50

RA

P(3)

50

RCA

+ 5

0 R

AP(

4)25

A

+ 7

5 R

AP(

1)25

A

+ 7

5 R

AP(

2)25

A

+ 7

5 R

AP(

3)25

A

+ 7

5 R

AP(

4)25

F

+ 7

5 R

AP(

1)25

F

+ 7

5 R

AP(

2)25

F

+ 7

5 R

AP(

3)25

F

+ 7

5 R

AP(

4)25

W

+ 7

5 R

AP(

1)25

W

+ 7

5 R

AP(

2)25

W

+ 7

5 R

AP(

3)25

W

+ 7

5 R

AP(

4)25

R

CA +

75

RA

P(1)

25

RCA

+ 7

5 R

AP(

2)25

R

CA +

75

RA

P(3)

25

RCA

+ 7

5 R

AP(

4)

Percentage of area within the critical limit of horizontal strain at the bottom of HMAPercentage of area within the critical limit of vertical strain at the top of subgrade

Figure 10 Percentage of area within the critical limits for horizontal strain at the bottom of HMA and vertical strain at the top of subgrade

30

35

40

45

50

55

60

65

70

100

A10

0 F

100

W10

0 R

CA75

A

+ 2

5 R

AP(

1)75

A

+ 2

5 R

AP(

2)75

A

+ 2

5 R

AP(

3)75

A

+ 2

5 R

AP(

4)75

F

+ 2

5 R

AP(

1)75

F

+ 2

5 R

AP(

2)75

F

+ 2

5 R

AP(

3)75

F

+ 2

5 R

AP(

4)75

W

+ 2

5 R

AP(

1)75

W

+ 2

5 R

AP(

2)75

W

+ 2

5 R

AP(

3)75

W

+ 2

5 R

AP(

4)75

R

CA +

25

RA

P(1)

75

RCA

+ 2

5 R

AP(

2)75

R

CA +

25

RA

P(3)

75

RCA

+ 2

5 R

AP(

4)50

A

+ 5

0 R

AP(

1)50

A

+ 5

0 R

AP(

2)50

A

+ 5

0 R

AP(

3)50

A

+ 5

0 R

AP(

4)50

F

+ 5

0 R

AP(

1)50

F

+ 5

0 R

AP(

2)50

F

+ 5

0 R

AP(

3)50

F

+ 5

0 R

AP(

4)50

W

+ 5

0 R

AP(

1)50

W

+ 5

0 R

AP(

2)50

W

+ 5

0 R

AP(

3)50

W

+ 5

0 R

AP(

4)50

R

CA +

50

RA

P(1)

50

RCA

+ 5

0 R

AP(

2)50

R

CA +

50

RA

P(3)

50

RCA

+ 5

0 R

AP(

4)25

A

+ 7

5 R

AP(

1)25

A

+ 7

5 R

AP(

2)25

A

+ 7

5 R

AP(

3)25

A

+ 7

5 R

AP(

4)25

F

+ 7

5 R

AP(

1)25

F

+ 7

5 R

AP(

2)25

F

+ 7

5 R

AP(

3)25

F

+ 7

5 R

AP(

4)25

W

+ 7

5 R

AP(

1)25

W

+ 7

5 R

AP(

2)25

W

+ 7

5 R

AP(

3)25

W

+ 7

5 R

AP(

4)25

R

CA +

75

RA

P(1)

25

RCA

+ 7

5 R

AP(

2)25

R

CA +

75

RA

P(3)

25

RCA

+ 7

5 R

AP(

4)

Year

s

Number of years required to reach CDF = 01 in terms of horizontal strain at the bottom of HMANumber of years required to reach CDF = 01 in terms of vertical strain at the top of subgrade

Figure 11 Number of years required to reach CDF 01 in terms of horizontal strain at the bottom of HMA and vertical strain at the top ofsubgrade

12 Advances in Materials Science and Engineering

the unity line indicating that the proposed regressionmodel has a moderate to strong correlation

(4) Statistical analysis of simulation results based onPerRoad and KenPave software demonstrates thatthe addition of RAP contents in the subbase layer ofthe copyexible pavement signicantly improves itsperformance against rutting and fatigue

(5) Residual strain during the long-term repeated loadtriaxial test was found to increase in line with anincrease in the ratio of ldquocyclic deviator stress to theconning stress (σdσc)rdquo in correlation to an increasein the percentage of RAP contents in the blendedsample

(6) From the authorrsquos perspective the addition of RAPcontents beyond a certain limit (sim50) may prove tobe detrimental for the overall performance of copyexiblepavement structure

Data Availability

yene experimental data used to support the ndings of thisstudy are included within the article in the form of graphsand tables

Conflicts of Interest

yene author declares that there are no concopyicts of interestregarding the publication of this paper

References

[1] R B Mallick and A Veeraragavan ldquoSustainable pavements inIndia-the time to start is nowrdquo New Building Materials andConstruction World (NBMampCW) Magazine vol 16 no 3pp 128ndash140 2010

[2] A Mohammadinia A Arulrajah S Horpibulsuk andA Chinkulkijniwat ldquoEect of copyy ash on properties of crushedbrick and reclaimed asphalt in pavement basesubbase

000

050

100

150

200

250

300

350

400

450

500

0 2000 4000 6000 8000 10000 12000 14000 16000 18000 20000

Axi

al st

rain

()

Number of load cycles

100 W50 W + 50 RAP(1)25 W + 75 RAP(1)100 F50 F + 50 RAP(2)25 F + 75 RAP(2)

σc = 1379kPa σd = 372kPa

Figure 12 Eect of RAP contents on residual strain under long-term repeated loading

000

005

010

015

020

025

0 1000 2000 3000 4000 5000 6000

Axi

al st

rain

()

Number of load cycles

091827

odoc

Figure 13 Eect of ratio of ldquocyclic deviator stress to the conningstress (σdσc)rdquo on the residual strain under long-term repeatedloading

Advances in Materials Science and Engineering 13

applicationsrdquo Journal of Hazardous Materials vol 321pp 547ndash556 2017

[3] L R Hoyos A J Puppala and C A Ordonez ldquoCharacter-ization of cement-fiber-treated reclaimed asphalt pavementaggregates preliminary investigationrdquo Journal of Materials inCivil Engineering vol 23 no 7 pp 977ndash989 2011

[4] R Taha A Al-Harthy K Al-Shamsi and M Al-ZubeidildquoCement stabilization of reclaimed asphalt pavement aggre-gate for road bases and subbasesrdquo Journal of Materials in CivilEngineering vol 14 no 3 pp 239ndash245 2002

[5] A M Azam and D A Cameron ldquoGeotechnical properties ofblends of recycled clay masonry and recycled concrete ag-gregates in unbound pavement constructionrdquo Journal ofMaterials in Civil Engineering vol 25 no 6 pp 788ndash7982013

[6] A Gabor and D Cameron ldquoProperties of recycled concreteaggregate for unbound pavement constructionrdquo Journal ofMaterials in Civil Engineering vol 24 no 6 pp 754ndash7642012

[7] C S Poon and D Chan ldquoFeasible use of recycled concreteaggregates and crushed clay brick as unbound road sub-baserdquoConstruction and Building Materials vol 20 no 8 pp 578ndash585 2006

[8] A Arulrajah M M Y Ali M M Disfani J Piratheepan andM W Bo ldquoGeotechnical performance of recycled glass-wasterock blends in footpath basesrdquo Journal of Materials in CivilEngineering vol 25 no 5 pp 653ndash661 2013

[9] L T Lee Jr ldquoRecycled glass and dredged materialsrdquo ReportNo ERDC TNDOER-T8 US Army Corps of EngineersEngineer Research and Development Center Mississippi MSUSA 2007

[10] M Ali A Arulrajah M Disfani and J Piratheepan ldquoSuit-ability of using recycled glassmdashcrushed rock blends forpavement subbase applicationsrdquo in Proceedings of the Geo-Frontiers 2011 Conference on Geotechnical Foundation Designpp 1325ndash1334 ASCE Reston VA USA 2011

[11] J Wartman D G Grubb and A S M Nasim ldquoSelectengineering characteristics of crushed glassrdquo Journal ofMaterials in Civil Engineering vol 16 no 6 pp 526ndash5392004

[12] W Kim and J Labuz Resilient Modulus and Strength of BaseCourse with Recycled Bituminous Material Minnesota De-partment of Transportation Research Services Section MNUSA 2007

[13] D Bloomquist G Diamond M Oden B Ruth and M TiaEngineering and Environmental Aspects of Recycled Materialsfor Highway Construction Appendix 1 Final Report 1993

[14] A Hussain and Q Yanjun ldquoEvaluation of asphalt mixescontaining reclaimed asphalt pavement for wearing cour-sesrdquo in Proceedings of the International Conference onTraffic and Transportation Engineering School of CivilEngineering Southwest Jiaotong University ChengduChina 2012

[15] M Solaimanian and M Tahmoressi ldquoVariability analysis ofhot-mix asphalt concrete containing high percentage ofreclaimed asphalt pavementrdquo Transportation Research Re-cord Journal of the Transportation Research Board vol 1543no 1 pp 89ndash96 1996

[16] A Gabr and D A Cameron ldquoProperties of recycled concreteaggregate for unbound pavement constructionrdquo Journal ofMaterials in Civil Engineering vol 24 no 6 pp 754ndash7642011

[17] W-L Huang D-H Lin N-B Chang and K-S LinldquoRecycling of construction and demolition waste via a

mechanical sorting processrdquo Resources Conservation andRecycling vol 37 no 1 pp 23ndash37 2002

[18] A R Pasandın and I Perez ldquoOverview of bituminous mix-tures made with recycled concrete Aggregatesrdquo Constructionand Building Materials vol 74 pp 151ndash161 2015

[19] P Jitsangiam H Nikraz and K Siripun ldquoConstruction anddemolition (CampD) waste as a road base material for WesternAustralia roadsrdquo Australian Geomechanics vol 44 no 3pp 57ndash62 2009

[20] A Nataatmadja and Y L Tan ldquoResilient response of recycledconcrete road aggregatesrdquo Journal of Transportation Engi-neering vol 127 no 5 pp 450ndash453 2001

[21] C Leek and K Siripun ldquoSpecification and performance ofrecycled materials in road pavementsrdquo Contract Rep (01119-1)2010

[22] J Green and J Hall Nondistructive Vibratory Testing ofAirport Pavement 1975

[23] W Heukelom and A Klomp ldquoDynamic testing as a means ofcontrolling pavements during and after constructionrdquo inProceedings of the International Conference on the StructuralDesign of Asphalt Pavements University of Michigan AnnArbor MI USA 1962

[24] Ohio Department of Transportation Pavement DesignManual Ohio Department of Transportation Office ofPavement Engineering OH USA 2008

[25] W D Powell H C Mayhew and M M Nunn ldquoestructural design of bituminous roadsrdquo Laboratory Report1132 Transport and Road Research Laboratory CrowthorneUK 1984

[26] M W Witczak X Qi and M W Mirza ldquoUse of nonlinearsubgrade modulus in AASHTO design procedurerdquo Journal ofTransportation Engineering vol 121 no 3 1995

[27] AASHTO Guide for Design of Pavement Structures Wash-ington DC USA 1993

[28] Asphalt Institute Research and Development of 5e AsphaltInstitutersquos 5ickness Design Manual (MS-1) 9th edition 1982

[29] T Buu Correlation of Resistance R-value and ResilientModulus of Idaho Subgrade Soil Idaho Department ofTransportation Division of Highways ID USA 1980

[30] S Muench J Mahoney and L Pierce WSDOT PavementGuide Washington State Department of TransportationInternet Module Washington DC USA 2009

[31] S Yeh and C Su ldquoResilient properties of Colorado soilsrdquoReport No CDOH-DH-SM-89-9 Colorado Department ofHighways Denver CO USA 1989

[32] M R ompson and Q L Robnett ldquoResilient properties ofsubgrade soilsrdquo Transportation Engineering Journal of ASCEvol 105 pp 71ndash89 1979

[33] W Lee N C Bohra A G Altschaeffl and T D WhiteldquoResilient modulus of cohesive soilsrdquo Journal of Geotechnicaland Geoenvironmental Engineering vol 123 no 2 pp 131ndash136 1997

[34] R Carmichael III and E Stuart ldquoPredicting resilient modulusa study to determine the mechanical properties of subgradesoilsrdquo Transportation Research Record vol 1043 pp 145ndash1481986

[35] E C Drumm Y Boateng-Poku and T Johnson PierceldquoEstimation of subgrade resilient modulus from standardtestsrdquo Journal of Geotechnical Engineering vol 116 no 5pp 774ndash789 1990

[36] M J Farrar and J P Turner Resilient Modulus of WyomingSubgrade Soils 1991

14 Advances in Materials Science and Engineering

[37] M P Jones and M W Witczak ldquoSubgrade modulus on thesan diego test roadrdquo Transportation Research Record Journalof the Transportation Research Board vol 641 pp 1ndash6 1977

[38] A M Rahim and K P George ldquoSubgrade soil indexproperties to estimate resilient modulusrdquo in Proceedings ofthe 83th Annual Meeting of the Transportation ResearchBoard National Research Council Washington DC USA2004

[39] M R ompson and T G LaGrow A Proposed ConventionalFlexible Pavement 5ickness Design Procedure University ofIllinois Peoria IL USA 1988

[40] R Pezo ldquoA general method of reporting resilient modulustests of soils a pavement engineerrsquos point of viewrdquo in Pro-ceedings of the 72nd Annual Meeting of Transportation Re-search Board Washington DC USA 1993

[41] R G Hicks and C L Monismith ldquoResilient properties ofgranular materialrdquo Transportation Research Record vol 345pp 15ndash31 1971

[42] J Uzan ldquoCharacterization of granular materialsrdquo Trans-portation Research Record Journal of the Transportation Re-search Board vol 1022 pp 52ndash59 1985

[43] National Cooperative Highway Research Program ldquoGuide formechanistic-empirical design of new and rehabilitatedpavement structuresrdquo NCHRP 1-37A NCHRP WashingtonDC USA 2004

[44] N M Louay H T Hani and H Ananda ldquoEvaluation ofresilient modulus of subgrade soil by cone penetration testrdquoTransportation Research Record Journal of the TransportationResearch Board vol 1652 pp 236ndash245 1999

[45] S Dai and J Zollars ldquoResilient modulus of Minnesota roadresearch project subgrade soilrdquo Transportation Research Re-cord Journal of the Transportation Research Board vol 1786no 1 pp 20ndash28 2002

[46] L Mohammad B Huang A Puppala and A Allen ldquoRe-gression model for resilient modulus of subgrade soilsrdquoTransportation Research Record Journal of the TransportationResearch Board vol 1687 no 1 pp 47ndash54 1999

[47] B Santa ldquoResilient modulus of subgrade soils comparison oftwo constitutive equationsrdquo Transportation Research RecordJournal of the Transportation Research Board vol 1462pp 79ndash90 1994

[48] H Von Quintus and B Killingsworth Analyses Relating toPavement Material Characterizations and their Effects onPavement Performance 1998

[49] O Porter ldquoe preparation of subgradesrdquo in Proceedings ofthe Nineteenth Annual Meeting Highway Research BoardWashington DC USA December 1939

[50] O J Porter ldquoDevelopment of the original method for highwaydesignrdquo Transactions of the American Society of Civil Engi-neers vol 115 pp 461ndash467 1950

[51] D W Hight and M G H Stevens ldquoAn analysis of theCalifornia Bearing Ratio test in saturated claysrdquoGeotechnique vol 32 no 4 pp 315ndash322 1982

[52] P R Fleming and C D F Rogers ldquoAssessment of pavementfoundations during constructionrdquo Proceedings of the In-stitution of Civil Engineers-Transport vol 111 no 2pp 105ndash115 1995

[53] M R ompson R Marshall and Q L Robnett ldquoResilientproperties of subgrade soilsrdquo Final Report No FHWA-IL-UI-160 University of Illinois Urbana IL USA 1976

[54] B Sukumaran V Kyatham A Shah and D Sheth ldquoSuit-ability of using California bearing ratio test to predict resilientmodulusrdquo in Proceedings Federal Aviation Administration

Airport Technology Transfer Conference Atlantic City NJUSA 2002

[55] N W Lister and D Powell ldquoDesign practices for pavementsin the United Kingdomrdquo in Proceedings of the 6th In-ternational Conference on the Structural Design of AsphaltPavements Ann Arbor MI USA July 1987

[56] S Hossain G Dickerson and C Weaver Comparative Studyof VTM and AASHTO Test Method for CBR Co MaterialsDivision VDOT 2005

[57] N Garg A Larkin and H Brar ldquoA comparative subgradeevaluation using CBR vane shear light weight deflectometerand resilient modulus testsrdquo in Proceedings of the 8th In-ternational Conference on the Bearing Capacity of RoadsRailways and Airfields CRC Press Champaign IL USA2009

[58] M Ayres Development of a rational probabilistic approach forflexible pavement analysis University of Maryland CollegePark MD USA 1997

[59] AASHTO T 307 Determining the Resilient Modulus of Soilsand Aggregate Materials (2012) American Association ofState Highway and Transportation Officials Washington DCUSA 2004

[60] M Arshad and M F Ahmed ldquoPotential use of reclaimedasphalt pavement and recycled concrete aggregate in basesubbase layers of flexible pavementsrdquo Construction andBuilding Materials vol 151 pp 83ndash97 2017

[61] M Arshad ldquoCorrelation between resilient modulus (MR) andconstrained modulus (Mc) values of granular materialsrdquoConstruction and Building Materials vol 159 pp 440ndash4502018

[62] P Guo and J Emery ldquoImportance of strain level inevaluating resilient modulus of granular materialsrdquo In-ternational Journal of Pavement Engineering vol 12 no 2pp 187ndash199 2011

[63] E J McGarrah ldquoEvaluation of current practices of reclaimedasphalt pavementvirgin aggregate as base course materialrdquoNo WA-RD 7131 Federal Highway AdministrationWashington DC USA 2007

[64] T B Alam M Abdelrahman and S A Schram ldquoLaboratorycharacterisation of recycled asphalt pavement as a base layerrdquoInternational Journal of Pavement Engineering vol 11 no 2pp 123ndash131 2010

[65] T Bennert and A Maher ldquoe development of a performancespecification for granular base and subbase materialrdquo ReportNo FHWA-NJ-2005-003 Department of TransportationEwing Township NJ USA 2005

[66] T H Wonnacott H omas and J Ronald ldquoRegression asecond course in statisticsrdquo No 04 QA2782 W6Wiley NewYork NY USA 1981

[67] W Penny and S Roberts Neural network predictions witherror bars Dept of Electrical and Electronic EngineeringTechnology and Medicine Research Report TR-97-1 ImperialCollege of Science London UK 1997

[68] R Dybowski and S J Roberts ldquoConfidence intervals andprediction intervals for feed-forward neural networksrdquoClinical Applications of Artificial Neural Networks pp 298ndash326 2001

[69] J Hauke and T Kossowski ldquoComparison of values ofPearsonrsquos and Spearmanrsquos correlation coefficients on the samesets of datardquo Quaestiones Geographicae vol 30 no 2pp 87ndash93 2011

[70] K-z Yan H-b Xu and G-h Shen ldquoNovel approach toresilient modulus using routine subgrade soil propertiesrdquo

Advances in Materials Science and Engineering 15

International Journal of Geomechanics vol 14 no 6 article04014025 2013

[71] Y H Chan ldquoBiostatistics 104 correlational analysisrdquoSingapore Medical Journal vol 44 no 12 pp 614ndash6192003

[72] B M Damghani D Welch C OrsquoMalley and S Knights ldquoemisleading value of measured correlationrdquoWilmott vol 2012no 62 pp 64ndash73 2012

[73] L B Christensen B Johnson and L A Turner ldquoResearchmethods design and analysisrdquo 2011

[74] W J Dixon and F J Massey Introduction to StatisticalAnalysis McGraw-Hill New York NY USA 1969

[75] B Colbert and Z You ldquoe determination of mechanicalperformance of laboratory produced hot mix asphalt mixturesusing controlled RAP and virgin aggregate size fractionsrdquoConstruction and Building Materials vol 26 no 1 pp 655ndash662 2012

[76] D H Timm and D E Newcomb ldquoPerpetual pavement designfor flexible pavements in the USrdquo International Journal ofPavement Engineering vol 7 no 2 pp 111ndash119 2006

[77] Y H Huang Pavement Analysis and Design Prentice-HallEnglewood Cliffs NJ USA 2nd edition 1993

[78] L Walubita W Liu and T Scullion Texas perpetualpavements-Experience overview and the way forward Tech-nical Report No 0-4822-3 Texas Transportation InstituteTexas AampM University College Station TX USA 2010

[79] D Timm and D Newcomb ldquoCalibration of flexible pavementperformance equations for Minnesota road research projectrdquoTransportation Research Record Journal of the TransportationResearch Board no 1853 pp 134ndash142 2003

16 Advances in Materials Science and Engineering

CorrosionInternational Journal of

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Materials Science and EngineeringHindawiwwwhindawicom Volume 2018

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ate

ria

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Journal ofNanomaterials

Submit your manuscripts atwwwhindawicom

function having a coefficient of determination sim081 canbe given as

MR 4937(CBR)059

(3)

Table 5 shows the experimental data and the estimatedvalues of MR based on the four steps explained above andequation (3)

Figure 6 shows the capabilities of the proposed regressionmodel on the basis of the distribution of the data pointswhich in fact involves the experimentally determined andestimated MR values along the unity line giving a 95prediction and confidence interval is figure illustrates thatthere is an almost equal distribution of the data points on bothsides of the unity line Additionally the entire set of the datapoints is confined within the 95 prediction interval which isdefined as the interval around the linear regression line suchthat 95 of the predicted values will fall in this intervalFurther details on the mathematical framework of the pre-diction and the confidence interval can be found in standardtextbooks dealing with statistics and probability analysis suchas those authored by Wonnacott and Ronald [66] Penny andRoberts [67] and Dybowski and Roberts [68]

52 Statistical Analysis of the Proposed Model A Pearsonrsquoscorrelation coefficient (r) as given by equation (4) is ameasure of the strength and direction of linear associationthat exists between two continuous variables More specif-ically for the drawn line of best fit for sample data points oftwo variables Pearsonrsquos correlation indicates how well thedata points fit this new modelline of best fit and its nu-merical value indicates how far away all these data points areto the line of best fit (ie how well the data points fit this newmodelline of best fit) [69 70]

r 1113936

ni1 ui minus ui( 1113857 ti minusti( 1113857

1113936ni1 ui minus ui( 1113857

2ti minus ti( 1113857

21113960 1113961

1113969 (4)

where ui and ti experimental and predicted values re-spectively for the ith output ui average of experimentaloutputs and n size of sample

e statistical value of r may range from minus1 for a perfectnegative linear relationship (inversely related) to +1 for aperfect positive linear relationship (directly related) In gen-eral from theoretical point of view the strength of the linearrelationship can be categorised as ldquovery strongrdquo ldquomoderatelystrongrdquo and ldquofairly strongrdquo for the corresponding numericalvalues of r in the range 08ndash10 06ndash08 and 03ndash05 [71] Itshould be emphasized that if r 00 it does not necessarilymean that the two variables have no relationship In order tolook into the real strength of the correlation usually a sta-tistical test of significance is performed as discussed in [72]For this study three different types of statistical tests wereapplied to assess the significance of the developed correlationpresented in equation (3) and Table 5

Case 1 t-Test for the assessment of the implication of co-efficient of correlation (r) at a specific degree of freedom andlevel of significance [73]

is provides the researcher with some idea of how largea correlation coefficient must be before it can be consideredas demonstrating that there really is a relationship betweentwo variables (in our case the (MR)measured and CBR values)It may be the situation that two variables are related bychance and a hypothesis test for r allows the researcher todecide whether the observed r could have emerged by chanceor not e null hypothesis is that there is no relationshipbetween the two variables at is if ρ is the true correlationcoefficient for the two variables and when all populationvalues have been observed then the null hypothesis can begiven as

H0 ρ 0 (5)

e alternative hypothesis could be written as

HA ρne 0 (6)

whereas the standardised t-test for the null hypothesis that ris equal to zero can be written as

t r

nminus 21minus r2

1113970

(7)

where n is the number of paired observations in the givensample

e null hypothesis is evaluated by comparing the t-statistic of equation (7) with t-critical (201) obtained from tdistribution having the nminus 2 degree of freedom

Case 2 Direct comparison of the coefficient of correlationvalue (09) with the r-critical value (027) obtained from astatistical table corresponding to a specific degree of freedomand level of significance [61 74]

Case 3 It often becomes mandatory to statistically evaluatethe difference between two datasets obtained by two dif-ferent sources As in our case one set of MR values wasobtained experimentally using the AASHTOT 307-99(2004)protocol and the other set of MR values was obtained usingthe proposed correlation A standard t-test was performed toevaluate the difference between the paired values of(MR)measured and (MR)estimated at a specific degree of freedomand level of significance [74 75]

Table 6 summarises the statistical analysis of the abovethree cases

6 Assessment of Pavement PerformanceContaining RAPContent in Its Subbase Layer

To examine the performance of the pavement containingnatural aggregates mixed with RAP and used as subbasematerials the following analyses were performed usingcomputer software simulation

(1) To access the likelihood that critical pavement re-sponses exceed predefined thresholds using com-puter program PerRoad [76]

Advances in Materials Science and Engineering 7

(2) To determine the stresses and strains at critical lo-cations in the pavement structure using computerprogram KenPave developed by the University ofKentucky [77]

PerRoad is a Monte Carlo-based simulation softwareused to develop probability-based analysis for flexiblepavement is software can easily demonstrate the influ-ence of the MR values of the pavement material on the

Table 5 A comparison of measured and estimated MR values along with CBR values

MaterialBlend Dry unit weightachieved (kNm3) CBR () Total axial

stress (kPa)

Estimatedbulk stress

in CBR test (kPa)

MR values measuredprojected (MPa)

MR valuesestimated(MPa)

100 A 211 65 9780 1663 550 584100 F 221 74 11130 1892 600 631100 W 224 85 12780 2173 670 685100 RCA 192 53 7980 1357 410 51875 A+ 25 RAP(1) 207 47 7080 1204 470 48250 A+ 50 RAP(1) 205 31 4680 796 300 37725 A+ 75 RAP(1) 202 22 3330 566 280 30875 A+ 25 RAP(2) 203 55 8280 1408 505 52950 A+ 50 RAP(2) 208 39 5880 1000 410 43225 A+ 75 RAP(2) 213 17 2580 439 260 26475 A+ 25 RAP(3) 201 51 7680 1306 490 50650 A+ 50 RAP(3) 205 30 4530 770 315 37025 A+ 75 RAP(3) 199 19 2880 490 310 28275 A+ 25 RAP(4) 197 55 8280 1408 505 52950 A+ 50 RAP(4) 198 43 6480 1102 402 45825 A+ 75 RAP(4) 192 27 4080 694 252 34775 F+ 25 RAP(1) 208 52 7830 1331 538 51250 F+ 50 RAP(1) 213 41 6180 1051 455 44525 F+ 75 RAP(1) 201 14 2130 362 356 23575 F+ 25 RAP(2) 205 59 8880 1510 525 55250 F+ 50 RAP(2) 199 48 7230 1229 407 48825 F+ 75 RAP(2) 197 31 4680 796 408 37775 F+ 25 RAP(3) 201 62 9330 1586 667 56850 F+ 50 RAP(3) 192 41 6180 1051 516 44525 F+ 75 RAP(3) 208 19 2880 490 343 28275 F+ 25 RAP(4) 213 43 6480 1102 515 45850 F+ 50 RAP(4) 201 32 4830 821 490 38425 F+ 75 RAP(4) 213 13 1980 337 278 22575 W+25 RAP(1) 208 51 7680 1306 510 50650 W+50 RAP(1) 205 44 6630 1127 500 46425 W+75 RAP(1) 199 16 2430 413 240 25575 W+25 RAP(2) 197 55 8280 1408 502 52950 W+50 RAP(2) 199 31 4680 796 438 37725 W+75 RAP(2) 213 12 1830 311 265 21575 W+25 RAP(3) 201 48 7230 1229 520 48850 W+50 RAP(3) 213 35 5280 898 447 40525 W+75 RAP(3) 207 21 3180 541 255 29975 W+25 RAP(4) 205 45 6780 1153 480 47050 W+50 RAP(4) 199 34 5130 872 473 39825 W+75 RAP(4) 192 9 1380 235 213 18175 RCA+ 25 RAP(1) 208 38 5730 974 486 42550 RCA+ 50 RAP(1) 213 23 3480 592 330 31625 RCA+ 75 RAP(1) 201 12 1830 311 187 21575 RCA+ 25 RAP(2) 213 38 5730 974 525 42550 RCA+ 50 RAP(2) 201 31 4680 796 356 37725 RCA+ 75 RAP(2) 214 14 2130 362 200 23575 RCA+ 25 RAP(3) 201 32 4830 821 447 38450 RCA+ 50 RAP(3) 205 15 2280 388 226 24525 RCA+ 75 RAP(3) 199 9 1380 235 148 18175 RCA+ 25 RAP(4) 192 39 5880 1000 473 43250 RCA+ 50 RAP(4) 201 13 1980 337 200 22525 RCA+ 75 RAP(4) 202 18 2730 464 161 273

8 Advances in Materials Science and Engineering

cumulative damage factor (CDF) It also demonstrates thelikelihood that critical pavement responses could exceedpredened thresholds which are the horizontal tensile strainof 70 microns at the bottom of the asphalt concrete (which islinked with fatigue cracking) and the vertical compressivestrain of 200 microns at the top of the subgrade (which isassociated with the structural rutting) [78]

61 Pavement Structure and Material CharacteristicsFigure 7 shows a typical cross section of copyexible pavementswhich consists of a hot mix asphalt layer supported by theunbound base unbound subbase and compacted subgradeyene thickness of each layer generally depends on the tracload or more specically the equivalent single axle load(ESAL) during the proposed life cycle of the road

In this parametric study the focus is placed on how theproperties of granular subbase materials are changed by theaddition of a certain amount of RAP and their eect on thepavementrsquos performance As such the resilient modulus ofthe granular base and the asphalt concrete is xed yenestructure of the pavement to be simulated and the propertiesof materials in dierent layers are summarised in Table 7 Inthis particular study the subbase material will be one of theaggregates or aggregateRAP blends tested during the ex-perimental studies of this research

yene properties of the dierent pavement layers used inthe analysis are shown in Table 7 yene bulk stresses at the top

and bottom of the granular subbase layer were determinedusing the computer program KenPave For the selectedHMA resilient moduli (MR 5000MPa) the bulk stresseswere found in the range of 27 kPa to 30 kPa and 14 kPa to18 kPa at the top and bottom of the subbase layers re-spectively for the wheel load of 40 kN In the simulationsvalues of MR are used corresponding to the bulk stress of100 kPa

62 Trac Load For this parametric study the trac datafor urban interstate highways as recommended byAASHTO were used In the case of the PerRoad softwaretrac is separated by axle type single axle tandem axletridem axle and steer axle After determining the percentageof each axle type in the total trac trac is then subdividedinto weight classes in 2 kip intervals yene following is thesummary of the trac data the average annual daily trac(AADT) is 1000 vehicles with 10 being trucks annualgrowth rate of trac is 4 the directional distribution is50 and the percentages of single tandem and tridem axlesare 5573 4266 and 161 respectively yene rest of thetrac loading characteristics in terms of the distribution ofvehicle types and axle weights are described in Figure 8yenese values were used as input in PerRoad 35 Axle weightswere used to evaluate the response of the pavement layers interms of stresses strains and deformations at critical lo-cations of certain layers of the copyexible pavement

Table 6 Summary of the statistical analysis of the proposed model at an alpha value of 005 which matches to 95 condence level

Case Comments

1 t-Critical 20 t-Statistic 1459Since t-statisticgt t-critical which implies that value of the correlation coecient is not dueto sampling error the null hypothesis is rejected and it is concluded that there is a

signicant correlation between (MR)measured and CBR value in the population

2 r-Pearson 09 r-Critical 027

Since r-Pearsongt r-critical which implies that the null hypothesis is rejectedit is quite realistic to accept the ldquoalternative hypothesisrdquo that is the value of r that

we have obtained from our sample represents a real relationship between (MR)measuredand CBR value in the population

3 t-Critical 20 t-Statistic 052Since t-statisticlt t-critical which implies that the null hypothesis is accepted

it is concluded that there is an insignicant dierence between(MR)measured and (MR)correlated values in the population

0

100

200

300

400

500

600

700

800

0 200 400 600 800

MR

(esti

mat

ed)

MR (measured)

1 1 line

95confidence

interval

95prediction

interval

Figure 6 A comparison of estimated and measured MR values along the unity line

Advances in Materials Science and Engineering 9

63 Pavement Performance Criteria In the design ofconventional flexible pavements pavement sectionsare designed corresponding to a cumulative damagefactor (CDF) of 10 which corresponds to a terminallevel of pavement damage For perpetual pavementshowever it is recommended that the CDF is equal to 01at the end of its design life [76] e fatigue and ruttingalgorithms developed at MnROAD [79] for the cali-bration of flexible pavement performance equations wereused to predict pavement damage in cases where pave-ment responses exceeded these thresholds ese corre-lations are as follows

Nf 283lowast 10minus61εt

1113888 1113889

3148

(fatigue)

Nr 6026lowast 10minus81εv

1113888 1113889

387

(ritting)

(8)

where Nf number of load repetitions when fatigue failureoccurs Nr number of load repetition when rutting failureoccurs εt the horizontal tensile strain at the bottom of theHMA and εv the vertical compressive strain at the top ofthe subgrade

