Assessment of Flatbed Scanner Method for Quality Assurance ... · ii Assessment of Flatbed Scanner...

Assessment of Flatbed Scanner Method for Quality Assurance Testing of Air Content and Spacing Factor in

Concrete

by

Sona Nezami

A thesis submitted in conformity with the requirements for the degree of Master of Applied Science

Department of Civil Engineering University of Toronto

© Copyright by Sona Nezami 2013

ii

Assessment of Flatbed Scanner Method for Quality Assurance

Testing of Air Content and Spacing Factor in Concrete

Sona Nezami

Master of Applied Science

Department of Civil Engineering University of Toronto

2013

Abstract

The flatbed scanner method for air void analysis of concrete is investigated through a

comparison study with the standard ASTM C457 manual and Rapid Air 457 test methods. Air

void parameters including air content and spacing factor are determined by image analysis

of a large population of scanned samples through contrast enhancement and threshold

determination procedures. It is shown that flatbed scanner method is giving comparable

results to manual and Rapid Air 457 methods. Furthermore, a comparison of the air void

chord length distributions obtained from the two methods of flatbed scanner and Rapid Air

457 has been implemented in this research. The effect of having different settings in the

scanning process of scanner method is also investigated. Moreover, a threshold study has

been performed that showed the flatbed scanner method can be employed in combination

with manual and Rapid Air 457 methods as a time and cost saving strategy.

iii

Acknowledgments

It is with my immense gratitude that I acknowledge the support and help of my Supervisor

Professor Karl Peterson whose supervision, guidance, and encouragement from the

preliminary to the concluding part of my research enabled me to develop a clear

understanding of the subject. I would like to thank the other member of my thesis

committee, Professor Daman Panesar for her guidance and continued interest in the

subject. I would like to extend my thanks to Hannah Schell, Jana Konecny, Jixing Jiang from

the Ministry of Transportation of Ontario, Gerald Anzalone from Michigan Technological

University and Kenneth Totty from Grace Construction Products company who provided the

basis for my research. I would also thank my best friend Hadi Malekghasemi who has greatly

helped and encouraged me in every step of my research. Most importantly, I wish to thank

my parents without whom I would never reach this stage of my life. They bore me, raised

me, supported me, taught me, and loved me and to them I dedicate this thesis. Finally, I

express my genuine appreciation towards the Almighty.

iv

Table of Contents

Abstract .................................................................................................................................................. ii

Acknowledgments ................................................................................................................................. iii

List of Tables ........................................................................................................................................... v

List of Figures ......................................................................................................................................... vi

Chapter 1 ................................................................................................................................................ 1

Introduction ............................................................................................................................................ 1

Chapter 2 ................................................................................................................................................ 5

Flatbed Scanner versus Manual Method ............................................................................................... 5

2.1 Sample Preparation .................................................................................................................. 6

2.2 Scanning Process ...................................................................................................................... 8

2.3 Image Analysis ........................................................................................................................ 12

2.3.1 Theoretical ....................................................................................................................... 12

2.3.2 Threshold Determination ................................................................................................ 14

2.4 Data Analysis .......................................................................................................................... 22

2.5 Threshold Study ...................................................................................................................... 28

2.6 Scanner Settings ..................................................................................................................... 32

2.6.1 Automatic Brightness Adjustment .................................................................................. 32

2.6.2 Image Sharpening Setting ................................................................................................ 34

2.7 Point Count ............................................................................................................................. 36

Chapter 3 .............................................................................................................................................. 39

Flatbed Scanner versus Rapid Air 457 Method ................................................................................ 39

3.1 Sample Preparation ................................................................................................................ 40

3.2 Image Collection and Analysis ................................................................................................ 43

3.3 Air Content and Spacing Factor Results ................................................................................. 45

3.4 Chord Length Distribution ...................................................................................................... 47

3.5 Threshold Study ...................................................................................................................... 49

Chapter 4 .............................................................................................................................................. 52

Conclusion ........................................................................................................................................ 52

References ............................................................................................................................................ 55

v

List of Tables

Table ‎2.1: Statistical Analysis Results. .................................................................................................. 26

Table 2.2: Threshold Values for All and Individual Labs. ...................................................................... 27

Table 2.3: Statistical Data of Different Sample Populations (AC). ........................................................ 29

Table 2.4: Statistical Data of Different Sample Populations (VF). ........................................................ 30

Table 3.1: Statistical Analysis Results. .................................................................................................. 47

Table 3.2: Statistical Data of Different Sample Populations. ............................................................... 50

Table C.1: Point Count Detailed Results. .............................................................................................. 69

Table D.1: Flatbed Scanner versus Manual Method Database. ........................................................... 72

Table E.1: Flatbed Scanner versus Rapid Air 457 Database ................................................................. 91

vi

List of Figures

Figure 2.1: Grinding Apparatus. ............................................................................................................. 7

Figure 2.2: Automated Lapping Machine (Top View). ............................................................................ 7

Figure ‎2.3: Adhesive-Backed 600 Grit Silicon Carbide Paper. ................................................................ 8

Figure ‎2.4: Final Polish Machinery. ........................................................................................................ 8

Figure ‎2.5: Samples after a) Placing Stickers and b) Blackening and Powdering (Scale Bar Represents

20 mm). .................................................................................................................................................. 9

Figure ‎2.6: Screen Shot of Adobe Photoshop Script Showing User Interface and Scanned Slab Image.

.............................................................................................................................................................. 11

Figure ‎2.7: Histograms and Probability Density Functions of Optimum Threshold Levels Determined

for Void Frequency for a) Normal Distribution with μ = 52 and b) General Extreme Value Distribution

with μ = 39. ........................................................................................................................................... 18

Figure ‎2.8: Histogram and Probability Density Functions of Optimum Threshold Levels Determined

for Air Content Fit with a) a Normal Distribution with μ = 71, and Fit with b) a General Extreme Value

Distribution with μ = 47. ....................................................................................................................... 19

Figure ‎2.9: Influence of Threshold Selection Method on Air Content Measurements, with Assumed

Paste Content of 30%: a) Dual Threshold (VF52, AC71) Normal Distribution Method, b) Single

Threshold (62) Normal Distribution Method, c) Dual Threshold (VF39, AC47) Extreme Value

Distribution Method, d) Single Threshold (43) Extreme Value Distribution Method. ......................... 20

Figure ‎2.10: Influence of Threshold Selection Method on Spacing Factor Measurements, with

Assumed Paste Content of 30%: a) Dual Threshold (VF52, AC71) Normal Distribution Method, b)

Single Threshold (62) Normal Distribution Method, c) Dual Threshold (VF39, AC47) Extreme Value

Distribution Method, d) Single Threshold (43) Extreme Value Distribution Method. ......................... 21

Figure ‎2.11: Manual versus Flatbed Scanner Air Content (All Labs). ................................................... 23

Figure ‎2.12: Manual versus Flatbed Scanner Spacing Factor (All Labs). .............................................. 24

Figure ‎2.13: Manual versus Flatbed Scanner Air Content (Lab 3). ....................................................... 24

Figure ‎2.14: Manual versus Flatbed Scanner Spacing Factor (Lab 3). .................................................. 25

Figure 2.15: Manual versus Flatbed Scanner Air Content (Lab 3 Excluded). ....................................... 25

Figure ‎2.16: Manual versus Flatbed Scanner Spacing Factor (Lab 3 Excluded). .................................. 26

Figure 2.17: False Negative Zone for Spacing Factor (Lab 3 and All Labs). .......................................... 27

Figure 2.18: Air Content Threshold of 72 (Proposed Threshold) versus 71 (True Threshold). ............ 30

Figure 2.19: Void Frequency Threshold of 55 (Proposed Threshold) versus 52 (True Threshold). ...... 31

Figure 2.20: Air Content Threshold of 78 (Proposed Threshold) versus 71 (True Threshold). ............ 31

Figure 2.21: Void Frequency Threshold of 57 (Proposed Threshold) versus 52 (True Threshold). ...... 32

Figure 2.22: Without Automatic Adjustment versus Automatically Adjusted Histogram (Air Content).

