Use of HVS Data to Calibrate/Verify ME Models and Analytical...
Transcript of Use of HVS Data to Calibrate/Verify ME Models and Analytical...
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Use of HVS Data to Calibrate/Verify ME Models and Analytical MethodsyJohn Harvey, Jeremy Lea and Rongzong WuUniversity of California Pavement Research Centery
Prepared for the HVSIA Annual MeetingIn Gainesville, Florida, August, 12th, 2014
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OutlineOutline
The Big Picture Data Storage The Process Thoughts on Future Directions
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The Big Picture – Why?The Big Picture Why?
The cycle of model, lab, APT, and field
Why do this? Account for construction variability Expand the knowledge More bang for the same buck!!!
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The Big Picture – What do we needThe Big Picture What do we need
Data Clean Complete Continuously Growing Continuously Growing
Models Response Response Fundamental Distress (damage, aging,
PD, etc.)) Derivative Distress (cracking, rutting) Incremental-recursive approach
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Data Storageg
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Rule 1 with APTRule 1 with APT
It doesn’t matter how many reps you do if
you don’t get any data!data!
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Data preparationData preparation
UCPRC follows a careful formula (based on the CSIR’s work) Construction report 1st level analysis: What happened on
each section? L b t t ti t Laboratory testing report 2nd level analysis: How do the sections
compare to each other?compare to each other? Calibration of CalME models 3rd level: Recommendations 3 level: Recommendations
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WorkflowWorkflow
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Traditional approach to APT dataTraditional approach to APT data
D t bDatabase
2nd Level 3rd Level Standards1st Level
Data
APT LTPP/Field Trial Practice
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The value of APT testingThe value of APT testing
D t bDatabase
2nd Level 3rd Level Standards1st Level
Data ME Design?
APT LTPP/Field Trial Practice
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Lesson 1:It’s about the databaseIt s about the database
2nd Level 3rd Level Standards1st Level
ME DesignDatabase
APT LTPP/Field Trial Practice/ e d a act ce
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Lesson 2:Use editable filesUse editable files
Text files can be1st Level Corrected Managed B k dD t b Backed up Moved around
Use revision
Database
Use revision controlText Files
APT
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Lesson 3:Always use the database
1st Level
Always use the database
1st Level
SpreadsheetsDatabase
Text Files
APT
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Lesson 3:Always use the database
1st Level
Always use the database
1st Level
SpreadsheetsDatabase
Text Files
APT
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Lesson 4:Use strong database relationshipsUse strong database relationships
Use an index on all iunique
combinations of fields
Use constraints on all fields with limited ranges
limited ranges
Use foreign keys between tables
Use the best data type – not strings
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Lesson 5:Combined location and time keysCombined location and time keys
Position
etiti
onRe
pe
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Lesson 5:Combined location and time keysCombined location and time keys
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Storage and Access at UCPRCStorage and Access at UCPRC A PostgreSQL database server An automatic loader Simple interface through the web More detailed data through SQL queries in
Matlab Daily data plots
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Other LessonsOther Lessons
Do not store too much detail Putting each data point in a separate
record resulted in massive tables with little gainlittle gain
Focus on training not documentationdocumentation Operators need to know how things work
N bl k b l ti No black box solutions
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The ProcessThe Process
Collect inputs Simulate HVS responses Match simulated and measured
responses Match simulated and measured
distressesdistresses Find optimal uniform shift factors R i l ti i if Re-run simulations using uniform
shift factors
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Collect Inputsp
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General PrinciplesGeneral Principles
ME design methods generally require all inputs Need to ensure adequate testing Collect and collate data during HVS
testing when possibleC lib ti h ld b t th t Calibration should be to the rawest data possible T t t Try not to average Forward fit when possible
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List of InputsList of Inputs
Structure Material Environment Loading Response Response Performance
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Inputs – StructureInputs Structure
Thickness As-built Determine variability if possible
How Coring DCP Site survey Record location
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Inputs – MaterialInputs Material
Stiffness L b Laboratory, or In-Situ
Performance Performance Fatigue Resistance Rutting Resistance
How Laboratory Testing FWD and Back-Calculation DCP and correlation