It should be noted that the damage of rutting estimatedby PerRoad only takes into account the permanent de-formation in the subgrade Any rutting associated with thedeformation of granular subbase materials is not consideredAccording to the test results in this study use of RAP ingranular subbase layers may induce substantial residualdeformation Further investigation should be performed toget a better understanding of its influence on the rutting offlexible pavements

64 Simulation Results and Discussion Simulation resultsare obtained and discussed in terms of

(1) e likelihood of the tensile strain at the bottom ofthe HMA exceeding 70 με

(2) e likelihood of the vertical strain at the top of thesubgrade soil exceeding 200 με

(3) e number of years it could take to reach a CDF of01 (the threshold level) for fatigue damage

(4) e number of years it could take to reach a CDF of01 for damage induced by rutting

Figure 9 illustrates the concept frequency distributionfor strain both within and outside the threshold limits

We first examine the likelihood of critical pavementresponses exceeding the predefined thresholds when theresilient modulus of the asphalt concrete is 5000MPa anddifferent aggregates or aggregate-RAP blends are used inthe granular subbase layer Figure 10 summarises (1) thelikelihood of the tensile strain at the bottom of the HMAremaining within the critical value of 70 με and (2) thelikelihood of the vertical strain at the top of the subgradesoil exceeding 200 με From this figure it can be inter-preted that all of the blends result in better pavementperformance than the natural aggregate both in terms ofthe tensile strains at the bottom of the HMA and thevertical compressive strains at the top of the subgrade soilFor instance the natural aggregates and RCA on averagehave an 813 likelihood that horizontal strain at thebottom of the HMA will remain within the critical limit of70 με

On the other hand the likelihood for blended ma-terials containing 25 50 and 75 of RAP materials inthe blended samples may reach (on average) 85758937 and 9377 (respectively) chance of remainingwithin the limit Similarly the likelihood that the com-pressive strain at the top of the subgrade will not exceedthe critical value of 200 microns is 8828 (naturalsamples) 9346 (25 RAP material blends) 9557(50 RAP material blends) and 982 (75 RAP ma-terial blends)

Figure 11 shows the number of years required to reacha CDF of 01 when fatigue is controlled by the horizontaltensile strain at the bottom of the subgrade and the HMAand vertical structural rutting are controlled by the verticalcompressive strain at the top of the subgrade e numberof years required to reach a CDF of 01 in general in-creases in line with the increase in the quantity of RAP inthe blend For example the number of years required toreach a CDF of 01 in terms of fatigue damage at thebottom of HMA is 4033 years for natural samples whilethe corresponding figure for the blends containing 75RAP is 5168 years on average A similar trend regarding anincrease in the number of years required to reach a CDF of01 in terms of structural damage at the top of the subgradewas also observed Furthermore for all the cases thenumber of years to reach a CDF of 01 was more than40 years but it is clear that fatigue will be the predominantpavement failure mode

Asphalt concrete

Unbound base

Unbound subbase

Compacted subgrade

Natural subgrade

Figure 7 A typical cross section of flexible pavement

Table 7 Material properties and pavement layer thicknesses

Parameters HMA Base course Subbasecourse Subgrade

MR (MPa) 5000 350 Variable 35Coefficient ofvariation for MR () 25 30 35 45

ickness ofthe layer (mm) 250 200 300 mdash

icknessVariability () 5 8 15 mdash

Poisson ratio 03 03 03 04

10 Advances in Materials Science and Engineering

7 Long-Term Effect of Cyclic Loading onBlended Samples

In order to explore the long-term eects of cyclic loading 9repeated load triaxial tests were performed under a range ofcyclic loading conditions and varying percentages of RAPcontents Figure 12 presents the variation of the residual strainof the tested samples subjected to 20000 load cycles under twodierent values of conning pressures of 345 kPa and1379 kPa each while the corresponding cyclic deviator stresswas maintained at 3105 kPa and 372 kPa From this gure itcan be inferred that the presence of RAP contents increases theresidual strain considerably for both of the conning pressurescenarios For instance for the repeated load test conducted atthe conning pressure of 345 kPa the residual strain for 100natural aggregate F is 012 after 20000 load cycles while forthe blend containing 50 RAP(2) and 75 RAP(2) thecorresponding gures reach 022 and 060 ie an additionof 50 RAP increases the residual strain by amargin of almost83 while the addition of 75 RAP increases the residualstrain by almost 400 Similarly for the repeated load testsconducted at a conning pressure of 1379 kPa on samples

containing natural aggregateW and the blends with RAP(1) at50 and 75 the residual strain after 20000 load cycles is 55and 300 higher when compared with the correspondingvalue for the 100 natural aggregate W Furthermore it isevident from the gures that almost 60 of the total residualstrain occurred during the rst 2000 load cycles out of the20000 total load cycles applied across all the cases

However it should be emphasized that there is a ten-dency for the elastic shakedown to be less pronounced forblended samples when compared to pure natural aggregatesFor instance for the blended sample 50 W and 50RAP(1) the rate of increase of strain becomes 0000154 forthe load cycles in the range of 2000ndash20000 On the otherhand this gure remained limited to 0000056 for thesample containing 100 natural aggregate W under thesame loading condition

Figure 13 shows the eect of the ratio of ldquocyclic deviatorstress to the conning stress (σdσc)rdquo on the residual strain forthe blended sample containing 50 A and 50 RAP(3)From this gure it can be inferred that the ratio σdσc has asubstantial eect on the residual strain generated undercyclic loading For instance at (σdσc) 09 the residualstrain after 6000 load cycles is limited to 006 however thisvalue reaches 011 and 021 at (σdσc) 18 and(σdσc) 27 respectively yene samples tend to stabilisemore quickly under a lower value of (σdσc) 09 whencompared to the stabilising tendency at the higher values of(σdσc) 18 and (σdσc) 27 which were also in-vestigated in this research A 50ndash60 residual strain occursduring the rst 1000 load cycles out of the total 6000 loadcycles applied during the experimental campaign irre-spective of the σdσc value

8 Summary and Conclusions

(1) yene blended samples (ie RAP combined withnatural granular materials) result in higher MRvalues than those obtained for natural granular

Figure 8 Vehicular load classication used in PerRoad 35

Area outside the threshold limit

Stra

in fr

eque

ncy

Figure 9 Example of frequency distribution of strain within andoutside the threshold limits

Advances in Materials Science and Engineering 11

samples under the same loading conditions whilevariations between MR values and the applied bulkstresses during the resilient modulus tests can beapproximated through power law having coecientof correlation (r) value in the range of 097ndash099

(2) yene CBR values of blended samples decrease withthe addition of RAP contents however a clear

decreasing trend in conjunction with an increasingpercentage of RAP contents could not be found

(3) yene new model for the estimation of MR values in-cludes the stress state through the experimentallydetermined CBR having a coecient of correlation ldquorrdquoequal to approximately 09 with fair distribution of thedata points (MR measured and MR estimated) about

Perc

enta

ge o

f are

a

70

75

80

85

90

95

100

100

A10

0 F

100

W10

0 R

CA75

A

+ 2

5 R

AP(

1)75

A

+ 2

5 R

AP(

2)75

A

+ 2

5 R

AP(

3)75

A

+ 2

5 R

AP(

4)75

F

+ 2

5 R

AP(

1)75

F

+ 2

5 R

AP(

2)75

F

+ 2

5 R

AP(

3)75

F

+ 2

5 R

AP(

4)75

W

+ 2

5 R

AP(

1)75

W

+ 2

5 R

AP(

2)75

W

+ 2

5 R

AP(

3)75

W

+ 2

5 R

AP(

4)75

R

CA +

25

RA

P(1)

75

RCA

+ 2

5 R

AP(

2)75

R

CA +

25

RA

P(3)

75

RCA

+ 2

5 R

AP(

4)50

A

+ 5

0 R

AP(

1)50

A

+ 5

0 R

AP(

2)50

A

+ 5

0 R

AP(

3)50

A

+ 5

0 R

AP(

4)50

F

+ 5

0 R

AP(

1)50

F

+ 5

0 R

AP(

2)50

F

+ 5

0 R

AP(

3)50

F

+ 5

0 R

AP(

4)50

W

+ 5

0 R

AP(

1)50

W

+ 5

0 R

AP(

2)50

W

+ 5

0 R

AP(

3)50

W

+ 5

0 R

AP(

4)50

R

CA +

50

RA

P(1)

50

RCA

+ 5

0 R

AP(

2)50

R

CA +

50

RA

P(3)

50

RCA

+ 5

0 R

AP(

4)25

A

+ 7

5 R

AP(

1)25

A

+ 7

5 R

AP(

2)25

A

+ 7

5 R

AP(

3)25

A

+ 7

5 R

AP(

4)25

F

+ 7

5 R

AP(

1)25

F

+ 7

5 R

AP(

2)25

F

+ 7

5 R

AP(

3)25

F

+ 7

5 R

AP(

4)25

W

+ 7

5 R

AP(

1)25

W

+ 7

5 R

AP(

2)25

W

+ 7

5 R

AP(

3)25

W

+ 7

5 R

AP(

4)25

R

CA +

75

RA

P(1)

25

RCA

+ 7

5 R

AP(

2)25

R

CA +

75

RA

P(3)

25

RCA

+ 7

5 R

AP(

4)

Percentage of area within the critical limit of horizontal strain at the bottom of HMAPercentage of area within the critical limit of vertical strain at the top of subgrade

Figure 10 Percentage of area within the critical limits for horizontal strain at the bottom of HMA and vertical strain at the top of subgrade

30

35

40

45

50

55

60

65

70

100

A10

0 F

100

W10

0 R

CA75

A

+ 2

5 R

AP(

1)75

A

+ 2

5 R

AP(

2)75

A

+ 2

5 R

AP(

3)75

A

+ 2

5 R

AP(

4)75

F

+ 2

5 R

AP(

1)75

F

+ 2

5 R

AP(

2)75

F

+ 2

5 R

AP(

3)75

F

+ 2

5 R

AP(

4)75

W

+ 2

5 R

AP(

1)75

W

+ 2

5 R

AP(

2)75

W

+ 2

5 R

AP(

3)75

W

+ 2

5 R

AP(

4)75

R

CA +

25

RA

P(1)

75

RCA

+ 2

5 R

AP(

2)75

R

CA +

25

RA

P(3)

75

RCA

+ 2

5 R

AP(

4)50

A

+ 5

0 R

AP(

1)50

A

+ 5

0 R

AP(

2)50

A

+ 5

0 R

AP(

3)50

A

+ 5

0 R

AP(

4)50

F

+ 5

0 R

AP(

1)50

F

+ 5

0 R

AP(

2)50

F

+ 5

0 R

AP(

3)50

F

+ 5

0 R

AP(

4)50

W

+ 5

0 R

AP(

1)50

W

+ 5

0 R

AP(

2)50

W

+ 5

0 R

AP(

3)50

W

+ 5

0 R

AP(

4)50

R

CA +

50

RA

P(1)

50

RCA

+ 5

0 R

AP(

2)50

R

CA +

50

RA

P(3)

50

RCA

+ 5

0 R

AP(

4)25

A

+ 7

5 R

AP(

1)25

A

+ 7

5 R

AP(

2)25

A

+ 7

5 R

AP(

3)25

A

+ 7

5 R

AP(

4)25

F

+ 7

5 R

AP(

1)25

F

+ 7

5 R

AP(

2)25

F

+ 7

5 R

AP(

3)25

F

+ 7

5 R

AP(

4)25

W

+ 7

5 R

AP(

1)25

W

+ 7

5 R

AP(

2)25

W

+ 7

5 R

AP(

3)25

W

+ 7

5 R

AP(

4)25

R

CA +

75

RA

P(1)

25

RCA

+ 7

5 R

AP(

2)25

R

CA +

75

RA

P(3)

25

RCA

+ 7

5 R

AP(

4)

Year

s

Number of years required to reach CDF = 01 in terms of horizontal strain at the bottom of HMANumber of years required to reach CDF = 01 in terms of vertical strain at the top of subgrade

Figure 11 Number of years required to reach CDF 01 in terms of horizontal strain at the bottom of HMA and vertical strain at the top ofsubgrade

12 Advances in Materials Science and Engineering

the unity line indicating that the proposed regressionmodel has a moderate to strong correlation

(4) Statistical analysis of simulation results based onPerRoad and KenPave software demonstrates thatthe addition of RAP contents in the subbase layer ofthe copyexible pavement signicantly improves itsperformance against rutting and fatigue

(5) Residual strain during the long-term repeated loadtriaxial test was found to increase in line with anincrease in the ratio of ldquocyclic deviator stress to theconning stress (σdσc)rdquo in correlation to an increasein the percentage of RAP contents in the blendedsample

(6) From the authorrsquos perspective the addition of RAPcontents beyond a certain limit (sim50) may prove tobe detrimental for the overall performance of copyexiblepavement structure

Data Availability

yene experimental data used to support the ndings of thisstudy are included within the article in the form of graphsand tables

Conflicts of Interest

yene author declares that there are no concopyicts of interestregarding the publication of this paper

References

[1] R B Mallick and A Veeraragavan ldquoSustainable pavements inIndia-the time to start is nowrdquo New Building Materials andConstruction World (NBMampCW) Magazine vol 16 no 3pp 128ndash140 2010

[2] A Mohammadinia A Arulrajah S Horpibulsuk andA Chinkulkijniwat ldquoEect of copyy ash on properties of crushedbrick and reclaimed asphalt in pavement basesubbase

000

050

100

150

200

250

300

350

400

450

500

0 2000 4000 6000 8000 10000 12000 14000 16000 18000 20000

Axi

al st

rain

()

Number of load cycles

100 W50 W + 50 RAP(1)25 W + 75 RAP(1)100 F50 F + 50 RAP(2)25 F + 75 RAP(2)

σc = 1379kPa σd = 372kPa

Figure 12 Eect of RAP contents on residual strain under long-term repeated loading

000

005

010

015

020

025

0 1000 2000 3000 4000 5000 6000

Axi

al st

rain

()

Number of load cycles

091827

odoc

Figure 13 Eect of ratio of ldquocyclic deviator stress to the conningstress (σdσc)rdquo on the residual strain under long-term repeatedloading

Advances in Materials Science and Engineering 13

applicationsrdquo Journal of Hazardous Materials vol 321pp 547ndash556 2017

[3] L R Hoyos A J Puppala and C A Ordonez ldquoCharacter-ization of cement-fiber-treated reclaimed asphalt pavementaggregates preliminary investigationrdquo Journal of Materials inCivil Engineering vol 23 no 7 pp 977ndash989 2011

[4] R Taha A Al-Harthy K Al-Shamsi and M Al-ZubeidildquoCement stabilization of reclaimed asphalt pavement aggre-gate for road bases and subbasesrdquo Journal of Materials in CivilEngineering vol 14 no 3 pp 239ndash245 2002

[5] A M Azam and D A Cameron ldquoGeotechnical properties ofblends of recycled clay masonry and recycled concrete ag-gregates in unbound pavement constructionrdquo Journal ofMaterials in Civil Engineering vol 25 no 6 pp 788ndash7982013

[6] A Gabor and D Cameron ldquoProperties of recycled concreteaggregate for unbound pavement constructionrdquo Journal ofMaterials in Civil Engineering vol 24 no 6 pp 754ndash7642012

[7] C S Poon and D Chan ldquoFeasible use of recycled concreteaggregates and crushed clay brick as unbound road sub-baserdquoConstruction and Building Materials vol 20 no 8 pp 578ndash585 2006

[8] A Arulrajah M M Y Ali M M Disfani J Piratheepan andM W Bo ldquoGeotechnical performance of recycled glass-wasterock blends in footpath basesrdquo Journal of Materials in CivilEngineering vol 25 no 5 pp 653ndash661 2013

[9] L T Lee Jr ldquoRecycled glass and dredged materialsrdquo ReportNo ERDC TNDOER-T8 US Army Corps of EngineersEngineer Research and Development Center Mississippi MSUSA 2007

[10] M Ali A Arulrajah M Disfani and J Piratheepan ldquoSuit-ability of using recycled glassmdashcrushed rock blends forpavement subbase applicationsrdquo in Proceedings of the Geo-Frontiers 2011 Conference on Geotechnical Foundation Designpp 1325ndash1334 ASCE Reston VA USA 2011

[11] J Wartman D G Grubb and A S M Nasim ldquoSelectengineering characteristics of crushed glassrdquo Journal ofMaterials in Civil Engineering vol 16 no 6 pp 526ndash5392004

[12] W Kim and J Labuz Resilient Modulus and Strength of BaseCourse with Recycled Bituminous Material Minnesota De-partment of Transportation Research Services Section MNUSA 2007

[13] D Bloomquist G Diamond M Oden B Ruth and M TiaEngineering and Environmental Aspects of Recycled Materialsfor Highway Construction Appendix 1 Final Report 1993

[14] A Hussain and Q Yanjun ldquoEvaluation of asphalt mixescontaining reclaimed asphalt pavement for wearing cour-sesrdquo in Proceedings of the International Conference onTraffic and Transportation Engineering School of CivilEngineering Southwest Jiaotong University ChengduChina 2012

[15] M Solaimanian and M Tahmoressi ldquoVariability analysis ofhot-mix asphalt concrete containing high percentage ofreclaimed asphalt pavementrdquo Transportation Research Re-cord Journal of the Transportation Research Board vol 1543no 1 pp 89ndash96 1996

[16] A Gabr and D A Cameron ldquoProperties of recycled concreteaggregate for unbound pavement constructionrdquo Journal ofMaterials in Civil Engineering vol 24 no 6 pp 754ndash7642011

[17] W-L Huang D-H Lin N-B Chang and K-S LinldquoRecycling of construction and demolition waste via a

mechanical sorting processrdquo Resources Conservation andRecycling vol 37 no 1 pp 23ndash37 2002

[18] A R Pasandın and I Perez ldquoOverview of bituminous mix-tures made with recycled concrete Aggregatesrdquo Constructionand Building Materials vol 74 pp 151ndash161 2015

[19] P Jitsangiam H Nikraz and K Siripun ldquoConstruction anddemolition (CampD) waste as a road base material for WesternAustralia roadsrdquo Australian Geomechanics vol 44 no 3pp 57ndash62 2009

[20] A Nataatmadja and Y L Tan ldquoResilient response of recycledconcrete road aggregatesrdquo Journal of Transportation Engi-neering vol 127 no 5 pp 450ndash453 2001

[21] C Leek and K Siripun ldquoSpecification and performance ofrecycled materials in road pavementsrdquo Contract Rep (01119-1)2010

[22] J Green and J Hall Nondistructive Vibratory Testing ofAirport Pavement 1975

[23] W Heukelom and A Klomp ldquoDynamic testing as a means ofcontrolling pavements during and after constructionrdquo inProceedings of the International Conference on the StructuralDesign of Asphalt Pavements University of Michigan AnnArbor MI USA 1962

[24] Ohio Department of Transportation Pavement DesignManual Ohio Department of Transportation Office ofPavement Engineering OH USA 2008

[25] W D Powell H C Mayhew and M M Nunn ldquoestructural design of bituminous roadsrdquo Laboratory Report1132 Transport and Road Research Laboratory CrowthorneUK 1984

[26] M W Witczak X Qi and M W Mirza ldquoUse of nonlinearsubgrade modulus in AASHTO design procedurerdquo Journal ofTransportation Engineering vol 121 no 3 1995

[27] AASHTO Guide for Design of Pavement Structures Wash-ington DC USA 1993

[28] Asphalt Institute Research and Development of 5e AsphaltInstitutersquos 5ickness Design Manual (MS-1) 9th edition 1982

[29] T Buu Correlation of Resistance R-value and ResilientModulus of Idaho Subgrade Soil Idaho Department ofTransportation Division of Highways ID USA 1980

[30] S Muench J Mahoney and L Pierce WSDOT PavementGuide Washington State Department of TransportationInternet Module Washington DC USA 2009

[31] S Yeh and C Su ldquoResilient properties of Colorado soilsrdquoReport No CDOH-DH-SM-89-9 Colorado Department ofHighways Denver CO USA 1989

[32] M R ompson and Q L Robnett ldquoResilient properties ofsubgrade soilsrdquo Transportation Engineering Journal of ASCEvol 105 pp 71ndash89 1979

[33] W Lee N C Bohra A G Altschaeffl and T D WhiteldquoResilient modulus of cohesive soilsrdquo Journal of Geotechnicaland Geoenvironmental Engineering vol 123 no 2 pp 131ndash136 1997

[34] R Carmichael III and E Stuart ldquoPredicting resilient modulusa study to determine the mechanical properties of subgradesoilsrdquo Transportation Research Record vol 1043 pp 145ndash1481986

[35] E C Drumm Y Boateng-Poku and T Johnson PierceldquoEstimation of subgrade resilient modulus from standardtestsrdquo Journal of Geotechnical Engineering vol 116 no 5pp 774ndash789 1990

[36] M J Farrar and J P Turner Resilient Modulus of WyomingSubgrade Soils 1991

14 Advances in Materials Science and Engineering

[37] M P Jones and M W Witczak ldquoSubgrade modulus on thesan diego test roadrdquo Transportation Research Record Journalof the Transportation Research Board vol 641 pp 1ndash6 1977

[38] A M Rahim and K P George ldquoSubgrade soil indexproperties to estimate resilient modulusrdquo in Proceedings ofthe 83th Annual Meeting of the Transportation ResearchBoard National Research Council Washington DC USA2004

[39] M R ompson and T G LaGrow A Proposed ConventionalFlexible Pavement 5ickness Design Procedure University ofIllinois Peoria IL USA 1988

[40] R Pezo ldquoA general method of reporting resilient modulustests of soils a pavement engineerrsquos point of viewrdquo in Pro-ceedings of the 72nd Annual Meeting of Transportation Re-search Board Washington DC USA 1993

[41] R G Hicks and C L Monismith ldquoResilient properties ofgranular materialrdquo Transportation Research Record vol 345pp 15ndash31 1971

[42] J Uzan ldquoCharacterization of granular materialsrdquo Trans-portation Research Record Journal of the Transportation Re-search Board vol 1022 pp 52ndash59 1985

[43] National Cooperative Highway Research Program ldquoGuide formechanistic-empirical design of new and rehabilitatedpavement structuresrdquo NCHRP 1-37A NCHRP WashingtonDC USA 2004

[44] N M Louay H T Hani and H Ananda ldquoEvaluation ofresilient modulus of subgrade soil by cone penetration testrdquoTransportation Research Record Journal of the TransportationResearch Board vol 1652 pp 236ndash245 1999

[45] S Dai and J Zollars ldquoResilient modulus of Minnesota roadresearch project subgrade soilrdquo Transportation Research Re-cord Journal of the Transportation Research Board vol 1786no 1 pp 20ndash28 2002

[46] L Mohammad B Huang A Puppala and A Allen ldquoRe-gression model for resilient modulus of subgrade soilsrdquoTransportation Research Record Journal of the TransportationResearch Board vol 1687 no 1 pp 47ndash54 1999

[47] B Santa ldquoResilient modulus of subgrade soils comparison oftwo constitutive equationsrdquo Transportation Research RecordJournal of the Transportation Research Board vol 1462pp 79ndash90 1994

[48] H Von Quintus and B Killingsworth Analyses Relating toPavement Material Characterizations and their Effects onPavement Performance 1998

[49] O Porter ldquoe preparation of subgradesrdquo in Proceedings ofthe Nineteenth Annual Meeting Highway Research BoardWashington DC USA December 1939

[50] O J Porter ldquoDevelopment of the original method for highwaydesignrdquo Transactions of the American Society of Civil Engi-neers vol 115 pp 461ndash467 1950

[51] D W Hight and M G H Stevens ldquoAn analysis of theCalifornia Bearing Ratio test in saturated claysrdquoGeotechnique vol 32 no 4 pp 315ndash322 1982

[52] P R Fleming and C D F Rogers ldquoAssessment of pavementfoundations during constructionrdquo Proceedings of the In-stitution of Civil Engineers-Transport vol 111 no 2pp 105ndash115 1995

[53] M R ompson R Marshall and Q L Robnett ldquoResilientproperties of subgrade soilsrdquo Final Report No FHWA-IL-UI-160 University of Illinois Urbana IL USA 1976

[54] B Sukumaran V Kyatham A Shah and D Sheth ldquoSuit-ability of using California bearing ratio test to predict resilientmodulusrdquo in Proceedings Federal Aviation Administration

Airport Technology Transfer Conference Atlantic City NJUSA 2002

[55] N W Lister and D Powell ldquoDesign practices for pavementsin the United Kingdomrdquo in Proceedings of the 6th In-ternational Conference on the Structural Design of AsphaltPavements Ann Arbor MI USA July 1987

[56] S Hossain G Dickerson and C Weaver Comparative Studyof VTM and AASHTO Test Method for CBR Co MaterialsDivision VDOT 2005

[57] N Garg A Larkin and H Brar ldquoA comparative subgradeevaluation using CBR vane shear light weight deflectometerand resilient modulus testsrdquo in Proceedings of the 8th In-ternational Conference on the Bearing Capacity of RoadsRailways and Airfields CRC Press Champaign IL USA2009

[58] M Ayres Development of a rational probabilistic approach forflexible pavement analysis University of Maryland CollegePark MD USA 1997

[59] AASHTO T 307 Determining the Resilient Modulus of Soilsand Aggregate Materials (2012) American Association ofState Highway and Transportation Officials Washington DCUSA 2004

[60] M Arshad and M F Ahmed ldquoPotential use of reclaimedasphalt pavement and recycled concrete aggregate in basesubbase layers of flexible pavementsrdquo Construction andBuilding Materials vol 151 pp 83ndash97 2017

[61] M Arshad ldquoCorrelation between resilient modulus (MR) andconstrained modulus (Mc) values of granular materialsrdquoConstruction and Building Materials vol 159 pp 440ndash4502018

[62] P Guo and J Emery ldquoImportance of strain level inevaluating resilient modulus of granular materialsrdquo In-ternational Journal of Pavement Engineering vol 12 no 2pp 187ndash199 2011

[63] E J McGarrah ldquoEvaluation of current practices of reclaimedasphalt pavementvirgin aggregate as base course materialrdquoNo WA-RD 7131 Federal Highway AdministrationWashington DC USA 2007

[64] T B Alam M Abdelrahman and S A Schram ldquoLaboratorycharacterisation of recycled asphalt pavement as a base layerrdquoInternational Journal of Pavement Engineering vol 11 no 2pp 123ndash131 2010

[65] T Bennert and A Maher ldquoe development of a performancespecification for granular base and subbase materialrdquo ReportNo FHWA-NJ-2005-003 Department of TransportationEwing Township NJ USA 2005

[66] T H Wonnacott H omas and J Ronald ldquoRegression asecond course in statisticsrdquo No 04 QA2782 W6Wiley NewYork NY USA 1981

[67] W Penny and S Roberts Neural network predictions witherror bars Dept of Electrical and Electronic EngineeringTechnology and Medicine Research Report TR-97-1 ImperialCollege of Science London UK 1997

[68] R Dybowski and S J Roberts ldquoConfidence intervals andprediction intervals for feed-forward neural networksrdquoClinical Applications of Artificial Neural Networks pp 298ndash326 2001

[69] J Hauke and T Kossowski ldquoComparison of values ofPearsonrsquos and Spearmanrsquos correlation coefficients on the samesets of datardquo Quaestiones Geographicae vol 30 no 2pp 87ndash93 2011

[70] K-z Yan H-b Xu and G-h Shen ldquoNovel approach toresilient modulus using routine subgrade soil propertiesrdquo

Advances in Materials Science and Engineering 15

International Journal of Geomechanics vol 14 no 6 article04014025 2013

[71] Y H Chan ldquoBiostatistics 104 correlational analysisrdquoSingapore Medical Journal vol 44 no 12 pp 614ndash6192003

[72] B M Damghani D Welch C OrsquoMalley and S Knights ldquoemisleading value of measured correlationrdquoWilmott vol 2012no 62 pp 64ndash73 2012

[73] L B Christensen B Johnson and L A Turner ldquoResearchmethods design and analysisrdquo 2011

[74] W J Dixon and F J Massey Introduction to StatisticalAnalysis McGraw-Hill New York NY USA 1969

[75] B Colbert and Z You ldquoe determination of mechanicalperformance of laboratory produced hot mix asphalt mixturesusing controlled RAP and virgin aggregate size fractionsrdquoConstruction and Building Materials vol 26 no 1 pp 655ndash662 2012

[76] D H Timm and D E Newcomb ldquoPerpetual pavement designfor flexible pavements in the USrdquo International Journal ofPavement Engineering vol 7 no 2 pp 111ndash119 2006

[77] Y H Huang Pavement Analysis and Design Prentice-HallEnglewood Cliffs NJ USA 2nd edition 1993

[78] L Walubita W Liu and T Scullion Texas perpetualpavements-Experience overview and the way forward Tech-nical Report No 0-4822-3 Texas Transportation InstituteTexas AampM University College Station TX USA 2010

[79] D Timm and D Newcomb ldquoCalibration of flexible pavementperformance equations for Minnesota road research projectrdquoTransportation Research Record Journal of the TransportationResearch Board no 1853 pp 134ndash142 2003

16 Advances in Materials Science and Engineering

CorrosionInternational Journal of

Hindawiwwwhindawicom Volume 2018

Advances in

Materials Science and EngineeringHindawiwwwhindawicom Volume 2018

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Chemistry

Analytical ChemistryInternational Journal of

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ScienticaHindawiwwwhindawicom Volume 2018

Polymer ScienceInternational Journal of

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Advances in Condensed Matter Physics

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Hindawi Publishing Corporation httpwwwhindawicom Volume 2013Hindawiwwwhindawicom

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Volume 2018

TribologyAdvances in

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ChemistryAdvances in

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Journal of

Hindawiwwwhindawicom Volume 2018

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nom

ate

ria

ls

Hindawiwwwhindawicom Volume 2018

Journal ofNanomaterials

Submit your manuscripts atwwwhindawicom

(2) To determine the stresses and strains at critical lo-cations in the pavement structure using computerprogram KenPave developed by the University ofKentucky [77]

PerRoad is a Monte Carlo-based simulation softwareused to develop probability-based analysis for flexiblepavement is software can easily demonstrate the influ-ence of the MR values of the pavement material on the

Table 5 A comparison of measured and estimated MR values along with CBR values

MaterialBlend Dry unit weightachieved (kNm3) CBR () Total axial

stress (kPa)

Estimatedbulk stress

in CBR test (kPa)

MR values measuredprojected (MPa)

MR valuesestimated(MPa)

100 A 211 65 9780 1663 550 584100 F 221 74 11130 1892 600 631100 W 224 85 12780 2173 670 685100 RCA 192 53 7980 1357 410 51875 A+ 25 RAP(1) 207 47 7080 1204 470 48250 A+ 50 RAP(1) 205 31 4680 796 300 37725 A+ 75 RAP(1) 202 22 3330 566 280 30875 A+ 25 RAP(2) 203 55 8280 1408 505 52950 A+ 50 RAP(2) 208 39 5880 1000 410 43225 A+ 75 RAP(2) 213 17 2580 439 260 26475 A+ 25 RAP(3) 201 51 7680 1306 490 50650 A+ 50 RAP(3) 205 30 4530 770 315 37025 A+ 75 RAP(3) 199 19 2880 490 310 28275 A+ 25 RAP(4) 197 55 8280 1408 505 52950 A+ 50 RAP(4) 198 43 6480 1102 402 45825 A+ 75 RAP(4) 192 27 4080 694 252 34775 F+ 25 RAP(1) 208 52 7830 1331 538 51250 F+ 50 RAP(1) 213 41 6180 1051 455 44525 F+ 75 RAP(1) 201 14 2130 362 356 23575 F+ 25 RAP(2) 205 59 8880 1510 525 55250 F+ 50 RAP(2) 199 48 7230 1229 407 48825 F+ 75 RAP(2) 197 31 4680 796 408 37775 F+ 25 RAP(3) 201 62 9330 1586 667 56850 F+ 50 RAP(3) 192 41 6180 1051 516 44525 F+ 75 RAP(3) 208 19 2880 490 343 28275 F+ 25 RAP(4) 213 43 6480 1102 515 45850 F+ 50 RAP(4) 201 32 4830 821 490 38425 F+ 75 RAP(4) 213 13 1980 337 278 22575 W+25 RAP(1) 208 51 7680 1306 510 50650 W+50 RAP(1) 205 44 6630 1127 500 46425 W+75 RAP(1) 199 16 2430 413 240 25575 W+25 RAP(2) 197 55 8280 1408 502 52950 W+50 RAP(2) 199 31 4680 796 438 37725 W+75 RAP(2) 213 12 1830 311 265 21575 W+25 RAP(3) 201 48 7230 1229 520 48850 W+50 RAP(3) 213 35 5280 898 447 40525 W+75 RAP(3) 207 21 3180 541 255 29975 W+25 RAP(4) 205 45 6780 1153 480 47050 W+50 RAP(4) 199 34 5130 872 473 39825 W+75 RAP(4) 192 9 1380 235 213 18175 RCA+ 25 RAP(1) 208 38 5730 974 486 42550 RCA+ 50 RAP(1) 213 23 3480 592 330 31625 RCA+ 75 RAP(1) 201 12 1830 311 187 21575 RCA+ 25 RAP(2) 213 38 5730 974 525 42550 RCA+ 50 RAP(2) 201 31 4680 796 356 37725 RCA+ 75 RAP(2) 214 14 2130 362 200 23575 RCA+ 25 RAP(3) 201 32 4830 821 447 38450 RCA+ 50 RAP(3) 205 15 2280 388 226 24525 RCA+ 75 RAP(3) 199 9 1380 235 148 18175 RCA+ 25 RAP(4) 192 39 5880 1000 473 43250 RCA+ 50 RAP(4) 201 13 1980 337 200 22525 RCA+ 75 RAP(4) 202 18 2730 464 161 273