.............................................................................................................................................................. 33

Figure 2.23: Without Automatic Adjustment versus Automatically Adjusted Histogram (Spacing

Factor). ................................................................................................................................................. 33

Figure 2.24: Sharpened versus Normal Scanner Setting (Air Content). ............................................... 35

Figure 2.25: Sharpened versus Normal Scanner Setting (Spacing Factor). .......................................... 35

vii

Figure 2.26: Spacing Factor Comparison of Point Counting and 30% Assumed Paste Contents. ........ 37

Figure 2.27: Spacing Factor Comparison of Manual and Flatbed Scanner 30% Assumed Paste

Contents. .............................................................................................................................................. 38

Figure 2.28: Spacing Factor Comparison of Manual and Flatbed Scanner 30% Assumed Paste

Contents. .............................................................................................................................................. 38

Figure 3.1: Polishing Apparatus. ........................................................................................................... 41

Figure 3.2: Surface Lapping with Water and Silicon Carbide Grit Suspension. .................................... 41

Figure 3.3: Polished Slabs (Left) and Close-up (Right). ......................................................................... 42

Figure 3.4: Slab after Blackening and White Powder (Left) and after Threshold Application (Right). . 43

Figure 3.5: Wiping Away Excess Powder (Left) and Performing Analysis (Right). ................................ 43

Figure 3.6: Air Content Comparison of Flatbed Scanner and Rapid Air 457. ....................................... 46

Figure 3.7: Spacing Factor Comparison of Flatbed Scanner and Rapid Air 457. .................................. 46

Figure 3.8: Chord Length Distributions from Rapid Air 457, and Flatbed Scanner at Thresholds of a)

115 and b) 140. ..................................................................................................................................... 48

Figure 3.9: Comparison of Flatbed Scanner Spacing Factor Results Using Void Frequency Threshold

Levels of 115 and 120. .......................................................................................................................... 51

Figure A.1: Manual versus Flatbed Scanner Air Content (All Labs). ..................................................... 57

Figure A.2: Manual versus Flatbed Scanner Spacing Factor (All Labs). ................................................ 57

Figure A.3: Manual versus Flatbed Scanner Air Content (No Lab ID). .................................................. 58

Figure A.4: Manual versus Flatbed Scanner Spacing Factor (No Lab ID). ............................................. 58

Figure A.5: Manual versus Flatbed Scanner Air Content (Lab 1). ......................................................... 59

Figure A.6: Manual versus Flatbed Scanner Spacing Factor (Lab 1). .................................................... 59


Figure A.8: Manual versus Flatbed Scanner Spacing Factor (Lab 2). .................................................... 60


Figure A.10: Manual versus Flatbed Scanner Spacing Factor (Lab 3). .................................................. 61

Figure A.11: Manual versus Flatbed Scanner Air Content (Lab 4). ....................................................... 62










Figure B.1: Optimum Threshold Value Distributions for a) Air Content and b) Void Frequency. ........ 67

viii

List of Appendices

Appendix A: .......................................................................................................................................... 57 Comparison Plots of Manual and Flatbed Scanner for Different Labs ............................................. 57

Appendix B............................................................................................................................................ 67 Normal Distributions for Threshold Determination of Rapid Air 457 versus Flatbed Scanner ........ 67

Appendix C ............................................................................................................................................ 68 Point Count Method Detailed Results .............................................................................................. 68

Appendix D ........................................................................................................................................... 71 Flatbed Scanner versus Manual Method Database ......................................................................... 71

Appendix E ............................................................................................................................................ 90

1

Chapter 1

Introduction

Air void parameters of air entrained concrete are closely linked to the freeze and thaw

deterioration of concrete and this phenomenon has for a long time lead the researchers

and the industry to evaluate these parameters for quality control of concrete infrastructure.

In Ontario, Air Void System (AVS) analysis is performed on all new Ministry of

Transportation concrete construction, and the parameters of air content and spacing actor

are used to define the quality of air entrainment [1]. Basically, a minimum volumetric

content of air should be provided and the bubbles must be close enough to one another to

protect the paste from freeze and thaw damage [2]. Air void spacing factor equations have

been introduced by Powers, Philleo, Attiogbe, and Pleau and Pigeon, and Snyder [3].

However, the spacing factor equation developed by Powers is the basis for American

Society for Testing and Materials (ASTM) C457 Standard Test Method for Microscopical

Determination of Parameters of the Air-void in Hardened Concrete [3]. It is described as a

parameter related to the maximum distance in the cement paste from the periphery of an

air void [3,4].

ASTM C457 is frequently used for evaluation of air entrainment in concrete. However,

microscopical examination of polished plane surface of concrete based on this standard is a

tedious and operator dependent procedure. Therefore, in recent years the importance of

achieving automated methods which are less operator dependent and are capable of

2

providing air void parameters of hardened concrete within shortest amount of time has

lead researchers to evaluate different ideas to automate the air void analysis of hardened

concrete.

Most of the new methods use digital image processing and contrast enhancement methods

to analyze air void system of concrete [5,6,7,11]. Rapid Air 457 and flatbed scanner methods

are two methods capable of providing air void parameter results comparable to the

standard manual test method according to a few small scale studies [7,8]. Both of these

methods are much less tedious compared to the manual test method [6,8,9,10,11,12] and

therefore, have gained popularity. For the Rapid Air 457, the operator sets a threshold level

for each analysis to distinguish air voids. The total traverse length, the length traversed in

air, the length traversed in paste, and the number of air voids intersected are provided by

this method. The air content, specific surface and spacing factor are then calculated.

Jakobsen et al. [6] describe techniques for Rapid Air 457 automatic analysis of concrete

samples as well as data from a round robin study in which samples were circulated to 7

different laboratories for automatic air void analysis. Also, for comparative study samples

were analyzed manually using linear traverse and point counting methods according to

ASTM C 457 [6]. The flatbed scanner method uses an ordinary flatbed scanner to scan the

prepared samples. Image analysis is then implemented to give air void parameters such as

air content and spacing factor. This method is very cost effective and convenient in

comparison with both the manual and Rapid Air 457 methods of analysis since it is

compromised of a computer and an inexpensive scanner and also the whole process of

scanning and analysis takes around just a few minutes depending on the brand of scanner.

3

Assessment of the amount and size distribution of entrapped air in concrete using a high

resolution flatbed scanner has also been implemented recently [13] in which image of the

curved surface with no distortion is provided by rolling the core surface on the scanner

using a traverse trolley. High resolution industrial computed tomography (CT) x-ray scan

method is another emerging technology to measure air void parameters in hardened

concrete [14, 15]. Yun et al. [14] have evaluated the ability of x-ray tomography to

quantitatively analyze the distribution of paste-void spacing in concrete. As a non-

destructive technique, CT scan can produce resolutions on the order of 10 microns or less.

However, other than cost and safety issues, small diameter samples are required to attain a

satisfactory resolution in CT scan.

