MEPDG Overview & National Perspective - Purdue … · Design Guide 1986; Update ... Rehabilitated...
Transcript of MEPDG Overview & National Perspective - Purdue … · Design Guide 1986; Update ... Rehabilitated...
MEPDG Overview & MEPDG Overview & National PerspectiveNational Perspective
(My Perspective)(My Perspective)
NorthNorth--Central MEPDG User GroupCentral MEPDG User GroupFebruary 19, 2008February 19, 2008
Harold L. Von Quintus, P.E.
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OutlineOutline1.
The Beginning
2.
Local Implementation Efforts3.
Integration of MEPDG into Practice
4.
Enhancements5.
Summary
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ItIt’’s Done; In Reality, s Done; In Reality, ItIt’’s the Beginning!!s the Beginning!!
April 2007 Irvine WorkshopApril 2007 Irvine Workshop
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Should we wait until its Should we wait until its PERFECTPERFECT??
1958; Road Test initiated
1962; AASHO Road Test complete
1972; Interim Design Guide
1986; Update
1993; Update
2007; still not perfect.
1989; LTPP initiated
1998; MEPDG initiated
2007; MEPDG delivered
Time, yrs.
-4
10
24
31
45
AASHTO Guide MEPDG
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Should we wait until its Should we wait until its PERFECTPERFECT?? If we wait until there are no more
changes, we will never use it. If we wait for perfection, it will be
impractical and cost will restrict its use.
There is NONO perfect procedure & it will never
be perfect!
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The BeginningThe BeginningWe have decided to implement the
new MEPDG!
Where do we begin; regional versus agency issues?
What will it cost?
Will we get a better design?
What am I responsible
for?
Why, aren’t we doing a good job?
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Remember where we Remember where we are coming from, as are coming from, as you use the MEPDG!you use the MEPDG!
Assumptions used in the Assumptions used in the Design Guides?Design Guides?
Calibration of both Design Calibration of both Design Guides?Guides?
Error in the service life Error in the service life predictions of both Design predictions of both Design Guides?Guides?
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OutlineOutline1.
The Beginning
2. Local Implementation Efforts3.
Integration of MEPDG into Practice
4.
Enhancements5.
Summary
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FHWA FHWA Summary Summary of Agency of Agency
PlansPlans
Efforts to Efforts to ImplementImplement
MEPDG MEPDG 20072007
0
20
40
60
80
100
Yes < 0.5 0.5 to 1.0 1.0 to 5.0 > 5.0
Range of Cost for Implementation Plan, $MPe
rcen
t of T
otal
R
espo
ndin
g (5
2)
Does Agency Have Implementation Plan?
010203040506070
Yes < Design Life Equals DesignLife
> Design Life
Perc
ent o
f Tot
al R
espo
ndin
g (5
2)Does Agency Track Perfomance for Use in Calibration?
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MEPDG Global CalibrationMEPDG Global CalibrationLTPP LTPP GPSGPS Test Sections Used in Test Sections Used in Calibration of Distress Prediction Calibration of Distress Prediction
Models;Models;NCHRP Projects 1NCHRP Projects 1--37A & 137A & 1--40D40D
Many assumptions used.Many inputs estimated.
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Local Implementation EffortsLocal Implementation Efforts—— DiversityDiversity
√√
√√
√√
√√
√√ √√
√√
√√
√√
√√
South-EastSouth-West
North-CentralNorth-EastNorth-West
1. Verify/confirm calibration factors & default values.
2. Establish input libraries.
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Expansive SoilsExpansive Soils Maintenance/Preservation Maintenance/Preservation
StrategiesStrategies New Technology & Material New Technology & Material
DifferencesDifferences Other Design Policies & Other Design Policies &
FeaturesFeatures
Why Local Calibration?Why Local Calibration?
Consideration of factors Consideration of factors NOT NOT included in MEPDG global calibration included in MEPDG global calibration
process.process.
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MEPDG MEPDG –– Local Local Validation/Calibration ToolsValidation/Calibration ToolsManual of Recommended Practice for Manual of Recommended Practice for
Calibration of MCalibration of M--E Based ModelsE Based Models1.
Confirming or adjusting the global calibration factors.
2.
Detailed and practical guide to complete local calibration.