8 Advances in Materials Science and Engineering

cumulative damage factor (CDF) It also demonstrates thelikelihood that critical pavement responses could exceedpredened thresholds which are the horizontal tensile strainof 70 microns at the bottom of the asphalt concrete (which islinked with fatigue cracking) and the vertical compressivestrain of 200 microns at the top of the subgrade (which isassociated with the structural rutting) [78]

61 Pavement Structure and Material CharacteristicsFigure 7 shows a typical cross section of copyexible pavementswhich consists of a hot mix asphalt layer supported by theunbound base unbound subbase and compacted subgradeyene thickness of each layer generally depends on the tracload or more specically the equivalent single axle load(ESAL) during the proposed life cycle of the road

In this parametric study the focus is placed on how theproperties of granular subbase materials are changed by theaddition of a certain amount of RAP and their eect on thepavementrsquos performance As such the resilient modulus ofthe granular base and the asphalt concrete is xed yenestructure of the pavement to be simulated and the propertiesof materials in dierent layers are summarised in Table 7 Inthis particular study the subbase material will be one of theaggregates or aggregateRAP blends tested during the ex-perimental studies of this research

yene properties of the dierent pavement layers used inthe analysis are shown in Table 7 yene bulk stresses at the top

and bottom of the granular subbase layer were determinedusing the computer program KenPave For the selectedHMA resilient moduli (MR 5000MPa) the bulk stresseswere found in the range of 27 kPa to 30 kPa and 14 kPa to18 kPa at the top and bottom of the subbase layers re-spectively for the wheel load of 40 kN In the simulationsvalues of MR are used corresponding to the bulk stress of100 kPa

62 Trac Load For this parametric study the trac datafor urban interstate highways as recommended byAASHTO were used In the case of the PerRoad softwaretrac is separated by axle type single axle tandem axletridem axle and steer axle After determining the percentageof each axle type in the total trac trac is then subdividedinto weight classes in 2 kip intervals yene following is thesummary of the trac data the average annual daily trac(AADT) is 1000 vehicles with 10 being trucks annualgrowth rate of trac is 4 the directional distribution is50 and the percentages of single tandem and tridem axlesare 5573 4266 and 161 respectively yene rest of thetrac loading characteristics in terms of the distribution ofvehicle types and axle weights are described in Figure 8yenese values were used as input in PerRoad 35 Axle weightswere used to evaluate the response of the pavement layers interms of stresses strains and deformations at critical lo-cations of certain layers of the copyexible pavement

Table 6 Summary of the statistical analysis of the proposed model at an alpha value of 005 which matches to 95 condence level

Case Comments

1 t-Critical 20 t-Statistic 1459Since t-statisticgt t-critical which implies that value of the correlation coecient is not dueto sampling error the null hypothesis is rejected and it is concluded that there is a

signicant correlation between (MR)measured and CBR value in the population

2 r-Pearson 09 r-Critical 027

Since r-Pearsongt r-critical which implies that the null hypothesis is rejectedit is quite realistic to accept the ldquoalternative hypothesisrdquo that is the value of r that

we have obtained from our sample represents a real relationship between (MR)measuredand CBR value in the population

3 t-Critical 20 t-Statistic 052Since t-statisticlt t-critical which implies that the null hypothesis is accepted

it is concluded that there is an insignicant dierence between(MR)measured and (MR)correlated values in the population

0

100

200

300

400

500

600

700

800

0 200 400 600 800

MR

(esti

mat

ed)

MR (measured)

1 1 line

95confidence

interval

95prediction

interval

Figure 6 A comparison of estimated and measured MR values along the unity line

Advances in Materials Science and Engineering 9

63 Pavement Performance Criteria In the design ofconventional flexible pavements pavement sectionsare designed corresponding to a cumulative damagefactor (CDF) of 10 which corresponds to a terminallevel of pavement damage For perpetual pavementshowever it is recommended that the CDF is equal to 01at the end of its design life [76] e fatigue and ruttingalgorithms developed at MnROAD [79] for the cali-bration of flexible pavement performance equations wereused to predict pavement damage in cases where pave-ment responses exceeded these thresholds ese corre-lations are as follows

Nf 283lowast 10minus61εt

1113888 1113889

3148

(fatigue)

Nr 6026lowast 10minus81εv

1113888 1113889

387

(ritting)

(8)

where Nf number of load repetitions when fatigue failureoccurs Nr number of load repetition when rutting failureoccurs εt the horizontal tensile strain at the bottom of theHMA and εv the vertical compressive strain at the top ofthe subgrade

It should be noted that the damage of rutting estimatedby PerRoad only takes into account the permanent de-formation in the subgrade Any rutting associated with thedeformation of granular subbase materials is not consideredAccording to the test results in this study use of RAP ingranular subbase layers may induce substantial residualdeformation Further investigation should be performed toget a better understanding of its influence on the rutting offlexible pavements

64 Simulation Results and Discussion Simulation resultsare obtained and discussed in terms of

(1) e likelihood of the tensile strain at the bottom ofthe HMA exceeding 70 με

(2) e likelihood of the vertical strain at the top of thesubgrade soil exceeding 200 με

(3) e number of years it could take to reach a CDF of01 (the threshold level) for fatigue damage

(4) e number of years it could take to reach a CDF of01 for damage induced by rutting

Figure 9 illustrates the concept frequency distributionfor strain both within and outside the threshold limits

We first examine the likelihood of critical pavementresponses exceeding the predefined thresholds when theresilient modulus of the asphalt concrete is 5000MPa anddifferent aggregates or aggregate-RAP blends are used inthe granular subbase layer Figure 10 summarises (1) thelikelihood of the tensile strain at the bottom of the HMAremaining within the critical value of 70 με and (2) thelikelihood of the vertical strain at the top of the subgradesoil exceeding 200 με From this figure it can be inter-preted that all of the blends result in better pavementperformance than the natural aggregate both in terms ofthe tensile strains at the bottom of the HMA and thevertical compressive strains at the top of the subgrade soilFor instance the natural aggregates and RCA on averagehave an 813 likelihood that horizontal strain at thebottom of the HMA will remain within the critical limit of70 με

On the other hand the likelihood for blended ma-terials containing 25 50 and 75 of RAP materials inthe blended samples may reach (on average) 85758937 and 9377 (respectively) chance of remainingwithin the limit Similarly the likelihood that the com-pressive strain at the top of the subgrade will not exceedthe critical value of 200 microns is 8828 (naturalsamples) 9346 (25 RAP material blends) 9557(50 RAP material blends) and 982 (75 RAP ma-terial blends)

Figure 11 shows the number of years required to reacha CDF of 01 when fatigue is controlled by the horizontaltensile strain at the bottom of the subgrade and the HMAand vertical structural rutting are controlled by the verticalcompressive strain at the top of the subgrade e numberof years required to reach a CDF of 01 in general in-creases in line with the increase in the quantity of RAP inthe blend For example the number of years required toreach a CDF of 01 in terms of fatigue damage at thebottom of HMA is 4033 years for natural samples whilethe corresponding figure for the blends containing 75RAP is 5168 years on average A similar trend regarding anincrease in the number of years required to reach a CDF of01 in terms of structural damage at the top of the subgradewas also observed Furthermore for all the cases thenumber of years to reach a CDF of 01 was more than40 years but it is clear that fatigue will be the predominantpavement failure mode

Asphalt concrete

Unbound base

Unbound subbase

Compacted subgrade

Natural subgrade

Figure 7 A typical cross section of flexible pavement

Table 7 Material properties and pavement layer thicknesses

Parameters HMA Base course Subbasecourse Subgrade

MR (MPa) 5000 350 Variable 35Coefficient ofvariation for MR () 25 30 35 45

ickness ofthe layer (mm) 250 200 300 mdash

icknessVariability () 5 8 15 mdash

Poisson ratio 03 03 03 04

10 Advances in Materials Science and Engineering

7 Long-Term Effect of Cyclic Loading onBlended Samples

In order to explore the long-term eects of cyclic loading 9repeated load triaxial tests were performed under a range ofcyclic loading conditions and varying percentages of RAPcontents Figure 12 presents the variation of the residual strainof the tested samples subjected to 20000 load cycles under twodierent values of conning pressures of 345 kPa and1379 kPa each while the corresponding cyclic deviator stresswas maintained at 3105 kPa and 372 kPa From this gure itcan be inferred that the presence of RAP contents increases theresidual strain considerably for both of the conning pressurescenarios For instance for the repeated load test conducted atthe conning pressure of 345 kPa the residual strain for 100natural aggregate F is 012 after 20000 load cycles while forthe blend containing 50 RAP(2) and 75 RAP(2) thecorresponding gures reach 022 and 060 ie an additionof 50 RAP increases the residual strain by amargin of almost83 while the addition of 75 RAP increases the residualstrain by almost 400 Similarly for the repeated load testsconducted at a conning pressure of 1379 kPa on samples

containing natural aggregateW and the blends with RAP(1) at50 and 75 the residual strain after 20000 load cycles is 55and 300 higher when compared with the correspondingvalue for the 100 natural aggregate W Furthermore it isevident from the gures that almost 60 of the total residualstrain occurred during the rst 2000 load cycles out of the20000 total load cycles applied across all the cases

However it should be emphasized that there is a ten-dency for the elastic shakedown to be less pronounced forblended samples when compared to pure natural aggregatesFor instance for the blended sample 50 W and 50RAP(1) the rate of increase of strain becomes 0000154 forthe load cycles in the range of 2000ndash20000 On the otherhand this gure remained limited to 0000056 for thesample containing 100 natural aggregate W under thesame loading condition

Figure 13 shows the eect of the ratio of ldquocyclic deviatorstress to the conning stress (σdσc)rdquo on the residual strain forthe blended sample containing 50 A and 50 RAP(3)From this gure it can be inferred that the ratio σdσc has asubstantial eect on the residual strain generated undercyclic loading For instance at (σdσc) 09 the residualstrain after 6000 load cycles is limited to 006 however thisvalue reaches 011 and 021 at (σdσc) 18 and(σdσc) 27 respectively yene samples tend to stabilisemore quickly under a lower value of (σdσc) 09 whencompared to the stabilising tendency at the higher values of(σdσc) 18 and (σdσc) 27 which were also in-vestigated in this research A 50ndash60 residual strain occursduring the rst 1000 load cycles out of the total 6000 loadcycles applied during the experimental campaign irre-spective of the σdσc value

8 Summary and Conclusions

(1) yene blended samples (ie RAP combined withnatural granular materials) result in higher MRvalues than those obtained for natural granular

Figure 8 Vehicular load classication used in PerRoad 35

Area outside the threshold limit

Stra

in fr

eque

ncy

Figure 9 Example of frequency distribution of strain within andoutside the threshold limits

Advances in Materials Science and Engineering 11

samples under the same loading conditions whilevariations between MR values and the applied bulkstresses during the resilient modulus tests can beapproximated through power law having coecientof correlation (r) value in the range of 097ndash099

(2) yene CBR values of blended samples decrease withthe addition of RAP contents however a clear

decreasing trend in conjunction with an increasingpercentage of RAP contents could not be found

(3) yene new model for the estimation of MR values in-cludes the stress state through the experimentallydetermined CBR having a coecient of correlation ldquorrdquoequal to approximately 09 with fair distribution of thedata points (MR measured and MR estimated) about

Perc

enta

ge o

f are

a

70

75

80

85

90

95

100

100

A10

0 F

100

W10

0 R

CA75

A

+ 2

5 R

AP(

1)75

A

+ 2

5 R

AP(

2)75

A

+ 2

5 R

AP(

3)75

A

+ 2

5 R

AP(

4)75

F

+ 2

5 R

AP(

1)75

F

+ 2

5 R

AP(

2)75

F

+ 2

5 R

AP(

3)75

F

+ 2

5 R

AP(

4)75

W

+ 2

5 R

AP(

1)75

W

+ 2

5 R

AP(

2)75

W

+ 2

5 R

AP(

3)75

W

+ 2

5 R

AP(

4)75

R

CA +

25

RA

P(1)

75

RCA

+ 2

5 R

AP(

2)75

R

CA +

25

RA

P(3)

75

RCA

+ 2

5 R

AP(

4)50

A

+ 5

0 R

AP(

1)50

A

+ 5

0 R

AP(

2)50

A

+ 5

0 R

AP(

3)50

A

+ 5

0 R

AP(

4)50

F

+ 5

0 R

AP(

1)50

F

+ 5

0 R

AP(

2)50

F

+ 5

0 R

AP(

3)50

F

+ 5

0 R

AP(

4)50

W

+ 5

0 R

AP(

1)50

W

+ 5

0 R

AP(

2)50

W

+ 5

0 R

AP(

3)50

W

+ 5

0 R

AP(

4)50

R

CA +

50

RA

P(1)

50

RCA

+ 5

0 R

AP(

2)50

R

CA +

50

RA

P(3)

50

RCA

+ 5

0 R

AP(

4)25

A

+ 7

5 R

AP(

1)25

A

+ 7

5 R

AP(

2)25

A

+ 7

5 R

AP(

3)25

A

+ 7

5 R

AP(

4)25

F

+ 7

5 R

AP(

1)25

F

+ 7

5 R

AP(

2)25

F

+ 7

5 R

AP(

3)25

F

+ 7

5 R

AP(

4)25

W

+ 7

5 R

AP(

1)25

W

+ 7

5 R

AP(

2)25

W

+ 7

5 R

AP(

3)25

W

+ 7

5 R

AP(

4)25

R

CA +

75

RA

P(1)

25

RCA

+ 7

5 R

AP(

2)25

R

CA +

75

RA

P(3)

25

RCA

+ 7

5 R

AP(

4)

Percentage of area within the critical limit of horizontal strain at the bottom of HMAPercentage of area within the critical limit of vertical strain at the top of subgrade

Figure 10 Percentage of area within the critical limits for horizontal strain at the bottom of HMA and vertical strain at the top of subgrade

30

35

40

45

50

55

60

65

70

100

A10

0 F

100

W10

0 R

CA75

A

+ 2

5 R

AP(

1)75

A

+ 2

5 R

AP(

2)75

A

+ 2

5 R

AP(

3)75

A

+ 2

5 R

AP(

4)75

F

+ 2

5 R

AP(

1)75

F

+ 2

5 R

AP(

2)75

F

+ 2

5 R

AP(

3)75

F

+ 2

5 R

AP(

4)75

W

+ 2

5 R

AP(

1)75

W

+ 2

5 R

AP(

2)75

W

+ 2

5 R

AP(

3)75

W

+ 2

5 R

AP(

4)75

R

CA +

25

RA

P(1)

75

RCA

+ 2

5 R

AP(

2)75

R

CA +

25

RA

P(3)

75

RCA

+ 2

5 R

AP(

4)50

A

+ 5

0 R

AP(

1)50

A

+ 5

0 R

AP(

2)50

A

+ 5

0 R

AP(

3)50

A

+ 5

0 R

AP(

4)50

F

+ 5

0 R

AP(

1)50

F

+ 5

0 R

AP(

2)50

F

+ 5

0 R

AP(

3)50

F

+ 5

0 R

AP(

4)50

W

+ 5

0 R

AP(

1)50

W

+ 5

0 R

AP(

2)50

W

+ 5

0 R

AP(

3)50

W

+ 5

0 R

AP(

4)50

R

CA +

50

RA

P(1)

50

RCA

+ 5

0 R

AP(

2)50

R

CA +

50

RA

P(3)

50

RCA

+ 5

0 R

AP(

4)25

A

+ 7

5 R

AP(

1)25

A

+ 7

5 R

AP(

2)25

A

+ 7

5 R

AP(

3)25

A

+ 7

5 R

AP(

4)25

F

+ 7

5 R

AP(

1)25

F

+ 7

5 R

AP(

2)25

F

+ 7

5 R

AP(

3)25

F

+ 7

5 R

AP(

4)25

W

+ 7

5 R

AP(

1)25

W

+ 7

5 R

AP(

2)25

W

+ 7

5 R

AP(

3)25

W

+ 7

5 R

AP(

4)25

R

CA +

75

RA

P(1)

25

RCA

+ 7

5 R

AP(

2)25

R

CA +

75

RA

P(3)

25

RCA

+ 7

5 R

AP(

4)

Year

s

Number of years required to reach CDF = 01 in terms of horizontal strain at the bottom of HMANumber of years required to reach CDF = 01 in terms of vertical strain at the top of subgrade

Figure 11 Number of years required to reach CDF 01 in terms of horizontal strain at the bottom of HMA and vertical strain at the top ofsubgrade

12 Advances in Materials Science and Engineering

the unity line indicating that the proposed regressionmodel has a moderate to strong correlation

(4) Statistical analysis of simulation results based onPerRoad and KenPave software demonstrates thatthe addition of RAP contents in the subbase layer ofthe copyexible pavement signicantly improves itsperformance against rutting and fatigue

(5) Residual strain during the long-term repeated loadtriaxial test was found to increase in line with anincrease in the ratio of ldquocyclic deviator stress to theconning stress (σdσc)rdquo in correlation to an increasein the percentage of RAP contents in the blendedsample

(6) From the authorrsquos perspective the addition of RAPcontents beyond a certain limit (sim50) may prove tobe detrimental for the overall performance of copyexiblepavement structure

Data Availability

yene experimental data used to support the ndings of thisstudy are included within the article in the form of graphsand tables

Conflicts of Interest

yene author declares that there are no concopyicts of interestregarding the publication of this paper

References

[1] R B Mallick and A Veeraragavan ldquoSustainable pavements inIndia-the time to start is nowrdquo New Building Materials andConstruction World (NBMampCW) Magazine vol 16 no 3pp 128ndash140 2010

[2] A Mohammadinia A Arulrajah S Horpibulsuk andA Chinkulkijniwat ldquoEect of copyy ash on properties of crushedbrick and reclaimed asphalt in pavement basesubbase

000

050

100

150

200

250

300

350

400

450

500

0 2000 4000 6000 8000 10000 12000 14000 16000 18000 20000

Axi

al st

rain

()

Number of load cycles

100 W50 W + 50 RAP(1)25 W + 75 RAP(1)100 F50 F + 50 RAP(2)25 F + 75 RAP(2)

σc = 1379kPa σd = 372kPa

Figure 12 Eect of RAP contents on residual strain under long-term repeated loading

000

005

010

015

020

025

0 1000 2000 3000 4000 5000 6000

Axi

al st

rain

()

Number of load cycles

091827

odoc

Figure 13 Eect of ratio of ldquocyclic deviator stress to the conningstress (σdσc)rdquo on the residual strain under long-term repeatedloading

Advances in Materials Science and Engineering 13

applicationsrdquo Journal of Hazardous Materials vol 321pp 547ndash556 2017

[3] L R Hoyos A J Puppala and C A Ordonez ldquoCharacter-ization of cement-fiber-treated reclaimed asphalt pavementaggregates preliminary investigationrdquo Journal of Materials inCivil Engineering vol 23 no 7 pp 977ndash989 2011

[4] R Taha A Al-Harthy K Al-Shamsi and M Al-ZubeidildquoCement stabilization of reclaimed asphalt pavement aggre-gate for road bases and subbasesrdquo Journal of Materials in CivilEngineering vol 14 no 3 pp 239ndash245 2002

[5] A M Azam and D A Cameron ldquoGeotechnical properties ofblends of recycled clay masonry and recycled concrete ag-gregates in unbound pavement constructionrdquo Journal ofMaterials in Civil Engineering vol 25 no 6 pp 788ndash7982013

[6] A Gabor and D Cameron ldquoProperties of recycled concreteaggregate for unbound pavement constructionrdquo Journal ofMaterials in Civil Engineering vol 24 no 6 pp 754ndash7642012

[7] C S Poon and D Chan ldquoFeasible use of recycled concreteaggregates and crushed clay brick as unbound road sub-baserdquoConstruction and Building Materials vol 20 no 8 pp 578ndash585 2006

[8] A Arulrajah M M Y Ali M M Disfani J Piratheepan andM W Bo ldquoGeotechnical performance of recycled glass-wasterock blends in footpath basesrdquo Journal of Materials in CivilEngineering vol 25 no 5 pp 653ndash661 2013

[9] L T Lee Jr ldquoRecycled glass and dredged materialsrdquo ReportNo ERDC TNDOER-T8 US Army Corps of EngineersEngineer Research and Development Center Mississippi MSUSA 2007

[10] M Ali A Arulrajah M Disfani and J Piratheepan ldquoSuit-ability of using recycled glassmdashcrushed rock blends forpavement subbase applicationsrdquo in Proceedings of the Geo-Frontiers 2011 Conference on Geotechnical Foundation Designpp 1325ndash1334 ASCE Reston VA USA 2011

[11] J Wartman D G Grubb and A S M Nasim ldquoSelectengineering characteristics of crushed glassrdquo Journal ofMaterials in Civil Engineering vol 16 no 6 pp 526ndash5392004

[12] W Kim and J Labuz Resilient Modulus and Strength of BaseCourse with Recycled Bituminous Material Minnesota De-partment of Transportation Research Services Section MNUSA 2007

[13] D Bloomquist G Diamond M Oden B Ruth and M TiaEngineering and Environmental Aspects of Recycled Materialsfor Highway Construction Appendix 1 Final Report 1993

[14] A Hussain and Q Yanjun ldquoEvaluation of asphalt mixescontaining reclaimed asphalt pavement for wearing cour-sesrdquo in Proceedings of the International Conference onTraffic and Transportation Engineering School of CivilEngineering Southwest Jiaotong University ChengduChina 2012

[15] M Solaimanian and M Tahmoressi ldquoVariability analysis ofhot-mix asphalt concrete containing high percentage ofreclaimed asphalt pavementrdquo Transportation Research Re-cord Journal of the Transportation Research Board vol 1543no 1 pp 89ndash96 1996

[16] A Gabr and D A Cameron ldquoProperties of recycled concreteaggregate for unbound pavement constructionrdquo Journal ofMaterials in Civil Engineering vol 24 no 6 pp 754ndash7642011

[17] W-L Huang D-H Lin N-B Chang and K-S LinldquoRecycling of construction and demolition waste via a

mechanical sorting processrdquo Resources Conservation andRecycling vol 37 no 1 pp 23ndash37 2002

[18] A R Pasandın and I Perez ldquoOverview of bituminous mix-tures made with recycled concrete Aggregatesrdquo Constructionand Building Materials vol 74 pp 151ndash161 2015

[19] P Jitsangiam H Nikraz and K Siripun ldquoConstruction anddemolition (CampD) waste as a road base material for WesternAustralia roadsrdquo Australian Geomechanics vol 44 no 3pp 57ndash62 2009

[20] A Nataatmadja and Y L Tan ldquoResilient response of recycledconcrete road aggregatesrdquo Journal of Transportation Engi-neering vol 127 no 5 pp 450ndash453 2001

[21] C Leek and K Siripun ldquoSpecification and performance ofrecycled materials in road pavementsrdquo Contract Rep (01119-1)2010

[22] J Green and J Hall Nondistructive Vibratory Testing ofAirport Pavement 1975

[23] W Heukelom and A Klomp ldquoDynamic testing as a means ofcontrolling pavements during and after constructionrdquo inProceedings of the International Conference on the StructuralDesign of Asphalt Pavements University of Michigan AnnArbor MI USA 1962

[24] Ohio Department of Transportation Pavement DesignManual Ohio Department of Transportation Office ofPavement Engineering OH USA 2008

[25] W D Powell H C Mayhew and M M Nunn ldquoestructural design of bituminous roadsrdquo Laboratory Report1132 Transport and Road Research Laboratory CrowthorneUK 1984

[26] M W Witczak X Qi and M W Mirza ldquoUse of nonlinearsubgrade modulus in AASHTO design procedurerdquo Journal ofTransportation Engineering vol 121 no 3 1995

[27] AASHTO Guide for Design of Pavement Structures Wash-ington DC USA 1993

[28] Asphalt Institute Research and Development of 5e AsphaltInstitutersquos 5ickness Design Manual (MS-1) 9th edition 1982

[29] T Buu Correlation of Resistance R-value and ResilientModulus of Idaho Subgrade Soil Idaho Department ofTransportation Division of Highways ID USA 1980

[30] S Muench J Mahoney and L Pierce WSDOT PavementGuide Washington State Department of TransportationInternet Module Washington DC USA 2009

[31] S Yeh and C Su ldquoResilient properties of Colorado soilsrdquoReport No CDOH-DH-SM-89-9 Colorado Department ofHighways Denver CO USA 1989

[32] M R ompson and Q L Robnett ldquoResilient properties ofsubgrade soilsrdquo Transportation Engineering Journal of ASCEvol 105 pp 71ndash89 1979

[33] W Lee N C Bohra A G Altschaeffl and T D WhiteldquoResilient modulus of cohesive soilsrdquo Journal of Geotechnicaland Geoenvironmental Engineering vol 123 no 2 pp 131ndash136 1997

[34] R Carmichael III and E Stuart ldquoPredicting resilient modulusa study to determine the mechanical properties of subgradesoilsrdquo Transportation Research Record vol 1043 pp 145ndash1481986

[35] E C Drumm Y Boateng-Poku and T Johnson PierceldquoEstimation of subgrade resilient modulus from standardtestsrdquo Journal of Geotechnical Engineering vol 116 no 5pp 774ndash789 1990

[36] M J Farrar and J P Turner Resilient Modulus of WyomingSubgrade Soils 1991

14 Advances in Materials Science and Engineering

[37] M P Jones and M W Witczak ldquoSubgrade modulus on thesan diego test roadrdquo Transportation Research Record Journalof the Transportation Research Board vol 641 pp 1ndash6 1977

[38] A M Rahim and K P George ldquoSubgrade soil indexproperties to estimate resilient modulusrdquo in Proceedings ofthe 83th Annual Meeting of the Transportation ResearchBoard National Research Council Washington DC USA2004

[39] M R ompson and T G LaGrow A Proposed ConventionalFlexible Pavement 5ickness Design Procedure University ofIllinois Peoria IL USA 1988

[40] R Pezo ldquoA general method of reporting resilient modulustests of soils a pavement engineerrsquos point of viewrdquo in Pro-ceedings of the 72nd Annual Meeting of Transportation Re-search Board Washington DC USA 1993

[41] R G Hicks and C L Monismith ldquoResilient properties ofgranular materialrdquo Transportation Research Record vol 345pp 15ndash31 1971

[42] J Uzan ldquoCharacterization of granular materialsrdquo Trans-portation Research Record Journal of the Transportation Re-search Board vol 1022 pp 52ndash59 1985

[43] National Cooperative Highway Research Program ldquoGuide formechanistic-empirical design of new and rehabilitatedpavement structuresrdquo NCHRP 1-37A NCHRP WashingtonDC USA 2004

[44] N M Louay H T Hani and H Ananda ldquoEvaluation ofresilient modulus of subgrade soil by cone penetration testrdquoTransportation Research Record Journal of the TransportationResearch Board vol 1652 pp 236ndash245 1999

[45] S Dai and J Zollars ldquoResilient modulus of Minnesota roadresearch project subgrade soilrdquo Transportation Research Re-cord Journal of the Transportation Research Board vol 1786no 1 pp 20ndash28 2002

[46] L Mohammad B Huang A Puppala and A Allen ldquoRe-gression model for resilient modulus of subgrade soilsrdquoTransportation Research Record Journal of the TransportationResearch Board vol 1687 no 1 pp 47ndash54 1999

[47] B Santa ldquoResilient modulus of subgrade soils comparison oftwo constitutive equationsrdquo Transportation Research RecordJournal of the Transportation Research Board vol 1462pp 79ndash90 1994

[48] H Von Quintus and B Killingsworth Analyses Relating toPavement Material Characterizations and their Effects onPavement Performance 1998

[49] O Porter ldquoe preparation of subgradesrdquo in Proceedings ofthe Nineteenth Annual Meeting Highway Research BoardWashington DC USA December 1939

[50] O J Porter ldquoDevelopment of the original method for highwaydesignrdquo Transactions of the American Society of Civil Engi-neers vol 115 pp 461ndash467 1950

[51] D W Hight and M G H Stevens ldquoAn analysis of theCalifornia Bearing Ratio test in saturated claysrdquoGeotechnique vol 32 no 4 pp 315ndash322 1982

[52] P R Fleming and C D F Rogers ldquoAssessment of pavementfoundations during constructionrdquo Proceedings of the In-stitution of Civil Engineers-Transport vol 111 no 2pp 105ndash115 1995

[53] M R ompson R Marshall and Q L Robnett ldquoResilientproperties of subgrade soilsrdquo Final Report No FHWA-IL-UI-160 University of Illinois Urbana IL USA 1976

[54] B Sukumaran V Kyatham A Shah and D Sheth ldquoSuit-ability of using California bearing ratio test to predict resilientmodulusrdquo in Proceedings Federal Aviation Administration

Airport Technology Transfer Conference Atlantic City NJUSA 2002

[55] N W Lister and D Powell ldquoDesign practices for pavementsin the United Kingdomrdquo in Proceedings of the 6th In-ternational Conference on the Structural Design of AsphaltPavements Ann Arbor MI USA July 1987

[56] S Hossain G Dickerson and C Weaver Comparative Studyof VTM and AASHTO Test Method for CBR Co MaterialsDivision VDOT 2005

[57] N Garg A Larkin and H Brar ldquoA comparative subgradeevaluation using CBR vane shear light weight deflectometerand resilient modulus testsrdquo in Proceedings of the 8th In-ternational Conference on the Bearing Capacity of RoadsRailways and Airfields CRC Press Champaign IL USA2009

[58] M Ayres Development of a rational probabilistic approach forflexible pavement analysis University of Maryland CollegePark MD USA 1997

[59] AASHTO T 307 Determining the Resilient Modulus of Soilsand Aggregate Materials (2012) American Association ofState Highway and Transportation Officials Washington DCUSA 2004

[60] M Arshad and M F Ahmed ldquoPotential use of reclaimedasphalt pavement and recycled concrete aggregate in basesubbase layers of flexible pavementsrdquo Construction andBuilding Materials vol 151 pp 83ndash97 2017

[61] M Arshad ldquoCorrelation between resilient modulus (MR) andconstrained modulus (Mc) values of granular materialsrdquoConstruction and Building Materials vol 159 pp 440ndash4502018

[62] P Guo and J Emery ldquoImportance of strain level inevaluating resilient modulus of granular materialsrdquo In-ternational Journal of Pavement Engineering vol 12 no 2pp 187ndash199 2011

[63] E J McGarrah ldquoEvaluation of current practices of reclaimedasphalt pavementvirgin aggregate as base course materialrdquoNo WA-RD 7131 Federal Highway AdministrationWashington DC USA 2007

[64] T B Alam M Abdelrahman and S A Schram ldquoLaboratorycharacterisation of recycled asphalt pavement as a base layerrdquoInternational Journal of Pavement Engineering vol 11 no 2pp 123ndash131 2010

[65] T Bennert and A Maher ldquoe development of a performancespecification for granular base and subbase materialrdquo ReportNo FHWA-NJ-2005-003 Department of TransportationEwing Township NJ USA 2005

[66] T H Wonnacott H omas and J Ronald ldquoRegression asecond course in statisticsrdquo No 04 QA2782 W6Wiley NewYork NY USA 1981

[67] W Penny and S Roberts Neural network predictions witherror bars Dept of Electrical and Electronic EngineeringTechnology and Medicine Research Report TR-97-1 ImperialCollege of Science London UK 1997

[68] R Dybowski and S J Roberts ldquoConfidence intervals andprediction intervals for feed-forward neural networksrdquoClinical Applications of Artificial Neural Networks pp 298ndash326 2001

[69] J Hauke and T Kossowski ldquoComparison of values ofPearsonrsquos and Spearmanrsquos correlation coefficients on the samesets of datardquo Quaestiones Geographicae vol 30 no 2pp 87ndash93 2011

[70] K-z Yan H-b Xu and G-h Shen ldquoNovel approach toresilient modulus using routine subgrade soil propertiesrdquo

Advances in Materials Science and Engineering 15

International Journal of Geomechanics vol 14 no 6 article04014025 2013

[71] Y H Chan ldquoBiostatistics 104 correlational analysisrdquoSingapore Medical Journal vol 44 no 12 pp 614ndash6192003

[72] B M Damghani D Welch C OrsquoMalley and S Knights ldquoemisleading value of measured correlationrdquoWilmott vol 2012no 62 pp 64ndash73 2012

[73] L B Christensen B Johnson and L A Turner ldquoResearchmethods design and analysisrdquo 2011

[74] W J Dixon and F J Massey Introduction to StatisticalAnalysis McGraw-Hill New York NY USA 1969

[75] B Colbert and Z You ldquoe determination of mechanicalperformance of laboratory produced hot mix asphalt mixturesusing controlled RAP and virgin aggregate size fractionsrdquoConstruction and Building Materials vol 26 no 1 pp 655ndash662 2012

[76] D H Timm and D E Newcomb ldquoPerpetual pavement designfor flexible pavements in the USrdquo International Journal ofPavement Engineering vol 7 no 2 pp 111ndash119 2006

[77] Y H Huang Pavement Analysis and Design Prentice-HallEnglewood Cliffs NJ USA 2nd edition 1993

[78] L Walubita W Liu and T Scullion Texas perpetualpavements-Experience overview and the way forward Tech-nical Report No 0-4822-3 Texas Transportation InstituteTexas AampM University College Station TX USA 2010

