Calibration and Application of HDM-4 for the WSDOT Highway System Jianhua Li Steve Muench Joe...
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Transcript of Calibration and Application of HDM-4 for the WSDOT Highway System Jianhua Li Steve Muench Joe...
Calibration and Application of HDM-4
for the WSDOT Highway System
Jianhua Li
Steve Muench
Joe Mahoney
Department of Civil and Environmental Engineering
University of Washington
November 19, 2004
Jianhua Li, University of Washington
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Outline
Background and Objectives Topics
Data Input Calibration of Road Deterioration Models Output Analysis
Conclusions and Recommendations
Jianhua Li, University of Washington
3
Background
HDM-4 can be used as an economic analysis supplement to the existing WSPMS.
The combination of these tools will create a robust system capable of addressing WSDOT’s pavement management needs.
HDM-4: Highway Development and Management System, version 1.3
Jianhua Li, University of Washington
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Research Objectives
Apply HDM-4 to the WSDOT highway system:
Test road maintenance standards Determine the required costs for target road conditions Predict pavement conditions under varying budgets Produce an optimal work program
select maintenance treatments select maintenance time
Jianhua Li, University of Washington
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Research Process
Input data collection, processing and formatting
Calibration of HDM-4 road deterioration models
Output analysis and applications
Jianhua Li, University of Washington
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Outline
Background and Objectives Topics
Data Input Calibration of Road Deterioration Models Output Analysis
Conclusions and Recommendations
Jianhua Li, University of Washington
7
Data Input
Road networks contains a detailed account of each road section’s physical attributes.
Vehicle fleets contains vehicle characteristics Preservation standards define road maintenance and
rehabilitation practices Traffic and Speed Flow Patterns
Traffic flow patterns model congestion effects on vehicle speeds and vehicle operation costs
Speed flow types model the effects of traffic volume on speeds Climate
(HDM-4 Series, Volume 4)
Jianhua Li, University of Washington
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Road Network Data
Project level units 2893 flexible sections 615 concrete sections
Program level units
Strategic level units 24 flexible sections 18 concrete sections
Jianhua Li, University of Washington
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Vehicle Fleets
The same as the WSDOT’s classifications: Passenger car Single unit (0.40 ESALs) Double unit (1.00 ESALs) Train (1.75 ESALs)
Jianhua Li, University of Washington
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Preservation Standards Asphalt concrete flexible pavements (ACP)
45mm Mill & Fill (Including patching and edge-repair)
45mm Overlay (without milling)(Including patching and edge-repair)
Pothole Patching
Bituminous surface treatment flexible pavements (BST) Bituminous Surface Treatment (double surface dressing)
(Including patching, edge-repair and crack sealing)
Concrete pavements Diamond Grinding Dowel Bar Retrofit Reconstruction
Jianhua Li, University of Washington
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Outline
Background and Objectives Topics
Data Input Calibration of Road Deterioration Models Output Analysis
Conclusions and Recommendations
Jianhua Li, University of Washington
12
Calibration of Road Deterioration Models
Calibration classification High traffic ACPs Medium traffic ACPs Low traffic ACPs BSTs Concrete pavements
Calibration methodology Flexible pavements Concrete pavements
Jianhua Li, University of Washington
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Calibration Factors for Flexible Pavements
High or medium sensitivity levels Roughness Rutting Cracking Raveling Potholing
Low or negligible sensitivity levels Edge-break Surface texture Skid resistance
(HDM-4 Series, Volume 4)
Jianhua Li, University of Washington
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Calibration for Flexible Pavements
Determine calibration coefficients
Derive values of calibration variables
Estimate calibration factors in LIMDEP
Validate calibration factors
Jianhua Li, University of Washington
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Validation of Estimated Factors
The predicted general shapes and trends of the distress progression curve.
The predicted time interval between preservation efforts.
Pavement preservation was generally triggered by the ≥ 10% cracked area criterion.
Post-rehabilitation conditions.
Jianhua Li, University of Washington
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Calibration Factors after ValidationCalibration Factor ACP High Traffic ACP Med. Traffic ACP Low Traffic BST
Kcia 1.00 0.84 0.76 0.20
Kciw 0.40 0.40 0.40 0.30
Kcpa 0.71 0.78 0.82 0.50
Kcpw 0.11 0.30 0.45 0.50
Kcit 0.10 0.10 0.10 0.04
Kcpt 0.20 0.20 0.20 0.62
Kpi 1.00a 1.10a 3.00a 1.00a
Kpp 0.10a 0.08a 0.40a 1.00a
Krid 0.12 0.12 0.12 0.01
Krst 0.15 0.15 0.15 0.22
Krpd 0.01 0.01 0.01 0.02
Krsw 0.32 0.32 0.32 2.05
Kgm 0.70 0.70 0.70 1.00
Kgp 1.62 1.62 1.62 0.70
Kvi 1.00a 1.00a 1.00a 1.00a
Kvp 0.04a 0.04a 0.04a 1.00a
Ksnpk 0.00a 0.00a 0.00a 0.00a
Jianhua Li, University of Washington
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Calibration for Concrete Pavements Determine calibration coefficients Run HDM-4
Use default value of 1.0 as calibration factors In project level One-year-forecasting from 2001 Predicted distress values of 2002
Reject outliers Find the real 2002 distress values in WSPMS Regress for Validate
'yY K Y yK
Jianhua Li, University of Washington
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Errores of Concrete Pavement Outputs
Joint spalling values remain constant over the PCCP life.
