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Calibration and Application of HDM-4 for the WSDOT Highway System Jianhua Li Steve Muench Joe Mahoney Department of Civil and Environmental Engineering.

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Presentation on theme: "Calibration and Application of HDM-4 for the WSDOT Highway System Jianhua Li Steve Muench Joe Mahoney Department of Civil and Environmental Engineering."— Presentation transcript:

1 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

2 Jianhua Li, University of Washington 2 Outline Background and Objectives Topics  Data Input  Calibration of Road Deterioration Models  Output Analysis Conclusions and Recommendations

3 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

4 Jianhua Li, University of Washington 4 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

5 Jianhua Li, University of Washington 5 Research Process Input data collection, processing and formatting Calibration of HDM-4 road deterioration models Output analysis and applications

6 Jianhua Li, University of Washington 6 Outline Background and Objectives Topics  Data Input  Calibration of Road Deterioration Models  Output Analysis Conclusions and Recommendations

7 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)

8 Jianhua Li, University of Washington 8 Road Network Data Project level units  2893 flexible sections  615 concrete sections Program level units Strategic level units  24 flexible sections  18 concrete sections

9 Jianhua Li, University of Washington 9 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)

10 Jianhua Li, University of Washington 10 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

11 Jianhua Li, University of Washington 11 Outline Background and Objectives Topics  Data Input  Calibration of Road Deterioration Models  Output Analysis Conclusions and Recommendations

12 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

13 Jianhua Li, University of Washington 13 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)

14 Jianhua Li, University of Washington 14 Calibration for Flexible Pavements Determine calibration coefficients Derive values of calibration variables Estimate calibration factors in LIMDEP Validate calibration factors

15 Jianhua Li, University of Washington 15 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.

16 Jianhua Li, University of Washington 16 Calibration Factors after Validation Calibration FactorACP High TrafficACP Med. TrafficACP Low TrafficBST K cia 1.000.840.760.20 K ciw 0.40 0.30 K cpa 0.710.780.820.50 K cpw 0.110.300.450.50 K cit 0.10 0.04 K cpt 0.20 0.62 K pi 1.00 a 1.10 a 3.00 a 1.00 a K pp 0.10 a 0.08 a 0.40 a 1.00 a K rid 0.12 0.01 K rst 0.15 0.22 K rpd 0.01 0.02 K rsw 0.32 2.05 K gm 0.70 1.00 K gp 1.62 0.70 K vi 1.00 a K vp 0.04 a 1.00 a K snpk 0.00 a

17 Jianhua Li, University of Washington 17 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

18 Jianhua Li, University of Washington 18 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.

19 Jianhua Li, University of Washington 19 Outline Background and Objectives Topics  Data Input  Calibration of Road Deterioration Models  Output Analysis Conclusions and Recommendations

20 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)

21 Jianhua Li, University of Washington 21 Project Level Analysis Pavement performance forecasting Optimal road treatment program

22 Jianhua Li, University of Washington 22 Current Conditions For SR 405, MP 13.82 – 15.17 (Southbound Direction) CharacteristicValue 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

23 Jianhua Li, University of Washington 23 Predicted Road Distress Conditions For SR 405, MP 13.82 – 15.17 (Southbound Direction)

24 Jianhua Li, University of Washington 24 Optimal Road Treatment Program For SR 405, MP 13.82 – 15.17 (Southbound Direction) YearDescriptionTriggerRoad Agency CostWork Quantity (m 2 ) 200945mm overlayCracking$452,29323,805 202045 mm overlayCracking$452,29323,805 203245 mm overlayCracking$452,29323,805 Total cost for the section:$1,356,879

25 Jianhua Li, University of Washington 25 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

26 Jianhua Li, University of Washington 26 Economic Indicators for All ACPs Under Varying Budgets Scenario Annual Budget a Repaired Length (Lane-km) 40-Year Agency Cost a Equilibrium IRI b (m/km)NPV a Optimal Funding Level$105.617,420$4,2241.35$198,052 Current WSDOT Funding $87.114,294$3,4825.00$162,461 75% of Optimal $79.213,094$3,1686.00$159,682 50% of Optimal $52.8 8,642$2,1129.00$146,619 Notes: a.All costs are in millions of present-day dollars b.The IRI that a given funding level can maintain over time.

27 Jianhua Li, University of Washington 27 Predicted Roughness of All ACPs Under Varying Budgets

28 Jianhua Li, University of Washington 28 WSDOT Funding Scenarios for All ACPs Scenario Funding (million/year) 2004-20052006-2043 Optimal$106 Current$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)

29 Jianhua Li, University of Washington 29 Predicted Roughness for All ACPs

30 Jianhua Li, University of Washington 30 Outline Background and Objectives Topics  Data Input  Calibration of Road Deterioration Models  Output Analysis Conclusions and Recommendations

31 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.

32 Jianhua Li, University of Washington 32 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.


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