[79] D Timm and D Newcomb ldquoCalibration of flexible pavementperformance equations for Minnesota road research projectrdquoTransportation Research Record Journal of the TransportationResearch Board no 1853 pp 134ndash142 2003

16 Advances in Materials Science and Engineering

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cumulative damage factor (CDF) It also demonstrates thelikelihood that critical pavement responses could exceedpredened thresholds which are the horizontal tensile strainof 70 microns at the bottom of the asphalt concrete (which islinked with fatigue cracking) and the vertical compressivestrain of 200 microns at the top of the subgrade (which isassociated with the structural rutting) [78]

61 Pavement Structure and Material CharacteristicsFigure 7 shows a typical cross section of copyexible pavementswhich consists of a hot mix asphalt layer supported by theunbound base unbound subbase and compacted subgradeyene thickness of each layer generally depends on the tracload or more specically the equivalent single axle load(ESAL) during the proposed life cycle of the road

In this parametric study the focus is placed on how theproperties of granular subbase materials are changed by theaddition of a certain amount of RAP and their eect on thepavementrsquos performance As such the resilient modulus ofthe granular base and the asphalt concrete is xed yenestructure of the pavement to be simulated and the propertiesof materials in dierent layers are summarised in Table 7 Inthis particular study the subbase material will be one of theaggregates or aggregateRAP blends tested during the ex-perimental studies of this research

yene properties of the dierent pavement layers used inthe analysis are shown in Table 7 yene bulk stresses at the top

and bottom of the granular subbase layer were determinedusing the computer program KenPave For the selectedHMA resilient moduli (MR 5000MPa) the bulk stresseswere found in the range of 27 kPa to 30 kPa and 14 kPa to18 kPa at the top and bottom of the subbase layers re-spectively for the wheel load of 40 kN In the simulationsvalues of MR are used corresponding to the bulk stress of100 kPa

62 Trac Load For this parametric study the trac datafor urban interstate highways as recommended byAASHTO were used In the case of the PerRoad softwaretrac is separated by axle type single axle tandem axletridem axle and steer axle After determining the percentageof each axle type in the total trac trac is then subdividedinto weight classes in 2 kip intervals yene following is thesummary of the trac data the average annual daily trac(AADT) is 1000 vehicles with 10 being trucks annualgrowth rate of trac is 4 the directional distribution is50 and the percentages of single tandem and tridem axlesare 5573 4266 and 161 respectively yene rest of thetrac loading characteristics in terms of the distribution ofvehicle types and axle weights are described in Figure 8yenese values were used as input in PerRoad 35 Axle weightswere used to evaluate the response of the pavement layers interms of stresses strains and deformations at critical lo-cations of certain layers of the copyexible pavement

Table 6 Summary of the statistical analysis of the proposed model at an alpha value of 005 which matches to 95 condence level

Case Comments

1 t-Critical 20 t-Statistic 1459Since t-statisticgt t-critical which implies that value of the correlation coecient is not dueto sampling error the null hypothesis is rejected and it is concluded that there is a

signicant correlation between (MR)measured and CBR value in the population

2 r-Pearson 09 r-Critical 027

Since r-Pearsongt r-critical which implies that the null hypothesis is rejectedit is quite realistic to accept the ldquoalternative hypothesisrdquo that is the value of r that

we have obtained from our sample represents a real relationship between (MR)measuredand CBR value in the population

3 t-Critical 20 t-Statistic 052Since t-statisticlt t-critical which implies that the null hypothesis is accepted

it is concluded that there is an insignicant dierence between(MR)measured and (MR)correlated values in the population

0

100

200

300

400

500

600

700

800

0 200 400 600 800

MR

(esti

mat

ed)

MR (measured)

1 1 line

95confidence

interval

95prediction

interval

Figure 6 A comparison of estimated and measured MR values along the unity line

Advances in Materials Science and Engineering 9

63 Pavement Performance Criteria In the design ofconventional flexible pavements pavement sectionsare designed corresponding to a cumulative damagefactor (CDF) of 10 which corresponds to a terminallevel of pavement damage For perpetual pavementshowever it is recommended that the CDF is equal to 01at the end of its design life [76] e fatigue and ruttingalgorithms developed at MnROAD [79] for the cali-bration of flexible pavement performance equations wereused to predict pavement damage in cases where pave-ment responses exceeded these thresholds ese corre-lations are as follows

Nf 283lowast 10minus61εt

1113888 1113889

3148

(fatigue)

Nr 6026lowast 10minus81εv

1113888 1113889

387

(ritting)

(8)

where Nf number of load repetitions when fatigue failureoccurs Nr number of load repetition when rutting failureoccurs εt the horizontal tensile strain at the bottom of theHMA and εv the vertical compressive strain at the top ofthe subgrade

It should be noted that the damage of rutting estimatedby PerRoad only takes into account the permanent de-formation in the subgrade Any rutting associated with thedeformation of granular subbase materials is not consideredAccording to the test results in this study use of RAP ingranular subbase layers may induce substantial residualdeformation Further investigation should be performed toget a better understanding of its influence on the rutting offlexible pavements

64 Simulation Results and Discussion Simulation resultsare obtained and discussed in terms of

(1) e likelihood of the tensile strain at the bottom ofthe HMA exceeding 70 με

(2) e likelihood of the vertical strain at the top of thesubgrade soil exceeding 200 με

(3) e number of years it could take to reach a CDF of01 (the threshold level) for fatigue damage

(4) e number of years it could take to reach a CDF of01 for damage induced by rutting

Figure 9 illustrates the concept frequency distributionfor strain both within and outside the threshold limits

We first examine the likelihood of critical pavementresponses exceeding the predefined thresholds when theresilient modulus of the asphalt concrete is 5000MPa anddifferent aggregates or aggregate-RAP blends are used inthe granular subbase layer Figure 10 summarises (1) thelikelihood of the tensile strain at the bottom of the HMAremaining within the critical value of 70 με and (2) thelikelihood of the vertical strain at the top of the subgradesoil exceeding 200 με From this figure it can be inter-preted that all of the blends result in better pavementperformance than the natural aggregate both in terms ofthe tensile strains at the bottom of the HMA and thevertical compressive strains at the top of the subgrade soilFor instance the natural aggregates and RCA on averagehave an 813 likelihood that horizontal strain at thebottom of the HMA will remain within the critical limit of70 με

On the other hand the likelihood for blended ma-terials containing 25 50 and 75 of RAP materials inthe blended samples may reach (on average) 85758937 and 9377 (respectively) chance of remainingwithin the limit Similarly the likelihood that the com-pressive strain at the top of the subgrade will not exceedthe critical value of 200 microns is 8828 (naturalsamples) 9346 (25 RAP material blends) 9557(50 RAP material blends) and 982 (75 RAP ma-terial blends)

Figure 11 shows the number of years required to reacha CDF of 01 when fatigue is controlled by the horizontaltensile strain at the bottom of the subgrade and the HMAand vertical structural rutting are controlled by the verticalcompressive strain at the top of the subgrade e numberof years required to reach a CDF of 01 in general in-creases in line with the increase in the quantity of RAP inthe blend For example the number of years required toreach a CDF of 01 in terms of fatigue damage at thebottom of HMA is 4033 years for natural samples whilethe corresponding figure for the blends containing 75RAP is 5168 years on average A similar trend regarding anincrease in the number of years required to reach a CDF of01 in terms of structural damage at the top of the subgradewas also observed Furthermore for all the cases thenumber of years to reach a CDF of 01 was more than40 years but it is clear that fatigue will be the predominantpavement failure mode

Asphalt concrete

Unbound base

Unbound subbase

Compacted subgrade

Natural subgrade

Figure 7 A typical cross section of flexible pavement

Table 7 Material properties and pavement layer thicknesses

Parameters HMA Base course Subbasecourse Subgrade

MR (MPa) 5000 350 Variable 35Coefficient ofvariation for MR () 25 30 35 45

ickness ofthe layer (mm) 250 200 300 mdash

icknessVariability () 5 8 15 mdash

Poisson ratio 03 03 03 04

10 Advances in Materials Science and Engineering

7 Long-Term Effect of Cyclic Loading onBlended Samples

In order to explore the long-term eects of cyclic loading 9repeated load triaxial tests were performed under a range ofcyclic loading conditions and varying percentages of RAPcontents Figure 12 presents the variation of the residual strainof the tested samples subjected to 20000 load cycles under twodierent values of conning pressures of 345 kPa and1379 kPa each while the corresponding cyclic deviator stresswas maintained at 3105 kPa and 372 kPa From this gure itcan be inferred that the presence of RAP contents increases theresidual strain considerably for both of the conning pressurescenarios For instance for the repeated load test conducted atthe conning pressure of 345 kPa the residual strain for 100natural aggregate F is 012 after 20000 load cycles while forthe blend containing 50 RAP(2) and 75 RAP(2) thecorresponding gures reach 022 and 060 ie an additionof 50 RAP increases the residual strain by amargin of almost83 while the addition of 75 RAP increases the residualstrain by almost 400 Similarly for the repeated load testsconducted at a conning pressure of 1379 kPa on samples

containing natural aggregateW and the blends with RAP(1) at50 and 75 the residual strain after 20000 load cycles is 55and 300 higher when compared with the correspondingvalue for the 100 natural aggregate W Furthermore it isevident from the gures that almost 60 of the total residualstrain occurred during the rst 2000 load cycles out of the20000 total load cycles applied across all the cases

However it should be emphasized that there is a ten-dency for the elastic shakedown to be less pronounced forblended samples when compared to pure natural aggregatesFor instance for the blended sample 50 W and 50RAP(1) the rate of increase of strain becomes 0000154 forthe load cycles in the range of 2000ndash20000 On the otherhand this gure remained limited to 0000056 for thesample containing 100 natural aggregate W under thesame loading condition

Figure 13 shows the eect of the ratio of ldquocyclic deviatorstress to the conning stress (σdσc)rdquo on the residual strain forthe blended sample containing 50 A and 50 RAP(3)From this gure it can be inferred that the ratio σdσc has asubstantial eect on the residual strain generated undercyclic loading For instance at (σdσc) 09 the residualstrain after 6000 load cycles is limited to 006 however thisvalue reaches 011 and 021 at (σdσc) 18 and(σdσc) 27 respectively yene samples tend to stabilisemore quickly under a lower value of (σdσc) 09 whencompared to the stabilising tendency at the higher values of(σdσc) 18 and (σdσc) 27 which were also in-vestigated in this research A 50ndash60 residual strain occursduring the rst 1000 load cycles out of the total 6000 loadcycles applied during the experimental campaign irre-spective of the σdσc value

8 Summary and Conclusions

(1) yene blended samples (ie RAP combined withnatural granular materials) result in higher MRvalues than those obtained for natural granular

Figure 8 Vehicular load classication used in PerRoad 35

Area outside the threshold limit

Stra

in fr

eque

ncy

Figure 9 Example of frequency distribution of strain within andoutside the threshold limits

Advances in Materials Science and Engineering 11

samples under the same loading conditions whilevariations between MR values and the applied bulkstresses during the resilient modulus tests can beapproximated through power law having coecientof correlation (r) value in the range of 097ndash099

(2) yene CBR values of blended samples decrease withthe addition of RAP contents however a clear

decreasing trend in conjunction with an increasingpercentage of RAP contents could not be found

(3) yene new model for the estimation of MR values in-cludes the stress state through the experimentallydetermined CBR having a coecient of correlation ldquorrdquoequal to approximately 09 with fair distribution of thedata points (MR measured and MR estimated) about

Perc

enta

ge o

f are

a

70

75

80

85

90

95

100

100

A10

0 F

100

W10

0 R

CA75

A

+ 2

5 R

AP(

1)75

A

+ 2

5 R

AP(

2)75

A

+ 2

5 R

AP(

3)75

A

+ 2

5 R

AP(

4)75

F

+ 2

5 R

AP(

1)75

F

+ 2

5 R

AP(

2)75

F

+ 2

5 R

AP(

3)75

F

+ 2

5 R

AP(

4)75

W

+ 2

5 R

AP(

1)75

W

+ 2

5 R

AP(

2)75

W

+ 2

5 R

AP(

3)75

W

+ 2

5 R

AP(

4)75

R

CA +

25

RA

P(1)

75

RCA

+ 2

5 R

AP(

2)75

R

CA +

25

RA

P(3)

75

RCA

+ 2

5 R

AP(

4)50

A

+ 5

0 R

AP(

1)50

A

+ 5

0 R

AP(

2)50

A

+ 5

0 R

AP(

3)50

A

+ 5

0 R

AP(

4)50

F

+ 5

0 R

AP(

1)50

F

+ 5

0 R

AP(

2)50

F

+ 5

0 R

AP(

3)50

F

+ 5

0 R

AP(

4)50

W

+ 5

0 R

AP(

1)50

W

+ 5

0 R

AP(

2)50

W

+ 5

0 R

AP(

3)50

W

+ 5

0 R

AP(

4)50

R

CA +

50

RA

P(1)

50

RCA

+ 5

0 R

AP(

2)50

R

CA +

50

RA

P(3)

50

RCA

+ 5

0 R

AP(

4)25

A

+ 7

5 R

AP(

1)25

A

+ 7

5 R

AP(

2)25

A

+ 7

5 R

AP(

3)25

A

+ 7

5 R

AP(

4)25

F

+ 7

5 R

AP(

1)25

F

+ 7

5 R

AP(

2)25

F

+ 7

5 R

AP(

3)25

F

+ 7

5 R

AP(

4)25

W

+ 7

5 R

AP(

1)25

W

+ 7

5 R

AP(

2)25

W

+ 7

5 R

AP(

3)25

W

+ 7

5 R

AP(

4)25

R

CA +

75

RA

P(1)

25

RCA

+ 7

5 R

AP(

2)25

R

CA +

75

RA

P(3)

25

RCA

+ 7

5 R

AP(

4)

Percentage of area within the critical limit of horizontal strain at the bottom of HMAPercentage of area within the critical limit of vertical strain at the top of subgrade

Figure 10 Percentage of area within the critical limits for horizontal strain at the bottom of HMA and vertical strain at the top of subgrade

30

35

40

45

50

55

60

65

70

100

A10

0 F

100

W10

0 R

CA75

A

+ 2

5 R

AP(

1)75

A

+ 2

5 R

AP(

2)75

A

+ 2

5 R

AP(

3)75

A

+ 2

5 R

AP(

4)75

F

+ 2

5 R

AP(

1)75

F

+ 2

5 R

AP(

2)75

F

+ 2

5 R

AP(

3)75

F

+ 2

5 R

AP(

4)75

W

+ 2

5 R

AP(

1)75

W

+ 2

5 R

AP(

2)75

W

+ 2

5 R

AP(

3)75

W

+ 2

5 R

AP(

4)75

R

CA +

25

RA

P(1)

75

RCA

+ 2

5 R

AP(

2)75

R

CA +

25

RA

P(3)

75

RCA

+ 2

5 R

AP(

4)50

A

+ 5

0 R

AP(

1)50

A

+ 5

0 R

AP(

2)50

A

+ 5

0 R

AP(

3)50

A

+ 5

0 R

AP(

4)50

F

+ 5

0 R

AP(

1)50

F

+ 5

0 R

AP(

2)50

F

+ 5

0 R

AP(

3)50

F

+ 5

0 R

AP(

4)50

W

+ 5

0 R

AP(

1)50

W

+ 5

0 R

AP(

2)50

W

+ 5

0 R

AP(

3)50

W

+ 5

0 R

AP(

4)50

R

CA +

50

RA

P(1)

50

RCA

+ 5

0 R

AP(

2)50

R

CA +

50

RA

P(3)

50

RCA

+ 5

0 R

AP(

4)25

A

+ 7

5 R

AP(

1)25

A

+ 7

5 R

AP(

2)25

A

+ 7

5 R

AP(

3)25

A

+ 7

5 R

AP(

4)25

F

+ 7

5 R

AP(

1)25

F

+ 7

5 R

AP(

2)25

F

+ 7

5 R

AP(

3)25

F

+ 7

5 R

AP(

4)25

W

+ 7

5 R

AP(

1)25

W

+ 7

5 R

AP(

2)25

W

+ 7

5 R

AP(

3)25

W

+ 7

5 R

AP(

4)25

R

CA +

75

RA

P(1)

25

RCA

+ 7

5 R

AP(

2)25

R

CA +

75

RA

P(3)

25

RCA

+ 7

5 R

AP(

4)

Year

s

Number of years required to reach CDF = 01 in terms of horizontal strain at the bottom of HMANumber of years required to reach CDF = 01 in terms of vertical strain at the top of subgrade

Figure 11 Number of years required to reach CDF 01 in terms of horizontal strain at the bottom of HMA and vertical strain at the top ofsubgrade

12 Advances in Materials Science and Engineering

the unity line indicating that the proposed regressionmodel has a moderate to strong correlation

(4) Statistical analysis of simulation results based onPerRoad and KenPave software demonstrates thatthe addition of RAP contents in the subbase layer ofthe copyexible pavement signicantly improves itsperformance against rutting and fatigue

(5) Residual strain during the long-term repeated loadtriaxial test was found to increase in line with anincrease in the ratio of ldquocyclic deviator stress to theconning stress (σdσc)rdquo in correlation to an increasein the percentage of RAP contents in the blendedsample

(6) From the authorrsquos perspective the addition of RAPcontents beyond a certain limit (sim50) may prove tobe detrimental for the overall performance of copyexiblepavement structure

Data Availability

yene experimental data used to support the ndings of thisstudy are included within the article in the form of graphsand tables

Conflicts of Interest

yene author declares that there are no concopyicts of interestregarding the publication of this paper

References

[1] R B Mallick and A Veeraragavan ldquoSustainable pavements inIndia-the time to start is nowrdquo New Building Materials andConstruction World (NBMampCW) Magazine vol 16 no 3pp 128ndash140 2010

[2] A Mohammadinia A Arulrajah S Horpibulsuk andA Chinkulkijniwat ldquoEect of copyy ash on properties of crushedbrick and reclaimed asphalt in pavement basesubbase

000

050

100

150

200

250

300

350

400

450

500

0 2000 4000 6000 8000 10000 12000 14000 16000 18000 20000

Axi

al st

rain

()

Number of load cycles

100 W50 W + 50 RAP(1)25 W + 75 RAP(1)100 F50 F + 50 RAP(2)25 F + 75 RAP(2)

σc = 1379kPa σd = 372kPa

Figure 12 Eect of RAP contents on residual strain under long-term repeated loading

000

005

010

015

020

025

0 1000 2000 3000 4000 5000 6000

Axi

al st

rain

()

Number of load cycles

091827

odoc

Figure 13 Eect of ratio of ldquocyclic deviator stress to the conningstress (σdσc)rdquo on the residual strain under long-term repeatedloading

Advances in Materials Science and Engineering 13

applicationsrdquo Journal of Hazardous Materials vol 321pp 547ndash556 2017

[3] L R Hoyos A J Puppala and C A Ordonez ldquoCharacter-ization of cement-fiber-treated reclaimed asphalt pavementaggregates preliminary investigationrdquo Journal of Materials inCivil Engineering vol 23 no 7 pp 977ndash989 2011

[4] R Taha A Al-Harthy K Al-Shamsi and M Al-ZubeidildquoCement stabilization of reclaimed asphalt pavement aggre-gate for road bases and subbasesrdquo Journal of Materials in CivilEngineering vol 14 no 3 pp 239ndash245 2002

[5] A M Azam and D A Cameron ldquoGeotechnical properties ofblends of recycled clay masonry and recycled concrete ag-gregates in unbound pavement constructionrdquo Journal ofMaterials in Civil Engineering vol 25 no 6 pp 788ndash7982013

[6] A Gabor and D Cameron ldquoProperties of recycled concreteaggregate for unbound pavement constructionrdquo Journal ofMaterials in Civil Engineering vol 24 no 6 pp 754ndash7642012

[7] C S Poon and D Chan ldquoFeasible use of recycled concreteaggregates and crushed clay brick as unbound road sub-baserdquoConstruction and Building Materials vol 20 no 8 pp 578ndash585 2006

[8] A Arulrajah M M Y Ali M M Disfani J Piratheepan andM W Bo ldquoGeotechnical performance of recycled glass-wasterock blends in footpath basesrdquo Journal of Materials in CivilEngineering vol 25 no 5 pp 653ndash661 2013

[9] L T Lee Jr ldquoRecycled glass and dredged materialsrdquo ReportNo ERDC TNDOER-T8 US Army Corps of EngineersEngineer Research and Development Center Mississippi MSUSA 2007

[10] M Ali A Arulrajah M Disfani and J Piratheepan ldquoSuit-ability of using recycled glassmdashcrushed rock blends forpavement subbase applicationsrdquo in Proceedings of the Geo-Frontiers 2011 Conference on Geotechnical Foundation Designpp 1325ndash1334 ASCE Reston VA USA 2011

[11] J Wartman D G Grubb and A S M Nasim ldquoSelectengineering characteristics of crushed glassrdquo Journal ofMaterials in Civil Engineering vol 16 no 6 pp 526ndash5392004

[12] W Kim and J Labuz Resilient Modulus and Strength of BaseCourse with Recycled Bituminous Material Minnesota De-partment of Transportation Research Services Section MNUSA 2007

[13] D Bloomquist G Diamond M Oden B Ruth and M TiaEngineering and Environmental Aspects of Recycled Materialsfor Highway Construction Appendix 1 Final Report 1993

[14] A Hussain and Q Yanjun ldquoEvaluation of asphalt mixescontaining reclaimed asphalt pavement for wearing cour-sesrdquo in Proceedings of the International Conference onTraffic and Transportation Engineering School of CivilEngineering Southwest Jiaotong University ChengduChina 2012

[15] M Solaimanian and M Tahmoressi ldquoVariability analysis ofhot-mix asphalt concrete containing high percentage ofreclaimed asphalt pavementrdquo Transportation Research Re-cord Journal of the Transportation Research Board vol 1543no 1 pp 89ndash96 1996

[16] A Gabr and D A Cameron ldquoProperties of recycled concreteaggregate for unbound pavement constructionrdquo Journal ofMaterials in Civil Engineering vol 24 no 6 pp 754ndash7642011

[17] W-L Huang D-H Lin N-B Chang and K-S LinldquoRecycling of construction and demolition waste via a

mechanical sorting processrdquo Resources Conservation andRecycling vol 37 no 1 pp 23ndash37 2002

[18] A R Pasandın and I Perez ldquoOverview of bituminous mix-tures made with recycled concrete Aggregatesrdquo Constructionand Building Materials vol 74 pp 151ndash161 2015

[19] P Jitsangiam H Nikraz and K Siripun ldquoConstruction anddemolition (CampD) waste as a road base material for WesternAustralia roadsrdquo Australian Geomechanics vol 44 no 3pp 57ndash62 2009

[20] A Nataatmadja and Y L Tan ldquoResilient response of recycledconcrete road aggregatesrdquo Journal of Transportation Engi-neering vol 127 no 5 pp 450ndash453 2001

[21] C Leek and K Siripun ldquoSpecification and performance ofrecycled materials in road pavementsrdquo Contract Rep (01119-1)2010

[22] J Green and J Hall Nondistructive Vibratory Testing ofAirport Pavement 1975

[23] W Heukelom and A Klomp ldquoDynamic testing as a means ofcontrolling pavements during and after constructionrdquo inProceedings of the International Conference on the StructuralDesign of Asphalt Pavements University of Michigan AnnArbor MI USA 1962

[24] Ohio Department of Transportation Pavement DesignManual Ohio Department of Transportation Office ofPavement Engineering OH USA 2008

[25] W D Powell H C Mayhew and M M Nunn ldquoestructural design of bituminous roadsrdquo Laboratory Report1132 Transport and Road Research Laboratory CrowthorneUK 1984

[26] M W Witczak X Qi and M W Mirza ldquoUse of nonlinearsubgrade modulus in AASHTO design procedurerdquo Journal ofTransportation Engineering vol 121 no 3 1995

[27] AASHTO Guide for Design of Pavement Structures Wash-ington DC USA 1993

[28] Asphalt Institute Research and Development of 5e AsphaltInstitutersquos 5ickness Design Manual (MS-1) 9th edition 1982

[29] T Buu Correlation of Resistance R-value and ResilientModulus of Idaho Subgrade Soil Idaho Department ofTransportation Division of Highways ID USA 1980

[30] S Muench J Mahoney and L Pierce WSDOT PavementGuide Washington State Department of TransportationInternet Module Washington DC USA 2009

[31] S Yeh and C Su ldquoResilient properties of Colorado soilsrdquoReport No CDOH-DH-SM-89-9 Colorado Department ofHighways Denver CO USA 1989

[32] M R ompson and Q L Robnett ldquoResilient properties ofsubgrade soilsrdquo Transportation Engineering Journal of ASCEvol 105 pp 71ndash89 1979

[33] W Lee N C Bohra A G Altschaeffl and T D WhiteldquoResilient modulus of cohesive soilsrdquo Journal of Geotechnicaland Geoenvironmental Engineering vol 123 no 2 pp 131ndash136 1997

[34] R Carmichael III and E Stuart ldquoPredicting resilient modulusa study to determine the mechanical properties of subgradesoilsrdquo Transportation Research Record vol 1043 pp 145ndash1481986

[35] E C Drumm Y Boateng-Poku and T Johnson PierceldquoEstimation of subgrade resilient modulus from standardtestsrdquo Journal of Geotechnical Engineering vol 116 no 5pp 774ndash789 1990

[36] M J Farrar and J P Turner Resilient Modulus of WyomingSubgrade Soils 1991

14 Advances in Materials Science and Engineering

[37] M P Jones and M W Witczak ldquoSubgrade modulus on thesan diego test roadrdquo Transportation Research Record Journalof the Transportation Research Board vol 641 pp 1ndash6 1977

[38] A M Rahim and K P George ldquoSubgrade soil indexproperties to estimate resilient modulusrdquo in Proceedings ofthe 83th Annual Meeting of the Transportation ResearchBoard National Research Council Washington DC USA2004

[39] M R ompson and T G LaGrow A Proposed ConventionalFlexible Pavement 5ickness Design Procedure University ofIllinois Peoria IL USA 1988

[40] R Pezo ldquoA general method of reporting resilient modulustests of soils a pavement engineerrsquos point of viewrdquo in Pro-ceedings of the 72nd Annual Meeting of Transportation Re-search Board Washington DC USA 1993

[41] R G Hicks and C L Monismith ldquoResilient properties ofgranular materialrdquo Transportation Research Record vol 345pp 15ndash31 1971

[42] J Uzan ldquoCharacterization of granular materialsrdquo Trans-portation Research Record Journal of the Transportation Re-search Board vol 1022 pp 52ndash59 1985

[43] National Cooperative Highway Research Program ldquoGuide formechanistic-empirical design of new and rehabilitatedpavement structuresrdquo NCHRP 1-37A NCHRP WashingtonDC USA 2004

[44] N M Louay H T Hani and H Ananda ldquoEvaluation ofresilient modulus of subgrade soil by cone penetration testrdquoTransportation Research Record Journal of the TransportationResearch Board vol 1652 pp 236ndash245 1999

[45] S Dai and J Zollars ldquoResilient modulus of Minnesota roadresearch project subgrade soilrdquo Transportation Research Re-cord Journal of the Transportation Research Board vol 1786no 1 pp 20ndash28 2002

[46] L Mohammad B Huang A Puppala and A Allen ldquoRe-gression model for resilient modulus of subgrade soilsrdquoTransportation Research Record Journal of the TransportationResearch Board vol 1687 no 1 pp 47ndash54 1999

[47] B Santa ldquoResilient modulus of subgrade soils comparison oftwo constitutive equationsrdquo Transportation Research RecordJournal of the Transportation Research Board vol 1462pp 79ndash90 1994

[48] H Von Quintus and B Killingsworth Analyses Relating toPavement Material Characterizations and their Effects onPavement Performance 1998

[49] O Porter ldquoe preparation of subgradesrdquo in Proceedings ofthe Nineteenth Annual Meeting Highway Research BoardWashington DC USA December 1939

[50] O J Porter ldquoDevelopment of the original method for highwaydesignrdquo Transactions of the American Society of Civil Engi-neers vol 115 pp 461ndash467 1950

[51] D W Hight and M G H Stevens ldquoAn analysis of theCalifornia Bearing Ratio test in saturated claysrdquoGeotechnique vol 32 no 4 pp 315ndash322 1982

[52] P R Fleming and C D F Rogers ldquoAssessment of pavementfoundations during constructionrdquo Proceedings of the In-stitution of Civil Engineers-Transport vol 111 no 2pp 105ndash115 1995

[53] M R ompson R Marshall and Q L Robnett ldquoResilientproperties of subgrade soilsrdquo Final Report No FHWA-IL-UI-160 University of Illinois Urbana IL USA 1976

[54] B Sukumaran V Kyatham A Shah and D Sheth ldquoSuit-ability of using California bearing ratio test to predict resilientmodulusrdquo in Proceedings Federal Aviation Administration

Airport Technology Transfer Conference Atlantic City NJUSA 2002

[55] N W Lister and D Powell ldquoDesign practices for pavementsin the United Kingdomrdquo in Proceedings of the 6th In-ternational Conference on the Structural Design of AsphaltPavements Ann Arbor MI USA July 1987

[56] S Hossain G Dickerson and C Weaver Comparative Studyof VTM and AASHTO Test Method for CBR Co MaterialsDivision VDOT 2005

[57] N Garg A Larkin and H Brar ldquoA comparative subgradeevaluation using CBR vane shear light weight deflectometerand resilient modulus testsrdquo in Proceedings of the 8th In-ternational Conference on the Bearing Capacity of RoadsRailways and Airfields CRC Press Champaign IL USA2009

[58] M Ayres Development of a rational probabilistic approach forflexible pavement analysis University of Maryland CollegePark MD USA 1997

[59] AASHTO T 307 Determining the Resilient Modulus of Soilsand Aggregate Materials (2012) American Association ofState Highway and Transportation Officials Washington DCUSA 2004

[60] M Arshad and M F Ahmed ldquoPotential use of reclaimedasphalt pavement and recycled concrete aggregate in basesubbase layers of flexible pavementsrdquo Construction andBuilding Materials vol 151 pp 83ndash97 2017

[61] M Arshad ldquoCorrelation between resilient modulus (MR) andconstrained modulus (Mc) values of granular materialsrdquoConstruction and Building Materials vol 159 pp 440ndash4502018

[62] P Guo and J Emery ldquoImportance of strain level inevaluating resilient modulus of granular materialsrdquo In-ternational Journal of Pavement Engineering vol 12 no 2pp 187ndash199 2011

[63] E J McGarrah ldquoEvaluation of current practices of reclaimedasphalt pavementvirgin aggregate as base course materialrdquoNo WA-RD 7131 Federal Highway AdministrationWashington DC USA 2007

[64] T B Alam M Abdelrahman and S A Schram ldquoLaboratorycharacterisation of recycled asphalt pavement as a base layerrdquoInternational Journal of Pavement Engineering vol 11 no 2pp 123ndash131 2010

[65] T Bennert and A Maher ldquoe development of a performancespecification for granular base and subbase materialrdquo ReportNo FHWA-NJ-2005-003 Department of TransportationEwing Township NJ USA 2005

[66] T H Wonnacott H omas and J Ronald ldquoRegression asecond course in statisticsrdquo No 04 QA2782 W6Wiley NewYork NY USA 1981

[67] W Penny and S Roberts Neural network predictions witherror bars Dept of Electrical and Electronic EngineeringTechnology and Medicine Research Report TR-97-1 ImperialCollege of Science London UK 1997

[68] R Dybowski and S J Roberts ldquoConfidence intervals andprediction intervals for feed-forward neural networksrdquoClinical Applications of Artificial Neural Networks pp 298ndash326 2001

[69] J Hauke and T Kossowski ldquoComparison of values ofPearsonrsquos and Spearmanrsquos correlation coefficients on the samesets of datardquo Quaestiones Geographicae vol 30 no 2pp 87ndash93 2011

[70] K-z Yan H-b Xu and G-h Shen ldquoNovel approach toresilient modulus using routine subgrade soil propertiesrdquo

Advances in Materials Science and Engineering 15

International Journal of Geomechanics vol 14 no 6 article04014025 2013

[71] Y H Chan ldquoBiostatistics 104 correlational analysisrdquoSingapore Medical Journal vol 44 no 12 pp 614ndash6192003

[72] B M Damghani D Welch C OrsquoMalley and S Knights ldquoemisleading value of measured correlationrdquoWilmott vol 2012no 62 pp 64ndash73 2012

[73] L B Christensen B Johnson and L A Turner ldquoResearchmethods design and analysisrdquo 2011

[74] W J Dixon and F J Massey Introduction to StatisticalAnalysis McGraw-Hill New York NY USA 1969

[75] B Colbert and Z You ldquoe determination of mechanicalperformance of laboratory produced hot mix asphalt mixturesusing controlled RAP and virgin aggregate size fractionsrdquoConstruction and Building Materials vol 26 no 1 pp 655ndash662 2012

[76] D H Timm and D E Newcomb ldquoPerpetual pavement designfor flexible pavements in the USrdquo International Journal ofPavement Engineering vol 7 no 2 pp 111ndash119 2006

[77] Y H Huang Pavement Analysis and Design Prentice-HallEnglewood Cliffs NJ USA 2nd edition 1993

[78] L Walubita W Liu and T Scullion Texas perpetualpavements-Experience overview and the way forward Tech-nical Report No 0-4822-3 Texas Transportation InstituteTexas AampM University College Station TX USA 2010

[79] D Timm and D Newcomb ldquoCalibration of flexible pavementperformance equations for Minnesota road research projectrdquoTransportation Research Record Journal of the TransportationResearch Board no 1853 pp 134ndash142 2003