Among the old and new air void system analysis methods, the flatbed scanner has been

under research and examination since scanners have become inexpensive and widely

available. In this study the flatbed scanner method of air void analysis is compared with

manual examination and Rapid Air 457 methods of analysis using 324 and 105 samples for

these comparisons respectively. Similar studies have been performed, but never with such

large population of samples [7,11,17]. A threshold optimization routine described by

Peterson et al. [8, 19] is employed along with scripts written in Adobe Photoshop to analyze

the scanned images and report the required air void parameters. For chapter 2 of this

dissertation, a set of 324 samples with air content and spacing factor parameter results

from manual examination are analyzed by the flatbed scanner method and the results are

used for comparison between the two methods. Another set of 105 samples with Rapid Air

457 parameter results are analyzed by the flatbed scanner method and the results are

4

compared and reported in chapter 3. In both of these chapters a more detailed threshold

study for image analysis of the samples has been provided.

.

5

Chapter 2

Flatbed Scanner versus Manual Method

The Ministry of Transportation of Ontario (MTO) requires air void analysis of concrete to be

conducted by approved laboratories for quality assurance as specified in the OPSS 1350

Material Specification for Concrete Materials and Production. In this regard air content of

over 3 percent (%) by volume and spacing factor below 0.23 mm are the accepted limits of

these parameters and the contractor receives a penalty by failing to achieve these limits. On

the other hand, for spacing factors between 0.1 and 0.15 mm and air contents in the range

of 4.5 to 6.5 volume %, the contractor receives bonuses [1]. Manual air void analysis is

performed according to MTO Test Method LS-431 [18] through microscopical examination

of concrete cores. However, as mentioned in chapter 1, this analysis is very time consuming

(up to several hours per sample) and operator dependent resulting in variation of the

results. Flatbed scanner as an automated method has the potential to reduce variation of

the results, and also solves time and cost issues involved with the manual method of

concrete core examination. Prior to this research, comparison between the results of this

method with the manual method has not yet been implemented in a large scale. In this

chapter the results of 324 samples analyzed by both the flatbed scanner and manual

methods are compared and discussed. Two important air void parameters, namely the air

content and spacing factor found by both methods are compared statistically. A detailed

6

study for determination of threshold using different portions of samples has also been

implemented in section 2.5.

Also, specific populations of samples were scanned with different scanner settings in order

to capture their impact on the results of air content and spacing factor (section 2.6).

Moreover, a point counting procedure is employed to estimate paste content percentage

for a population of 77 samples (section 2.7).

2.1 Sample Preparation

In order to eliminate variations between test results from a single concrete core due to

different sample preparation procedures, all of the sample surfaces coming from different

laboratories were ground, and re-polished for this study. The laboratory-prepared surfaces

were removed (about 1 mm) by applying hand pressure on a rotating water-cooled 80 grit

diamond 200 mm diameter platen shown in Figure 2.1. Then the sample surfaces were

lapped flat to within 2 μm from edge to edge for a period of 12 minutes using water and

loose 600 grit silicon carbide on the automated lapping machine shown in Figure 2.2.

7

Figure 2.1: Grinding Apparatus.

Figure 2.2: Automated Lapping Machine (Top View). Due to possible erosion of edges that define the perimeter of the entrained air-voids

exposed at the surface during polishing, a dilute solution of nitrocellulose in acetone (5:1

acetone to commercial clear fingernail polish) was applied on the polished surfaces [16]. As

a final step, surfaces were polished on a rotating lap covered with a sheet of adhesive-

backed 600 grit silicon carbide paper shown in Figures 2.3 and 2.4.

8

Figure 2.3: Adhesive-Backed 600 Grit Silicon Carbide Paper.

Figure 2.4: Final Polish Machinery. It should be considered that due to the limitations of machinery used in this study (i.e. 300

mm diameter platen of the automated lapping machine) sample sizes could not exceed 100

mm × 75 mm. Therefore, the cores were cut into two approximately equal segments

representing the top and bottom of the core. Also, the surfaces were cleaned with air-water

pressure between grinding, lapping and polishing steps.

2.2 Scanning Process

In this stage the prepared samples were scanned and analyzed to get the required

parameters such as air content and spacing factor. Before scanning, stickers were placed on

9

the corners of the polished surfaces (Figure 2.5a) to prevent the polished surface from

scratching the scanner surface.

a)

b)

Figure 2.5: Samples after a) Placing Stickers and b) Blackening and Powdering (Scale Bar Represents 20 mm).

10

An EPSON Perfection V500 photo scanner was used to collect all of the images in this study.

As a first step 24 bit color images were collected at a resolution of 125 dpm (3,175 dpi) for

further studies involving point counting which is covered in section 2.7 of this study.

A second scan is performed after the following contrast enhancement (Figure 2.5b) steps:

The polished surface of samples were darkened by drawing approximately overlapping

parallel lines with a wide tipped black opaque pigment marker (SAKURA Color Products

Corporation, Japan). Darkening was implemented in two coats, changing the orientation

90° between coats.

Then, the dry darkened surface was covered with 2 μm median size white powder

(NYCO Minerals Inc. NYAD 1250 wollastonite) and the powder was pushed into the

sample surface filling nearly all of the surface voids. A razor blade was then used to

scrape away excess powder. Also, surface was wiped off with an oily fingertip leaving a

shiny black and white surface.

A fine tipped black marker (Sharpie brand) was used to darken voids in aggregates with

the help of a stereo microscope.

After preparing the sample surfaces, 8-bit grayscale images at the resolution of 125 dpm

(3,175 dpi) were collected with all automatic image enhancement scanner software options

deactivated. A flat steel plate having black and white vinyl electrical tape was placed on top

of each sample to act as a reference defining the upper and lower brightness limits in the

analysis (Figure 2.6). In the Adobe Photoshop script, the first step is to identify the location

of the black and white reference. A histogram stretch is performed by the script on the

entire image to assign a value of zero for any portion of the sample darker than the black

11

reference and a value of 255 for any portion of the sample brighter than the white

reference. Therefore, the threshold level used to distinguish between air and non-air may

remain consistent from scan to scan.

Figure 2.6: Screen Shot of Adobe Photoshop Script Showing User Interface and Scanned Slab Image.

12

2.3 Image Analysis

As mentioned earlier, in this study the air content and spacing factor are the two

parameters required by the MTO, and these parameters were used for comparison of

flatbed scanner results with manual examination results. Image analysis for the scanned

images was implemented in Adobe Photoshop software using scripts. In many image

analysis schemes, including the flatbed scanner method, a simple threshold level must be

set in order to identify features of interest. However, a description of the threshold

determination routine used in this study first requires a full explanation of air void

parameters and formulas involved with it. Therefore, in this section these parameters and

formulas is summarized and then threshold determination will be described in details.

2.3.1 Theoretical

Air void parameters defined in ASTM C457 are as follows:

Average Chord Length ( ): the average length of the chords formed by the intersection of

the voids by the line of traverse; the unit is a length.

Paste-air Ratio (p/A): the ratio of the volume of hardened cement paste to the volume of

the air voids in the concrete.

Paste Content (p): the proportion of the total volume of the concrete that is hardened

cement paste expressed as percentage by volume.

Spacing Factor ( ): a parameter related to the maximum distance in the cement paste from

the periphery of an air void, the unit is length.

13

Specific Surface (α): the surface area of the air voids divided by their volume, expressed in

compatible units so that the unit of specific surface is a reciprocal length.

Void Frequency (n): voids per unit length of traverse; the number of air voids intercepted by

a traverse line divided by the length of that line.

Below are formulas from ASTM C457 which are used in this study to calculate air content,

void frequency and spacing factor:

Air Content (A), in %:

Void Frequency (n):

Average Chord Length ( ):

or

Specific Surface (α): α

Paste Content (p), in %:

Paste-Air Ratio (p/A):

Spacing Factor ( ) =

where:

= total length of traverse.

