Improving Pavements With Long-Term Pavement Performance: Products for Today and Tomorrow

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FOREWORD

In 1998, the Federal Highway Administration (FHWA), Long-Term Pavement Performance (LTPP) Program and the Highway Division Pavements Committee of the American Society of Civil Engineers (ASCE) initiated a program to organize an international contest on the use of LTPP data. The competition was designed to promote the use of LTPP data and involve the future pavement engineers in university in the analysis of data from the LTPP database. The program has been in operation for 4 years with three contests. The papers contained in this document are the results of the 2001-2002 contest.

 

Technical Report Documentation Page

1. Report No  FHWA–RD–03–049	2. Government Accession No.	3. Recipient’s Catalog No.
4. Title and Subtitle  Improving Pavements With Long-Term Pavement Performance: Products for Today and Tomorrow Papers From the 2001-2002 International Contest on Long-Term Pavement Performance Data Analysis		5. Report Date  November 2005
		6. Performing Organization Code  N/A
7. Authors(s)  N. Buch, K. Chatti, S.A. Dewan, R. Haas, C.M. Raymond, L. Rothenburg, H.M. Salem, S.L. Tighe		8. Performing Organization Report No.
9. Performing Organization Name and Address  Office of Infrastructure Research and Development Federal Highway Administration 6300 Georgetown Pike, HRDI-13 McLean, VA 22101-2296		10. Work Unit No. (TRAIS)  N/A
		11. Contract or Grant No.
12. Sponsoring Agency Name and Address  American Society of Civil Engineers (ASCE) Transportation and Development Institute Federal Highway Administration Long-Term Pavement Performance (LTPP) Program		13. Type of Report and Period Covered  2001-2002
		14. Sponsoring Agency Code  N/A
15. Supplementary Notes  The Contract Officer’s Technical Representative (COTR) was Antonio Nieves—HRDI-13.
16. Abstract  This report is a compilation of award-winning technical papers from the Third Annual International Contest on LTPP Data Analysis 2001–2002, various authors.
17. Key Words  LTPP, pavement performance, DataPave contest, DataPave		18. Distribution Statement  No restrictions. This document is available to the public through the National Technical Information Service, Springfield, VA 22161.
19. Security Classif. (of this report)  Unclassified	20. Security Classif. (of this page)  Unclassified	21. No. of Pages  151	22. Price

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TABLE OF CONTENTS

INTRODUCTION

     BACKGROUND
     DATA ANALYSIS CONTEST

PAPER 1. THE USE OF THE LONG-TERM PAVEMENT PERFORMANCE DATABASE IN THE PAVEMENT ENGINEERING CURRICULUM AT MICHIGAN STATE UNIVERSITY

     ABSTRACT
     INTRODUCTION
          Undergraduate Pavement Design and Rehabilitation Courses
          Graduate Pavement Design Course
     EXAMPLES OF DATAPAVE 3.0 APPLICATION
          CE432—Pavement Rehabilitation
                Inventory Data
                Distress Evaluation
                Functional Evaluation
                Structural Evaluation
          CE831—Pavement Analysis and Design II
                TASK 1: Selection of Sections from SPS-1 Sites
                TASK 2: Data for Selected SPS-1 Sites
                TASK 3: Pavement Performance and Response for Selected SPS-1 Sites
                TASK 4: Engineering Discussion and Summary of Findings
     CONCLUSIONS
     REFERENCES
     DISCLAIMER

PAPER 2. TRANSFORMING LTPP DISTRESS INFORMATION FOR USE IN MTC–PMS

     ABSTRACT
     INTRODUCTION
     DATA EXTRACTION FROM LTPP DATABASE
     LTPP DISTRESSES VERSUS MTC DISTRESSES
     DATA TRANSFORMATION TECHNIQUES
          LTPP Transverse Profile Data to MTC Rutting Data
          LTPP Block Cracking to MTC Block Cracking
          LTPP Alligator Cracking to MTC Alligator Cracking
          LTPP Longitudinal and Transverse Cracking to MTC Longitudinal and Transverse Cracking
          LTPP Patching, Shoving, and Raveling to MTC Patching, Distortions, Weathering, and Raveling
     PCI AND DEDUCTS FROM MTC-PMS
     STATISTICAL ANALYSIS AND ESTABLISHING IRI MODEL
     CRITICAL REMARKS
     SUMMARY
     REFERENCES