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Inputs - Asphalt Bound Material at UCPRCUCPRC
HMA Property
Test Type Experiment DesignPropertyStiffness
Master CurveBeam bending
frequency sweep3 Temp x 2 Replicates
= 6Fatigue
ResistanceBeam bending fatigue
(AASHTO T 321)1 Temp x 2 Strain x 3
Replicates = 6Previously used 3 T
Rutting Resistance
Repeated Simple Shear (AASHTO T
320)R t d L d T i
2 Temp x 3 Stress x 3 Replicates = 18
or Repeated Load Tri-axial with AMPT
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Inputs - Unbound Materials at UCPRCInputs Unbound Materials at UCPRC
Stiffness FWD Testing and Back-Calculation Load level sensitivity Confinement effect
Rutting Resistance Empirical model from a Danish Study
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Inputs – EnvironmentInputs Environment
Pavement TemperatureTemperature
Moisture content Optional: ambient p
environment How Thermocouple and Thermocouple and
water table data logging
Automatic weather Automatic weather station
Sampling for moisture contentcontent
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Inputs – LoadingInputs Loading
Axle Load History Tire Assembly Layout Wheel Speed Tire Pressure Wander Pattern How HVS OCU log HVS Load Calibration Tire Pressure Measurements
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Inputs - ResponseInputs Response
Minimum: deflection Surface: RSD In-Depth: MDDG f Good to have: FWD data before and after Stiffness change caused by trafficking Stiffness change caused by trafficking
Good to have: pressure Pressure Cells Pressure Cells
Good to have: strain Strain Gauges Strain Gauges
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Inputs – PerformanceInputs Performance
Surface Cracking Crack Density
HiHistory Digital ImagingP t Permanent Deformation S f R t Surface Rut:
laser profilometerprofilometer
In-depth: MDD
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General Calibration ProcedureGeneral Calibration Procedure
Calibration parameter Fatigue shift factor (FSF) for fatigue damage Fatigue shift factor (FSF) for fatigue damage Rutting shift factor (RSF) for permanent
deformation P d Procedure Adjust FSF to match pavement responses Adjust RSF to match permanent deformations
Special notes Correlation between layer damage and cracking is
developed from a separate calibrationdeveloped from a separate calibration
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Matching Pavement ResponsesMatching Pavement Responses
Minimum requirement Matching the pavement deflections
Good to have Matching stiffness change from FWD
back-calculation Matching pressures and strains
How Apply fatigue damage model Adjust fatigue damage shift factor
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Example: HMA Stiffness Change during HVS Testingduring HVS Testing
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Example: Matching MDD Elastic DeflectionsDeflections
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HVS Example – Matching Surface DeflectionsDeflections
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Matching DistressesMatching Distresses
Surface and in-depth permanent deformation
Surface crack density
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Plots for Performance Comparison Example – Max Surface Deformation from Profilometerfrom Profilometer
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Data Source – HVS Testing at UCPRCUCPRC 27 Sections Four studiesFour studies
Goal 1: drain vs. undrained base Goal 3:
R-HMA vs. HMA Single vs. Dual Tire
Goal 5: wet testing Goal 9: R-HMA on cracked old pavement
Main Responses Main Responses Deflections: elastic and permanent
Main Performance Surface cracking Surface cracking Surface rutting
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HVS Example – Matching Surface RutHVS Example Matching Surface Rut
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HVS Calibration Summary – Surface DeflectionsDeflections
Comparison of Calculated and Measured Surface Elastic Deflections
2
2.5
(mm
)
1.5
2
ic D
efle
ctio
ns (
1
Sur
face
Ela
sti
0.5
Cal
cula
ted
00 0.5 1 1.5 2 2.5 3 3.5
Measured Surface Elastic Deflections (mm)
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HVS Calibration Summary – Surface RutRut
Comparison of Measured and Calculated Surface Downward Rut
20
25R
ut (m
m)
10
15
face
Dow
nwar
d R
5
10
Cal
cula
ted
Sur
f
00 5 10 15 20 25 30 35 40 45
Measured Surface Downward Rut (mm)
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Thoughts on Future Directiong
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Future calibration workFuture calibration work
CalME will be calibrated using statewide PMS data Automated Pavement Condition Survey PaveM databases Matching variables and definitions?
Future calibration will focus on reliability Pavements are inherently variable Still thinking this through
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The promise of ME design?The promise of ME design?
From Witczak, TRB, 2014
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ReliabilityReliability
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ReliabilityReliability
St t id
What variable or variables?Statewide or within project or APT section?
Correlated?Withi j tWithin project on statewide using error bars
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ReliabilityReliability
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ReliabilityReliability
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Questions?Q