MEPDG Software ItselfMEPDG Software ItselfNCHRP Project 1NCHRP Project 1--40B40B
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Previous & OnPrevious & On--Going StudiesGoing Studies1. NCHRP 9-30 –
Experimental Plan for Calibration &
Validation of HMA Performance Models for Mix & Structural Design.
2. NCHRP 9-30(001) –
Conduct Pre-Implementation Studies & Database Enhancement.
3. NCHRP 1-40D –
A review of the M-E PDG software & prediction methodology; & Correcting errors/blunders in the software.
4. NCHRP 1-40B –
Local Calibration for the Recommended Guide for M-E Design of New and Rehabilitated Pavement Structures.
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Previous & OnPrevious & On--Going StudiesGoing Studies
Calibration Documents:
NCHRP Digest 284, December 2003; Refining the Calibration & Validation of HMA Performance Models: An Experimental Plan and Database.
NCHRP Digest 283, December 2003; Jackknife Testing – An Experimental Approach to Refine Model Calibration and Validation.
FHWA: Use of PMS data for local calibration.
FHWA: Use of deflection basin data in the MEPDG.
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OutlineOutline1.
The Beginning
2.
Local Implementation Efforts3. Integration of MEPDG into
Practice4.
Enhancements
5.
Summary
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Integration into PracticeIntegration into PracticeHow do I get How do I get
this input level 1 this input level 1 or 2 for design?or 2 for design?
A Major Issue A Major Issue –– The The Unknowns!!Unknowns!!
Determination of properties Determination of properties & other inputs.& other inputs.
Factors affecting properties Factors affecting properties needed for design!!!!needed for design!!!!•• Source of MaterialsSource of Materials•• ContractorContractor•• Construction EquipmentConstruction Equipment 4-Day NHI Course
for MEPDG Software Training
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Data Integration: Effective use of Data Integration: Effective use of available but limited local resources.available but limited local resources.
PMISDatabase
Project Project Level DataLevel Data
Data integration: an automated process?Probably NOT!
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Structural Structural –– Mix Design Mix Design CompatibilityCompatibility
JMFJMFMixture design & material Mixture design & material specifications determine specifications determine
the inputs.the inputs.
11 22
33
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Data Integration into PracticeData Integration into PracticeDevelop Designs
Low-bid; optimize on design features
Alternate bids; establish equivalent designs
Design-build & warranties; optimize on performance
Establish Specification Limits
Quality Assurance
Performance-
Related
End-Result
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OutlineOutline1.
The Beginning
2.
Local Implementation Efforts3.
Integration of MEPDG into Practice
4. Enhancements5.
Summary
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Enhancements:Enhancements: Global & LocalGlobal & LocalGlobal√
Distress prediction equations or transfer functions
√
Revisions to the software; functionality
√
Add additional distresses
Local or Regional√
Revisions to the default values
√
Revisions to the transfer function and calibration coefficients
√
Build libraries of inputs
NCHRP Project 1-40B Local Calibration Guide
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Previous & OnPrevious & On--Going StudiesGoing Studies1. NCHRP 1-40A –
Independent Review,
prioritize the modifications.2. NCHRP 9-30A –
Calibration of Rutting
Models for HMA Structural and Mix Design.3. NCHRP 9-42 –
Top-Down Cracking of HMA.
4. Reflection Cracking of HMA Overlays.5. NCHRP 9-44 –
Application of the Endurance
Limit for HMA Mixes.
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New Construction Design New Construction Design StrategiesStrategiesIncluded:
Conventional flexible pavements
Deep strength
Full depth
Excluded:
Aggregate surfaced roadways
Semi-rigid pavements
Staged construction
Asphalt treated permeable base
Geogrids, fabrics, & other strengthening materials
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Rehabilitation StrategiesRehabilitation StrategiesIncluded:
HMA overlays with & without milling
Excluded:
Full depth reclamation
Hot in place recycling
Cold in place recycling
Pavement preservation programs
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Site Features Excluded from Site Features Excluded from MEPDGMEPDG
Super single tires or single tires.
Durability & mixture disintegration.
Volume change in soils (frost heave or expansive soils).
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OutlineOutline1.
The Beginning
2.
Local Implementation Efforts3.
Integration of MEPDG into Practice
4.