PAPER 3. ANALYSIS OF INFLUENCES ON AS-BUILT PAVEMENT ROUGHNESS IN ASPHALT OVERLAYS

     ABSTRACT
     INTRODUCTION
          Related Studies
     DESCRIPTION OF DATA SOURCES
          As-Built Roughness Pavement Sections
          Prior Roughness of Pavement Sections
     INVESTIGATION OF INFLUENCES ON AS-BUILT ROUGHNESS
          Surface Preparation
          Overlay Thickness
          Comparison of Overlay Material
          Comparison of Pavement Roughness Before Resurfacing
          Investigation of Interactive Effects
     VALIDATION WITH C-LTPP DATA
          Validation of the Effect of Surface Preparation
          Validation of the Effect of Overlay Thickness
          Prediction Equations for As-built Roughness
          Basic Surface Preparation and Thin Overlay
          Basic Surface Preparation and Thick Overlay
          Intensive Surface Preparation and Thin Overlay
          Intensive Surface Preparation and Thick Overlay
     CONCLUSIONS
     RECOMMENDATIONS
     REFERENCES

PAPER 4. EFFECT OF SEASONAL MOISTURE VARIATION ON SUBGRADE RESILIENT MODULUS

     ABSTRACT
     INTRODUCTION AND BACKGROUND
          Study Objective
          Moisture Effects on Soil Resilient Modulus
          Temperature Effects on Soil Resilient Modulus
          Seasonal Variation and Seasonal Adjustment Factors
          Approach
     MOISTURE AND MODULUS DATA
     DATA ANALYSIS
          Seasonal Variation of Moisture and Modulus of Subgrade Soil
                Moisture and Modulus Variation with Time
                Relating Moisture Content to Average Precipitation
          Correlating the Backcalculated Elastic Modulus to Subgrade Soil Moisture and Other Soil Properties
                Model Development for Plastic Soils
                Model Development for Nonplastic Soils
          Estimating Seasonal Adjustment Factors
     SUMMARY AND CONCLUSION
     REFERENCES

PAPER 5. DEVELOPMENT OF A PAVEMENT CLIMATE MAP BASED ON LTPP DATA

     ABSTRACT
     INTRODUCTION
     RESEARCH APPROACH
     CLIMATE DATA PREPROCESSING AND TRANSFORMATION
     CLUSTER ANALYSIS
     DETERMINING THE NUMBER OF CLUSTERS
          Number of Clusters for the Type I Data
          Number of Clusters for the Type II Data
     VERIFICATION OF THE CLUSTERING RESULTS
     CLUSTER MEMBERSHIPS ON GIS MAPS
     SUMMARY AND CONCLUSTIONS
     REFERENCES

LIST OF FIGURES

CHAPTER 1

Figure 1. Pavement inventory and cross section information for SHRP ID 1-4084-1
Figure 2. Distress progression as a function of time
Figure 3. Progression of distress as a function of time
Figure 4. Relationship between IRI and joint and crack faulting
Figure 5. Relationship between IRI and transverse cracking
Figure 6. Deflection profile as function of distance
Figure 7. LTPP FWD positions
Figure 8. Backcalculated layer parameters
Figure 9. D-ratio versus point location for years 1990, 1994, and 1999
Figure 10. LTE versus point location (J4)
Figure 11. Relationship between LTE and void ratio
Figure 12. Measured ESAL and predicted ESAL
Figure 13. Example of a distress map
Figure 14. The pavement structure details for Section 22-0114
Figure 15. Tandem axle load spectrum
Figure 16. Actual and predicted ESALs
Figure 17. The average surface moduli plot with depth for three selected sections
Figure 18. Example of observed and predicted fatigue cracking
Figure 19. Example of observed and predicted rutting
Figure 20. Predicted rut depth for section 116

CHAPTER 2

Figure 1. A schematic diagram for the measurement of rutted widths and rut depths from LTPP transverse profile data
Figure 2. A comparison between SHRP and MTC definitions for block cracking severities, and conversion of LTPP quantities to MTC quantities
Figure 3. Actual versus predicted values of IRI

CHAPTER 3

Figure 1. Limitation on achieving a smooth pavement with a single lift of asphalt
Figure 2. As-built roughness versus prior roughness for SPS-5 data
Figure 3. As-built roughness versus prior roughness for C-LTPP data
Figure 4. As-built roughness versus overlay thickness for C-LTPP data
Figure 5. As-built roughness versus prior roughness for SPS-5 data with basic surface preparation and thin overlay
Figure 6. As-Built roughness versus prior roughness for SPS-5 data with basic surface preparation and thick overlay
Figure 7. As-built roughness versus prior roughness for SPS-5 data with intensive surface preparation and thin overlay
Figure 8. As-built roughness versus prior roughness for SPS-5 data with intensive surface preparation and thick overlay