= traverse length through air.

= traverse length through paste.

14

2.3.2 Threshold Determination

In this study, for determination of a threshold level, manual AVS test results of MTO-

approved laboratories are used to “train” the automated scanner method [19]. In other

words, for any individual sample a threshold level exists that can best approximate the

“true” value of the air void parameter. In this study, results from MTO-approved

laboratories are taken as the true values. The threshold for the scanned image is adjusted

until the measured air void parameter by flatbed scanner analysis best matches the results

of MTO manual examination. Therefore, by analyzing a significant population of scanned

images from samples with manual AVS test results, a threshold optimization routine has

been developed and is applied to find a single threshold level that is appropriate for all of

the samples. Since air content (AC) and void frequency (VF) are the only physical

parameters measured by the flatbed scanner analysis, thresholding is implemented based

on these two values.

In the flatbed scanner method of analysis a series of lines are extracted with a total line

length on the order of 4 m. The air content parameter is determined by the number of air-

pixels in the line divided by the total number of pixels in the line. The void frequency

parameter is measured by the number of air-void intercepts with the line divided by the

total line length. From these two parameters and the paste content from mix design

information, the spacing factor can be computed. Paste content can also be determined by

manual point counts performed on the color images. This is explained in details in section

2.7.

15

Air content and spacing factor are the only two parameters with specified limits in

OPSS1350. These two values were also the only parameters provided for this study by the

MTO for more than half of the samples. Therefore, an assumed paste content of 30% was

substituted into the spacing factor formula for these samples to determine the void

frequency. The assumed value of 30% for paste content is based on typical MTO concrete

mixtures, and has been used in previous air entrainment studies [7]. For the rest of the

samples, values for specific surface were also included, along with air content and spacing

factor. Having specific surface known for these samples, the void frequency was calculated

directly using the specific surface and air content values without the need to assume a value

for paste content.

The calculation procedures are illustrated below:

If specific surface ( ) is known, void frequency ( ) can be found using cord length:

Paste content not included

If specific surface is unknown void frequency ( ) can be found using spacing factor and

assuming paste content of 30%:

Spacing Factor ( ) =

If

=

where

, and

Then

16

If

Specific surface can be found from =

Then void frequency will be found from the following:

and

Once the manual results for void frequency were calculated for each sample the ideal

threshold levels were determined using a script that iterates through different thresholds to

best approximate the manually determined values for air content and void frequency. To

perform the iterations for all of the 324 samples in this study the script required only a few

hours to find appropriate thresholds for air content and void frequency. In order to help

determine a consistent value of threshold suitable for the two parameters, the entire

population of optimum threshold levels were fit using both normal and extreme value

distributions, and the parameter μ used as the fixed threshold level (Figures 2.7 and 2.8).

Following are the equations of the two distributions:

Normal Distribution

Generalized Extreme Value Distribution

Two different approaches of thresholding were applied: a single threshold approach, and a

dual threshold approach. These two approaches were explored along with the use of

normal and extreme value distributions to identify the best case for threshold

determination. In single thresholding, the average of the void frequency and air content

thresholds was used, while, in the case of dual thresholding, separate air content and void

17

frequency thresholds were used individually. Having two different distributions, four cases

can be investigated as shown in Figures 2.7 and 2.8. Note that threshold levels must consist

of whole numbers from 0 to 255 (all threshold units in this paper were rounded to the

nearest whole number).

To find the best thresholding method, air content and spacing factor parameters were

assessed according to two types of errors, Type I and Type II. According to OPSS 1350 and

MTO, air content above 3% and spacing factor smaller than 0.23 mm are acceptable values

for these parameters. A Type II error (false-negative) represents a situation where flatbed

scanner reports a spacing factor of smaller than 0.23 mm while the true value (manual data)

is above 0.23. In the case of air content, a Type II error (false-negative) represents a

situation where the flatbed scanner recognizes more than 3% air content while the true

value is below 3%. Type II false-negative errors must be avoided, especially from the

owner’s perspective. On the other hand, a Type I error (false-positive) occurs when flatbed

scanner finds spacing factor larger than 0.23 mm, while the true value is below 0.23mm. For

air content, a Type I error (false-positive) occurs when the flatbed scanner reports a value

below 3% air content while the true value is above 3%. It should be noted that a Type I error

is not as crucial for the owner as it is for the contractor. Ideally, none of the data points

should fall within the false-positive and false–negative zones. These areas as well as the

number of data points that fall in each of them are shown in Figures 2.9 and 2.10. Based on

the above considerations, the use of a normal distribution, and dual thresholding came to

be the best choice as it minimizes both Type I and II errors.

18

a)

b)

Figure 2.7: Histograms and Probability Density Functions of Optimum Threshold Levels

Determined for Void Frequency for a) Normal Distribution with μ = 52 and b) General

Extreme Value Distribution with μ = 39.

19

a)

b)

Figure 2.8: Histogram and Probability Density Functions of Optimum Threshold Levels

Determined for Air Content Fit with a) a Normal Distribution with μ = 71, and Fit with b) a General Extreme Value Distribution with μ = 47.

20

a) b) c) d)

Figure 2.9: Influence of Threshold Selection Method on Air Content Measurements, with Assumed Paste Content of 30%: a) Dual Threshold (VF52, AC71) Normal Distribution Method, b) Single Threshold (62) Normal Distribution Method, c) Dual Threshold (VF39, AC47) Extreme Value

Distribution Method, d) Single Threshold (43) Extreme Value Distribution Method.

21

a) b) c) d) Figure 2.10: Influence of Threshold Selection Method on Spacing Factor Measurements, with Assumed Paste Content of 30%: a) Dual Threshold (VF52, AC71) Normal Distribution Method, b) Single Threshold (62) Normal Distribution Method, c) Dual Threshold (VF39, AC47) Extreme Value

Distribution Method, d) Single Threshold (43) Extreme Value Distribution Method.

22

2.4 Data Analysis

In the previous section the normal distribution dual threshold approach was chosen as the best

case, in which a threshold value of 52 was used for the void frequency and a threshold of 71

was used for the air content. Using these two thresholds the scanned images were analyzed by

the Photoshop scripts and the results of this analysis (flatbed scanner) were compared with

those of manual method. Results of all 324 samples coming from at least 8 different MTO

approved labs are plotted for both air content and spacing factor (Figures 2.11 and 2.12). In all

of the plots in this section, other than data points, a trend line of linear regression analysis and

the x=y line (called the line of equity in this study) are illustrated. The best case for our study

occurs when data are as much as possible on and around the line of equity which means that

flatbed scanner is giving the same air content or spacing factor as the manual method of AVS

analysis.

It can be seen that the results are comparable and flatbed scanner appears to output air

content and spacing factor values near to those of manual method (Figure 2.11 and 2.12).

As explained in section 2.3.2, for a smaller population of 121 samples coming from Lab 3 in this

study, specific surface parameters were known. For these samples, the void frequency was

directly calculated with no assumption for the paste content in the thresholding stage. To

explore the effect of assuming a paste content value in determination of void frequency

threshold, two sets of plots are given in this study for air content and spacing factor. Figures

2.13 and 2.14 are comparison plots of Lab 3 results for air content and spacing factor, while,

Figures 2.15 and 2.16 present all of the results excluding Lab 3.

23

A statistical analysis of the three sets of plots is reported in Table 2.1. In this table, average

deviation from zero difference between manual and flatbed scanner values are calculated as

shown below; and reported along with regression analysis of the results.

=

According to the regression analysis (Table 2.1) Lab 3 data has given a slightly better R2 value.