Enhancements5. Summary
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SummarySummaryImplementation Considerations:
Regional design features not included in global calibration.
Regional defaults that are different from global defaults.
Design criteria as compared to measured values included in calibration.
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SummarySummary
Response Parameter & Calibration Factors
Transfer Function & Calibration Factors
Standard Error orStandard Deviation
Agency/User has options readily Agency/User has options readily available for design!available for design!
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Value of Increased Costs & Time?Value of Increased Costs & Time?
If improved performance/longer lasting pavements & reduced life cycle costs;
Then it is worth the effort, time, and cost!! Then it is worth the effort, time, and cost!! Assuming enforcement of specifications.Assuming enforcement of specifications.
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Advanced Pavement DesignAdvanced Pavement Design
Distress specific—defines what controls the design.
Design features—considers many more design features and what effect they have on distress.
Smoothness
Construction defect effects.
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Current Pavement Design Current Pavement Design ProceduresProcedures
01020304050607080
AgencySpecific
72-AASHTO
81-AASHTO
93-AASHTO
98-AASHTO
Pavement Design Procedures
Perc
ent o
f Tot
al
Res
pond
ing
(52)
Flexible Pavements Rigid Pavements
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Agency Road Maps for:Agency Road Maps for: Implementing the MEPDGImplementing the MEPDG
••
To streamline the design process To streamline the design process using the MEPDG, & to verify and using the MEPDG, & to verify and calibrate the distress prediction calibrate the distress prediction models or transfer function included models or transfer function included in the MEPDG.in the MEPDG.
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ReliabilityReliability1993 AASHTO
Based on traffic level; standard deviation of the design process & applied to traffic level.
MEPDG
Standard error for each distress prediction model & defined from calibration.
Carefully review and consider the standard errors of the distress prediction equations for application to low volume roadways.
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SummarySummary
Remember:The hierarchical input procedure allows a user to use the MEPDG with NO major investment.
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Deciding on Design InputsDeciding on Design Inputs
Communications within & between departments
TrafficMaterialsConstruction
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Decision FactorsDecision Factors1.
Cost of validation/calibration.
2.
Value of potential improvement in prediction accuracy.
3.
Cost/Value of design & construction.
Decision: Yes, validate & calibrate MEPDG to our local
conditions!
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Preparation of a MPreparation of a M--E Design in E Design in a Lowa Low--Bid ProcessBid ProcessFoundation
AnalysisClimateEICM
MaterialsMaterialsLibraryLibrary
Traffic Library
Design Criteria Structural DesignStructural Designby Agencyby Agency
Layer Thickness,Layer Thickness,Type & PropertiesType & Properties
Mixture Design & Mixture Design & Confirm PropertiesConfirm Properties
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Implementation Areas & Implementation Areas & Technology TransferTechnology Transfer
Training & communications within & between departments
Traffic
Materials
Construction
Calibration
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1. Project Selection
2. Planning
3.Structural Design
4. Plan Preparation
5. Bid Letting
6.HMA Mixture Design
7. Construction
8. As-Built Plans & Performance Confirmation
Library of MixLibrary of MixProperties:Properties:
Dynamic ModulusDynamic ModulusFlow NumberFlow NumberIDT StrengthIDT StrengthIDT CreepIDT Creep
VMAVMA
DesignDesignValues:Values:E*>?E*>?SSIDTIDT >?>?D(tD(t)<?)<?
Structural Structural –– Mix Design IntegrationMix Design Integration
Volumetric& SPT
Design, more Design, more than just than just volumetricsvolumetrics..
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Technology Transfer & Technology Transfer & Implementation ProductsImplementation ProductsRemember Products:
Management video
Interactive CD for software
Implementation notes
Training course
Guide text & appendices.
User’s Manual in support of software.
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Important Activities Important Activities for Implementationfor Implementation
Training Courses:
Determining inputs & using software
Communication:
Departments need to know what information is needed & how it is used.
Establish sensitivity of inputs to distress
Identify problem areas to reduce frustration with software use
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Global Calibration of Distress Global Calibration of Distress Transfer FunctionsTransfer Functions
Pavement Pavement ResponseResponse DistressDistress
TRANSFERTRANSFERFUNCTIONFUNCTION
●●
StressesStresses●●
StrainsStrains
●●
DeflectionsDeflections
●●
CrackingCracking●●
DistortionDistortion
●●
RoughnessRoughnessCalibrat
ion
Calibrat
ion
is a k
ey.
is a k
ey.