16 Advances in Materials Science and Engineering

CorrosionInternational Journal of

Hindawiwwwhindawicom Volume 2018

Advances in

Materials Science and EngineeringHindawiwwwhindawicom Volume 2018

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Chemistry

Analytical ChemistryInternational Journal of

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ScienticaHindawiwwwhindawicom Volume 2018

Polymer ScienceInternational Journal of

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Advances in Condensed Matter Physics

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Hindawi Publishing Corporation httpwwwhindawicom Volume 2013Hindawiwwwhindawicom

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Volume 2018

TribologyAdvances in

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Journal of

Hindawiwwwhindawicom Volume 2018

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nom

ate

ria

ls

Hindawiwwwhindawicom Volume 2018

Journal ofNanomaterials

Submit your manuscripts atwwwhindawicom

63 Pavement Performance Criteria In the design ofconventional flexible pavements pavement sectionsare designed corresponding to a cumulative damagefactor (CDF) of 10 which corresponds to a terminallevel of pavement damage For perpetual pavementshowever it is recommended that the CDF is equal to 01at the end of its design life [76] e fatigue and ruttingalgorithms developed at MnROAD [79] for the cali-bration of flexible pavement performance equations wereused to predict pavement damage in cases where pave-ment responses exceeded these thresholds ese corre-lations are as follows

Nf 283lowast 10minus61εt

1113888 1113889

3148

(fatigue)

Nr 6026lowast 10minus81εv

1113888 1113889

387

(ritting)

(8)

where Nf number of load repetitions when fatigue failureoccurs Nr number of load repetition when rutting failureoccurs εt the horizontal tensile strain at the bottom of theHMA and εv the vertical compressive strain at the top ofthe subgrade

It should be noted that the damage of rutting estimatedby PerRoad only takes into account the permanent de-formation in the subgrade Any rutting associated with thedeformation of granular subbase materials is not consideredAccording to the test results in this study use of RAP ingranular subbase layers may induce substantial residualdeformation Further investigation should be performed toget a better understanding of its influence on the rutting offlexible pavements

64 Simulation Results and Discussion Simulation resultsare obtained and discussed in terms of

(1) e likelihood of the tensile strain at the bottom ofthe HMA exceeding 70 με

(2) e likelihood of the vertical strain at the top of thesubgrade soil exceeding 200 με

(3) e number of years it could take to reach a CDF of01 (the threshold level) for fatigue damage

(4) e number of years it could take to reach a CDF of01 for damage induced by rutting

Figure 9 illustrates the concept frequency distributionfor strain both within and outside the threshold limits

We first examine the likelihood of critical pavementresponses exceeding the predefined thresholds when theresilient modulus of the asphalt concrete is 5000MPa anddifferent aggregates or aggregate-RAP blends are used inthe granular subbase layer Figure 10 summarises (1) thelikelihood of the tensile strain at the bottom of the HMAremaining within the critical value of 70 με and (2) thelikelihood of the vertical strain at the top of the subgradesoil exceeding 200 με From this figure it can be inter-preted that all of the blends result in better pavementperformance than the natural aggregate both in terms ofthe tensile strains at the bottom of the HMA and thevertical compressive strains at the top of the subgrade soilFor instance the natural aggregates and RCA on averagehave an 813 likelihood that horizontal strain at thebottom of the HMA will remain within the critical limit of70 με

On the other hand the likelihood for blended ma-terials containing 25 50 and 75 of RAP materials inthe blended samples may reach (on average) 85758937 and 9377 (respectively) chance of remainingwithin the limit Similarly the likelihood that the com-pressive strain at the top of the subgrade will not exceedthe critical value of 200 microns is 8828 (naturalsamples) 9346 (25 RAP material blends) 9557(50 RAP material blends) and 982 (75 RAP ma-terial blends)

Figure 11 shows the number of years required to reacha CDF of 01 when fatigue is controlled by the horizontaltensile strain at the bottom of the subgrade and the HMAand vertical structural rutting are controlled by the verticalcompressive strain at the top of the subgrade e numberof years required to reach a CDF of 01 in general in-creases in line with the increase in the quantity of RAP inthe blend For example the number of years required toreach a CDF of 01 in terms of fatigue damage at thebottom of HMA is 4033 years for natural samples whilethe corresponding figure for the blends containing 75RAP is 5168 years on average A similar trend regarding anincrease in the number of years required to reach a CDF of01 in terms of structural damage at the top of the subgradewas also observed Furthermore for all the cases thenumber of years to reach a CDF of 01 was more than40 years but it is clear that fatigue will be the predominantpavement failure mode

Asphalt concrete

Unbound base

Unbound subbase

Compacted subgrade

Natural subgrade

Figure 7 A typical cross section of flexible pavement

Table 7 Material properties and pavement layer thicknesses

Parameters HMA Base course Subbasecourse Subgrade

MR (MPa) 5000 350 Variable 35Coefficient ofvariation for MR () 25 30 35 45

ickness ofthe layer (mm) 250 200 300 mdash

icknessVariability () 5 8 15 mdash

Poisson ratio 03 03 03 04

10 Advances in Materials Science and Engineering

7 Long-Term Effect of Cyclic Loading onBlended Samples

In order to explore the long-term eects of cyclic loading 9repeated load triaxial tests were performed under a range ofcyclic loading conditions and varying percentages of RAPcontents Figure 12 presents the variation of the residual strainof the tested samples subjected to 20000 load cycles under twodierent values of conning pressures of 345 kPa and1379 kPa each while the corresponding cyclic deviator stresswas maintained at 3105 kPa and 372 kPa From this gure itcan be inferred that the presence of RAP contents increases theresidual strain considerably for both of the conning pressurescenarios For instance for the repeated load test conducted atthe conning pressure of 345 kPa the residual strain for 100natural aggregate F is 012 after 20000 load cycles while forthe blend containing 50 RAP(2) and 75 RAP(2) thecorresponding gures reach 022 and 060 ie an additionof 50 RAP increases the residual strain by amargin of almost83 while the addition of 75 RAP increases the residualstrain by almost 400 Similarly for the repeated load testsconducted at a conning pressure of 1379 kPa on samples

containing natural aggregateW and the blends with RAP(1) at50 and 75 the residual strain after 20000 load cycles is 55and 300 higher when compared with the correspondingvalue for the 100 natural aggregate W Furthermore it isevident from the gures that almost 60 of the total residualstrain occurred during the rst 2000 load cycles out of the20000 total load cycles applied across all the cases

However it should be emphasized that there is a ten-dency for the elastic shakedown to be less pronounced forblended samples when compared to pure natural aggregatesFor instance for the blended sample 50 W and 50RAP(1) the rate of increase of strain becomes 0000154 forthe load cycles in the range of 2000ndash20000 On the otherhand this gure remained limited to 0000056 for thesample containing 100 natural aggregate W under thesame loading condition

Figure 13 shows the eect of the ratio of ldquocyclic deviatorstress to the conning stress (σdσc)rdquo on the residual strain forthe blended sample containing 50 A and 50 RAP(3)From this gure it can be inferred that the ratio σdσc has asubstantial eect on the residual strain generated undercyclic loading For instance at (σdσc) 09 the residualstrain after 6000 load cycles is limited to 006 however thisvalue reaches 011 and 021 at (σdσc) 18 and(σdσc) 27 respectively yene samples tend to stabilisemore quickly under a lower value of (σdσc) 09 whencompared to the stabilising tendency at the higher values of(σdσc) 18 and (σdσc) 27 which were also in-vestigated in this research A 50ndash60 residual strain occursduring the rst 1000 load cycles out of the total 6000 loadcycles applied during the experimental campaign irre-spective of the σdσc value

8 Summary and Conclusions

(1) yene blended samples (ie RAP combined withnatural granular materials) result in higher MRvalues than those obtained for natural granular

Figure 8 Vehicular load classication used in PerRoad 35

Area outside the threshold limit

Stra

in fr

eque

ncy

Figure 9 Example of frequency distribution of strain within andoutside the threshold limits

Advances in Materials Science and Engineering 11

samples under the same loading conditions whilevariations between MR values and the applied bulkstresses during the resilient modulus tests can beapproximated through power law having coecientof correlation (r) value in the range of 097ndash099

(2) yene CBR values of blended samples decrease withthe addition of RAP contents however a clear

decreasing trend in conjunction with an increasingpercentage of RAP contents could not be found

(3) yene new model for the estimation of MR values in-cludes the stress state through the experimentallydetermined CBR having a coecient of correlation ldquorrdquoequal to approximately 09 with fair distribution of thedata points (MR measured and MR estimated) about

Perc

enta

ge o

f are

a

70

75

80

85

90

95

100

100

A10

0 F

100

W10

0 R

CA75

A

+ 2

5 R

AP(

1)75

A

+ 2

5 R

AP(

2)75

A

+ 2

5 R

AP(

3)75

A

+ 2

5 R

AP(

4)75

F

+ 2

5 R

AP(

1)75

F

+ 2

5 R

AP(

2)75

F

+ 2

5 R

AP(

3)75

F

+ 2

5 R

AP(

4)75

W

+ 2

5 R

AP(

1)75

W

+ 2

5 R

AP(

2)75

W

+ 2

5 R

AP(

3)75

W

+ 2

5 R

AP(

4)75

R

CA +

25

RA

P(1)

75

RCA

+ 2

5 R

AP(

2)75

R

CA +

25

RA

P(3)

75

RCA

+ 2

5 R

AP(

4)50

A

+ 5

0 R

AP(

1)50

A

+ 5

0 R

AP(

2)50

A

+ 5

0 R

AP(

3)50

A

+ 5

0 R

AP(

4)50

F

+ 5

0 R

AP(

1)50

F

+ 5

0 R

AP(

2)50

F

+ 5

0 R

AP(

3)50

F

+ 5

0 R

AP(

4)50

W

+ 5

0 R

AP(

1)50

W

+ 5

0 R

AP(

2)50

W

+ 5

0 R

AP(

3)50

W

+ 5

0 R

AP(

4)50

R

CA +

50

RA

P(1)

50

RCA

+ 5

0 R

AP(

2)50

R

CA +

50

RA

P(3)

50

RCA

+ 5

0 R

AP(

4)25

A

+ 7

5 R

AP(

1)25

A

+ 7

5 R

AP(

2)25

A

+ 7

5 R

AP(

3)25

A

+ 7

5 R

AP(

4)25

F

+ 7

5 R

AP(

1)25

F

+ 7

5 R

AP(

2)25

F

+ 7

5 R

AP(

3)25

F

+ 7

5 R

AP(

4)25

W

+ 7

5 R

AP(

1)25

W

+ 7

5 R

AP(

2)25

W

+ 7

5 R

AP(

3)25

W

+ 7

5 R

AP(

4)25

R

CA +

75

RA

P(1)

25

RCA

+ 7

5 R

AP(

2)25

R

CA +

75

RA

P(3)

25

RCA

+ 7

5 R

AP(

4)

Percentage of area within the critical limit of horizontal strain at the bottom of HMAPercentage of area within the critical limit of vertical strain at the top of subgrade

Figure 10 Percentage of area within the critical limits for horizontal strain at the bottom of HMA and vertical strain at the top of subgrade

30

35

40

45

50

55

60

65

70

100

A10

0 F

100

W10

0 R

CA75

A

+ 2

5 R

AP(

1)75

A

+ 2

5 R

AP(

2)75

A

+ 2

5 R

AP(

3)75

A

+ 2

5 R

AP(

4)75

F

+ 2

5 R

AP(

1)75

F

+ 2

5 R

AP(

2)75

F

+ 2

5 R

AP(

3)75

F

+ 2

5 R

AP(

4)75

W

+ 2

5 R

AP(

1)75

W

+ 2

5 R

AP(

2)75

W

+ 2

5 R

AP(

3)75

W

+ 2

5 R

AP(

4)75

R

CA +

25

RA

P(1)

75

RCA

+ 2

5 R

AP(

2)75

R

CA +

25

RA

P(3)

75

RCA

+ 2

5 R

AP(

4)50

A

+ 5

0 R

AP(

1)50

A

+ 5

0 R

AP(

2)50

A

+ 5

0 R

AP(

3)50

A

+ 5

0 R

AP(

4)50

F

+ 5

0 R

AP(

1)50

F

+ 5

0 R

AP(

2)50

F

+ 5

0 R

AP(

3)50

F

+ 5

0 R

AP(

4)50

W

+ 5

0 R

AP(

1)50

W

+ 5

0 R

AP(

2)50

W

+ 5

0 R

AP(

3)50

W

+ 5

0 R

AP(

4)50

R

CA +

50

RA

P(1)

50

RCA

+ 5

0 R

AP(

2)50

R

CA +

50

RA

P(3)

50

RCA

+ 5

0 R

AP(

4)25

A

+ 7

5 R

AP(

1)25

A

+ 7

5 R

AP(

2)25

A

+ 7

5 R

AP(

3)25

A

+ 7

5 R

AP(

4)25

F

+ 7

5 R

AP(

1)25

F

+ 7

5 R

AP(

2)25

F

+ 7

5 R

AP(

3)25

F

+ 7

5 R

AP(

4)25

W

+ 7

5 R

AP(

1)25

W

+ 7

5 R

AP(

2)25

W

+ 7

5 R

AP(

3)25

W

+ 7

5 R

AP(

4)25

R

CA +

75

RA

P(1)

25

RCA

+ 7

5 R

AP(

2)25

R

CA +

75

RA

P(3)

25

RCA

+ 7

5 R

AP(

4)

Year

s

Number of years required to reach CDF = 01 in terms of horizontal strain at the bottom of HMANumber of years required to reach CDF = 01 in terms of vertical strain at the top of subgrade

Figure 11 Number of years required to reach CDF 01 in terms of horizontal strain at the bottom of HMA and vertical strain at the top ofsubgrade

12 Advances in Materials Science and Engineering

the unity line indicating that the proposed regressionmodel has a moderate to strong correlation

(4) Statistical analysis of simulation results based onPerRoad and KenPave software demonstrates thatthe addition of RAP contents in the subbase layer ofthe copyexible pavement signicantly improves itsperformance against rutting and fatigue

(5) Residual strain during the long-term repeated loadtriaxial test was found to increase in line with anincrease in the ratio of ldquocyclic deviator stress to theconning stress (σdσc)rdquo in correlation to an increasein the percentage of RAP contents in the blendedsample

(6) From the authorrsquos perspective the addition of RAPcontents beyond a certain limit (sim50) may prove tobe detrimental for the overall performance of copyexiblepavement structure

Data Availability

yene experimental data used to support the ndings of thisstudy are included within the article in the form of graphsand tables

Conflicts of Interest

yene author declares that there are no concopyicts of interestregarding the publication of this paper

References

[1] R B Mallick and A Veeraragavan ldquoSustainable pavements inIndia-the time to start is nowrdquo New Building Materials andConstruction World (NBMampCW) Magazine vol 16 no 3pp 128ndash140 2010

[2] A Mohammadinia A Arulrajah S Horpibulsuk andA Chinkulkijniwat ldquoEect of copyy ash on properties of crushedbrick and reclaimed asphalt in pavement basesubbase

000

050

100

150

200

250

300

350

400

450

500

0 2000 4000 6000 8000 10000 12000 14000 16000 18000 20000

Axi

al st

rain

()

Number of load cycles

100 W50 W + 50 RAP(1)25 W + 75 RAP(1)100 F50 F + 50 RAP(2)25 F + 75 RAP(2)

σc = 1379kPa σd = 372kPa

Figure 12 Eect of RAP contents on residual strain under long-term repeated loading

000

005

010

015

020

025

0 1000 2000 3000 4000 5000 6000

Axi

al st

rain

()

Number of load cycles

091827

odoc

Figure 13 Eect of ratio of ldquocyclic deviator stress to the conningstress (σdσc)rdquo on the residual strain under long-term repeatedloading

Advances in Materials Science and Engineering 13

applicationsrdquo Journal of Hazardous Materials vol 321pp 547ndash556 2017

[3] L R Hoyos A J Puppala and C A Ordonez ldquoCharacter-ization of cement-fiber-treated reclaimed asphalt pavementaggregates preliminary investigationrdquo Journal of Materials inCivil Engineering vol 23 no 7 pp 977ndash989 2011

[4] R Taha A Al-Harthy K Al-Shamsi and M Al-ZubeidildquoCement stabilization of reclaimed asphalt pavement aggre-gate for road bases and subbasesrdquo Journal of Materials in CivilEngineering vol 14 no 3 pp 239ndash245 2002

[5] A M Azam and D A Cameron ldquoGeotechnical properties ofblends of recycled clay masonry and recycled concrete ag-gregates in unbound pavement constructionrdquo Journal ofMaterials in Civil Engineering vol 25 no 6 pp 788ndash7982013

[6] A Gabor and D Cameron ldquoProperties of recycled concreteaggregate for unbound pavement constructionrdquo Journal ofMaterials in Civil Engineering vol 24 no 6 pp 754ndash7642012

[7] C S Poon and D Chan ldquoFeasible use of recycled concreteaggregates and crushed clay brick as unbound road sub-baserdquoConstruction and Building Materials vol 20 no 8 pp 578ndash585 2006

[8] A Arulrajah M M Y Ali M M Disfani J Piratheepan andM W Bo ldquoGeotechnical performance of recycled glass-wasterock blends in footpath basesrdquo Journal of Materials in CivilEngineering vol 25 no 5 pp 653ndash661 2013

[9] L T Lee Jr ldquoRecycled glass and dredged materialsrdquo ReportNo ERDC TNDOER-T8 US Army Corps of EngineersEngineer Research and Development Center Mississippi MSUSA 2007

[10] M Ali A Arulrajah M Disfani and J Piratheepan ldquoSuit-ability of using recycled glassmdashcrushed rock blends forpavement subbase applicationsrdquo in Proceedings of the Geo-Frontiers 2011 Conference on Geotechnical Foundation Designpp 1325ndash1334 ASCE Reston VA USA 2011

[11] J Wartman D G Grubb and A S M Nasim ldquoSelectengineering characteristics of crushed glassrdquo Journal ofMaterials in Civil Engineering vol 16 no 6 pp 526ndash5392004

[12] W Kim and J Labuz Resilient Modulus and Strength of BaseCourse with Recycled Bituminous Material Minnesota De-partment of Transportation Research Services Section MNUSA 2007

[13] D Bloomquist G Diamond M Oden B Ruth and M TiaEngineering and Environmental Aspects of Recycled Materialsfor Highway Construction Appendix 1 Final Report 1993

[14] A Hussain and Q Yanjun ldquoEvaluation of asphalt mixescontaining reclaimed asphalt pavement for wearing cour-sesrdquo in Proceedings of the International Conference onTraffic and Transportation Engineering School of CivilEngineering Southwest Jiaotong University ChengduChina 2012

[15] M Solaimanian and M Tahmoressi ldquoVariability analysis ofhot-mix asphalt concrete containing high percentage ofreclaimed asphalt pavementrdquo Transportation Research Re-cord Journal of the Transportation Research Board vol 1543no 1 pp 89ndash96 1996

[16] A Gabr and D A Cameron ldquoProperties of recycled concreteaggregate for unbound pavement constructionrdquo Journal ofMaterials in Civil Engineering vol 24 no 6 pp 754ndash7642011

[17] W-L Huang D-H Lin N-B Chang and K-S LinldquoRecycling of construction and demolition waste via a

mechanical sorting processrdquo Resources Conservation andRecycling vol 37 no 1 pp 23ndash37 2002

[18] A R Pasandın and I Perez ldquoOverview of bituminous mix-tures made with recycled concrete Aggregatesrdquo Constructionand Building Materials vol 74 pp 151ndash161 2015

[19] P Jitsangiam H Nikraz and K Siripun ldquoConstruction anddemolition (CampD) waste as a road base material for WesternAustralia roadsrdquo Australian Geomechanics vol 44 no 3pp 57ndash62 2009

[20] A Nataatmadja and Y L Tan ldquoResilient response of recycledconcrete road aggregatesrdquo Journal of Transportation Engi-neering vol 127 no 5 pp 450ndash453 2001

[21] C Leek and K Siripun ldquoSpecification and performance ofrecycled materials in road pavementsrdquo Contract Rep (01119-1)2010

[22] J Green and J Hall Nondistructive Vibratory Testing ofAirport Pavement 1975

[23] W Heukelom and A Klomp ldquoDynamic testing as a means ofcontrolling pavements during and after constructionrdquo inProceedings of the International Conference on the StructuralDesign of Asphalt Pavements University of Michigan AnnArbor MI USA 1962

[24] Ohio Department of Transportation Pavement DesignManual Ohio Department of Transportation Office ofPavement Engineering OH USA 2008

[25] W D Powell H C Mayhew and M M Nunn ldquoestructural design of bituminous roadsrdquo Laboratory Report1132 Transport and Road Research Laboratory CrowthorneUK 1984

[26] M W Witczak X Qi and M W Mirza ldquoUse of nonlinearsubgrade modulus in AASHTO design procedurerdquo Journal ofTransportation Engineering vol 121 no 3 1995

[27] AASHTO Guide for Design of Pavement Structures Wash-ington DC USA 1993

[28] Asphalt Institute Research and Development of 5e AsphaltInstitutersquos 5ickness Design Manual (MS-1) 9th edition 1982

[29] T Buu Correlation of Resistance R-value and ResilientModulus of Idaho Subgrade Soil Idaho Department ofTransportation Division of Highways ID USA 1980

[30] S Muench J Mahoney and L Pierce WSDOT PavementGuide Washington State Department of TransportationInternet Module Washington DC USA 2009

[31] S Yeh and C Su ldquoResilient properties of Colorado soilsrdquoReport No CDOH-DH-SM-89-9 Colorado Department ofHighways Denver CO USA 1989

[32] M R ompson and Q L Robnett ldquoResilient properties ofsubgrade soilsrdquo Transportation Engineering Journal of ASCEvol 105 pp 71ndash89 1979

[33] W Lee N C Bohra A G Altschaeffl and T D WhiteldquoResilient modulus of cohesive soilsrdquo Journal of Geotechnicaland Geoenvironmental Engineering vol 123 no 2 pp 131ndash136 1997

[34] R Carmichael III and E Stuart ldquoPredicting resilient modulusa study to determine the mechanical properties of subgradesoilsrdquo Transportation Research Record vol 1043 pp 145ndash1481986

[35] E C Drumm Y Boateng-Poku and T Johnson PierceldquoEstimation of subgrade resilient modulus from standardtestsrdquo Journal of Geotechnical Engineering vol 116 no 5pp 774ndash789 1990

[36] M J Farrar and J P Turner Resilient Modulus of WyomingSubgrade Soils 1991

14 Advances in Materials Science and Engineering

[37] M P Jones and M W Witczak ldquoSubgrade modulus on thesan diego test roadrdquo Transportation Research Record Journalof the Transportation Research Board vol 641 pp 1ndash6 1977

[38] A M Rahim and K P George ldquoSubgrade soil indexproperties to estimate resilient modulusrdquo in Proceedings ofthe 83th Annual Meeting of the Transportation ResearchBoard National Research Council Washington DC USA2004

[39] M R ompson and T G LaGrow A Proposed ConventionalFlexible Pavement 5ickness Design Procedure University ofIllinois Peoria IL USA 1988

[40] R Pezo ldquoA general method of reporting resilient modulustests of soils a pavement engineerrsquos point of viewrdquo in Pro-ceedings of the 72nd Annual Meeting of Transportation Re-search Board Washington DC USA 1993

[41] R G Hicks and C L Monismith ldquoResilient properties ofgranular materialrdquo Transportation Research Record vol 345pp 15ndash31 1971

[42] J Uzan ldquoCharacterization of granular materialsrdquo Trans-portation Research Record Journal of the Transportation Re-search Board vol 1022 pp 52ndash59 1985

[43] National Cooperative Highway Research Program ldquoGuide formechanistic-empirical design of new and rehabilitatedpavement structuresrdquo NCHRP 1-37A NCHRP WashingtonDC USA 2004

[44] N M Louay H T Hani and H Ananda ldquoEvaluation ofresilient modulus of subgrade soil by cone penetration testrdquoTransportation Research Record Journal of the TransportationResearch Board vol 1652 pp 236ndash245 1999

[45] S Dai and J Zollars ldquoResilient modulus of Minnesota roadresearch project subgrade soilrdquo Transportation Research Re-cord Journal of the Transportation Research Board vol 1786no 1 pp 20ndash28 2002

[46] L Mohammad B Huang A Puppala and A Allen ldquoRe-gression model for resilient modulus of subgrade soilsrdquoTransportation Research Record Journal of the TransportationResearch Board vol 1687 no 1 pp 47ndash54 1999

[47] B Santa ldquoResilient modulus of subgrade soils comparison oftwo constitutive equationsrdquo Transportation Research RecordJournal of the Transportation Research Board vol 1462pp 79ndash90 1994

[48] H Von Quintus and B Killingsworth Analyses Relating toPavement Material Characterizations and their Effects onPavement Performance 1998

[49] O Porter ldquoe preparation of subgradesrdquo in Proceedings ofthe Nineteenth Annual Meeting Highway Research BoardWashington DC USA December 1939

[50] O J Porter ldquoDevelopment of the original method for highwaydesignrdquo Transactions of the American Society of Civil Engi-neers vol 115 pp 461ndash467 1950

[51] D W Hight and M G H Stevens ldquoAn analysis of theCalifornia Bearing Ratio test in saturated claysrdquoGeotechnique vol 32 no 4 pp 315ndash322 1982

[52] P R Fleming and C D F Rogers ldquoAssessment of pavementfoundations during constructionrdquo Proceedings of the In-stitution of Civil Engineers-Transport vol 111 no 2pp 105ndash115 1995

[53] M R ompson R Marshall and Q L Robnett ldquoResilientproperties of subgrade soilsrdquo Final Report No FHWA-IL-UI-160 University of Illinois Urbana IL USA 1976

[54] B Sukumaran V Kyatham A Shah and D Sheth ldquoSuit-ability of using California bearing ratio test to predict resilientmodulusrdquo in Proceedings Federal Aviation Administration

Airport Technology Transfer Conference Atlantic City NJUSA 2002

[55] N W Lister and D Powell ldquoDesign practices for pavementsin the United Kingdomrdquo in Proceedings of the 6th In-ternational Conference on the Structural Design of AsphaltPavements Ann Arbor MI USA July 1987

[56] S Hossain G Dickerson and C Weaver Comparative Studyof VTM and AASHTO Test Method for CBR Co MaterialsDivision VDOT 2005

[57] N Garg A Larkin and H Brar ldquoA comparative subgradeevaluation using CBR vane shear light weight deflectometerand resilient modulus testsrdquo in Proceedings of the 8th In-ternational Conference on the Bearing Capacity of RoadsRailways and Airfields CRC Press Champaign IL USA2009

[58] M Ayres Development of a rational probabilistic approach forflexible pavement analysis University of Maryland CollegePark MD USA 1997

[59] AASHTO T 307 Determining the Resilient Modulus of Soilsand Aggregate Materials (2012) American Association ofState Highway and Transportation Officials Washington DCUSA 2004

[60] M Arshad and M F Ahmed ldquoPotential use of reclaimedasphalt pavement and recycled concrete aggregate in basesubbase layers of flexible pavementsrdquo Construction andBuilding Materials vol 151 pp 83ndash97 2017

[61] M Arshad ldquoCorrelation between resilient modulus (MR) andconstrained modulus (Mc) values of granular materialsrdquoConstruction and Building Materials vol 159 pp 440ndash4502018

[62] P Guo and J Emery ldquoImportance of strain level inevaluating resilient modulus of granular materialsrdquo In-ternational Journal of Pavement Engineering vol 12 no 2pp 187ndash199 2011

[63] E J McGarrah ldquoEvaluation of current practices of reclaimedasphalt pavementvirgin aggregate as base course materialrdquoNo WA-RD 7131 Federal Highway AdministrationWashington DC USA 2007

[64] T B Alam M Abdelrahman and S A Schram ldquoLaboratorycharacterisation of recycled asphalt pavement as a base layerrdquoInternational Journal of Pavement Engineering vol 11 no 2pp 123ndash131 2010

[65] T Bennert and A Maher ldquoe development of a performancespecification for granular base and subbase materialrdquo ReportNo FHWA-NJ-2005-003 Department of TransportationEwing Township NJ USA 2005

[66] T H Wonnacott H omas and J Ronald ldquoRegression asecond course in statisticsrdquo No 04 QA2782 W6Wiley NewYork NY USA 1981

[67] W Penny and S Roberts Neural network predictions witherror bars Dept of Electrical and Electronic EngineeringTechnology and Medicine Research Report TR-97-1 ImperialCollege of Science London UK 1997

[68] R Dybowski and S J Roberts ldquoConfidence intervals andprediction intervals for feed-forward neural networksrdquoClinical Applications of Artificial Neural Networks pp 298ndash326 2001

[69] J Hauke and T Kossowski ldquoComparison of values ofPearsonrsquos and Spearmanrsquos correlation coefficients on the samesets of datardquo Quaestiones Geographicae vol 30 no 2pp 87ndash93 2011

[70] K-z Yan H-b Xu and G-h Shen ldquoNovel approach toresilient modulus using routine subgrade soil propertiesrdquo

Advances in Materials Science and Engineering 15

International Journal of Geomechanics vol 14 no 6 article04014025 2013

[71] Y H Chan ldquoBiostatistics 104 correlational analysisrdquoSingapore Medical Journal vol 44 no 12 pp 614ndash6192003

[72] B M Damghani D Welch C OrsquoMalley and S Knights ldquoemisleading value of measured correlationrdquoWilmott vol 2012no 62 pp 64ndash73 2012

[73] L B Christensen B Johnson and L A Turner ldquoResearchmethods design and analysisrdquo 2011

[74] W J Dixon and F J Massey Introduction to StatisticalAnalysis McGraw-Hill New York NY USA 1969

[75] B Colbert and Z You ldquoe determination of mechanicalperformance of laboratory produced hot mix asphalt mixturesusing controlled RAP and virgin aggregate size fractionsrdquoConstruction and Building Materials vol 26 no 1 pp 655ndash662 2012

[76] D H Timm and D E Newcomb ldquoPerpetual pavement designfor flexible pavements in the USrdquo International Journal ofPavement Engineering vol 7 no 2 pp 111ndash119 2006

[77] Y H Huang Pavement Analysis and Design Prentice-HallEnglewood Cliffs NJ USA 2nd edition 1993

[78] L Walubita W Liu and T Scullion Texas perpetualpavements-Experience overview and the way forward Tech-nical Report No 0-4822-3 Texas Transportation InstituteTexas AampM University College Station TX USA 2010

[79] D Timm and D Newcomb ldquoCalibration of flexible pavementperformance equations for Minnesota road research projectrdquoTransportation Research Record Journal of the TransportationResearch Board no 1853 pp 134ndash142 2003

16 Advances in Materials Science and Engineering

CorrosionInternational Journal of

Hindawiwwwhindawicom Volume 2018

Advances in

Materials Science and EngineeringHindawiwwwhindawicom Volume 2018

Hindawiwwwhindawicom Volume 2018

Journal of

Chemistry

Analytical ChemistryInternational Journal of

Hindawiwwwhindawicom Volume 2018

ScienticaHindawiwwwhindawicom Volume 2018

Polymer ScienceInternational Journal of

Hindawiwwwhindawicom Volume 2018

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Advances in Condensed Matter Physics

Hindawiwwwhindawicom Volume 2018

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BiomaterialsHindawiwwwhindawicom

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Applied ChemistryJournal of

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NanotechnologyHindawiwwwhindawicom Volume 2018

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Hindawiwwwhindawicom Volume 2018

High Energy PhysicsAdvances in

Hindawi Publishing Corporation httpwwwhindawicom Volume 2013Hindawiwwwhindawicom

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Volume 2018

TribologyAdvances in

Hindawiwwwhindawicom Volume 2018

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ChemistryAdvances in

Hindawiwwwhindawicom Volume 2018

Advances inPhysical Chemistry

Hindawiwwwhindawicom Volume 2018

BioMed Research InternationalMaterials

Journal of

Hindawiwwwhindawicom Volume 2018

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nom

ate

ria

ls

Hindawiwwwhindawicom Volume 2018

Journal ofNanomaterials

Submit your manuscripts atwwwhindawicom

7 Long-Term Effect of Cyclic Loading onBlended Samples

In order to explore the long-term eects of cyclic loading 9repeated load triaxial tests were performed under a range ofcyclic loading conditions and varying percentages of RAPcontents Figure 12 presents the variation of the residual strainof the tested samples subjected to 20000 load cycles under twodierent values of conning pressures of 345 kPa and1379 kPa each while the corresponding cyclic deviator stresswas maintained at 3105 kPa and 372 kPa From this gure itcan be inferred that the presence of RAP contents increases theresidual strain considerably for both of the conning pressurescenarios For instance for the repeated load test conducted atthe conning pressure of 345 kPa the residual strain for 100natural aggregate F is 012 after 20000 load cycles while forthe blend containing 50 RAP(2) and 75 RAP(2) thecorresponding gures reach 022 and 060 ie an additionof 50 RAP increases the residual strain by amargin of almost83 while the addition of 75 RAP increases the residualstrain by almost 400 Similarly for the repeated load testsconducted at a conning pressure of 1379 kPa on samples

containing natural aggregateW and the blends with RAP(1) at50 and 75 the residual strain after 20000 load cycles is 55and 300 higher when compared with the correspondingvalue for the 100 natural aggregate W Furthermore it isevident from the gures that almost 60 of the total residualstrain occurred during the rst 2000 load cycles out of the20000 total load cycles applied across all the cases