Also, deviation for this particular lab is to some extent less as illustrated in Table 2.1. The

performance can also be assessed through the number of false negative occurrences for

spacing factor. As shown in Figure 2.17, 14 data points fall in the false negative zone for all 324

samples (4.3%), however, in the case of lab 3 only 1 of 121 data points (0.8%) falls in this zone.

Figure 2.11: Manual versus Flatbed Scanner Air Content (All Labs).

24

Figure 2.12: Manual versus Flatbed Scanner Spacing Factor (All Labs).

Figure 2.13: Manual versus Flatbed Scanner Air Content (Lab 3).

25

Figure 2.14: Manual versus Flatbed Scanner Spacing Factor (Lab 3).

Figure 2.15: Manual versus Flatbed Scanner Air Content (Lab 3 Excluded).

26

Figure 2.16: Manual versus Flatbed Scanner Spacing Factor (Lab 3 Excluded).

Table 2.1: Statistical Analysis Results.

Samples Air Content Spacing Factor

--- Deviation

(vol%) R2

Deviation (mm)

R2

All Labs 1.634 0.44 0.049 0.36

Lab 3 1.539 0.5 0.036 0.56

Lab 3 Excluded

1.688 0.4 0.055 0.33

27

Figure 2.17: False Negative Zone for Spacing Factor (Lab 3 and All Labs).

A database containing all of the data and analysis results is provided in Appendix D (Table D-1).

Also, a detailed comparison between the results of flatbed scanner and manual method for all

other labs has been implemented and the plots are presented in Appendix A. Figures of air

content and spacing factor showing all of the lab results with different colors is presented in

Appendix A as well. Table 2.2 shows threshold values determined for individual labs.

Table 2.2: Threshold Values for All and Individual Labs.

Lab ID Optimum Air

content Threshold

Optimum void frequency Threshold

No Lab ID 42 60

Lab 1 79 69

Lab 2 44 61

Lab 3 48 78

Lab 4 66 61

Lab 5 39 27

Lab 6 94 74

Lab 7 53 84

Lab 8 41 52

Average Value 52 71

28

2.5 Threshold Study

Threshold values mentioned and used above were found using all 324 samples. In other words,

all 324 manual results were used to train the flatbed scanner analysis. However, to explore

whether a smaller population of samples can give the same threshold values, average air

content (AC) and void frequency (VF) thresholds are found for different population of samples.

The results are reported in Tables 2.3 and 2.4.

From the statistical results in tables 2.3 and 2.4, it can be concluded that half of the samples

can be used to ideally predict the required thresholds for analysis of all samples with average

deviations as small as 1.25 for air content (AC) and 3.07 for void frequency (VF). Also, choosing

one third and one fifth of the total 324 samples to find the threshold gives very close answers

to those of all samples. Selecting one tenth of samples however reports acceptable threshold

values in the case of AC only. In the case of VF threshold, choosing one tenth of samples results

in a high variance among the five populations corresponding to a lower reliability. In order to

verify the accuracy of the threshold coming from half of the samples, AC and VF deviated

threshold values (or 71+1 72 and 52+3.07 55) are used and the resulting air content and

spacing factor values are compared with those analyzed with the true threshold AC and VF

values of 71 and 52 (Figures 2.18 and 2.19). As it is obvious in these figures, choosing only half

of the samples for the purpose of thresholding and applying this threshold to all other images is

ideal for flatbed scanner analysis. Also, using threshold values of one third and one fifth of total

samples gave a threshold value of 78 (71+7 78) for AC and using this threshold gives suited

results when used for all samples analysis (Figure 2.20). Use of the threshold from one tenth of

samples for AC was not encouraging due to high variance reported in Table 2.3. In the case of

29

VF using threshold values coming from one third, one fifth, and also one tenth of samples (or

52+4 57) has given a fitted results when used for all samples analysis (Figure 2.21). This

statistical study considering that the samples used for this study are from different concrete

structures shows that employing a combination of manual and flatbed scanner methods where

only a portion of the samples need to be analyzed manually is valid for threshold determination

of flatbed scanner method. For a large number of samples similar to this study, a set of 160

samples seems to be a very good representative of all samples for threshold determination.

Table 2.3: Statistical Data of Different Sample Populations (AC).

Number of Samples out of 324 Samples

Trial # Average AC Threshold

Value (True Value = 71)

Variance and Average Deviation from True

Value

162 (half of total population)

1 71

Variance=1.5 Deviation=1

2 72

3 71

4 70

5 72

108 (one third of total population)

1 64

Variance=38 Deviation=6

2 68

3 65

4 77

5 63

66 (one fifth of total population)

1 65


2 79

3 69

4 59

5 74

32 (one tenth of total population)

1 51


2 67

3 75

4 79

5 87

30

Table 2.4: Statistical Data of Different Sample Populations (VF).


Trial # Average VF Threshold

Value (True Value = 52)

Variance and Average Deviation from True

Value


1 49

Variance= 9.4 Deviation=3.07

2 51

3 52

4 55

5 57


1 46

Variance= 11 Deviation=3.3

2 49

3 50

4 52

5 54


1 48

Variance=13 Deviation=3.6

2 50

3 51

4 52

5 59

32 (one tenth of total population)

1 51

Variance= 22 Deviation= 5

2 52

3 54

4 54

5 62

Figure 2.18: Air Content Threshold of 72 (Proposed Threshold) versus 71 (True Threshold).

31

Figure 2.19: Void Frequency Threshold of 55 (Proposed Threshold) versus 52 (True Threshold).

Figure 2.20: Air Content Threshold of 78 (Proposed Threshold) versus 71 (True Threshold).

32

Figure 2.21: Void Frequency Threshold of 57 (Proposed Threshold) versus 52 (True Threshold).

2.6 Scanner Settings

In this section, possible effects of scanner settings on the image and therefore on the results of

flatbed scanner method are investigated. Settings such as automatic brightness adjustment and

auto sharpening were chosen to be further studied in this section.

2.6.1 Automatic Brightness Adjustment

In most scanner driver software, there is the possibility for the automatic adjustment of the

brightness of the scanned image. In an 8-bit grayscale image, 0 represents the darkest and 255

the brightest pixels in an image. The EPSON scanner used in this study performs an automatic

adjustment based on the brightness histogram for each scanned image. In other words, it

adjusts the locations of the bright and dark end points, and the midpoint. A subset of the 324

33

samples was scanned using the automatic adjustment, and repeated without the automatic

adjustment, and the results are presented in Figures 2.22 and 2.23.

Figure 2.22: Without Automatic Adjustment versus Automatically Adjusted Histogram (Air

Content).

Figure 2.23: Without Automatic Adjustment versus Automatically Adjusted Histogram (Spacing

Factor).

34

As shown in Figures 2.22 and 2.23, most of the data points are on or near the line of equity

indicating that automatic brightness adjustment does not have a significant effect on the

results for both air content and spacing factor. The reference black and white vinyl electrical

tape present at the top of each scanned image (section 2.2 and Figure 2.6) is what the Adobe

Photoshop script uses as end points. Therefore, even if the end points and mid points vary from

scan to scan, as they do when the automatic brightness is used, the effect is mitigated by the

utilization of the black and white reference included in each scan.

2.6.2 Image Sharpening Setting

Another common setting in almost every scanner is automatic sharpening which is used to

make the images sharper and less blurry. An important consideration is that some of the details

in the image might be changed with automatic sharpening. Therefore, in flatbed scanner

method it is of crucial importance to have the sharpening and other auto-adjustment tools

turned off while scanning. In order to investigate how these tools can affect the results of

flatbed scanner method, a small population of the samples were scanned having auto-

sharpening turned on and the results are compared with those of normal setting (auto-

sharpening off) and presented for both air content and spacing factor in Figures 2.24 and 2.25.