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Local CalibrationLocal Calibration
A difficult & costly issue to resolve!
How close is close enough?
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Outline of Recommended Practice Outline of Recommended Practice for Local Calibrationfor Local Calibration
Introduction
Scope of Document
Referenced Documents
Definition of Terms
Significant of Use
Defining Accuracy
Standard Error Components
Step-by-Step Procedure
Revisions to calibration coefficients
Demonstration Studies
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Validate/Calibrate MEPDGValidate/Calibrate MEPDG
How many sites?Length of roadway segments?How many distress observations?
Multiple points within segment at any one point in time?
Multiple points over time?
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Distress Data SourcesDistress Data SourcesLTPPSpecial Agency Test SectionsPMIS Sections –
A quick check:
Do the distress predictions match our Do the distress predictions match our local experience for traditional designs?local experience for traditional designs?
What is the primary failure mode What is the primary failure mode triggering rehabilitation?triggering rehabilitation?
NCHRP 9NCHRP 9--30 Database for 30 Database for MM--E Based ModelsE Based Models
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Calibration: Ease of UseCalibration: Ease of Use
Calibration Options:Calibration Options:
Special AnalysisSpecial Analysis
National CalibrationNational Calibration
State CalibrationState Calibration
Typical Agency Typical Agency ValuesValues
National/Global National/Global Calibration;Calibration;
kk--
or Cor C--ValuesValues
State/Regional State/Regional Calibration;Calibration;ββ--
or Cor C--ValuesValues
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Calibration: Ease of UseCalibration: Ease of Use
Transfer Transfer FunctionFunction
CC-- ValuesValues
Standard Standard DeviationDeviation
HMA Alligator HMA Alligator CrackingCracking
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Calibration: Ease of UseCalibration: Ease of Use
Response Parameter Response Parameter & Calibration Factors& Calibration Factors
Transfer Function & Transfer Function & Calibration FactorsCalibration Factors
Standard DeviationStandard Deviation
JPCP CrackingJPCP Cracking
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MEPDG Unique FeatureMEPDG Unique Feature
Response Parameter & Calibration Factors
Transfer Function & Calibration Factors
Standard Deviation
Agency/User has options readily Agency/User has options readily available for design!available for design!
Batch runs can be completed!Batch runs can be completed!
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Local Validation/Calibration Local Validation/Calibration HypothesesHypothesesMathematical models –
assumed to be
correct.Pavement response modelsClimatic model –
ICM
HMA aging/PCC strength time dependent model
Statistical or empirical models (transfer functions) may result in bias.Revision of model coefficients to remove bias.
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General Approach to Validation & General Approach to Validation & Calibration of MCalibration of M--E Based ModelsE Based Models
1.
Traditional Split-Sample Approach2.
Jack-Knife Testing Approach
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Validate/Calibrate MEPDGValidate/Calibrate MEPDG
How many sites?
Length of roadway segments?
How many distress observations?
Multiple points within segment at any one point in time?
Multiple points over time?
What data do we use?LTPP/PMIS & other databases!!
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Data Quality ReviewData Quality Review
0.0
0.1
0.2
0.3
0.4
0 20 40 60 80 100Time (Months)
Rut
ting
(in/m
ile)
Measured
Predicted
What caused this increase in measured rutting?
Data measurement issues!Data measurement issues!
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Data Quality ReviewData Quality Review
0.0
1000.0
2000.0
3000.0
4000.0
0 20 40 60 80 100 120 140Time (Months)
Tran
sver
se C
rack
ing
(ft/m
ile)
Measured
Predicted
Why are transverse cracking values so diverse?
Pavement preservation issues!Pavement preservation issues!
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Distress Data, Example:Distress Data, Example:
Variability; A key data
issue.
Example; Fatigue
Cracking
0100200
300400
500600
700
47 48 49 50 51 52 53
Mile Post
Fatig
ue C
rack
ing,
sq.
ft./0
.1m
i.