Slab cracking values remain constant over the PCCP life.
HDM-4 reports do not show values for “deteriorated cracks” and “failures”.
Predictions of faulting and roughness are incorrect.
Jianhua Li, University of Washington
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Outline
Background and Objectives Topics
Data Input Calibration of Road Deterioration Models Output Analysis
Conclusions and Recommendations
Jianhua Li, University of Washington
20
Output Analysis
Project level One or more road projects
Program level A defined long list of road projects A one-year or multi-year program Under constrained budgets
Strategic level Entire networks Medium to long term
(HDM-4 Series, Volume 4)
Jianhua Li, University of Washington
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Project Level Analysis
Pavement performance forecasting
Optimal road treatment program
Jianhua Li, University of Washington
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Current Conditions For SR 405, MP 13.82 – 15.17 (Southbound Direction)
Characteristic Value
Current Surface Thickness 46 mm
Cement Treated Base Thickness 152 mm
IRI 1.54 m/km
Percentage of Pavement Surface Cracked 0.04%
Potholes 0
Rut Depth 5 mm
Average Annual Daily Traffic (AADT) 97,813
Number of Lanes 3
Construction Year 1956
Year of Most Recent Overlay 1994
Jianhua Li, University of Washington
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0
4
8
12
16
0 5 10 15 20 25 30 35 40
Year
IRI (
m/k
m)
Do Nothing
45 mm Mill & Fill
Pothole Patching Only
45 mm Overlay
Predicted Road Distress Conditions For SR 405, MP 13.82 – 15.17 (Southbound Direction)
Jianhua Li, University of Washington
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Optimal Road Treatment Program For SR 405, MP 13.82 – 15.17 (Southbound Direction)
Year Description Trigger Road Agency CostWork Quantity
(m2)
2009 45mm overlay Cracking $452,293 23,805
2020 45 mm overlay Cracking $452,293 23,805
2032 45 mm overlay Cracking $452,293 23,805
Total cost for the section: $1,356,879
Jianhua Li, University of Washington
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Strategic Level Analysis
Optimized Preservation Program (over 40 years) $4.221 billion for all ACPs. $340 million for all BSTs.
Economic Indicators under Varying Budgets
Road Performance under Varying Budgets
Simulation of the WSDOT Funding Scenarios
Jianhua Li, University of Washington
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Economic Indicators for All ACPs Under Varying Budgets
ScenarioAnnual Budgeta
Repaired Length
(Lane-km)40-Year
Agency Costa
Equilibrium IRIb
(m/km) NPVa
Optimal Funding Level $105.6 17,420 $4,224 1.35 $198,052
Current WSDOT Funding $87.1 14,294 $3,482 5.00 $162,461
75% of Optimal $79.2 13,094 $3,168 6.00 $159,682
50% of Optimal $52.8 8,642 $2,112 9.00 $146,619
Notes:a. All costs are in millions of present-day dollarsb. The IRI that a given funding level can maintain over time.
Jianhua Li, University of Washington
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0
4
8
12
16
0 5 10 15 20 25 30 35 40
Year
IRI (m
/km
)
Optimal Budget
Current Budget
75% of Optimal
50% of Optimal
No Budget
Predicted Roughness of All ACPs Under Varying Budgets
Jianhua Li, University of Washington
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WSDOT Funding Scenarios for All ACPs
Scenario Funding (million/year)
2004-2005 2006-2043
Optimal $106 $106
Current $87 $87
Cut + Optimal $91 $106
Cut + Current $62 $87
Cut + Restore $62 ?
(All costs are in millions of dollars and represent a constant annual purchasing power)
Jianhua Li, University of Washington
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Predicted Roughness for All ACPs
0
2
4
6
0 5 10 15 20 25 30 35 40
Year
IRI (
m/k
m)
Cut + Current
Cut + Optimal
Current andCut + Restore
Optimal
Notes: 1. The "Current" and "Cut + Restore" scenarios have virtually identical roughness plots
2. The "Cut + Restore" scenario costs $150 million more than the "Current" scenario
Jianhua Li, University of Washington
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Outline
Background and Objectives Topics
Data Input Calibration of Road Deterioration Models Output Analysis
Conclusions and Recommendations
Jianhua Li, University of Washington
31
Conclusions HDM-4 can be used for the WSDOT road network. The flexible pavements deterioration models can be
calibrated. The WSDOT road network requires calibration factors
significantly different than default HDM-4 values. The current version of HDM-4 (v1.3) does not provide
meaningful analysis output for PCCP road deterioration models .
Based on the available data and calibrated models for flexible pavements, WSDOT can use HDM-4 to
Predict the required budget based on selected target road conditions. Produce road treatment strategies under varying budget levels. Assist WSDOT and policy makers in determining the long-term effects
of different funding scenarios.
Jianhua Li, University of Washington
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Recommendations
Check the program code for concrete pavement analysis.
Allow input of specific deterioration models. Determine if and how calibration factors change
from year-to-year given new WSPMS data. Determine how useful WSDOT calibration factors
are for other states.