However it should be emphasized that there is a ten-dency for the elastic shakedown to be less pronounced forblended samples when compared to pure natural aggregatesFor instance for the blended sample 50 W and 50RAP(1) the rate of increase of strain becomes 0000154 forthe load cycles in the range of 2000ndash20000 On the otherhand this gure remained limited to 0000056 for thesample containing 100 natural aggregate W under thesame loading condition

Figure 13 shows the eect of the ratio of ldquocyclic deviatorstress to the conning stress (σdσc)rdquo on the residual strain forthe blended sample containing 50 A and 50 RAP(3)From this gure it can be inferred that the ratio σdσc has asubstantial eect on the residual strain generated undercyclic loading For instance at (σdσc) 09 the residualstrain after 6000 load cycles is limited to 006 however thisvalue reaches 011 and 021 at (σdσc) 18 and(σdσc) 27 respectively yene samples tend to stabilisemore quickly under a lower value of (σdσc) 09 whencompared to the stabilising tendency at the higher values of(σdσc) 18 and (σdσc) 27 which were also in-vestigated in this research A 50ndash60 residual strain occursduring the rst 1000 load cycles out of the total 6000 loadcycles applied during the experimental campaign irre-spective of the σdσc value

8 Summary and Conclusions

(1) yene blended samples (ie RAP combined withnatural granular materials) result in higher MRvalues than those obtained for natural granular

Figure 8 Vehicular load classication used in PerRoad 35

Area outside the threshold limit

Stra

in fr

eque

ncy

Figure 9 Example of frequency distribution of strain within andoutside the threshold limits

Advances in Materials Science and Engineering 11

samples under the same loading conditions whilevariations between MR values and the applied bulkstresses during the resilient modulus tests can beapproximated through power law having coecientof correlation (r) value in the range of 097ndash099

(2) yene CBR values of blended samples decrease withthe addition of RAP contents however a clear

decreasing trend in conjunction with an increasingpercentage of RAP contents could not be found

(3) yene new model for the estimation of MR values in-cludes the stress state through the experimentallydetermined CBR having a coecient of correlation ldquorrdquoequal to approximately 09 with fair distribution of thedata points (MR measured and MR estimated) about

Perc

enta

ge o

f are

a

70

75

80

85

90

95

100

100

A10

0 F

100

W10

0 R

CA75

A

+ 2

5 R

AP(

1)75

A

+ 2

5 R

AP(

2)75

A

+ 2

5 R

AP(

3)75

A

+ 2

5 R

AP(

4)75

F

+ 2

5 R

AP(

1)75

F

+ 2

5 R

AP(

2)75

F

+ 2

5 R

AP(

3)75

F

+ 2

5 R

AP(

4)75

W

+ 2

5 R

AP(

1)75

W

+ 2

5 R

AP(

2)75

W

+ 2

5 R

AP(

3)75

W

+ 2

5 R

AP(

4)75

R

CA +

25

RA

P(1)

75

RCA

+ 2

5 R

AP(

2)75

R

CA +

25

RA

P(3)

75

RCA

+ 2

5 R

AP(

4)50

A

+ 5

0 R

AP(

1)50

A

+ 5

0 R

AP(

2)50

A

+ 5

0 R

AP(

3)50

A

+ 5

0 R

AP(

4)50

F

+ 5

0 R

AP(

1)50

F

+ 5

0 R

AP(

2)50

F

+ 5

0 R

AP(

3)50

F

+ 5

0 R

AP(

4)50

W

+ 5

0 R

AP(

1)50

W

+ 5

0 R

AP(

2)50

W

+ 5

0 R

AP(

3)50

W

+ 5

0 R

AP(

4)50

R

CA +

50

RA

P(1)

50

RCA

+ 5

0 R

AP(

2)50

R

CA +

50

RA

P(3)

50

RCA

+ 5

0 R

AP(

4)25

A

+ 7

5 R

AP(

1)25

A

+ 7

5 R

AP(

2)25

A

+ 7

5 R

AP(

3)25

A

+ 7

5 R

AP(

4)25

F

+ 7

5 R

AP(

1)25

F

+ 7

5 R

AP(

2)25

F

+ 7

5 R

AP(

3)25

F

+ 7

5 R

AP(

4)25

W

+ 7

5 R

AP(

1)25

W

+ 7

5 R

AP(

2)25

W

+ 7

5 R

AP(

3)25

W

+ 7

5 R

AP(

4)25

R

CA +

75

RA

P(1)

25

RCA

+ 7

5 R

AP(

2)25

R

CA +

75

RA

P(3)

25

RCA

+ 7

5 R

AP(

4)

Percentage of area within the critical limit of horizontal strain at the bottom of HMAPercentage of area within the critical limit of vertical strain at the top of subgrade

Figure 10 Percentage of area within the critical limits for horizontal strain at the bottom of HMA and vertical strain at the top of subgrade

30

35

40

45

50

55

60

65

70

100

A10

0 F

100

W10

0 R

CA75

A

+ 2

5 R

AP(

1)75

A

+ 2

5 R

AP(

2)75

A

+ 2

5 R

AP(

3)75

A

+ 2

5 R

AP(

4)75

F

+ 2

5 R

AP(

1)75

F

+ 2

5 R

AP(

2)75

F

+ 2

5 R

AP(

3)75

F

+ 2

5 R

AP(

4)75

W

+ 2

5 R

AP(

1)75

W

+ 2

5 R

AP(

2)75

W

+ 2

5 R

AP(

3)75

W

+ 2

5 R

AP(

4)75

R

CA +

25

RA

P(1)

75

RCA

+ 2

5 R

AP(

2)75

R

CA +

25

RA

P(3)

75

RCA

+ 2

5 R

AP(

4)50

A

+ 5

0 R

AP(

1)50

A

+ 5

0 R

AP(

2)50

A

+ 5

0 R

AP(

3)50

A

+ 5

0 R

AP(

4)50

F

+ 5

0 R

AP(

1)50

F

+ 5

0 R

AP(

2)50

F

+ 5

0 R

AP(

3)50

F

+ 5

0 R

AP(

4)50

W

+ 5

0 R

AP(

1)50

W

+ 5

0 R

AP(

2)50

W

+ 5

0 R

AP(

3)50

W

+ 5

0 R

AP(

4)50

R

CA +

50

RA

P(1)

50

RCA

+ 5

0 R

AP(

2)50

R

CA +

50

RA

P(3)

50

RCA

+ 5

0 R

AP(

4)25

A

+ 7

5 R

AP(

1)25

A

+ 7

5 R

AP(

2)25

A

+ 7

5 R

AP(

3)25

A

+ 7

5 R

AP(

4)25

F

+ 7

5 R

AP(

1)25

F

+ 7

5 R

AP(

2)25

F

+ 7

5 R

AP(

3)25

F

+ 7

5 R

AP(

4)25

W

+ 7

5 R

AP(

1)25

W

+ 7

5 R

AP(

2)25

W

+ 7

5 R

AP(

3)25

W

+ 7

5 R

AP(

4)25

R

CA +

75

RA

P(1)

25

RCA

+ 7

5 R

AP(

2)25

R

CA +

75

RA

P(3)

25

RCA

+ 7

5 R

AP(

4)

Year

s

Number of years required to reach CDF = 01 in terms of horizontal strain at the bottom of HMANumber of years required to reach CDF = 01 in terms of vertical strain at the top of subgrade

Figure 11 Number of years required to reach CDF 01 in terms of horizontal strain at the bottom of HMA and vertical strain at the top ofsubgrade

12 Advances in Materials Science and Engineering

the unity line indicating that the proposed regressionmodel has a moderate to strong correlation

(4) Statistical analysis of simulation results based onPerRoad and KenPave software demonstrates thatthe addition of RAP contents in the subbase layer ofthe copyexible pavement signicantly improves itsperformance against rutting and fatigue

(5) Residual strain during the long-term repeated loadtriaxial test was found to increase in line with anincrease in the ratio of ldquocyclic deviator stress to theconning stress (σdσc)rdquo in correlation to an increasein the percentage of RAP contents in the blendedsample

(6) From the authorrsquos perspective the addition of RAPcontents beyond a certain limit (sim50) may prove tobe detrimental for the overall performance of copyexiblepavement structure

Data Availability

yene experimental data used to support the ndings of thisstudy are included within the article in the form of graphsand tables

Conflicts of Interest

yene author declares that there are no concopyicts of interestregarding the publication of this paper

References

[1] R B Mallick and A Veeraragavan ldquoSustainable pavements inIndia-the time to start is nowrdquo New Building Materials andConstruction World (NBMampCW) Magazine vol 16 no 3pp 128ndash140 2010

[2] A Mohammadinia A Arulrajah S Horpibulsuk andA Chinkulkijniwat ldquoEect of copyy ash on properties of crushedbrick and reclaimed asphalt in pavement basesubbase

000

050

100

150

200

250

300

350

400

450

500

0 2000 4000 6000 8000 10000 12000 14000 16000 18000 20000

Axi

al st

rain

()

Number of load cycles

100 W50 W + 50 RAP(1)25 W + 75 RAP(1)100 F50 F + 50 RAP(2)25 F + 75 RAP(2)

σc = 1379kPa σd = 372kPa

Figure 12 Eect of RAP contents on residual strain under long-term repeated loading

000

005

010

015

020

025

0 1000 2000 3000 4000 5000 6000

Axi

al st

rain

()

Number of load cycles

091827

odoc

Figure 13 Eect of ratio of ldquocyclic deviator stress to the conningstress (σdσc)rdquo on the residual strain under long-term repeatedloading

Advances in Materials Science and Engineering 13

applicationsrdquo Journal of Hazardous Materials vol 321pp 547ndash556 2017

[3] L R Hoyos A J Puppala and C A Ordonez ldquoCharacter-ization of cement-fiber-treated reclaimed asphalt pavementaggregates preliminary investigationrdquo Journal of Materials inCivil Engineering vol 23 no 7 pp 977ndash989 2011

[4] R Taha A Al-Harthy K Al-Shamsi and M Al-ZubeidildquoCement stabilization of reclaimed asphalt pavement aggre-gate for road bases and subbasesrdquo Journal of Materials in CivilEngineering vol 14 no 3 pp 239ndash245 2002

[5] A M Azam and D A Cameron ldquoGeotechnical properties ofblends of recycled clay masonry and recycled concrete ag-gregates in unbound pavement constructionrdquo Journal ofMaterials in Civil Engineering vol 25 no 6 pp 788ndash7982013

[6] A Gabor and D Cameron ldquoProperties of recycled concreteaggregate for unbound pavement constructionrdquo Journal ofMaterials in Civil Engineering vol 24 no 6 pp 754ndash7642012

[7] C S Poon and D Chan ldquoFeasible use of recycled concreteaggregates and crushed clay brick as unbound road sub-baserdquoConstruction and Building Materials vol 20 no 8 pp 578ndash585 2006

[8] A Arulrajah M M Y Ali M M Disfani J Piratheepan andM W Bo ldquoGeotechnical performance of recycled glass-wasterock blends in footpath basesrdquo Journal of Materials in CivilEngineering vol 25 no 5 pp 653ndash661 2013

[9] L T Lee Jr ldquoRecycled glass and dredged materialsrdquo ReportNo ERDC TNDOER-T8 US Army Corps of EngineersEngineer Research and Development Center Mississippi MSUSA 2007

[10] M Ali A Arulrajah M Disfani and J Piratheepan ldquoSuit-ability of using recycled glassmdashcrushed rock blends forpavement subbase applicationsrdquo in Proceedings of the Geo-Frontiers 2011 Conference on Geotechnical Foundation Designpp 1325ndash1334 ASCE Reston VA USA 2011

[11] J Wartman D G Grubb and A S M Nasim ldquoSelectengineering characteristics of crushed glassrdquo Journal ofMaterials in Civil Engineering vol 16 no 6 pp 526ndash5392004

[12] W Kim and J Labuz Resilient Modulus and Strength of BaseCourse with Recycled Bituminous Material Minnesota De-partment of Transportation Research Services Section MNUSA 2007

[13] D Bloomquist G Diamond M Oden B Ruth and M TiaEngineering and Environmental Aspects of Recycled Materialsfor Highway Construction Appendix 1 Final Report 1993

[14] A Hussain and Q Yanjun ldquoEvaluation of asphalt mixescontaining reclaimed asphalt pavement for wearing cour-sesrdquo in Proceedings of the International Conference onTraffic and Transportation Engineering School of CivilEngineering Southwest Jiaotong University ChengduChina 2012

[15] M Solaimanian and M Tahmoressi ldquoVariability analysis ofhot-mix asphalt concrete containing high percentage ofreclaimed asphalt pavementrdquo Transportation Research Re-cord Journal of the Transportation Research Board vol 1543no 1 pp 89ndash96 1996

[16] A Gabr and D A Cameron ldquoProperties of recycled concreteaggregate for unbound pavement constructionrdquo Journal ofMaterials in Civil Engineering vol 24 no 6 pp 754ndash7642011

[17] W-L Huang D-H Lin N-B Chang and K-S LinldquoRecycling of construction and demolition waste via a

mechanical sorting processrdquo Resources Conservation andRecycling vol 37 no 1 pp 23ndash37 2002

[18] A R Pasandın and I Perez ldquoOverview of bituminous mix-tures made with recycled concrete Aggregatesrdquo Constructionand Building Materials vol 74 pp 151ndash161 2015

[19] P Jitsangiam H Nikraz and K Siripun ldquoConstruction anddemolition (CampD) waste as a road base material for WesternAustralia roadsrdquo Australian Geomechanics vol 44 no 3pp 57ndash62 2009

[20] A Nataatmadja and Y L Tan ldquoResilient response of recycledconcrete road aggregatesrdquo Journal of Transportation Engi-neering vol 127 no 5 pp 450ndash453 2001

[21] C Leek and K Siripun ldquoSpecification and performance ofrecycled materials in road pavementsrdquo Contract Rep (01119-1)2010

[22] J Green and J Hall Nondistructive Vibratory Testing ofAirport Pavement 1975

[23] W Heukelom and A Klomp ldquoDynamic testing as a means ofcontrolling pavements during and after constructionrdquo inProceedings of the International Conference on the StructuralDesign of Asphalt Pavements University of Michigan AnnArbor MI USA 1962

[24] Ohio Department of Transportation Pavement DesignManual Ohio Department of Transportation Office ofPavement Engineering OH USA 2008

[25] W D Powell H C Mayhew and M M Nunn ldquoestructural design of bituminous roadsrdquo Laboratory Report1132 Transport and Road Research Laboratory CrowthorneUK 1984

[26] M W Witczak X Qi and M W Mirza ldquoUse of nonlinearsubgrade modulus in AASHTO design procedurerdquo Journal ofTransportation Engineering vol 121 no 3 1995

[27] AASHTO Guide for Design of Pavement Structures Wash-ington DC USA 1993

[28] Asphalt Institute Research and Development of 5e AsphaltInstitutersquos 5ickness Design Manual (MS-1) 9th edition 1982

[29] T Buu Correlation of Resistance R-value and ResilientModulus of Idaho Subgrade Soil Idaho Department ofTransportation Division of Highways ID USA 1980

[30] S Muench J Mahoney and L Pierce WSDOT PavementGuide Washington State Department of TransportationInternet Module Washington DC USA 2009

[31] S Yeh and C Su ldquoResilient properties of Colorado soilsrdquoReport No CDOH-DH-SM-89-9 Colorado Department ofHighways Denver CO USA 1989

[32] M R ompson and Q L Robnett ldquoResilient properties ofsubgrade soilsrdquo Transportation Engineering Journal of ASCEvol 105 pp 71ndash89 1979

[33] W Lee N C Bohra A G Altschaeffl and T D WhiteldquoResilient modulus of cohesive soilsrdquo Journal of Geotechnicaland Geoenvironmental Engineering vol 123 no 2 pp 131ndash136 1997

[34] R Carmichael III and E Stuart ldquoPredicting resilient modulusa study to determine the mechanical properties of subgradesoilsrdquo Transportation Research Record vol 1043 pp 145ndash1481986

[35] E C Drumm Y Boateng-Poku and T Johnson PierceldquoEstimation of subgrade resilient modulus from standardtestsrdquo Journal of Geotechnical Engineering vol 116 no 5pp 774ndash789 1990

[36] M J Farrar and J P Turner Resilient Modulus of WyomingSubgrade Soils 1991

14 Advances in Materials Science and Engineering

[37] M P Jones and M W Witczak ldquoSubgrade modulus on thesan diego test roadrdquo Transportation Research Record Journalof the Transportation Research Board vol 641 pp 1ndash6 1977

[38] A M Rahim and K P George ldquoSubgrade soil indexproperties to estimate resilient modulusrdquo in Proceedings ofthe 83th Annual Meeting of the Transportation ResearchBoard National Research Council Washington DC USA2004

[39] M R ompson and T G LaGrow A Proposed ConventionalFlexible Pavement 5ickness Design Procedure University ofIllinois Peoria IL USA 1988

[40] R Pezo ldquoA general method of reporting resilient modulustests of soils a pavement engineerrsquos point of viewrdquo in Pro-ceedings of the 72nd Annual Meeting of Transportation Re-search Board Washington DC USA 1993

[41] R G Hicks and C L Monismith ldquoResilient properties ofgranular materialrdquo Transportation Research Record vol 345pp 15ndash31 1971

[42] J Uzan ldquoCharacterization of granular materialsrdquo Trans-portation Research Record Journal of the Transportation Re-search Board vol 1022 pp 52ndash59 1985

[43] National Cooperative Highway Research Program ldquoGuide formechanistic-empirical design of new and rehabilitatedpavement structuresrdquo NCHRP 1-37A NCHRP WashingtonDC USA 2004

[44] N M Louay H T Hani and H Ananda ldquoEvaluation ofresilient modulus of subgrade soil by cone penetration testrdquoTransportation Research Record Journal of the TransportationResearch Board vol 1652 pp 236ndash245 1999

[45] S Dai and J Zollars ldquoResilient modulus of Minnesota roadresearch project subgrade soilrdquo Transportation Research Re-cord Journal of the Transportation Research Board vol 1786no 1 pp 20ndash28 2002

[46] L Mohammad B Huang A Puppala and A Allen ldquoRe-gression model for resilient modulus of subgrade soilsrdquoTransportation Research Record Journal of the TransportationResearch Board vol 1687 no 1 pp 47ndash54 1999

[47] B Santa ldquoResilient modulus of subgrade soils comparison oftwo constitutive equationsrdquo Transportation Research RecordJournal of the Transportation Research Board vol 1462pp 79ndash90 1994

[48] H Von Quintus and B Killingsworth Analyses Relating toPavement Material Characterizations and their Effects onPavement Performance 1998

[49] O Porter ldquoe preparation of subgradesrdquo in Proceedings ofthe Nineteenth Annual Meeting Highway Research BoardWashington DC USA December 1939

[50] O J Porter ldquoDevelopment of the original method for highwaydesignrdquo Transactions of the American Society of Civil Engi-neers vol 115 pp 461ndash467 1950

[51] D W Hight and M G H Stevens ldquoAn analysis of theCalifornia Bearing Ratio test in saturated claysrdquoGeotechnique vol 32 no 4 pp 315ndash322 1982

[52] P R Fleming and C D F Rogers ldquoAssessment of pavementfoundations during constructionrdquo Proceedings of the In-stitution of Civil Engineers-Transport vol 111 no 2pp 105ndash115 1995

[53] M R ompson R Marshall and Q L Robnett ldquoResilientproperties of subgrade soilsrdquo Final Report No FHWA-IL-UI-160 University of Illinois Urbana IL USA 1976

[54] B Sukumaran V Kyatham A Shah and D Sheth ldquoSuit-ability of using California bearing ratio test to predict resilientmodulusrdquo in Proceedings Federal Aviation Administration

Airport Technology Transfer Conference Atlantic City NJUSA 2002

[55] N W Lister and D Powell ldquoDesign practices for pavementsin the United Kingdomrdquo in Proceedings of the 6th In-ternational Conference on the Structural Design of AsphaltPavements Ann Arbor MI USA July 1987

[56] S Hossain G Dickerson and C Weaver Comparative Studyof VTM and AASHTO Test Method for CBR Co MaterialsDivision VDOT 2005

[57] N Garg A Larkin and H Brar ldquoA comparative subgradeevaluation using CBR vane shear light weight deflectometerand resilient modulus testsrdquo in Proceedings of the 8th In-ternational Conference on the Bearing Capacity of RoadsRailways and Airfields CRC Press Champaign IL USA2009

[58] M Ayres Development of a rational probabilistic approach forflexible pavement analysis University of Maryland CollegePark MD USA 1997

[59] AASHTO T 307 Determining the Resilient Modulus of Soilsand Aggregate Materials (2012) American Association ofState Highway and Transportation Officials Washington DCUSA 2004

[60] M Arshad and M F Ahmed ldquoPotential use of reclaimedasphalt pavement and recycled concrete aggregate in basesubbase layers of flexible pavementsrdquo Construction andBuilding Materials vol 151 pp 83ndash97 2017

[61] M Arshad ldquoCorrelation between resilient modulus (MR) andconstrained modulus (Mc) values of granular materialsrdquoConstruction and Building Materials vol 159 pp 440ndash4502018

[62] P Guo and J Emery ldquoImportance of strain level inevaluating resilient modulus of granular materialsrdquo In-ternational Journal of Pavement Engineering vol 12 no 2pp 187ndash199 2011

[63] E J McGarrah ldquoEvaluation of current practices of reclaimedasphalt pavementvirgin aggregate as base course materialrdquoNo WA-RD 7131 Federal Highway AdministrationWashington DC USA 2007

[64] T B Alam M Abdelrahman and S A Schram ldquoLaboratorycharacterisation of recycled asphalt pavement as a base layerrdquoInternational Journal of Pavement Engineering vol 11 no 2pp 123ndash131 2010

[65] T Bennert and A Maher ldquoe development of a performancespecification for granular base and subbase materialrdquo ReportNo FHWA-NJ-2005-003 Department of TransportationEwing Township NJ USA 2005

[66] T H Wonnacott H omas and J Ronald ldquoRegression asecond course in statisticsrdquo No 04 QA2782 W6Wiley NewYork NY USA 1981

[67] W Penny and S Roberts Neural network predictions witherror bars Dept of Electrical and Electronic EngineeringTechnology and Medicine Research Report TR-97-1 ImperialCollege of Science London UK 1997

[68] R Dybowski and S J Roberts ldquoConfidence intervals andprediction intervals for feed-forward neural networksrdquoClinical Applications of Artificial Neural Networks pp 298ndash326 2001

[69] J Hauke and T Kossowski ldquoComparison of values ofPearsonrsquos and Spearmanrsquos correlation coefficients on the samesets of datardquo Quaestiones Geographicae vol 30 no 2pp 87ndash93 2011

[70] K-z Yan H-b Xu and G-h Shen ldquoNovel approach toresilient modulus using routine subgrade soil propertiesrdquo

Advances in Materials Science and Engineering 15

International Journal of Geomechanics vol 14 no 6 article04014025 2013

[71] Y H Chan ldquoBiostatistics 104 correlational analysisrdquoSingapore Medical Journal vol 44 no 12 pp 614ndash6192003

[72] B M Damghani D Welch C OrsquoMalley and S Knights ldquoemisleading value of measured correlationrdquoWilmott vol 2012no 62 pp 64ndash73 2012

[73] L B Christensen B Johnson and L A Turner ldquoResearchmethods design and analysisrdquo 2011

[74] W J Dixon and F J Massey Introduction to StatisticalAnalysis McGraw-Hill New York NY USA 1969

[75] B Colbert and Z You ldquoe determination of mechanicalperformance of laboratory produced hot mix asphalt mixturesusing controlled RAP and virgin aggregate size fractionsrdquoConstruction and Building Materials vol 26 no 1 pp 655ndash662 2012

[76] D H Timm and D E Newcomb ldquoPerpetual pavement designfor flexible pavements in the USrdquo International Journal ofPavement Engineering vol 7 no 2 pp 111ndash119 2006

[77] Y H Huang Pavement Analysis and Design Prentice-HallEnglewood Cliffs NJ USA 2nd edition 1993

[78] L Walubita W Liu and T Scullion Texas perpetualpavements-Experience overview and the way forward Tech-nical Report No 0-4822-3 Texas Transportation InstituteTexas AampM University College Station TX USA 2010

[79] D Timm and D Newcomb ldquoCalibration of flexible pavementperformance equations for Minnesota road research projectrdquoTransportation Research Record Journal of the TransportationResearch Board no 1853 pp 134ndash142 2003

16 Advances in Materials Science and Engineering

CorrosionInternational Journal of

Hindawiwwwhindawicom Volume 2018

Advances in

Materials Science and EngineeringHindawiwwwhindawicom Volume 2018

Hindawiwwwhindawicom Volume 2018

Journal of

Chemistry

Analytical ChemistryInternational Journal of

Hindawiwwwhindawicom Volume 2018

ScienticaHindawiwwwhindawicom Volume 2018

Polymer ScienceInternational Journal of

Hindawiwwwhindawicom Volume 2018

Hindawiwwwhindawicom Volume 2018

Advances in Condensed Matter Physics

Hindawiwwwhindawicom Volume 2018

International Journal of

BiomaterialsHindawiwwwhindawicom

Journal ofEngineeringVolume 2018

Applied ChemistryJournal of

Hindawiwwwhindawicom Volume 2018

NanotechnologyHindawiwwwhindawicom Volume 2018

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Hindawiwwwhindawicom Volume 2018

High Energy PhysicsAdvances in

Hindawi Publishing Corporation httpwwwhindawicom Volume 2013Hindawiwwwhindawicom

The Scientific World Journal

Volume 2018

TribologyAdvances in

Hindawiwwwhindawicom Volume 2018

Hindawiwwwhindawicom Volume 2018

ChemistryAdvances in

Hindawiwwwhindawicom Volume 2018

Advances inPhysical Chemistry

Hindawiwwwhindawicom Volume 2018

BioMed Research InternationalMaterials

Journal of

Hindawiwwwhindawicom Volume 2018

Na

nom

ate

ria

ls

Hindawiwwwhindawicom Volume 2018

Journal ofNanomaterials

Submit your manuscripts atwwwhindawicom

samples under the same loading conditions whilevariations between MR values and the applied bulkstresses during the resilient modulus tests can beapproximated through power law having coecientof correlation (r) value in the range of 097ndash099

(2) yene CBR values of blended samples decrease withthe addition of RAP contents however a clear

decreasing trend in conjunction with an increasingpercentage of RAP contents could not be found

(3) yene new model for the estimation of MR values in-cludes the stress state through the experimentallydetermined CBR having a coecient of correlation ldquorrdquoequal to approximately 09 with fair distribution of thedata points (MR measured and MR estimated) about

Perc

enta

ge o

f are

a

70

75

80

85

90

95

100

100

A10

0 F

100

W10

0 R

CA75

A

+ 2

5 R

AP(

1)75

A

+ 2

5 R

AP(

2)75

A

+ 2

5 R

AP(

3)75

A

+ 2

5 R

AP(

4)75

F

+ 2

5 R

AP(

1)75

F

+ 2

5 R

AP(

2)75

F

+ 2

5 R

AP(

3)75

F

+ 2

5 R

AP(

4)75

W

+ 2

5 R

AP(

1)75

W

+ 2

5 R

AP(

2)75

W

+ 2

5 R

AP(

3)75

W

+ 2

5 R

AP(

4)75

R

CA +

25

RA

P(1)

75

RCA

+ 2

5 R

AP(

2)75

R

CA +

25

RA

P(3)

75

RCA

+ 2

5 R

AP(

4)50

A

+ 5

0 R

AP(

1)50

A

+ 5

0 R

AP(

2)50

A

+ 5

0 R

AP(

3)50

A

+ 5

0 R

AP(

4)50

F

+ 5

0 R

AP(

1)50

F

+ 5

0 R

AP(

2)50

F

+ 5

0 R

AP(

3)50

F

+ 5

0 R

AP(

4)50

W

+ 5

0 R

AP(

1)50

W

+ 5

0 R

AP(

2)50

W

+ 5

0 R

AP(

3)50

W

+ 5

0 R

AP(

4)50

R

CA +

50

RA

P(1)

50

RCA

+ 5

0 R

AP(

2)50

R

CA +

50

RA

P(3)

50

RCA

+ 5

0 R

AP(

4)25

A

+ 7

5 R

AP(

1)25

A

+ 7

5 R

AP(

2)25

A

+ 7

5 R

AP(

3)25

A

+ 7

5 R

AP(

4)25

F

+ 7

5 R

AP(

1)25

F

+ 7

5 R

AP(

2)25

F

+ 7

5 R

AP(

3)25

F

+ 7

5 R

AP(

4)25

W

+ 7

5 R

AP(

1)25

W

+ 7

5 R

AP(

2)25

W

+ 7

5 R

AP(

3)25

W

+ 7

5 R

AP(

4)25

R

CA +

75

RA

P(1)

25

RCA

+ 7

5 R

AP(

2)25

R

CA +

75

RA

P(3)

25

RCA

+ 7

5 R

AP(

4)

Percentage of area within the critical limit of horizontal strain at the bottom of HMAPercentage of area within the critical limit of vertical strain at the top of subgrade

Figure 10 Percentage of area within the critical limits for horizontal strain at the bottom of HMA and vertical strain at the top of subgrade

30

35

40

45

50

55

60

65

70

100

A10

0 F

100

W10

0 R

CA75

A

+ 2

5 R

AP(

1)75

A

+ 2

5 R

AP(

2)75

A

+ 2

5 R

AP(

3)75

A

+ 2

5 R

AP(

4)75

F

+ 2

5 R

AP(

1)75

F

+ 2

5 R

AP(

2)75

F

+ 2

5 R

AP(

3)75

F

+ 2

5 R

AP(

4)75

W

+ 2

5 R

AP(

1)75

W

+ 2

5 R

AP(

2)75

W

+ 2

5 R

AP(

3)75

W

+ 2

5 R

AP(

4)75

R

CA +

25

RA

P(1)

75

RCA

+ 2

5 R

AP(

2)75

R

CA +

25

RA

P(3)

75

RCA

+ 2

5 R

AP(

4)50

A

+ 5

0 R

AP(

1)50

A

+ 5

0 R

AP(

2)50

A

+ 5

0 R

AP(

3)50

A

+ 5

0 R

AP(

4)50

F

+ 5

0 R

AP(

1)50

F

+ 5

0 R

AP(

2)50

F

+ 5

0 R

AP(

3)50

F

+ 5

0 R

AP(

4)50

W

+ 5

0 R

AP(

1)50

W

+ 5

0 R

AP(

2)50

W

+ 5

0 R

AP(

3)50

W

+ 5

0 R

AP(

4)50

R

CA +

50

RA

P(1)

50

RCA

+ 5

0 R

AP(

2)50

R

CA +

50

RA

P(3)

50

RCA

+ 5

0 R

AP(

4)25

A

+ 7

5 R

AP(

1)25

A

+ 7

5 R

AP(

2)25

A

+ 7

5 R

AP(

3)25

A

+ 7

5 R

AP(

4)25

F

+ 7

5 R

AP(

1)25

F

+ 7

5 R

AP(

2)25

F

+ 7

5 R

AP(

3)25

F

+ 7

5 R

AP(

4)25

W

+ 7

5 R

AP(

1)25

W

+ 7

5 R

AP(

2)25

W

+ 7

5 R

AP(

3)25

W

+ 7

5 R

AP(

4)25

R

CA +

75

RA

P(1)

25

RCA

+ 7

5 R

AP(

2)25

R

CA +

75

RA

P(3)

25

RCA

+ 7

5 R

AP(

4)

Year

s

Number of years required to reach CDF = 01 in terms of horizontal strain at the bottom of HMANumber of years required to reach CDF = 01 in terms of vertical strain at the top of subgrade

Figure 11 Number of years required to reach CDF 01 in terms of horizontal strain at the bottom of HMA and vertical strain at the top ofsubgrade

12 Advances in Materials Science and Engineering

the unity line indicating that the proposed regressionmodel has a moderate to strong correlation

(4) Statistical analysis of simulation results based onPerRoad and KenPave software demonstrates thatthe addition of RAP contents in the subbase layer ofthe copyexible pavement signicantly improves itsperformance against rutting and fatigue

(5) Residual strain during the long-term repeated loadtriaxial test was found to increase in line with anincrease in the ratio of ldquocyclic deviator stress to theconning stress (σdσc)rdquo in correlation to an increasein the percentage of RAP contents in the blendedsample

(6) From the authorrsquos perspective the addition of RAPcontents beyond a certain limit (sim50) may prove tobe detrimental for the overall performance of copyexiblepavement structure

Data Availability

yene experimental data used to support the ndings of thisstudy are included within the article in the form of graphsand tables

Conflicts of Interest

yene author declares that there are no concopyicts of interestregarding the publication of this paper

References

[1] R B Mallick and A Veeraragavan ldquoSustainable pavements inIndia-the time to start is nowrdquo New Building Materials andConstruction World (NBMampCW) Magazine vol 16 no 3pp 128ndash140 2010

[2] A Mohammadinia A Arulrajah S Horpibulsuk andA Chinkulkijniwat ldquoEect of copyy ash on properties of crushedbrick and reclaimed asphalt in pavement basesubbase

000

050

100

150

200

250

300

350

400

450

500

0 2000 4000 6000 8000 10000 12000 14000 16000 18000 20000

Axi

al st

rain

()

Number of load cycles

100 W50 W + 50 RAP(1)25 W + 75 RAP(1)100 F50 F + 50 RAP(2)25 F + 75 RAP(2)

σc = 1379kPa σd = 372kPa

Figure 12 Eect of RAP contents on residual strain under long-term repeated loading