As it can be seen in these figures, sharpening the images has a considerable negative effect on

the results, in the case of spacing factor, but not as pronounced in the case of air content. This

is due to the fact that sharpening enhances the contrast between brighter and darker regions.

This results in inclusion of small air bubbles that are not literally present. Therefore, Adobe

Photoshop script reports a higher void frequency, which leads to a lower value for spacing

35

factor. However, air content is not considerably affected because these added fake air voids are

very small, and therefore do not change the overall air content very much.

Figure 2.24: Sharpened versus Normal Scanner Setting (Air Content).

Figure 2.25: Sharpened versus Normal Scanner Setting (Spacing Factor).

36

2.7 Point Count

As mentioned in section 2.3 a paste content value of 30% was assumed for the purpose of

image analysis in this study. In an effort to explore whether paste content can be better

approximated, manual point counting was implemented on the 24 bit color images collected

from the samples prior to the black and white treatment. To carry out point counting, images

are divided into 500 frames with a cross-hair at the centre in Adobe Photoshop using a script.

Then, for each frame, an operator answers “yes” or “no” as to whether or not the cross-hair is

on an aggregate. With this manual point counting aggregate fractions are determined as

follows:

where

P = Paste content (vol. %) where paste is defined as the total concrete volume minus the aggregate and air volumes. A = Air content (vol. %) from automated AVS test result. Agg = Aggregate content (vol. %) from manual point count.

A population of 77 samples coming from Lab 3 was selected for point counting in this research.

Spacing factor values calculated with individual paste content values coming from point

counting were compared with those of calculated using the 30% paste content assumption

(Figure 2.26). Furthermore, manual spacing factor values are plotted with flatbed scanner

spacing factors calculated based on individual point count results (Figure 2.27) and with flatbed

scanner spacing factor values resulted from 30% assumed paste content (Figure 2.28). As

illustrated in Figure 2.26 the flatbed scanner reports slightly higher spacing factor values using

point counted paste content results. Deviation from manual results in both cases of point

37

counting paste content results and 30% paste content assumption are 0.047 and 0.036 mm

respectively. It should be considered that although this point counting method can assist in

predicting the paste content values, it is operator dependent and in this study only one

operator has performed the point counts. A table containing individual point counting results is

provided in Appendix C (Table C-1).

Figure 2.26: Spacing Factor Comparison of Point Counting and 30% Assumed Paste Contents.

38

Figure 2.27: Spacing Factor Comparison of Manual and Flatbed Scanner 30% Assumed Paste Contents.

Figure 2.28: Spacing Factor Comparison of Manual and Flatbed Scanner 30% Assumed Paste Contents.

39

Chapter 3

Flatbed Scanner versus Rapid Air 457 Method

Rapid Air 457 method of analysis is being used by many companies and universities around the

world and as previously mentioned it is capable of providing air void parameter results

comparable to the ASTM C457 standard [7, 10]. In this chapter this automated method is

compared with the flatbed scanner method of air void analysis. Similar studies have been

performed comparing the Rapid Air 457 and flatbed scanner methods, but never with such a

large population of samples as in this study [7,11,17].

In order to investigate the correlation between flatbed scanner results with those of Rapid Air

457, air content and spacing factor results of 105 samples analyzed by both the Rapid Air 457

and flatbed scanner methods are found and compared. Other than air content and spacing

factor normalized void frequency chord length distribution graphs from both methods are

plotted and studied. Also, different populations of samples are studied to find a specific number

of samples which would be adequate to find an acceptable threshold for image analysis of all

samples.

This chapter includes materials that are also presented in a paper by the author that is accepted

for publication in the proceedings of the 35th annual meeting of the international cement

microscopy association (ICMA).

40

3.1 Sample Preparation

For both automated methods, the sample surfaces need to be flat and smooth, and clear of any

rough texture. Polishing was performed on a Struers Abripol machine, using a steel screen

embedded with 250 µm diamond. The screen attaches to a magnetic rotating platen. The

specimen is then attached to a sample holder via double sided tape. A yellow crayon is used to

draw a crisscross grid across the surface to be polished. The sample holder is then attached to

the polisher head and the process begins. Depending on the condition of the screen and

concrete, the yellow crayon is removed in as little as 35 seconds or up to 2 minutes. The 250

µm screen is then changed for the 68 µm screen and the same process is repeated for 1 to 2

minutes. Note that water is used as the lubricant for this process (Figure 3.1).The specimen

surface is then rinsed with water, patted dry and then held under an air hose to remove water

from voids until completely dry. At this point, the surface appears very smooth with a light

sheen. A 12-inch cast iron lapping platen with concentric circles cut into the surface is then

placed onto the Abripol machine along with attaching the specimen holder. The machine runs

for two minutes while it is wetted with a splash containing a solution of 800 grit silicon carbide

(12 µm) and water (10/90 grit/water ratio) (Figure 3.2). This process is then repeated with a

1000 grit silicon carbide (7 µm). The specimen is then rinsed, dried with air hose and placed into

a 100 oven for 2 hours. Figure 3.3 shows examples of the polished surfaces.

41

Figure 3.1: Polishing Apparatus.

Figure 3.2: Surface Lapping with Water and Silicon Carbide Grit Suspension.

For contrast enhancement of the samples, they are blackened with an inked stamp pad and left

for 30 minutes to dry followed by gently removal of the excess ink with a soft, lint free cloth.

Then, a non-abrasive white powder (barium sulfate, BaSO4) of small enough particle size (3-7

µm) is applied to fill all the voids on the blackened polished surface. A small vibrating table is

used to ease the filling voids with the powder. The excess powder is removed using the palm of

the hand. Note that a very small amount of mineral oil can be rubbed onto the palm to enhance

the removal process.

42

Figure 3.3: Polished Slabs (Left) and Close-up (Right).

Finally, the aggregates are blackened with a marker to exclude aggregate voids (Figure 3.4), and

the sample placed on the Rapid Air 457 stage for analysis (Figure 3.5). A camera and a

motorized stage are used to collect digital images of the prepared surface. The pixel dimensions

in the images are 1.1 by 1.1 µm, which is suitable for the detection of air void intercepts with

diameters on the order of 10 µm. The operator sets a threshold level for each analysis to detect

the air voids. Traverse lines are applied to the images. The total traverse length, the length

traversed in air, the length traversed in paste, the number of air voids intersected, and the

chord length distribution are provided by this method. The air content, specific surface, and

spacing factor are then calculated, using a pre-determined value for paste content [12,20].

43

Figure 3.4: Slab after Blackening and White Powder (Left) and after Threshold Application (Right).

Figure 3.5: Wiping Away Excess Powder (Left) and Performing Analysis (Right).

3.2 Image Collection and Analysis

After analysis by the Rapid Air 457, small stickers were placed at the four corners of each

sample, and the samples were scanned in 8-bit grayscale at a resolution of 125 dpm (3,175 dpi)

44

with the EPSON scanner similar to chapter 2. Then, the same image analysis in Adobe

Photoshop as is explained in chapter 2 was applied to find AVS parameters.