CHAPTER 4

Figure 1. Moisture content and elastic modulus versus season for clayey soil, site 48-1122
Figure 2. Moisture content and elastic modulus versus season for silty soil, site 24-1634
Figure 3. Moisture content and elastic modulus versus season for clayey soil, site 13-1005
Figure 4. Moisture content and elastic modulus versus season for silty sand, site 28-1016
Figure 5. Moisture content and rainfall versus season for silty sand soil, site 28-1016
Figure 6. Moisture content and rainfall versus season for silty soil, site 24-1634
Figure 7. Moisture content and rainfall versus season for clayey soil, site 13-1005
Figure 8. Moisture content and rainfall versus season for clayey soil, site 48-4143
Figure 9. Moisture content versus rainfall for clayey soil, site 48-4143
Figure 10. Backcalculated modulus versus moisture content for clayey soil, site 48-4143
Figure 11. Backcalculated modulus versus moisture content for fine sandy clay soil, site 13-1005
Figure 12. Backcalculated modulus versus moisture content for coarse sandy clay soil, site 48-1122
Figure 13. Backcalculated modulus versus moisture content for silty soil, site 28-1634
Figure 14. Backcalculated modulus versus moisture content for fine sandy silt, site 48-1077
Figure 15. Backcalculated modulus versus moisture content for sandy soil, site 35-1112
Figure 16. Estimated modulus shift factor for different soil types

CHAPTER 5

Figure 1. The number of text sections having climate records each year
Figure 2. Distance measurement of the average linkage clustering method
Figure 3. CCC versus number of clusters (Type I data)
Figure 4. Scatter plot of the first two PC scores labeled with average link cluster analysis results
Figure 5. Scatter plot of the first two PC scores labeled with K-means cluster analysis results
Figure 6. Scatter plot of the first two PC scores labeled with average link plus K-means cluster analysis results
Figure 7. Cluster membership map based on the average link plus K-means method
Figure 8. Cluster membership map based on the average link method
Figure 9. Cluster membership map based on the K-means methods

LIST OF TABLES

INTRODUCTION

Table 1. Data Analysis Contest winners for 2001—2002

CHAPTER 1

Table 1. Other distresses found in this section
Table 2. Ranking based on distress and computed responses
Table 3. The LTPP section report
Table 4. Summary results for material properties based on backcalculation, September, 1998
Table 5. Summary of the pavement response

CHAPTER 2

Table 1. Differences in definitions between MTC and LTPP for MTC distresses-severities (MTC, 1986; SHRP, 1993)
Table 2. Distress quantities in LTPP system used to obtain distress quantities in MTC system
Table 3. Severity levels of distress types related to cause of deterioration for asphalt and surface treatment pavements (Smith, 1999)
Table 4. Partial results from MTC-PMS and corresponding IRI values

CHAPTER 3

Table 1. SPS-5 experimental test sections
Table 2. As-built IRI measurements
Table 3. IRI measurements before resurfacing
Table 4. Paired data analysis of the effect of surface preparation on as-built IRI
Table 5. Paired data analysis of the effect of design overlay thickness on as-built IRI
Table 6. Paired data analysis of the effect of overlay material on as-built IRI
Table 7. Results of analysis of variance for logarithm of prior roughness for SPS-5 sites
Table 8. Within-subjects effects of repeated measures analysis
Table 9. Between-subjects effects of repeated measures analysis
Table 10. Results of analysis of variance for prior roughness with C-LTPP data
Table 11. Results of analysis of variance for overlay thickness with C-LTPP data
Table 12. Results of analysis of variance for basic surface preparation and thin overlay
Table 13. Results of analysis of variance for basic surface preparation and thick overlay
Table 14. Results of analysis of variance for intensive surface preparation and thin overlay
Table 15. Results of analysis of variance for intensive surface preparation and thick overlay

CHAPTER 4

Table 1. LTPP site locations and subgrade soil characterization
Table 2. The regression procedure using R-square selection method for three sites
Table 3. Analysis of variance table and estimated model parameters
Table 4. Estimated model constants for nonplastic soils

CHAPTER 5

Table 1. Final climate parameters in cluster analysis
Table 2. Transformation of the Type I data
Table 3. Preprocessing of the Type II data
Table 4. Pseudo T2 statistic versus number of clusters (Type I data)
Table 5. Number of clusters versus pseudo F statistic (Type I data)
Table 6. Eigenvalues larger than one