000

005

010

015

020

025

0 1000 2000 3000 4000 5000 6000

Axi

al st

rain

()

Number of load cycles

091827

odoc

Figure 13 Eect of ratio of ldquocyclic deviator stress to the conningstress (σdσc)rdquo on the residual strain under long-term repeatedloading

Advances in Materials Science and Engineering 13

applicationsrdquo Journal of Hazardous Materials vol 321pp 547ndash556 2017

[3] L R Hoyos A J Puppala and C A Ordonez ldquoCharacter-ization of cement-fiber-treated reclaimed asphalt pavementaggregates preliminary investigationrdquo Journal of Materials inCivil Engineering vol 23 no 7 pp 977ndash989 2011

[4] R Taha A Al-Harthy K Al-Shamsi and M Al-ZubeidildquoCement stabilization of reclaimed asphalt pavement aggre-gate for road bases and subbasesrdquo Journal of Materials in CivilEngineering vol 14 no 3 pp 239ndash245 2002

[5] A M Azam and D A Cameron ldquoGeotechnical properties ofblends of recycled clay masonry and recycled concrete ag-gregates in unbound pavement constructionrdquo Journal ofMaterials in Civil Engineering vol 25 no 6 pp 788ndash7982013

[6] A Gabor and D Cameron ldquoProperties of recycled concreteaggregate for unbound pavement constructionrdquo Journal ofMaterials in Civil Engineering vol 24 no 6 pp 754ndash7642012

[7] C S Poon and D Chan ldquoFeasible use of recycled concreteaggregates and crushed clay brick as unbound road sub-baserdquoConstruction and Building Materials vol 20 no 8 pp 578ndash585 2006

[8] A Arulrajah M M Y Ali M M Disfani J Piratheepan andM W Bo ldquoGeotechnical performance of recycled glass-wasterock blends in footpath basesrdquo Journal of Materials in CivilEngineering vol 25 no 5 pp 653ndash661 2013

[9] L T Lee Jr ldquoRecycled glass and dredged materialsrdquo ReportNo ERDC TNDOER-T8 US Army Corps of EngineersEngineer Research and Development Center Mississippi MSUSA 2007

[10] M Ali A Arulrajah M Disfani and J Piratheepan ldquoSuit-ability of using recycled glassmdashcrushed rock blends forpavement subbase applicationsrdquo in Proceedings of the Geo-Frontiers 2011 Conference on Geotechnical Foundation Designpp 1325ndash1334 ASCE Reston VA USA 2011

[11] J Wartman D G Grubb and A S M Nasim ldquoSelectengineering characteristics of crushed glassrdquo Journal ofMaterials in Civil Engineering vol 16 no 6 pp 526ndash5392004

[12] W Kim and J Labuz Resilient Modulus and Strength of BaseCourse with Recycled Bituminous Material Minnesota De-partment of Transportation Research Services Section MNUSA 2007

[13] D Bloomquist G Diamond M Oden B Ruth and M TiaEngineering and Environmental Aspects of Recycled Materialsfor Highway Construction Appendix 1 Final Report 1993

[14] A Hussain and Q Yanjun ldquoEvaluation of asphalt mixescontaining reclaimed asphalt pavement for wearing cour-sesrdquo in Proceedings of the International Conference onTraffic and Transportation Engineering School of CivilEngineering Southwest Jiaotong University ChengduChina 2012

[15] M Solaimanian and M Tahmoressi ldquoVariability analysis ofhot-mix asphalt concrete containing high percentage ofreclaimed asphalt pavementrdquo Transportation Research Re-cord Journal of the Transportation Research Board vol 1543no 1 pp 89ndash96 1996

[16] A Gabr and D A Cameron ldquoProperties of recycled concreteaggregate for unbound pavement constructionrdquo Journal ofMaterials in Civil Engineering vol 24 no 6 pp 754ndash7642011

[17] W-L Huang D-H Lin N-B Chang and K-S LinldquoRecycling of construction and demolition waste via a

mechanical sorting processrdquo Resources Conservation andRecycling vol 37 no 1 pp 23ndash37 2002

[18] A R Pasandın and I Perez ldquoOverview of bituminous mix-tures made with recycled concrete Aggregatesrdquo Constructionand Building Materials vol 74 pp 151ndash161 2015

[19] P Jitsangiam H Nikraz and K Siripun ldquoConstruction anddemolition (CampD) waste as a road base material for WesternAustralia roadsrdquo Australian Geomechanics vol 44 no 3pp 57ndash62 2009

[20] A Nataatmadja and Y L Tan ldquoResilient response of recycledconcrete road aggregatesrdquo Journal of Transportation Engi-neering vol 127 no 5 pp 450ndash453 2001

[21] C Leek and K Siripun ldquoSpecification and performance ofrecycled materials in road pavementsrdquo Contract Rep (01119-1)2010

[22] J Green and J Hall Nondistructive Vibratory Testing ofAirport Pavement 1975

[23] W Heukelom and A Klomp ldquoDynamic testing as a means ofcontrolling pavements during and after constructionrdquo inProceedings of the International Conference on the StructuralDesign of Asphalt Pavements University of Michigan AnnArbor MI USA 1962

[24] Ohio Department of Transportation Pavement DesignManual Ohio Department of Transportation Office ofPavement Engineering OH USA 2008

[25] W D Powell H C Mayhew and M M Nunn ldquoestructural design of bituminous roadsrdquo Laboratory Report1132 Transport and Road Research Laboratory CrowthorneUK 1984

[26] M W Witczak X Qi and M W Mirza ldquoUse of nonlinearsubgrade modulus in AASHTO design procedurerdquo Journal ofTransportation Engineering vol 121 no 3 1995

[27] AASHTO Guide for Design of Pavement Structures Wash-ington DC USA 1993

[28] Asphalt Institute Research and Development of 5e AsphaltInstitutersquos 5ickness Design Manual (MS-1) 9th edition 1982

[29] T Buu Correlation of Resistance R-value and ResilientModulus of Idaho Subgrade Soil Idaho Department ofTransportation Division of Highways ID USA 1980

[30] S Muench J Mahoney and L Pierce WSDOT PavementGuide Washington State Department of TransportationInternet Module Washington DC USA 2009

[31] S Yeh and C Su ldquoResilient properties of Colorado soilsrdquoReport No CDOH-DH-SM-89-9 Colorado Department ofHighways Denver CO USA 1989

[32] M R ompson and Q L Robnett ldquoResilient properties ofsubgrade soilsrdquo Transportation Engineering Journal of ASCEvol 105 pp 71ndash89 1979

[33] W Lee N C Bohra A G Altschaeffl and T D WhiteldquoResilient modulus of cohesive soilsrdquo Journal of Geotechnicaland Geoenvironmental Engineering vol 123 no 2 pp 131ndash136 1997

[34] R Carmichael III and E Stuart ldquoPredicting resilient modulusa study to determine the mechanical properties of subgradesoilsrdquo Transportation Research Record vol 1043 pp 145ndash1481986

[35] E C Drumm Y Boateng-Poku and T Johnson PierceldquoEstimation of subgrade resilient modulus from standardtestsrdquo Journal of Geotechnical Engineering vol 116 no 5pp 774ndash789 1990

[36] M J Farrar and J P Turner Resilient Modulus of WyomingSubgrade Soils 1991

14 Advances in Materials Science and Engineering

[37] M P Jones and M W Witczak ldquoSubgrade modulus on thesan diego test roadrdquo Transportation Research Record Journalof the Transportation Research Board vol 641 pp 1ndash6 1977

[38] A M Rahim and K P George ldquoSubgrade soil indexproperties to estimate resilient modulusrdquo in Proceedings ofthe 83th Annual Meeting of the Transportation ResearchBoard National Research Council Washington DC USA2004

[39] M R ompson and T G LaGrow A Proposed ConventionalFlexible Pavement 5ickness Design Procedure University ofIllinois Peoria IL USA 1988

[40] R Pezo ldquoA general method of reporting resilient modulustests of soils a pavement engineerrsquos point of viewrdquo in Pro-ceedings of the 72nd Annual Meeting of Transportation Re-search Board Washington DC USA 1993

[41] R G Hicks and C L Monismith ldquoResilient properties ofgranular materialrdquo Transportation Research Record vol 345pp 15ndash31 1971

[42] J Uzan ldquoCharacterization of granular materialsrdquo Trans-portation Research Record Journal of the Transportation Re-search Board vol 1022 pp 52ndash59 1985

[43] National Cooperative Highway Research Program ldquoGuide formechanistic-empirical design of new and rehabilitatedpavement structuresrdquo NCHRP 1-37A NCHRP WashingtonDC USA 2004

[44] N M Louay H T Hani and H Ananda ldquoEvaluation ofresilient modulus of subgrade soil by cone penetration testrdquoTransportation Research Record Journal of the TransportationResearch Board vol 1652 pp 236ndash245 1999

[45] S Dai and J Zollars ldquoResilient modulus of Minnesota roadresearch project subgrade soilrdquo Transportation Research Re-cord Journal of the Transportation Research Board vol 1786no 1 pp 20ndash28 2002

[46] L Mohammad B Huang A Puppala and A Allen ldquoRe-gression model for resilient modulus of subgrade soilsrdquoTransportation Research Record Journal of the TransportationResearch Board vol 1687 no 1 pp 47ndash54 1999

[47] B Santa ldquoResilient modulus of subgrade soils comparison oftwo constitutive equationsrdquo Transportation Research RecordJournal of the Transportation Research Board vol 1462pp 79ndash90 1994

[48] H Von Quintus and B Killingsworth Analyses Relating toPavement Material Characterizations and their Effects onPavement Performance 1998

[49] O Porter ldquoe preparation of subgradesrdquo in Proceedings ofthe Nineteenth Annual Meeting Highway Research BoardWashington DC USA December 1939

[50] O J Porter ldquoDevelopment of the original method for highwaydesignrdquo Transactions of the American Society of Civil Engi-neers vol 115 pp 461ndash467 1950

[51] D W Hight and M G H Stevens ldquoAn analysis of theCalifornia Bearing Ratio test in saturated claysrdquoGeotechnique vol 32 no 4 pp 315ndash322 1982

[52] P R Fleming and C D F Rogers ldquoAssessment of pavementfoundations during constructionrdquo Proceedings of the In-stitution of Civil Engineers-Transport vol 111 no 2pp 105ndash115 1995

[53] M R ompson R Marshall and Q L Robnett ldquoResilientproperties of subgrade soilsrdquo Final Report No FHWA-IL-UI-160 University of Illinois Urbana IL USA 1976

[54] B Sukumaran V Kyatham A Shah and D Sheth ldquoSuit-ability of using California bearing ratio test to predict resilientmodulusrdquo in Proceedings Federal Aviation Administration

Airport Technology Transfer Conference Atlantic City NJUSA 2002

[55] N W Lister and D Powell ldquoDesign practices for pavementsin the United Kingdomrdquo in Proceedings of the 6th In-ternational Conference on the Structural Design of AsphaltPavements Ann Arbor MI USA July 1987

[56] S Hossain G Dickerson and C Weaver Comparative Studyof VTM and AASHTO Test Method for CBR Co MaterialsDivision VDOT 2005

[57] N Garg A Larkin and H Brar ldquoA comparative subgradeevaluation using CBR vane shear light weight deflectometerand resilient modulus testsrdquo in Proceedings of the 8th In-ternational Conference on the Bearing Capacity of RoadsRailways and Airfields CRC Press Champaign IL USA2009

[58] M Ayres Development of a rational probabilistic approach forflexible pavement analysis University of Maryland CollegePark MD USA 1997

[59] AASHTO T 307 Determining the Resilient Modulus of Soilsand Aggregate Materials (2012) American Association ofState Highway and Transportation Officials Washington DCUSA 2004

[60] M Arshad and M F Ahmed ldquoPotential use of reclaimedasphalt pavement and recycled concrete aggregate in basesubbase layers of flexible pavementsrdquo Construction andBuilding Materials vol 151 pp 83ndash97 2017

[61] M Arshad ldquoCorrelation between resilient modulus (MR) andconstrained modulus (Mc) values of granular materialsrdquoConstruction and Building Materials vol 159 pp 440ndash4502018

[62] P Guo and J Emery ldquoImportance of strain level inevaluating resilient modulus of granular materialsrdquo In-ternational Journal of Pavement Engineering vol 12 no 2pp 187ndash199 2011

[63] E J McGarrah ldquoEvaluation of current practices of reclaimedasphalt pavementvirgin aggregate as base course materialrdquoNo WA-RD 7131 Federal Highway AdministrationWashington DC USA 2007

[64] T B Alam M Abdelrahman and S A Schram ldquoLaboratorycharacterisation of recycled asphalt pavement as a base layerrdquoInternational Journal of Pavement Engineering vol 11 no 2pp 123ndash131 2010

[65] T Bennert and A Maher ldquoe development of a performancespecification for granular base and subbase materialrdquo ReportNo FHWA-NJ-2005-003 Department of TransportationEwing Township NJ USA 2005

[66] T H Wonnacott H omas and J Ronald ldquoRegression asecond course in statisticsrdquo No 04 QA2782 W6Wiley NewYork NY USA 1981

[67] W Penny and S Roberts Neural network predictions witherror bars Dept of Electrical and Electronic EngineeringTechnology and Medicine Research Report TR-97-1 ImperialCollege of Science London UK 1997

[68] R Dybowski and S J Roberts ldquoConfidence intervals andprediction intervals for feed-forward neural networksrdquoClinical Applications of Artificial Neural Networks pp 298ndash326 2001

[69] J Hauke and T Kossowski ldquoComparison of values ofPearsonrsquos and Spearmanrsquos correlation coefficients on the samesets of datardquo Quaestiones Geographicae vol 30 no 2pp 87ndash93 2011

[70] K-z Yan H-b Xu and G-h Shen ldquoNovel approach toresilient modulus using routine subgrade soil propertiesrdquo

Advances in Materials Science and Engineering 15

International Journal of Geomechanics vol 14 no 6 article04014025 2013

[71] Y H Chan ldquoBiostatistics 104 correlational analysisrdquoSingapore Medical Journal vol 44 no 12 pp 614ndash6192003

[72] B M Damghani D Welch C OrsquoMalley and S Knights ldquoemisleading value of measured correlationrdquoWilmott vol 2012no 62 pp 64ndash73 2012

[73] L B Christensen B Johnson and L A Turner ldquoResearchmethods design and analysisrdquo 2011

[74] W J Dixon and F J Massey Introduction to StatisticalAnalysis McGraw-Hill New York NY USA 1969

[75] B Colbert and Z You ldquoe determination of mechanicalperformance of laboratory produced hot mix asphalt mixturesusing controlled RAP and virgin aggregate size fractionsrdquoConstruction and Building Materials vol 26 no 1 pp 655ndash662 2012

[76] D H Timm and D E Newcomb ldquoPerpetual pavement designfor flexible pavements in the USrdquo International Journal ofPavement Engineering vol 7 no 2 pp 111ndash119 2006

[77] Y H Huang Pavement Analysis and Design Prentice-HallEnglewood Cliffs NJ USA 2nd edition 1993

[78] L Walubita W Liu and T Scullion Texas perpetualpavements-Experience overview and the way forward Tech-nical Report No 0-4822-3 Texas Transportation InstituteTexas AampM University College Station TX USA 2010

[79] D Timm and D Newcomb ldquoCalibration of flexible pavementperformance equations for Minnesota road research projectrdquoTransportation Research Record Journal of the TransportationResearch Board no 1853 pp 134ndash142 2003

16 Advances in Materials Science and Engineering

CorrosionInternational Journal of

Hindawiwwwhindawicom Volume 2018

Advances in

Materials Science and EngineeringHindawiwwwhindawicom Volume 2018

Hindawiwwwhindawicom Volume 2018

Journal of

Chemistry

Analytical ChemistryInternational Journal of

Hindawiwwwhindawicom Volume 2018

ScienticaHindawiwwwhindawicom Volume 2018

Polymer ScienceInternational Journal of

Hindawiwwwhindawicom Volume 2018

Hindawiwwwhindawicom Volume 2018

Advances in Condensed Matter Physics

Hindawiwwwhindawicom Volume 2018

International Journal of

BiomaterialsHindawiwwwhindawicom

Journal ofEngineeringVolume 2018

Applied ChemistryJournal of

Hindawiwwwhindawicom Volume 2018

NanotechnologyHindawiwwwhindawicom Volume 2018

Journal of

Hindawiwwwhindawicom Volume 2018

High Energy PhysicsAdvances in

Hindawi Publishing Corporation httpwwwhindawicom Volume 2013Hindawiwwwhindawicom

The Scientific World Journal

Volume 2018

TribologyAdvances in

Hindawiwwwhindawicom Volume 2018

Hindawiwwwhindawicom Volume 2018

ChemistryAdvances in

Hindawiwwwhindawicom Volume 2018

Advances inPhysical Chemistry

Hindawiwwwhindawicom Volume 2018

BioMed Research InternationalMaterials

Journal of

Hindawiwwwhindawicom Volume 2018

Na

nom

ate

ria

ls

Hindawiwwwhindawicom Volume 2018

Journal ofNanomaterials

Submit your manuscripts atwwwhindawicom

the unity line indicating that the proposed regressionmodel has a moderate to strong correlation

(4) Statistical analysis of simulation results based onPerRoad and KenPave software demonstrates thatthe addition of RAP contents in the subbase layer ofthe copyexible pavement signicantly improves itsperformance against rutting and fatigue

(5) Residual strain during the long-term repeated loadtriaxial test was found to increase in line with anincrease in the ratio of ldquocyclic deviator stress to theconning stress (σdσc)rdquo in correlation to an increasein the percentage of RAP contents in the blendedsample

(6) From the authorrsquos perspective the addition of RAPcontents beyond a certain limit (sim50) may prove tobe detrimental for the overall performance of copyexiblepavement structure

Data Availability

yene experimental data used to support the ndings of thisstudy are included within the article in the form of graphsand tables

Conflicts of Interest

yene author declares that there are no concopyicts of interestregarding the publication of this paper

References

[1] R B Mallick and A Veeraragavan ldquoSustainable pavements inIndia-the time to start is nowrdquo New Building Materials andConstruction World (NBMampCW) Magazine vol 16 no 3pp 128ndash140 2010

[2] A Mohammadinia A Arulrajah S Horpibulsuk andA Chinkulkijniwat ldquoEect of copyy ash on properties of crushedbrick and reclaimed asphalt in pavement basesubbase

000

050

100

150

200

250

300

350

400

450

500

0 2000 4000 6000 8000 10000 12000 14000 16000 18000 20000

Axi

al st

rain

()

Number of load cycles

100 W50 W + 50 RAP(1)25 W + 75 RAP(1)100 F50 F + 50 RAP(2)25 F + 75 RAP(2)

σc = 1379kPa σd = 372kPa

Figure 12 Eect of RAP contents on residual strain under long-term repeated loading

000

005

010

015

020

025

0 1000 2000 3000 4000 5000 6000

Axi

al st

rain

()

Number of load cycles

091827

odoc

Figure 13 Eect of ratio of ldquocyclic deviator stress to the conningstress (σdσc)rdquo on the residual strain under long-term repeatedloading

Advances in Materials Science and Engineering 13

applicationsrdquo Journal of Hazardous Materials vol 321pp 547ndash556 2017

[3] L R Hoyos A J Puppala and C A Ordonez ldquoCharacter-ization of cement-fiber-treated reclaimed asphalt pavementaggregates preliminary investigationrdquo Journal of Materials inCivil Engineering vol 23 no 7 pp 977ndash989 2011

[4] R Taha A Al-Harthy K Al-Shamsi and M Al-ZubeidildquoCement stabilization of reclaimed asphalt pavement aggre-gate for road bases and subbasesrdquo Journal of Materials in CivilEngineering vol 14 no 3 pp 239ndash245 2002

[5] A M Azam and D A Cameron ldquoGeotechnical properties ofblends of recycled clay masonry and recycled concrete ag-gregates in unbound pavement constructionrdquo Journal ofMaterials in Civil Engineering vol 25 no 6 pp 788ndash7982013

[6] A Gabor and D Cameron ldquoProperties of recycled concreteaggregate for unbound pavement constructionrdquo Journal ofMaterials in Civil Engineering vol 24 no 6 pp 754ndash7642012

[7] C S Poon and D Chan ldquoFeasible use of recycled concreteaggregates and crushed clay brick as unbound road sub-baserdquoConstruction and Building Materials vol 20 no 8 pp 578ndash585 2006

[8] A Arulrajah M M Y Ali M M Disfani J Piratheepan andM W Bo ldquoGeotechnical performance of recycled glass-wasterock blends in footpath basesrdquo Journal of Materials in CivilEngineering vol 25 no 5 pp 653ndash661 2013

[9] L T Lee Jr ldquoRecycled glass and dredged materialsrdquo ReportNo ERDC TNDOER-T8 US Army Corps of EngineersEngineer Research and Development Center Mississippi MSUSA 2007

[10] M Ali A Arulrajah M Disfani and J Piratheepan ldquoSuit-ability of using recycled glassmdashcrushed rock blends forpavement subbase applicationsrdquo in Proceedings of the Geo-Frontiers 2011 Conference on Geotechnical Foundation Designpp 1325ndash1334 ASCE Reston VA USA 2011

[11] J Wartman D G Grubb and A S M Nasim ldquoSelectengineering characteristics of crushed glassrdquo Journal ofMaterials in Civil Engineering vol 16 no 6 pp 526ndash5392004

[12] W Kim and J Labuz Resilient Modulus and Strength of BaseCourse with Recycled Bituminous Material Minnesota De-partment of Transportation Research Services Section MNUSA 2007

[13] D Bloomquist G Diamond M Oden B Ruth and M TiaEngineering and Environmental Aspects of Recycled Materialsfor Highway Construction Appendix 1 Final Report 1993

[14] A Hussain and Q Yanjun ldquoEvaluation of asphalt mixescontaining reclaimed asphalt pavement for wearing cour-sesrdquo in Proceedings of the International Conference onTraffic and Transportation Engineering School of CivilEngineering Southwest Jiaotong University ChengduChina 2012

[15] M Solaimanian and M Tahmoressi ldquoVariability analysis ofhot-mix asphalt concrete containing high percentage ofreclaimed asphalt pavementrdquo Transportation Research Re-cord Journal of the Transportation Research Board vol 1543no 1 pp 89ndash96 1996

[16] A Gabr and D A Cameron ldquoProperties of recycled concreteaggregate for unbound pavement constructionrdquo Journal ofMaterials in Civil Engineering vol 24 no 6 pp 754ndash7642011

[17] W-L Huang D-H Lin N-B Chang and K-S LinldquoRecycling of construction and demolition waste via a

mechanical sorting processrdquo Resources Conservation andRecycling vol 37 no 1 pp 23ndash37 2002

[18] A R Pasandın and I Perez ldquoOverview of bituminous mix-tures made with recycled concrete Aggregatesrdquo Constructionand Building Materials vol 74 pp 151ndash161 2015

[19] P Jitsangiam H Nikraz and K Siripun ldquoConstruction anddemolition (CampD) waste as a road base material for WesternAustralia roadsrdquo Australian Geomechanics vol 44 no 3pp 57ndash62 2009

[20] A Nataatmadja and Y L Tan ldquoResilient response of recycledconcrete road aggregatesrdquo Journal of Transportation Engi-neering vol 127 no 5 pp 450ndash453 2001

[21] C Leek and K Siripun ldquoSpecification and performance ofrecycled materials in road pavementsrdquo Contract Rep (01119-1)2010

[22] J Green and J Hall Nondistructive Vibratory Testing ofAirport Pavement 1975

[23] W Heukelom and A Klomp ldquoDynamic testing as a means ofcontrolling pavements during and after constructionrdquo inProceedings of the International Conference on the StructuralDesign of Asphalt Pavements University of Michigan AnnArbor MI USA 1962

[24] Ohio Department of Transportation Pavement DesignManual Ohio Department of Transportation Office ofPavement Engineering OH USA 2008

[25] W D Powell H C Mayhew and M M Nunn ldquoestructural design of bituminous roadsrdquo Laboratory Report1132 Transport and Road Research Laboratory CrowthorneUK 1984

[26] M W Witczak X Qi and M W Mirza ldquoUse of nonlinearsubgrade modulus in AASHTO design procedurerdquo Journal ofTransportation Engineering vol 121 no 3 1995

[27] AASHTO Guide for Design of Pavement Structures Wash-ington DC USA 1993

[28] Asphalt Institute Research and Development of 5e AsphaltInstitutersquos 5ickness Design Manual (MS-1) 9th edition 1982

[29] T Buu Correlation of Resistance R-value and ResilientModulus of Idaho Subgrade Soil Idaho Department ofTransportation Division of Highways ID USA 1980

[30] S Muench J Mahoney and L Pierce WSDOT PavementGuide Washington State Department of TransportationInternet Module Washington DC USA 2009

[31] S Yeh and C Su ldquoResilient properties of Colorado soilsrdquoReport No CDOH-DH-SM-89-9 Colorado Department ofHighways Denver CO USA 1989

[32] M R ompson and Q L Robnett ldquoResilient properties ofsubgrade soilsrdquo Transportation Engineering Journal of ASCEvol 105 pp 71ndash89 1979

[33] W Lee N C Bohra A G Altschaeffl and T D WhiteldquoResilient modulus of cohesive soilsrdquo Journal of Geotechnicaland Geoenvironmental Engineering vol 123 no 2 pp 131ndash136 1997

[34] R Carmichael III and E Stuart ldquoPredicting resilient modulusa study to determine the mechanical properties of subgradesoilsrdquo Transportation Research Record vol 1043 pp 145ndash1481986

[35] E C Drumm Y Boateng-Poku and T Johnson PierceldquoEstimation of subgrade resilient modulus from standardtestsrdquo Journal of Geotechnical Engineering vol 116 no 5pp 774ndash789 1990

[36] M J Farrar and J P Turner Resilient Modulus of WyomingSubgrade Soils 1991

14 Advances in Materials Science and Engineering

[37] M P Jones and M W Witczak ldquoSubgrade modulus on thesan diego test roadrdquo Transportation Research Record Journalof the Transportation Research Board vol 641 pp 1ndash6 1977

[38] A M Rahim and K P George ldquoSubgrade soil indexproperties to estimate resilient modulusrdquo in Proceedings ofthe 83th Annual Meeting of the Transportation ResearchBoard National Research Council Washington DC USA2004

[39] M R ompson and T G LaGrow A Proposed ConventionalFlexible Pavement 5ickness Design Procedure University ofIllinois Peoria IL USA 1988

[40] R Pezo ldquoA general method of reporting resilient modulustests of soils a pavement engineerrsquos point of viewrdquo in Pro-ceedings of the 72nd Annual Meeting of Transportation Re-search Board Washington DC USA 1993

[41] R G Hicks and C L Monismith ldquoResilient properties ofgranular materialrdquo Transportation Research Record vol 345pp 15ndash31 1971

[42] J Uzan ldquoCharacterization of granular materialsrdquo Trans-portation Research Record Journal of the Transportation Re-search Board vol 1022 pp 52ndash59 1985

[43] National Cooperative Highway Research Program ldquoGuide formechanistic-empirical design of new and rehabilitatedpavement structuresrdquo NCHRP 1-37A NCHRP WashingtonDC USA 2004

[44] N M Louay H T Hani and H Ananda ldquoEvaluation ofresilient modulus of subgrade soil by cone penetration testrdquoTransportation Research Record Journal of the TransportationResearch Board vol 1652 pp 236ndash245 1999

[45] S Dai and J Zollars ldquoResilient modulus of Minnesota roadresearch project subgrade soilrdquo Transportation Research Re-cord Journal of the Transportation Research Board vol 1786no 1 pp 20ndash28 2002

[46] L Mohammad B Huang A Puppala and A Allen ldquoRe-gression model for resilient modulus of subgrade soilsrdquoTransportation Research Record Journal of the TransportationResearch Board vol 1687 no 1 pp 47ndash54 1999

[47] B Santa ldquoResilient modulus of subgrade soils comparison oftwo constitutive equationsrdquo Transportation Research RecordJournal of the Transportation Research Board vol 1462pp 79ndash90 1994

[48] H Von Quintus and B Killingsworth Analyses Relating toPavement Material Characterizations and their Effects onPavement Performance 1998

[49] O Porter ldquoe preparation of subgradesrdquo in Proceedings ofthe Nineteenth Annual Meeting Highway Research BoardWashington DC USA December 1939

[50] O J Porter ldquoDevelopment of the original method for highwaydesignrdquo Transactions of the American Society of Civil Engi-neers vol 115 pp 461ndash467 1950

[51] D W Hight and M G H Stevens ldquoAn analysis of theCalifornia Bearing Ratio test in saturated claysrdquoGeotechnique vol 32 no 4 pp 315ndash322 1982

[52] P R Fleming and C D F Rogers ldquoAssessment of pavementfoundations during constructionrdquo Proceedings of the In-stitution of Civil Engineers-Transport vol 111 no 2pp 105ndash115 1995

[53] M R ompson R Marshall and Q L Robnett ldquoResilientproperties of subgrade soilsrdquo Final Report No FHWA-IL-UI-160 University of Illinois Urbana IL USA 1976

[54] B Sukumaran V Kyatham A Shah and D Sheth ldquoSuit-ability of using California bearing ratio test to predict resilientmodulusrdquo in Proceedings Federal Aviation Administration

Airport Technology Transfer Conference Atlantic City NJUSA 2002

[55] N W Lister and D Powell ldquoDesign practices for pavementsin the United Kingdomrdquo in Proceedings of the 6th In-ternational Conference on the Structural Design of AsphaltPavements Ann Arbor MI USA July 1987

[56] S Hossain G Dickerson and C Weaver Comparative Studyof VTM and AASHTO Test Method for CBR Co MaterialsDivision VDOT 2005

[57] N Garg A Larkin and H Brar ldquoA comparative subgradeevaluation using CBR vane shear light weight deflectometerand resilient modulus testsrdquo in Proceedings of the 8th In-ternational Conference on the Bearing Capacity of RoadsRailways and Airfields CRC Press Champaign IL USA2009

[58] M Ayres Development of a rational probabilistic approach forflexible pavement analysis University of Maryland CollegePark MD USA 1997

[59] AASHTO T 307 Determining the Resilient Modulus of Soilsand Aggregate Materials (2012) American Association ofState Highway and Transportation Officials Washington DCUSA 2004

[60] M Arshad and M F Ahmed ldquoPotential use of reclaimedasphalt pavement and recycled concrete aggregate in basesubbase layers of flexible pavementsrdquo Construction andBuilding Materials vol 151 pp 83ndash97 2017

[61] M Arshad ldquoCorrelation between resilient modulus (MR) andconstrained modulus (Mc) values of granular materialsrdquoConstruction and Building Materials vol 159 pp 440ndash4502018

[62] P Guo and J Emery ldquoImportance of strain level inevaluating resilient modulus of granular materialsrdquo In-ternational Journal of Pavement Engineering vol 12 no 2pp 187ndash199 2011

[63] E J McGarrah ldquoEvaluation of current practices of reclaimedasphalt pavementvirgin aggregate as base course materialrdquoNo WA-RD 7131 Federal Highway AdministrationWashington DC USA 2007

[64] T B Alam M Abdelrahman and S A Schram ldquoLaboratorycharacterisation of recycled asphalt pavement as a base layerrdquoInternational Journal of Pavement Engineering vol 11 no 2pp 123ndash131 2010

[65] T Bennert and A Maher ldquoe development of a performancespecification for granular base and subbase materialrdquo ReportNo FHWA-NJ-2005-003 Department of TransportationEwing Township NJ USA 2005

[66] T H Wonnacott H omas and J Ronald ldquoRegression asecond course in statisticsrdquo No 04 QA2782 W6Wiley NewYork NY USA 1981

[67] W Penny and S Roberts Neural network predictions witherror bars Dept of Electrical and Electronic EngineeringTechnology and Medicine Research Report TR-97-1 ImperialCollege of Science London UK 1997

[68] R Dybowski and S J Roberts ldquoConfidence intervals andprediction intervals for feed-forward neural networksrdquoClinical Applications of Artificial Neural Networks pp 298ndash326 2001

[69] J Hauke and T Kossowski ldquoComparison of values ofPearsonrsquos and Spearmanrsquos correlation coefficients on the samesets of datardquo Quaestiones Geographicae vol 30 no 2pp 87ndash93 2011

[70] K-z Yan H-b Xu and G-h Shen ldquoNovel approach toresilient modulus using routine subgrade soil propertiesrdquo

Advances in Materials Science and Engineering 15

International Journal of Geomechanics vol 14 no 6 article04014025 2013

[71] Y H Chan ldquoBiostatistics 104 correlational analysisrdquoSingapore Medical Journal vol 44 no 12 pp 614ndash6192003

[72] B M Damghani D Welch C OrsquoMalley and S Knights ldquoemisleading value of measured correlationrdquoWilmott vol 2012no 62 pp 64ndash73 2012

[73] L B Christensen B Johnson and L A Turner ldquoResearchmethods design and analysisrdquo 2011

[74] W J Dixon and F J Massey Introduction to StatisticalAnalysis McGraw-Hill New York NY USA 1969

[75] B Colbert and Z You ldquoe determination of mechanicalperformance of laboratory produced hot mix asphalt mixturesusing controlled RAP and virgin aggregate size fractionsrdquoConstruction and Building Materials vol 26 no 1 pp 655ndash662 2012

[76] D H Timm and D E Newcomb ldquoPerpetual pavement designfor flexible pavements in the USrdquo International Journal ofPavement Engineering vol 7 no 2 pp 111ndash119 2006

[77] Y H Huang Pavement Analysis and Design Prentice-HallEnglewood Cliffs NJ USA 2nd edition 1993

