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Local Calibration of the MEPDG Using Pavement Management Systems

HIF-11-026

Final Report Volume I

Submitted To:

Federal Highway Administration Office of Asset Management 1200 New Jersey Avenue, SE Washington, DC 20590

July 2010

Notice

This document is disseminated under the sponsorship of the U.S. Department of Transportation in the interest of information exchange. The U.S. Government assumes no liability for the use of the information contained in this document.

The U.S. Government does not endorse products or manufacturers. Trademarks or manufacturers’ names appear in this report only because they are considered essential to the objective of the document.

Quality Assurance Statement

The Federal Highway Administration (FHWA) provides high-quality information to serve Government, industry, and the public in a manner that promotes public understanding. Standards and policies are used to ensure and maximize the quality, objectivity, utility, and integrity of its information. FHWA periodically reviews quality issues and adjusts its programs and processes to ensure continuous quality improvement.

SI (Modern Metric) Conversion Factors

TABLE OF CONTENTS

1. INTRODUCTION

2. THREE STATE SELECTION APPROACH

• Introduction
• Selection Concepts
• Discussion of Selection Categories
  • Category I: Level of Commitment
  • Category II: Availability of Data
  • Category III: Required Level of Effort
  • Category IV: Data Format
• Other Selection Considerations
• Summary

3. THREE STATE SELECTION RESULTS

• Introduction
• Scoring Summary
• Discussion and Results
  • Minnesota
  • Mississippi
  • North Carolina
  • Florida
• States Recommended for Inclusion in the Remainder of the Study

4. SINGLE STATE SELECTION

• Introduction
• State Visit Summaries
  • Minnesota Department of Transportation
  • Mississippi Department of Transportation
  • North Carolina Department of Transportation
• State Recommended for the Study

5. PRELIMINARY FRAMEWORK

• Introduction
• Project Summary Module
• Traffic Module
• Environmental/Climatic Model
• Pavement Structure Model
• Material Characterization
• Pavement Distress Prediction and Measurements
• Database Development Framework
  • Project
  • Traffic
  • Climate
  • Material
  • Performance
  • Other Tables
  • Future Enhancements
• Summary

6. FINAL FRAMEWORK

• Introduction
• Integration of Input Data into the MEPDG Calibration Database
• Summary

7. DATABASE VERIFICATION

• Introduction
• Project Selection
• MEPDG Calibration Database
  • Review of NCDOT Data
  • MEPDG Calibration Database
• Summary

8. MEPDG MODEL CALIBRATION

• Performance Models
• Quantifying Pavement Condition
  • NCDOT Pavement Condition Assessment Methodology
• NCDOT Pavement Sections and Design Inputs
  • Climate
  • Traffic
  • Materials
• Local Calibration
  • NCDOT HMA Pavement Sections
  • NCDOT PCC Pavement Sections
• Summary

9. RECOMMENDATIONS

REFERENCES

LIST OF FIGURES

• Figure 1. Supplemental database approach for MEPDG calibration activities (FHWA 2006a)
• Figure 2. General MEPDG calibration database structure
• Figure 3. Flowchart for calibration
• Figure 4. MEPDG calibration site locations (Mastin 2010)
• Figure 5. MEPDG predicted (uncalibrated) versus NCDOT distress – rutting
• Figure 6. MEPDG predicted (uncalibrated) versus NCDOT distress – alligator cracking
• Figure 7. MEPDG predicted (uncalibrated) versus NCDOT distress – thermal cracking
• Figure 8. Residual error for rutting predictions (uncalibrated)
• Figure 9. Residual error for alligator cracking predictions (uncalibrated)
• Figure 10. Residual error for HMA thermal cracking predictions (uncalibrated)
• Figure 11. Progression of rut depth for NCDOT low severity rating
• Figure 12. Locally calibrated rutting model – section 1006-3
• Figure 13. Locally calibrated rutting model – section 1024-2
• Figure 14. Locally calibrated rutting model – section 1817
• Figure 15. Locally calibrated rutting model – section R2211BA
• Figure 16. Locally calibrated rutting model – section R2232A
• Figure 17. MEPDG predicted (calibrated) versus NCDOT distress – Rutting
• Figure 18. Locally calibrated alligator cracking model – section 1006-3
• Figure 19. Locally calibrated alligator cracking model – section 1802
• Figure 20. Locally calibrated alligator cracking model – section 1817
• Figure 21. Locally calibrated alligator cracking model – section R2211BA
• Figure 22. Locally calibrated alligator cracking model – section R2313B
• Figure 23. Locally calibrated alligator cracking model – section U508CA
• Figure 24. MEPDG predicted (calibrated) versus NCDOT distress – alligator cracking
• Figure 25. Locally calibrated thermal cracking model – section R2000BB
• Figure 26. Locally calibrated thermal cracking model – section R2211BA
• Figure 27. Locally calibrated thermal cracking model – section R2232A
• Figure 28. Comparison of residual errors for thermal cracking model
• Figure 29. MEPDG predicted (uncalibrated) versus NCDOT distress – transverse cracking
• Figure 30. MEPDG predicted (uncalibrated) versus NCDOT distress – Faulting
• Figure 31. Residual error for transverse cracking predictions (uncalibrated)
• Figure 32. Residual error for faulting predictions (uncalibrated)
• Figure 33. Locally calibrated PCC transverse cracking model – section I-10CC
• Figure 34. Locally calibrated PCC transverse cracking model – section I-2511BB
• Figure 35. Locally calibrated PCC transverse cracking model – section I-900AC
• Figure 36. MEPDG predicted (calibrated) versus NCDOT distress – transverse cracking
• Figure 37. Locally calibrated joint faulting model – section I-10CC
• Figure 38. Locally calibrated faulting model – section I-2511BB
• Figure 39. Locally calibrated faulting model – section I-900AC
• Figure 40. MEPDG predicted (calibrated) versus NCDOT distress – Faulting