Air content and void frequency are the only physical parameters directly measured by both the

Rapid Air 457 and the flatbed scanner methods. The spacing factor is calculated using these

parameters, along with a pre-determined value for the paste content. In this study, the paste

content was computed from the mix design. For the Rapid Air 457, a single threshold level is

selected by the operator. For the flatbed scanner routine employed here, two thresholds are

used: one to determine air content, and another to determine void frequency as explained in

chapter 2 as well. This approach is used to minimize errors that may occur due to the

competing nature of the air content and void frequency parameters. To efficiently detect small

voids, the threshold level tends to be set lower, which at the same time will inflate the values

for air content. By performing the thresholding separately for each parameter, the errors are

minimized [19]. In order to find a set of appropriate thresholds, a subset of samples for which

the air void parameters are already known are analyzed iteratively by the script. The threshold

levels that yield the closest match to the air content and spacing factor values reported by the

Rapid Air 457 for each individual sample are recorded. Then, a normal distribution is used to

find the average value for each threshold (Figure B-1 in Appendix B). These values are in turn

set as constant for all of the analyses. Using the entire population of 105 samples, threshold

values of 132 and 115 are found for air content and void frequency respectively. Again, it

should be noted that due to the discrete nature of the 8-bit grayscale images, threshold values

are restricted to integer values.

45

3.3 Air Content and Spacing Factor Results

The results of the two automated methods are plotted in Figures 3.6 and 3.7. In these plots

both the trend line of the linear regression analysis and the x=y line (the line of equity) are

illustrated. As shown in Figures 3.6 and 3.7, there exists a reasonably good correlation between

the results of both methods. Average deviation from difference of zero (deviation from equity

line) between the results is 0.64 vol % in the case of air content and 0.06 mm for spacing factor

(Table 3.1). Regression analysis of the results yields an R2 value of 0.88 for both the air content

and spacing factor (Table 3.1). Although the correlation is reasonably good, the flatbed scanner

appears to consistently overestimate the spacing factor at values above 0.3 mm relative to the

Rapid Air 457 results. Furthermore, there are a few notable outliers present in the spacing

factor data. It should be noted that since spacing factor values higher than 0.3 mm are well

beyond the MTO limit of 0.23 mm, the slight overestimation by the flatbed scanner is not as

crucial; that is, samples that have exceeded the acceptable limit are still readily identified. A

database containing all of the data and analysis results is provided in Appendix E (Table E-1).

46

Figure 3.6: Air Content Comparison of Flatbed Scanner and Rapid Air 457.

Figure 3.7: Spacing Factor Comparison of Flatbed Scanner and Rapid Air 457.

47

Table 3.1: Statistical Analysis Results.

Air Content Spacing Factor

Deviation (%) R2 Deviation (mm) R2

0.64 0.88 0.06 0.88

3.4 Chord Length Distribution

A comparison of chord length distributions of the two methods was also performed. The

comparison is complicated by the fact that two different thresholds are used by the flatbed

scanner method, which would yield two different chord length distributions, one resulting from

the void frequency threshold level of 115, and another resulting from the air content threshold

level of 132. In order to compare the two methods, the chord length distribution resulting from

the void frequency threshold is used to include the smallest air voids detected by the scanner.

Figure 3.8a illustrates distributions of the two methods for a single sample with air content and

spacing factor values within the “good” range (air content = 4.74 vol. %, spacing factor = 0.14

mm). It can be seen that for chord lengths above 0.07 mm, the flatbed scanner reports slightly

more air void intercepts than the rapid Air 457, and below 0.07 mm, the flatbed scanner

reports slightly less air void intercepts than the Rapid Air 457. This same pattern is also seen for

the rest of samples. To also explore the influence of choice of threshold level for the flatbed

scanner method, Figure 3.8b shows the chord length distribution obtained using a threshold

level of 140. The difference between the flatbed scanner chord length distributions at

thresholds of 115 and 140 is negligible.

48

Figure 3.8: Chord Length Distributions from Rapid Air 457, and Flatbed Scanner at Thresholds of

a) 115 and b) 140.

49

In an associated comparative investigation undertaken at W.R. Grace, a selection of these same

‘reference’ samples, which had been previously tested in the Grace Laboratory in Cambridge,

were also tested using the University of Toronto Rapid Air 457 and on a new second Rapid Air

457 machine at the Grace Laboratory. The results of chord length distribution and associated

data obtained for the second Grace Rapid Air 457 equated reasonably well with the data shown

in Figure 3.8 for the Toronto Rapid Air 457 machine for the selected samples. However, it was

also noted that the frequency of the extremely fine chord lengths as indicated by the peaks at

0.03mm was noticeably higher on both the Toronto machine and new Grace machine, than had

been previously recorded on the older Grace machine. This effect was most pronounced for a

coarser mean sized air void reference sample. Close examination of the camera and associated

threshold imaging on the new Rapid Air 457 machine indicated that additional ‘noise’ was now

being included in the subsequent air void analysis, this being primarily recorded as an increase

in the frequency of the very fine chord lengths, such as shown in Figures 3.8. Fine tuning of the

image capture settings was subsequently able to remove this effect giving the new machine

comparable results to the older Grace system, without significantly affecting the other air void

parameters.

3.5 Threshold Study

To explore whether a smaller population of samples can give the same threshold values,

average void frequency thresholds are found for different populations of samples. The results

are as follows in Table 3.2.

50

Table 3.2: Statistical Data of Different Sample Populations.


Trial #

Average Void Frequency

Threshold Value (True Value =115)

Variance and Deviation from

True Value


1 106

Variance=18.96

Deviation=4.5

2 113

3 115

4 116

5 119


1 108

Variance=28.96

Deviation=5.4

2 112

3 116

4 120

5 123


1 109

Variance=45.04

Deviation=8.6

2 118

3 121

4 126

5 128

The statistical data from Table 3.2 shows that choosing only half of the samples to explore a

threshold for all samples gives a very close answer to that of coming from all samples, with a

deviation as small as 4.5. On the other hand, choosing one third and one fifth of total

population to find the threshold, also gives small amount of deviation. However, it must be

noted that in comparison with the population containing half of the samples, third and fifth

portions introduce a higher variance. In order to verify the accuracy of the threshold coming

from half of the samples, the most deviated value (or 115+4.5 120) is used as a threshold and

the spacing factors are compared with those analyzed with the true threshold value of 115

(Figure 3.9). As shown in Figure 3.9, choosing only half of the samples for the purpose of

thresholding and applying this threshold to all other images appear sufficient for flatbed

scanner analysis. This statistical study shows that only a portion of the Rapid Air 457 samples

need to be used for determination of appropriate threshold levels for the flatbed scanner.

51

Figure 3.9: Comparison of Flatbed Scanner Spacing Factor Results Using Void Frequency

Threshold Levels of 115 and 120.

.

52

Chapter 4

Conclusion

The flatbed scanner as an automated method for air void analysis is investigated in this study.

Contrast enhancement and image analysis has been used to measure air content and spacing

factor based on threshold optimization of prepolished scanned concrete samples. The

performance of this method has been studied by comparing the results of air content and

spacing factor with those of manual ASTM C457 method for a large population of 324 samples

received from MTO. It is shown that the results of both methods are in an acceptable

agreement with 1.6 volume percent of average air content and 0.049 mm of spacing factor

deviation. However, for a smaller population of the samples where more manual information

(i.e. void frequency) was known, the deviation came to be less (1.54 volume percent deviation

for air content and 0.036 mm deviation for spacing factor). Different populations of samples

were also studied to find a specific number of training samples which would be adequate to

find an acceptable threshold for image analysis of all samples. Neither the Rapid Air 457 nor the

flatbed scanner approaches provide a value for paste content. An assumed paste content of

30% was used in this study which affects the accuracy of the results. Therefore, a point

counting method was explored on scanned images from a subset of samples and the results of

spacing factor were compared with those of 30% assumed paste content and a deviation

difference of 0.01 mm was captured between the two results. The most important drawback of

flatbed scanner method is considered to be its dependency on the determination of threshold

values based on manual test results. To investigate this issue, a threshold study is also

53

performed and showed that smaller population of samples can be used to report a threshold

representing that of coming from all samples. Therefore, to examine a large population of

samples (e.g. above 300 samples) a smaller population of those samples (i.e. 160 samples) need

to be examined by the manual method to report the required threshold values for flatbed

scanner method analysis. This approach can lead to an invaluable air void analysis considering

flatbed scanner method’s time efficiency and less operator dependency.