[78] L Walubita W Liu and T Scullion Texas perpetualpavements-Experience overview and the way forward Tech-nical Report No 0-4822-3 Texas Transportation InstituteTexas AampM University College Station TX USA 2010

[79] D Timm and D Newcomb ldquoCalibration of flexible pavementperformance equations for Minnesota road research projectrdquoTransportation Research Record Journal of the TransportationResearch Board no 1853 pp 134ndash142 2003

16 Advances in Materials Science and Engineering

CorrosionInternational Journal of

Hindawiwwwhindawicom Volume 2018

Advances in

Materials Science and EngineeringHindawiwwwhindawicom Volume 2018

Hindawiwwwhindawicom Volume 2018

Journal of

Chemistry

Analytical ChemistryInternational Journal of

Hindawiwwwhindawicom Volume 2018

ScienticaHindawiwwwhindawicom Volume 2018

Polymer ScienceInternational Journal of

Hindawiwwwhindawicom Volume 2018

Hindawiwwwhindawicom Volume 2018

Advances in Condensed Matter Physics

Hindawiwwwhindawicom Volume 2018

International Journal of

BiomaterialsHindawiwwwhindawicom

Journal ofEngineeringVolume 2018

Applied ChemistryJournal of

Hindawiwwwhindawicom Volume 2018

NanotechnologyHindawiwwwhindawicom Volume 2018

Journal of

Hindawiwwwhindawicom Volume 2018

High Energy PhysicsAdvances in

Hindawi Publishing Corporation httpwwwhindawicom Volume 2013Hindawiwwwhindawicom

The Scientific World Journal

Volume 2018

TribologyAdvances in

Hindawiwwwhindawicom Volume 2018

Hindawiwwwhindawicom Volume 2018

ChemistryAdvances in

Hindawiwwwhindawicom Volume 2018

Advances inPhysical Chemistry

Hindawiwwwhindawicom Volume 2018

BioMed Research InternationalMaterials

Journal of

Hindawiwwwhindawicom Volume 2018

Na

nom

ate

ria

ls

Hindawiwwwhindawicom Volume 2018

Journal ofNanomaterials

Submit your manuscripts atwwwhindawicom

applicationsrdquo Journal of Hazardous Materials vol 321pp 547ndash556 2017

[3] L R Hoyos A J Puppala and C A Ordonez ldquoCharacter-ization of cement-fiber-treated reclaimed asphalt pavementaggregates preliminary investigationrdquo Journal of Materials inCivil Engineering vol 23 no 7 pp 977ndash989 2011

[4] R Taha A Al-Harthy K Al-Shamsi and M Al-ZubeidildquoCement stabilization of reclaimed asphalt pavement aggre-gate for road bases and subbasesrdquo Journal of Materials in CivilEngineering vol 14 no 3 pp 239ndash245 2002

[5] A M Azam and D A Cameron ldquoGeotechnical properties ofblends of recycled clay masonry and recycled concrete ag-gregates in unbound pavement constructionrdquo Journal ofMaterials in Civil Engineering vol 25 no 6 pp 788ndash7982013

[6] A Gabor and D Cameron ldquoProperties of recycled concreteaggregate for unbound pavement constructionrdquo Journal ofMaterials in Civil Engineering vol 24 no 6 pp 754ndash7642012

[7] C S Poon and D Chan ldquoFeasible use of recycled concreteaggregates and crushed clay brick as unbound road sub-baserdquoConstruction and Building Materials vol 20 no 8 pp 578ndash585 2006

[8] A Arulrajah M M Y Ali M M Disfani J Piratheepan andM W Bo ldquoGeotechnical performance of recycled glass-wasterock blends in footpath basesrdquo Journal of Materials in CivilEngineering vol 25 no 5 pp 653ndash661 2013

[9] L T Lee Jr ldquoRecycled glass and dredged materialsrdquo ReportNo ERDC TNDOER-T8 US Army Corps of EngineersEngineer Research and Development Center Mississippi MSUSA 2007

[10] M Ali A Arulrajah M Disfani and J Piratheepan ldquoSuit-ability of using recycled glassmdashcrushed rock blends forpavement subbase applicationsrdquo in Proceedings of the Geo-Frontiers 2011 Conference on Geotechnical Foundation Designpp 1325ndash1334 ASCE Reston VA USA 2011

[11] J Wartman D G Grubb and A S M Nasim ldquoSelectengineering characteristics of crushed glassrdquo Journal ofMaterials in Civil Engineering vol 16 no 6 pp 526ndash5392004

[12] W Kim and J Labuz Resilient Modulus and Strength of BaseCourse with Recycled Bituminous Material Minnesota De-partment of Transportation Research Services Section MNUSA 2007

[13] D Bloomquist G Diamond M Oden B Ruth and M TiaEngineering and Environmental Aspects of Recycled Materialsfor Highway Construction Appendix 1 Final Report 1993

[14] A Hussain and Q Yanjun ldquoEvaluation of asphalt mixescontaining reclaimed asphalt pavement for wearing cour-sesrdquo in Proceedings of the International Conference onTraffic and Transportation Engineering School of CivilEngineering Southwest Jiaotong University ChengduChina 2012

[15] M Solaimanian and M Tahmoressi ldquoVariability analysis ofhot-mix asphalt concrete containing high percentage ofreclaimed asphalt pavementrdquo Transportation Research Re-cord Journal of the Transportation Research Board vol 1543no 1 pp 89ndash96 1996

[16] A Gabr and D A Cameron ldquoProperties of recycled concreteaggregate for unbound pavement constructionrdquo Journal ofMaterials in Civil Engineering vol 24 no 6 pp 754ndash7642011

[17] W-L Huang D-H Lin N-B Chang and K-S LinldquoRecycling of construction and demolition waste via a

mechanical sorting processrdquo Resources Conservation andRecycling vol 37 no 1 pp 23ndash37 2002

[18] A R Pasandın and I Perez ldquoOverview of bituminous mix-tures made with recycled concrete Aggregatesrdquo Constructionand Building Materials vol 74 pp 151ndash161 2015

[19] P Jitsangiam H Nikraz and K Siripun ldquoConstruction anddemolition (CampD) waste as a road base material for WesternAustralia roadsrdquo Australian Geomechanics vol 44 no 3pp 57ndash62 2009

[20] A Nataatmadja and Y L Tan ldquoResilient response of recycledconcrete road aggregatesrdquo Journal of Transportation Engi-neering vol 127 no 5 pp 450ndash453 2001

[21] C Leek and K Siripun ldquoSpecification and performance ofrecycled materials in road pavementsrdquo Contract Rep (01119-1)2010

[22] J Green and J Hall Nondistructive Vibratory Testing ofAirport Pavement 1975

[23] W Heukelom and A Klomp ldquoDynamic testing as a means ofcontrolling pavements during and after constructionrdquo inProceedings of the International Conference on the StructuralDesign of Asphalt Pavements University of Michigan AnnArbor MI USA 1962

[24] Ohio Department of Transportation Pavement DesignManual Ohio Department of Transportation Office ofPavement Engineering OH USA 2008

[25] W D Powell H C Mayhew and M M Nunn ldquoestructural design of bituminous roadsrdquo Laboratory Report1132 Transport and Road Research Laboratory CrowthorneUK 1984

[26] M W Witczak X Qi and M W Mirza ldquoUse of nonlinearsubgrade modulus in AASHTO design procedurerdquo Journal ofTransportation Engineering vol 121 no 3 1995

[27] AASHTO Guide for Design of Pavement Structures Wash-ington DC USA 1993

[28] Asphalt Institute Research and Development of 5e AsphaltInstitutersquos 5ickness Design Manual (MS-1) 9th edition 1982

[29] T Buu Correlation of Resistance R-value and ResilientModulus of Idaho Subgrade Soil Idaho Department ofTransportation Division of Highways ID USA 1980

[30] S Muench J Mahoney and L Pierce WSDOT PavementGuide Washington State Department of TransportationInternet Module Washington DC USA 2009

[31] S Yeh and C Su ldquoResilient properties of Colorado soilsrdquoReport No CDOH-DH-SM-89-9 Colorado Department ofHighways Denver CO USA 1989

[32] M R ompson and Q L Robnett ldquoResilient properties ofsubgrade soilsrdquo Transportation Engineering Journal of ASCEvol 105 pp 71ndash89 1979

[33] W Lee N C Bohra A G Altschaeffl and T D WhiteldquoResilient modulus of cohesive soilsrdquo Journal of Geotechnicaland Geoenvironmental Engineering vol 123 no 2 pp 131ndash136 1997

[34] R Carmichael III and E Stuart ldquoPredicting resilient modulusa study to determine the mechanical properties of subgradesoilsrdquo Transportation Research Record vol 1043 pp 145ndash1481986

[35] E C Drumm Y Boateng-Poku and T Johnson PierceldquoEstimation of subgrade resilient modulus from standardtestsrdquo Journal of Geotechnical Engineering vol 116 no 5pp 774ndash789 1990

[36] M J Farrar and J P Turner Resilient Modulus of WyomingSubgrade Soils 1991

14 Advances in Materials Science and Engineering

[37] M P Jones and M W Witczak ldquoSubgrade modulus on thesan diego test roadrdquo Transportation Research Record Journalof the Transportation Research Board vol 641 pp 1ndash6 1977

[38] A M Rahim and K P George ldquoSubgrade soil indexproperties to estimate resilient modulusrdquo in Proceedings ofthe 83th Annual Meeting of the Transportation ResearchBoard National Research Council Washington DC USA2004

[39] M R ompson and T G LaGrow A Proposed ConventionalFlexible Pavement 5ickness Design Procedure University ofIllinois Peoria IL USA 1988

[40] R Pezo ldquoA general method of reporting resilient modulustests of soils a pavement engineerrsquos point of viewrdquo in Pro-ceedings of the 72nd Annual Meeting of Transportation Re-search Board Washington DC USA 1993

[41] R G Hicks and C L Monismith ldquoResilient properties ofgranular materialrdquo Transportation Research Record vol 345pp 15ndash31 1971

[42] J Uzan ldquoCharacterization of granular materialsrdquo Trans-portation Research Record Journal of the Transportation Re-search Board vol 1022 pp 52ndash59 1985

[43] National Cooperative Highway Research Program ldquoGuide formechanistic-empirical design of new and rehabilitatedpavement structuresrdquo NCHRP 1-37A NCHRP WashingtonDC USA 2004

[44] N M Louay H T Hani and H Ananda ldquoEvaluation ofresilient modulus of subgrade soil by cone penetration testrdquoTransportation Research Record Journal of the TransportationResearch Board vol 1652 pp 236ndash245 1999

[45] S Dai and J Zollars ldquoResilient modulus of Minnesota roadresearch project subgrade soilrdquo Transportation Research Re-cord Journal of the Transportation Research Board vol 1786no 1 pp 20ndash28 2002

[46] L Mohammad B Huang A Puppala and A Allen ldquoRe-gression model for resilient modulus of subgrade soilsrdquoTransportation Research Record Journal of the TransportationResearch Board vol 1687 no 1 pp 47ndash54 1999

[47] B Santa ldquoResilient modulus of subgrade soils comparison oftwo constitutive equationsrdquo Transportation Research RecordJournal of the Transportation Research Board vol 1462pp 79ndash90 1994

[48] H Von Quintus and B Killingsworth Analyses Relating toPavement Material Characterizations and their Effects onPavement Performance 1998

[49] O Porter ldquoe preparation of subgradesrdquo in Proceedings ofthe Nineteenth Annual Meeting Highway Research BoardWashington DC USA December 1939

[50] O J Porter ldquoDevelopment of the original method for highwaydesignrdquo Transactions of the American Society of Civil Engi-neers vol 115 pp 461ndash467 1950

[51] D W Hight and M G H Stevens ldquoAn analysis of theCalifornia Bearing Ratio test in saturated claysrdquoGeotechnique vol 32 no 4 pp 315ndash322 1982

[52] P R Fleming and C D F Rogers ldquoAssessment of pavementfoundations during constructionrdquo Proceedings of the In-stitution of Civil Engineers-Transport vol 111 no 2pp 105ndash115 1995

[53] M R ompson R Marshall and Q L Robnett ldquoResilientproperties of subgrade soilsrdquo Final Report No FHWA-IL-UI-160 University of Illinois Urbana IL USA 1976

[54] B Sukumaran V Kyatham A Shah and D Sheth ldquoSuit-ability of using California bearing ratio test to predict resilientmodulusrdquo in Proceedings Federal Aviation Administration

Airport Technology Transfer Conference Atlantic City NJUSA 2002

[55] N W Lister and D Powell ldquoDesign practices for pavementsin the United Kingdomrdquo in Proceedings of the 6th In-ternational Conference on the Structural Design of AsphaltPavements Ann Arbor MI USA July 1987

[56] S Hossain G Dickerson and C Weaver Comparative Studyof VTM and AASHTO Test Method for CBR Co MaterialsDivision VDOT 2005

[57] N Garg A Larkin and H Brar ldquoA comparative subgradeevaluation using CBR vane shear light weight deflectometerand resilient modulus testsrdquo in Proceedings of the 8th In-ternational Conference on the Bearing Capacity of RoadsRailways and Airfields CRC Press Champaign IL USA2009

[58] M Ayres Development of a rational probabilistic approach forflexible pavement analysis University of Maryland CollegePark MD USA 1997

[59] AASHTO T 307 Determining the Resilient Modulus of Soilsand Aggregate Materials (2012) American Association ofState Highway and Transportation Officials Washington DCUSA 2004

[60] M Arshad and M F Ahmed ldquoPotential use of reclaimedasphalt pavement and recycled concrete aggregate in basesubbase layers of flexible pavementsrdquo Construction andBuilding Materials vol 151 pp 83ndash97 2017

[61] M Arshad ldquoCorrelation between resilient modulus (MR) andconstrained modulus (Mc) values of granular materialsrdquoConstruction and Building Materials vol 159 pp 440ndash4502018

[62] P Guo and J Emery ldquoImportance of strain level inevaluating resilient modulus of granular materialsrdquo In-ternational Journal of Pavement Engineering vol 12 no 2pp 187ndash199 2011

[63] E J McGarrah ldquoEvaluation of current practices of reclaimedasphalt pavementvirgin aggregate as base course materialrdquoNo WA-RD 7131 Federal Highway AdministrationWashington DC USA 2007

[64] T B Alam M Abdelrahman and S A Schram ldquoLaboratorycharacterisation of recycled asphalt pavement as a base layerrdquoInternational Journal of Pavement Engineering vol 11 no 2pp 123ndash131 2010

[65] T Bennert and A Maher ldquoe development of a performancespecification for granular base and subbase materialrdquo ReportNo FHWA-NJ-2005-003 Department of TransportationEwing Township NJ USA 2005

[66] T H Wonnacott H omas and J Ronald ldquoRegression asecond course in statisticsrdquo No 04 QA2782 W6Wiley NewYork NY USA 1981

[67] W Penny and S Roberts Neural network predictions witherror bars Dept of Electrical and Electronic EngineeringTechnology and Medicine Research Report TR-97-1 ImperialCollege of Science London UK 1997

[68] R Dybowski and S J Roberts ldquoConfidence intervals andprediction intervals for feed-forward neural networksrdquoClinical Applications of Artificial Neural Networks pp 298ndash326 2001

[69] J Hauke and T Kossowski ldquoComparison of values ofPearsonrsquos and Spearmanrsquos correlation coefficients on the samesets of datardquo Quaestiones Geographicae vol 30 no 2pp 87ndash93 2011

[70] K-z Yan H-b Xu and G-h Shen ldquoNovel approach toresilient modulus using routine subgrade soil propertiesrdquo

Advances in Materials Science and Engineering 15

International Journal of Geomechanics vol 14 no 6 article04014025 2013

[71] Y H Chan ldquoBiostatistics 104 correlational analysisrdquoSingapore Medical Journal vol 44 no 12 pp 614ndash6192003

[72] B M Damghani D Welch C OrsquoMalley and S Knights ldquoemisleading value of measured correlationrdquoWilmott vol 2012no 62 pp 64ndash73 2012

[73] L B Christensen B Johnson and L A Turner ldquoResearchmethods design and analysisrdquo 2011

[74] W J Dixon and F J Massey Introduction to StatisticalAnalysis McGraw-Hill New York NY USA 1969

[75] B Colbert and Z You ldquoe determination of mechanicalperformance of laboratory produced hot mix asphalt mixturesusing controlled RAP and virgin aggregate size fractionsrdquoConstruction and Building Materials vol 26 no 1 pp 655ndash662 2012

[76] D H Timm and D E Newcomb ldquoPerpetual pavement designfor flexible pavements in the USrdquo International Journal ofPavement Engineering vol 7 no 2 pp 111ndash119 2006

[77] Y H Huang Pavement Analysis and Design Prentice-HallEnglewood Cliffs NJ USA 2nd edition 1993

[78] L Walubita W Liu and T Scullion Texas perpetualpavements-Experience overview and the way forward Tech-nical Report No 0-4822-3 Texas Transportation InstituteTexas AampM University College Station TX USA 2010

[79] D Timm and D Newcomb ldquoCalibration of flexible pavementperformance equations for Minnesota road research projectrdquoTransportation Research Record Journal of the TransportationResearch Board no 1853 pp 134ndash142 2003

16 Advances in Materials Science and Engineering

CorrosionInternational Journal of

Hindawiwwwhindawicom Volume 2018

Advances in

Materials Science and EngineeringHindawiwwwhindawicom Volume 2018

Hindawiwwwhindawicom Volume 2018

Journal of

Chemistry

Analytical ChemistryInternational Journal of

Hindawiwwwhindawicom Volume 2018

ScienticaHindawiwwwhindawicom Volume 2018

Polymer ScienceInternational Journal of

Hindawiwwwhindawicom Volume 2018

Hindawiwwwhindawicom Volume 2018

Advances in Condensed Matter Physics

Hindawiwwwhindawicom Volume 2018

International Journal of

BiomaterialsHindawiwwwhindawicom

Journal ofEngineeringVolume 2018

Applied ChemistryJournal of

Hindawiwwwhindawicom Volume 2018

NanotechnologyHindawiwwwhindawicom Volume 2018

Journal of

Hindawiwwwhindawicom Volume 2018

High Energy PhysicsAdvances in

Hindawi Publishing Corporation httpwwwhindawicom Volume 2013Hindawiwwwhindawicom

The Scientific World Journal

Volume 2018

TribologyAdvances in

Hindawiwwwhindawicom Volume 2018

Hindawiwwwhindawicom Volume 2018

ChemistryAdvances in

Hindawiwwwhindawicom Volume 2018

Advances inPhysical Chemistry

Hindawiwwwhindawicom Volume 2018

BioMed Research InternationalMaterials

Journal of

Hindawiwwwhindawicom Volume 2018

Na

nom

ate

ria

ls

Hindawiwwwhindawicom Volume 2018

Journal ofNanomaterials

Submit your manuscripts atwwwhindawicom

[37] M P Jones and M W Witczak ldquoSubgrade modulus on thesan diego test roadrdquo Transportation Research Record Journalof the Transportation Research Board vol 641 pp 1ndash6 1977

[38] A M Rahim and K P George ldquoSubgrade soil indexproperties to estimate resilient modulusrdquo in Proceedings ofthe 83th Annual Meeting of the Transportation ResearchBoard National Research Council Washington DC USA2004

[39] M R ompson and T G LaGrow A Proposed ConventionalFlexible Pavement 5ickness Design Procedure University ofIllinois Peoria IL USA 1988

[40] R Pezo ldquoA general method of reporting resilient modulustests of soils a pavement engineerrsquos point of viewrdquo in Pro-ceedings of the 72nd Annual Meeting of Transportation Re-search Board Washington DC USA 1993

[41] R G Hicks and C L Monismith ldquoResilient properties ofgranular materialrdquo Transportation Research Record vol 345pp 15ndash31 1971

[42] J Uzan ldquoCharacterization of granular materialsrdquo Trans-portation Research Record Journal of the Transportation Re-search Board vol 1022 pp 52ndash59 1985

[43] National Cooperative Highway Research Program ldquoGuide formechanistic-empirical design of new and rehabilitatedpavement structuresrdquo NCHRP 1-37A NCHRP WashingtonDC USA 2004

[44] N M Louay H T Hani and H Ananda ldquoEvaluation ofresilient modulus of subgrade soil by cone penetration testrdquoTransportation Research Record Journal of the TransportationResearch Board vol 1652 pp 236ndash245 1999

[45] S Dai and J Zollars ldquoResilient modulus of Minnesota roadresearch project subgrade soilrdquo Transportation Research Re-cord Journal of the Transportation Research Board vol 1786no 1 pp 20ndash28 2002

[46] L Mohammad B Huang A Puppala and A Allen ldquoRe-gression model for resilient modulus of subgrade soilsrdquoTransportation Research Record Journal of the TransportationResearch Board vol 1687 no 1 pp 47ndash54 1999

[47] B Santa ldquoResilient modulus of subgrade soils comparison oftwo constitutive equationsrdquo Transportation Research RecordJournal of the Transportation Research Board vol 1462pp 79ndash90 1994

[48] H Von Quintus and B Killingsworth Analyses Relating toPavement Material Characterizations and their Effects onPavement Performance 1998

[49] O Porter ldquoe preparation of subgradesrdquo in Proceedings ofthe Nineteenth Annual Meeting Highway Research BoardWashington DC USA December 1939

[50] O J Porter ldquoDevelopment of the original method for highwaydesignrdquo Transactions of the American Society of Civil Engi-neers vol 115 pp 461ndash467 1950

[51] D W Hight and M G H Stevens ldquoAn analysis of theCalifornia Bearing Ratio test in saturated claysrdquoGeotechnique vol 32 no 4 pp 315ndash322 1982

[52] P R Fleming and C D F Rogers ldquoAssessment of pavementfoundations during constructionrdquo Proceedings of the In-stitution of Civil Engineers-Transport vol 111 no 2pp 105ndash115 1995

[53] M R ompson R Marshall and Q L Robnett ldquoResilientproperties of subgrade soilsrdquo Final Report No FHWA-IL-UI-160 University of Illinois Urbana IL USA 1976

[54] B Sukumaran V Kyatham A Shah and D Sheth ldquoSuit-ability of using California bearing ratio test to predict resilientmodulusrdquo in Proceedings Federal Aviation Administration

Airport Technology Transfer Conference Atlantic City NJUSA 2002

[55] N W Lister and D Powell ldquoDesign practices for pavementsin the United Kingdomrdquo in Proceedings of the 6th In-ternational Conference on the Structural Design of AsphaltPavements Ann Arbor MI USA July 1987

[56] S Hossain G Dickerson and C Weaver Comparative Studyof VTM and AASHTO Test Method for CBR Co MaterialsDivision VDOT 2005

[57] N Garg A Larkin and H Brar ldquoA comparative subgradeevaluation using CBR vane shear light weight deflectometerand resilient modulus testsrdquo in Proceedings of the 8th In-ternational Conference on the Bearing Capacity of RoadsRailways and Airfields CRC Press Champaign IL USA2009

[58] M Ayres Development of a rational probabilistic approach forflexible pavement analysis University of Maryland CollegePark MD USA 1997

[59] AASHTO T 307 Determining the Resilient Modulus of Soilsand Aggregate Materials (2012) American Association ofState Highway and Transportation Officials Washington DCUSA 2004

[60] M Arshad and M F Ahmed ldquoPotential use of reclaimedasphalt pavement and recycled concrete aggregate in basesubbase layers of flexible pavementsrdquo Construction andBuilding Materials vol 151 pp 83ndash97 2017

[61] M Arshad ldquoCorrelation between resilient modulus (MR) andconstrained modulus (Mc) values of granular materialsrdquoConstruction and Building Materials vol 159 pp 440ndash4502018

[62] P Guo and J Emery ldquoImportance of strain level inevaluating resilient modulus of granular materialsrdquo In-ternational Journal of Pavement Engineering vol 12 no 2pp 187ndash199 2011

[63] E J McGarrah ldquoEvaluation of current practices of reclaimedasphalt pavementvirgin aggregate as base course materialrdquoNo WA-RD 7131 Federal Highway AdministrationWashington DC USA 2007

[64] T B Alam M Abdelrahman and S A Schram ldquoLaboratorycharacterisation of recycled asphalt pavement as a base layerrdquoInternational Journal of Pavement Engineering vol 11 no 2pp 123ndash131 2010

[65] T Bennert and A Maher ldquoe development of a performancespecification for granular base and subbase materialrdquo ReportNo FHWA-NJ-2005-003 Department of TransportationEwing Township NJ USA 2005

[66] T H Wonnacott H omas and J Ronald ldquoRegression asecond course in statisticsrdquo No 04 QA2782 W6Wiley NewYork NY USA 1981

[67] W Penny and S Roberts Neural network predictions witherror bars Dept of Electrical and Electronic EngineeringTechnology and Medicine Research Report TR-97-1 ImperialCollege of Science London UK 1997

[68] R Dybowski and S J Roberts ldquoConfidence intervals andprediction intervals for feed-forward neural networksrdquoClinical Applications of Artificial Neural Networks pp 298ndash326 2001

[69] J Hauke and T Kossowski ldquoComparison of values ofPearsonrsquos and Spearmanrsquos correlation coefficients on the samesets of datardquo Quaestiones Geographicae vol 30 no 2pp 87ndash93 2011

[70] K-z Yan H-b Xu and G-h Shen ldquoNovel approach toresilient modulus using routine subgrade soil propertiesrdquo

Advances in Materials Science and Engineering 15

International Journal of Geomechanics vol 14 no 6 article04014025 2013

[71] Y H Chan ldquoBiostatistics 104 correlational analysisrdquoSingapore Medical Journal vol 44 no 12 pp 614ndash6192003

[72] B M Damghani D Welch C OrsquoMalley and S Knights ldquoemisleading value of measured correlationrdquoWilmott vol 2012no 62 pp 64ndash73 2012

[73] L B Christensen B Johnson and L A Turner ldquoResearchmethods design and analysisrdquo 2011

[74] W J Dixon and F J Massey Introduction to StatisticalAnalysis McGraw-Hill New York NY USA 1969

[75] B Colbert and Z You ldquoe determination of mechanicalperformance of laboratory produced hot mix asphalt mixturesusing controlled RAP and virgin aggregate size fractionsrdquoConstruction and Building Materials vol 26 no 1 pp 655ndash662 2012

[76] D H Timm and D E Newcomb ldquoPerpetual pavement designfor flexible pavements in the USrdquo International Journal ofPavement Engineering vol 7 no 2 pp 111ndash119 2006

[77] Y H Huang Pavement Analysis and Design Prentice-HallEnglewood Cliffs NJ USA 2nd edition 1993

[78] L Walubita W Liu and T Scullion Texas perpetualpavements-Experience overview and the way forward Tech-nical Report No 0-4822-3 Texas Transportation InstituteTexas AampM University College Station TX USA 2010

[79] D Timm and D Newcomb ldquoCalibration of flexible pavementperformance equations for Minnesota road research projectrdquoTransportation Research Record Journal of the TransportationResearch Board no 1853 pp 134ndash142 2003

16 Advances in Materials Science and Engineering

CorrosionInternational Journal of

Hindawiwwwhindawicom Volume 2018

Advances in

Materials Science and EngineeringHindawiwwwhindawicom Volume 2018

Hindawiwwwhindawicom Volume 2018

Journal of

Chemistry

Analytical ChemistryInternational Journal of

Hindawiwwwhindawicom Volume 2018

ScienticaHindawiwwwhindawicom Volume 2018

Polymer ScienceInternational Journal of

Hindawiwwwhindawicom Volume 2018

Hindawiwwwhindawicom Volume 2018

Advances in Condensed Matter Physics

Hindawiwwwhindawicom Volume 2018

International Journal of

BiomaterialsHindawiwwwhindawicom

Journal ofEngineeringVolume 2018

Applied ChemistryJournal of

Hindawiwwwhindawicom Volume 2018

NanotechnologyHindawiwwwhindawicom Volume 2018

Journal of

Hindawiwwwhindawicom Volume 2018

High Energy PhysicsAdvances in

Hindawi Publishing Corporation httpwwwhindawicom Volume 2013Hindawiwwwhindawicom

The Scientific World Journal

Volume 2018

TribologyAdvances in

Hindawiwwwhindawicom Volume 2018

Hindawiwwwhindawicom Volume 2018

ChemistryAdvances in

Hindawiwwwhindawicom Volume 2018

Advances inPhysical Chemistry

Hindawiwwwhindawicom Volume 2018

BioMed Research InternationalMaterials

Journal of

Hindawiwwwhindawicom Volume 2018

Na

nom

ate

ria

ls

Hindawiwwwhindawicom Volume 2018

Journal ofNanomaterials

Submit your manuscripts atwwwhindawicom

International Journal of Geomechanics vol 14 no 6 article04014025 2013

[71] Y H Chan ldquoBiostatistics 104 correlational analysisrdquoSingapore Medical Journal vol 44 no 12 pp 614ndash6192003

[72] B M Damghani D Welch C OrsquoMalley and S Knights ldquoemisleading value of measured correlationrdquoWilmott vol 2012no 62 pp 64ndash73 2012

[73] L B Christensen B Johnson and L A Turner ldquoResearchmethods design and analysisrdquo 2011

[74] W J Dixon and F J Massey Introduction to StatisticalAnalysis McGraw-Hill New York NY USA 1969

[75] B Colbert and Z You ldquoe determination of mechanicalperformance of laboratory produced hot mix asphalt mixturesusing controlled RAP and virgin aggregate size fractionsrdquoConstruction and Building Materials vol 26 no 1 pp 655ndash662 2012

[76] D H Timm and D E Newcomb ldquoPerpetual pavement designfor flexible pavements in the USrdquo International Journal ofPavement Engineering vol 7 no 2 pp 111ndash119 2006

[77] Y H Huang Pavement Analysis and Design Prentice-HallEnglewood Cliffs NJ USA 2nd edition 1993

[78] L Walubita W Liu and T Scullion Texas perpetualpavements-Experience overview and the way forward Tech-nical Report No 0-4822-3 Texas Transportation InstituteTexas AampM University College Station TX USA 2010

[79] D Timm and D Newcomb ldquoCalibration of flexible pavementperformance equations for Minnesota road research projectrdquoTransportation Research Record Journal of the TransportationResearch Board no 1853 pp 134ndash142 2003

16 Advances in Materials Science and Engineering

CorrosionInternational Journal of

Hindawiwwwhindawicom Volume 2018

Advances in

Materials Science and EngineeringHindawiwwwhindawicom Volume 2018

Hindawiwwwhindawicom Volume 2018

Journal of

Chemistry

Analytical ChemistryInternational Journal of

Hindawiwwwhindawicom Volume 2018

ScienticaHindawiwwwhindawicom Volume 2018

Polymer ScienceInternational Journal of

Hindawiwwwhindawicom Volume 2018

Hindawiwwwhindawicom Volume 2018

Advances in Condensed Matter Physics

Hindawiwwwhindawicom Volume 2018

International Journal of

BiomaterialsHindawiwwwhindawicom

Journal ofEngineeringVolume 2018

Applied ChemistryJournal of

Hindawiwwwhindawicom Volume 2018

NanotechnologyHindawiwwwhindawicom Volume 2018

Journal of

Hindawiwwwhindawicom Volume 2018

High Energy PhysicsAdvances in

Hindawi Publishing Corporation httpwwwhindawicom Volume 2013Hindawiwwwhindawicom

The Scientific World Journal

Volume 2018

TribologyAdvances in

Hindawiwwwhindawicom Volume 2018

Hindawiwwwhindawicom Volume 2018

ChemistryAdvances in

Hindawiwwwhindawicom Volume 2018

Advances inPhysical Chemistry

Hindawiwwwhindawicom Volume 2018

BioMed Research InternationalMaterials

Journal of

Hindawiwwwhindawicom Volume 2018

Na

nom

ate

ria

ls

Hindawiwwwhindawicom Volume 2018

Journal ofNanomaterials

Submit your manuscripts atwwwhindawicom

CorrosionInternational Journal of

Hindawiwwwhindawicom Volume 2018

Advances in

Materials Science and EngineeringHindawiwwwhindawicom Volume 2018

Hindawiwwwhindawicom Volume 2018

Journal of

Chemistry

Analytical ChemistryInternational Journal of

Hindawiwwwhindawicom Volume 2018

ScienticaHindawiwwwhindawicom Volume 2018

Polymer ScienceInternational Journal of

Hindawiwwwhindawicom Volume 2018

Hindawiwwwhindawicom Volume 2018

Advances in Condensed Matter Physics

Hindawiwwwhindawicom Volume 2018

International Journal of

BiomaterialsHindawiwwwhindawicom

Journal ofEngineeringVolume 2018

Applied ChemistryJournal of

Hindawiwwwhindawicom Volume 2018

NanotechnologyHindawiwwwhindawicom Volume 2018

Journal of

Hindawiwwwhindawicom Volume 2018

High Energy PhysicsAdvances in

Hindawi Publishing Corporation httpwwwhindawicom Volume 2013Hindawiwwwhindawicom

The Scientific World Journal

Volume 2018

TribologyAdvances in

Hindawiwwwhindawicom Volume 2018

Hindawiwwwhindawicom Volume 2018

ChemistryAdvances in

Hindawiwwwhindawicom Volume 2018

Advances inPhysical Chemistry

Hindawiwwwhindawicom Volume 2018

BioMed Research InternationalMaterials

Journal of

Hindawiwwwhindawicom Volume 2018

Na

nom

ate

ria

ls

Hindawiwwwhindawicom Volume 2018

Journal ofNanomaterials

Submit your manuscripts atwwwhindawicom