Neat Mix, Region 6, Route 36B, Both Directions, 2004
0200400600800
1000120014001600
85 90 95 100 105
Mile Post
Fatig
ue C
rack
ing,
sq.
ft. p
er0.
1 m
i.
Modified Mix, Region 5, Route 285B, Direction 2, 2004
PMA Mixes
Neat Mixes
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Distress Data, Example:Distress Data, Example:
0
0.1
0.2
0.3
0.4
0.5
47 48 49 50 51 52 53
Mile Post
Rut
Dep
th, i
nche
s
Neat Mix, Region 6, Route 36B, Both Directions, 2004
0
0.050.1
0.150.2
0.250.3
0.35
86 88 90 92 94 96 98 100 102
Mile Post
Rut
Dep
th, i
nche
s
Modified Mix, Region 5, Route 285B, Direction 2, 2004
Variability; A key data
issue.
Example; Rut Depth
Neat Mixes
PMA Mixes
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Distress Data Analyses:Distress Data Analyses: Within Project Variation; Within Project Variation; OutliersOutliers
0
0.2
0.4
0.6
0.8
1
278 278.5 279 279.5 280 280.5 281
Mile Post
Rut
Dep
th, i
nche
s
PMA Mix, Region 6, Route 6G, Both Directions, 2005
Limited area with significant different distress value within PMIS segment.
Outliers, removed from calibration set.
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Distress Data Analyses:Distress Data Analyses: Within Project Variation; Within Project Variation; Abrupt ChangeAbrupt Change
0
0.1
0.2
0.3
0.4
0.5
0.6
211 211.5 212 212.5 213 213.5
Mile Post
Rut
Dep
th, i
nche
s
Neat Mix, Region 6, Route 25A, Both Directions, 2005
Sudden increase or decrease in distress value within PMIS segment.
Identify reasons for abrupt changes.
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Distress Data Analyses:Distress Data Analyses: Within Project Variation; Within Project Variation; DriftDrift
00.05
0.10.15
0.20.25
0.30.35
0.40.45
0.5
258 260 262 264 266 268
Mile Post
Rut
Dep
th, i
nche
s
Modified Mix, Region 6, Route 70-A, Both Directions, 2005
Consistent change in distress over project length, within PMIS segment.
Use segments w/consistent averages.
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Data Analyses: Bias & Residual Data Analyses: Bias & Residual Error from Validation/CalibrationError from Validation/Calibration
02468
1012141618
0 2 4 6 8 10 12
Measured Value
Pred
icte
d Va
lue
Line of Equality
02468
1012141618
0 2 4 6 8 10 12
Measured Value
Pred
icte
d Va
lue
Line of Equality
02468
1012141618
0 2 4 6 8 10 12
Measured Value
Pred
icte
d Va
lue
Line of Equality
02468
1012141618
0 2 4 6 8 10 12
Measured Value
Pred
icte
d Va
lue
Line of Equality
BiasBias
Residual Residual ErrorError
Suggestion: Determine bias and error for Suggestion: Determine bias and error for local conditions & materials.local conditions & materials.
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Global Calibration HypothesisGlobal Calibration Hypothesis
Level 3DefaultValue
Level 2Calculated
Value
CalibrationError
Level 1Measured
Value
Reduce uncertainty, use level 1
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How Close is Close Enough?How Close is Close Enough?
0
20
40
60
80
100
120
140
5 10 15 20 25 30
Standard Error
Res
earc
h/C
alib
ratio
nC
osts
222
22
PureInputFitofLack
tMeasuremenTotal
Quantify the total error to answer this question!Quantify the total error to answer this question!
60
80
100
120
140
160
180
5 10 15 20 25 30
Standard Error
Con
stru
ctio
n C
osts
Impact of Reliability
Lack-of-fit & Input
Pure & measurement
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Uses of PMIS Data for Uses of PMIS Data for Validation/CalibrationValidation/Calibration
Identify factors/site features deviations or anomalies between performance observations.
Identify bias between observations & predicted distresses for different design features & strategies.
Determination of the standard error – Probably NOT!
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Pavement Management Pavement Management Systems Data Systems Data -- A Resource:A Resource:Large time-series database on
distress & pavement performance.Many dollars expended to develop
PMIS and collect data.Use of PMIS data for
validation/calibration not a simple & quick process!!!!