Furthermore, a comparison of flatbed scanner and Rapid Air 457 methods of air void analysis is

performed in this study. In addition to air content and spacing factor values, chord length

distribution from both of methods are plotted for this comparison study. In the case of both air

content and void frequency flatbed scanner reported very similar values to those of Rapid Air

457 (0.64 volume percent and 0.06 mm deviation). In this case the threshold study also showed

that a smaller population of samples can be a very good representative of all samples for

threshold determination. Also, comparison of the normalized chord length distributions

showed that for chord lengths above 0.07 mm, the flatbed scanner reports slightly more air

void intercepts than the Rapid Air 457, and below 0.07 mm, the flatbed scanner reports slightly

less air void intercepts than the Rapid Air 457. One possible explanation for the discrepancy

could be that the higher resolution of the Rapid Air 457 images (1.1 x 1.1 µm pixels) allows for

the detection of air voids too small for detection buy the flatbed scanner method (8 x 8 µm

pixels).

Finally, it is concluded that the flatbed scanner as a time and cost saving method is fairly

qualified to output results that are in agreement with the manual and Rapid Air 457 methods

54

and it can be effectively used in combination with any of them. Future work could expand on

the effect of sample preparation on the results of flatbed scanner method.

55

References

[1] Ontario Provincial Standard Specification, “Material Specification for Concrete – Materials and Production”, OPPS.PROV 1350, (2010). [2] Sutter, L. L., “Evaluation of Methods for Characterizing Air-Void Systems in Wisconsin Paving Concrete”, Wisconsin Highway Research Program, WHRP 07-05, (2007). [3] Snyder, K. A., “A Numerical Test of Air-Void Spacing Equations”, National Institute of Standards and Technology Building Materials Division, Gaithersburg, (1998). [4] ASTM Standard C457: Standard Test Method for Microscopical Determination of Parameters of the Air-void in Hardened Concrete, Annual Book of ASTM Standards, ASTM International, West Conshohocken, PA, USA, (2012). [5] Zhang, Z., Ansari, F., and Vitillo, N., “Automated determination of entrained air-void parameters in hardened concrete”, ACI Materials Journal, 102 (1), (2005). [6] Jakobsen, U. H., Pade , C., Thaulow , N., Brown, D., Sahu, S., Magnusson, O., De Buck, S., and De Schutter, G., “Automated air void analysis of hardened concrete — a Round Robin study”, Cement and Concrete Research, 36, 1444–1452, (2006). [7] Ramezanianpour, A. M., Hooton, R. D., and Dean, S., “Evaluation of Two Automated Methods for Air-Void Analysis of Hardened Concrete”, Journal of ASTM International, V. 7 (2), (2009). [8] Peterson, K., Carlson, J., Sutter, L., and Van Dam, T., “Methods for threshold optimization for images collected from contrast enhanced concrete surfaces for air-void system characterization”, Materials Characterization, 60, 710-715, (2009). [9] Mateusz, R., Olek, J., Zhang, Q., and Peterson, K., “Evaluation of the critical air-void system parameters for freeze-thaw resistant ternary concrete using the manual point-count and the flatbed scanner methods”, Journal of ASTM International, v 7, n 4, April (2010). [10] Peterson, K. W., Swartz, R. A., Sutter, L. L., and Van Dam, T. J., “Air Void Analysis of Hardened Concrete with a Flatbed Scanner”, 24th ICMA proceedings. San Diego, CA, April 8–11; (2002). [11] Carlson, J.; Sutter, L.; Van Dam, T.; and Peterson, K., “Comparison of Flatbed Scanner and Rapid Air 457 System for Determining Air Void System Parameters of Hardened Concrete”, Transportation Research Record (Concrete Materials), n 1979, p 54-59, (2006).

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[12] Zalocha, D., and Kasperkiewicz, J., “Estimation of the Structure of Air Entrained Concrete Using a Flatbed Scanner”, Cement and Concrete Research, 35, 2041 – 2046, (2005).

[13] True, G., Searle, D., Sear, L., and Khatib, J., “Voidage assessment of concrete using digital image processing”, Magazine of Concrete Research, 62, 857–868, (2010). [14] Yun, T.S., Kim, K.Y., Choo, J., and Kang, D. H., “Quantifying the distribution of paste-void spacing of hardened cement paste using X-ray computed tomography”, Material Characterization, 73, 137–143, (2012). [15] Kim, K.Y., Yun, T.S., Choo , J., Kang, D.H., and Shin, H.S., “Determination of air-void parameters of hardened cement-based materials using X-ray computed tomography”, Construction and Building Materials, 37, 93–101, (2012). [16] Roberts, L. R., Scali, M. J., “Factors Affecting Image Analysis for Measurement of Air Content in Hardened Concrete,” Proceedings of the 6th International Conference on Cement Microscopy, Albuquerque, NM, USA, March 26-29, pp. 402-419, (1984). [17] Jana, D., “A Round Robin Test on Measurements of Air Void paramewters in Hardened Concrete by Various Automated Image Analyses and ASTM C457 Methods,” Proceedings of the 29th International Conference on Cement Microscopy, (2007). [18] Ministry of Transportation, Ontario Test Method LS-431, “Method of Test for MicroscopicaL DETERMINATION OF AIR VOID SYSTEM PARAMETERS IN HARDENED Concrete, for Referee Testing”, Laboratory Testing Manual, Rev. No 26., (2001). [19] Peterson, K., Sutter, L., Radlinski, M., “The Practical Application of a Flatbed Scanner for Air-Void Characterization of Hardened Concrete” Journal of ASTM International, v. 6, n. 9, (2009). [20] Elsen J., “Automated Air-Void Analysis on Hardened Concrete – Results of a European Intercomparison Testing Program,” Cement and Concrete Research, vol. 31, pp. 1027-1031, (2001).

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Appendix A:

Comparison Plots of Manual and Flatbed Scanner for Different Labs

Figure A.1: Manual versus Flatbed Scanner Air Content (All Labs).

Figure A.2: Manual versus Flatbed Scanner Spacing Factor (All Labs).

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Figure A.3: Manual versus Flatbed Scanner Air Content (No Lab ID).

Figure A.4: Manual versus Flatbed Scanner Spacing Factor (No Lab ID).

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Figure A.5: Manual versus Flatbed Scanner Air Content (Lab 1).

Figure A.6: Manual versus Flatbed Scanner Spacing Factor (Lab 1).

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Appendix B

Normal Distributions for Threshold Determination of Rapid Air 457 versus Flatbed

Scanner

Figure B.1: Optimum Threshold Value Distributions for a) Air Content and b) Void Frequency.

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Appendix C

Point Count Method Detailed Results

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Table C.1: Point Count Detailed Results.

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Appendix D

Flatbed Scanner versus Manual Method Database

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Table D.1: Flatbed Scanner versus Manual Method Database.

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* In the aggregate type column, Igneous Meta stands for Igneous Metamorphic.

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Appendix E

Flatbed Scanner versus Rapid Air 457 Database

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Table E.1: Flatbed Scanner versus Rapid Air 457 Database.

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