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

OutlineOutline

The Big Picture Data Storage The Process Thoughts on Future Directions

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!!!

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

Data Storageg

Rule 1 with APTRule 1 with APT

It doesn’t matter how many reps you do if

you don’t get any data!data!

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

WorkflowWorkflow

Traditional approach to APT dataTraditional approach to APT data

D t bDatabase

2nd Level 3rd Level Standards1st Level

Data

APT LTPP/Field Trial Practice

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

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

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

Lesson 3:Always use the database

1st Level

Always use the database

1st Level

SpreadsheetsDatabase

Text Files

APT

Lesson 3:Always use the database

1st Level

Always use the database

1st Level

SpreadsheetsDatabase

Text Files

APT

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

Lesson 5:Combined location and time keysCombined location and time keys

Position

etiti

onRe

pe

Lesson 5:Combined location and time keysCombined location and time keys

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

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

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

Collect Inputsp

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

List of InputsList of Inputs

Structure Material Environment Loading Response Response Performance

Inputs – StructureInputs Structure

Thickness As-built Determine variability if possible

How Coring DCP Site survey Record location

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

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

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

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

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

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

Inputs – PerformanceInputs Performance

Surface Cracking Crack Density

HiHistory Digital ImagingP t Permanent Deformation S f R t Surface Rut:

laser profilometerprofilometer

In-depth: MDD

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

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

Example: HMA Stiffness Change during HVS Testingduring HVS Testing

Example: Matching MDD Elastic DeflectionsDeflections

HVS Example – Matching Surface DeflectionsDeflections

Matching DistressesMatching Distresses

Surface and in-depth permanent deformation

Surface crack density

Plots for Performance Comparison Example – Max Surface Deformation from Profilometerfrom Profilometer

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

HVS Example – Matching Surface RutHVS Example Matching Surface Rut

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)

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)

Thoughts on Future Directiong

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

The promise of ME design?The promise of ME design?

From Witczak, TRB, 2014

ReliabilityReliability

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

ReliabilityReliability

ReliabilityReliability

Questions?Q