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In SummaryIn Summary
0
1
2
3
4
0 1 2 3 4
Measured IRI, m/km
Pred
icte
d IR
I, m
/km
Local validation/calibration:It’s an important decision but it’s your to make.AccuracyCosts
Manual of Manual of Recommended Recommended Practice for Calibrating Practice for Calibrating MM--E Based Models.E Based Models.
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Material Testing Material Testing –– Equipment Equipment
Purchased for ImplementationPurchased for ImplementationUnbound Mtls.Montana –
No
Missouri –
NoUtah -
Yes
HMAMontana –
No
Missouri –
YesUtah -
Yes
PCCMost agencies have equip.
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Testing Testing –– Lab TestingLab Testing
Build library of material properties
Build library of default values
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Questions for Establishing a Questions for Establishing a Data Collection PlanData Collection Plan1.
Is input parameter important for predicting distress?
2.
Is the input parameter site/facility specific?
3.
Can input parameter be easily/adequately measured?
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TimeTime--History Data for CalibrationHistory Data for Calibration
00.10.20.30.40.5
0 2 4 6 8 10 12
Age, years
Rut
Dep
th, i
nche
sMnRoad Measured Mississippi Measured Arizona MeasuredMnRoad Predicted Mississippi Predicted Arizona Predicted
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Local Calibration HypothesesLocal Calibration HypothesesMathematical models –
assumed to be
correct.Response modelsClimatic model –
ICM
HMA aging/PCC strength time dependent model
Statistical or empirical models (transfer functions) may result in bias.Revision of model coefficients to remove bias.
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Steps for Local CalibrationSteps for Local Calibration1.
Select hierarchical input level
2.
Develop experimental design & matrix
3.
Determine sample size4.
Identify roadway segments
5.
Collect & evaluate data for anomalies
6.
Conduct field investigations
Level of confidence.
1.
LTPP sections2.
Research sections
3.
PMIS segments
Testing & distress definitions
Policy decision.
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Steps for Local CalibrationSteps for Local Calibration7.
Assess bias
8.
Eliminate bias9.
Assess standard error
10.Improve model precision
11.Interpretation of results & decide on adequacy of calibration factors
Execute MEPDG & evaluate residual
errors.
Dispersion around line of equality
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0
0.2
0.4
0.6
0.8
1
0 0.2 0.4 0.6 0.8
Observed Distress Value
Pred
icte
d D
istr
ess
Valu
e
eDtD edictedCI Pr
0
0.2
0.4
0.6
0.8
0 10 20
Age, year
Pred
icte
d D
istr
ess
Reliability = 50%
Reliability = 75%
Reliability = 95%
Design Confidence Interval ConceptDesign Confidence Interval Concept
Predicted Distress ValuePredicted Distress Value
50%50%
75%75%
95%95%
BUT, where does the BUT, where does the error come from?error come from?
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Quantifying the Prediction Quantifying the Prediction ErrorError
PureInput
tMeasuremenFitofLackTotal
ee
eee
0
0.2
0.4
0.6
0.8
1
0 0.2 0.4 0.6 0.8
Predicted Values
Obs
erve
d V
alue
s
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Objective:Objective:
•
To streamline the design process using the MEPDG, & to verify and calibrate the distress prediction models or transfer function included in the MEPDG.
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Rutting in Unbound Layers & Rutting in Unbound Layers & SubgradeSubgrade..
Trenches not completed for the
LTPP test sections!
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Based on Volumetric Based on Volumetric PropertiesProperties
HMA RuttingHMA Rutting
Wear vs. plastic deformation
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Based on Based on Volumetric Volumetric PropertiesProperties
Fatigue Fatigue CrackingCracking
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Fatigue CrackingFatigue Cracking
Cores not taken to
confirm crack direction for LTPP Test Sections!
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Smoothness or IRISmoothness or IRI
Regression equations developed from LTPP
test sections,
higher speed
roadways!
Expanding the Realm of Possibility
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Calibration Data OptionsCalibration Data Options
3. Using PMIS 3. Using PMIS segments for the segments for the local calibrationlocal calibration
1. Using existing test 1. Using existing test sections (LTPP & other sections (LTPP & other projects) for calibrationprojects) for calibration
2. Using PMIS segments with detailed distress
surveys & LTPP sections.