LIST OF TABLES

• Table 1. Selection Criteria Matrix -One State Example
• Table 2. MEPDG Required Distresses for Local Calibration
• Table 3. Scoring results
• Table 4. Project summary information
• Table 5. Traffic data inputs
• Table 6. Traffic data estimation
• Table 7. Environment/climatic parameters
• Table 8. Pavement structure summary
• Table 9. Determining surface short-wave absorptivity
• Table 10. HMA layer characterization
• Table 11. PCC layer properties
• Table 12. Stabilized layer inputs
• Table 13. Unbound layer inputs
• Table 14. Bedrock layer inputs
• Table 15. Estimating HMA layer parameters
• Table 16. Determining PCC layer values
• Table 17. Characterizing stabilized layer inputs
• Table 18. Characterizing unbound layer inputs
• Table 19. Characterizing bedrock layer inputs
• Table 20. Pavement performance indicators
• Table 21. Differences between databases and spreadsheets
• Table 22. Example of data needs for preventive maintenance treatments
• Table 23. Project summary information
• Table 24. Traffic data
• Table 25. Existing pavement structure
• Table 26. HMA layer characterization
• Table 27. PCC layer properties
• Table 28. Stabilized layer inputs
• Table 30. Bedrock layer inputs
• Table 31. HMA pavement performance indicators
• Table 32. PCC pavement performance indicators
• Table 34. Minimum sample size for MEPDG calibration
• Table 35. Projects by pavement type
• Table 36. Project reference information
• Table 37. Climatic input descriptions
• Table 38. AC materials input descriptions
• Table 39. PCC materials input descriptions
• Table 40. PCC maintenance input descriptions
• Table 41. Unstabilized/stabilized materials input descriptions
• Table 42. Pavement performance input descriptions – HMA
• Table 43. Pavement performance input descriptions – PCC
• Table 44. Traffic input descriptions
• Table 45. Agency data input descriptions – HMA
• Table 46. Agency data input descriptions – JCP
• Table 47. Agency data input descriptions – CRC
• Table 48. LTPP and NCDOT HMA distress definition – rutting
• Table 49. LTPP and NCDOT HMA distress definition – alligator cracking
• Table 50. LTPP and NCDOT HMA distress definition – thermal cracking
• Table 51. LTPP and NCDOT PCC distress definition – transverse cracking
• Table 52. LTPP and NCDOT PCC distress definition – faulting
• Table 53. Summary of HMA pavement sections
• Table 54. Summary of PCC pavement sections
• Table 55. Calibration coefficients to adjust for reducing bias – HMA pavements
• Table 56. Calibration coefficients to adjust for reducing bias – PCC pavements
• Table 57. Pavement sections used in the calibration of the HMA performance models.
• Table 58. Rut progression – low severity
• Table 59. Estimated rut depth by pavement section
• Table 60. Rutting model calibration coefficients
• Table 61. Alligator cracking model calibration coefficients
• Table 62. Thermal cracking model calibration coefficients
• Table 63. Transverse cracking model calibration coefficients
• Table 64. Summary of faulting model calibration coefficients
• Table 65. Estimated timeline for local calibration

LIST OF ABBREVIATIONS AND SYMBOLS

AADT

Average Annual Daily Traffic

AADTT

Average Annual Daily Truck Traffic

AASHTO

American Association of State Highway and Transportation Officials

CRC

Continuously Reinforced Concrete

CRCP

Continuously Reinforced Concrete Pavement

DOT

Department of Transportation

ESAL

Equivalent Single Axle Loads

FHWA

Federal Highway Administration

GIS

Geographic Information System

GPS

Global Positioning System

HMA

Hot Mix Asphalt

IT

Information Technology

IRI

International Roughness Index

JCP

Jointed Concrete Pavement

JPCP

Jointed Plain Concrete Pavement

LTPP

Long-Term Pavement Performance

MEPDG

Mechanistic-Empirical Pavement Design Guide

MS

Microsoft

NCHRP

National Cooperative Highway Research Program

PCC

Portland Cement Concrete

PMS

Pavement Management System

SHA

State Highway Agencies

More Information

• Pavement Publications

Contact

Nastaran Saadatmand
Office of Asset Management, Pavement, and Construction
202-366-1337
E-mail Nastaran

 

Updated: 10/12/2011