Development of Prediction Models for Joint Faulting using Long-Term Pavement Performance Database




Hsiang-Wei Ker;Ying-Haur Lee;Chia-Huei Lin

Key Words

Concrete pavements ; Joint faulting ; Long-term pavement performance ; Modern regression ; Prediction models


International Journal of Pavement Research and Technology

Volume or Term/Year and Month of Publication

6卷5期(2013 / 09 / 01)

Page #

658 - 666

Content Language


English Abstract

The main objective of this study is to develop improved faulting prediction models for jointed concrete pavements using the Long-Term Pavement Performance (LTPP) database. The retrieval, preparation, and cleaning of the database were carefully handled in a systematic and automatic approach. The prediction accuracy of the existing prediction models implemented in the recommended Mechanistic-Empirical Pavement Design Guide (NCHRP Project 1-37A) was found to be inadequate. Exploratory data analysis of the response variables indicated that the normality assumption with random errors and constant variance using conventional regression techniques might not be appropriate for prediction modeling. Therefore, without assuming the error distribution of the response variable, several modern regression techniques including generalized linear model (GLM) and generalized additive model (GAM) along with quasi-likelihood estimation method and Poisson distribution were adopted in the subsequent analysis. Box-Cox power transformation and visual graphical techniques were frequently adopted during the prediction modeling process. By keeping only those parameters with significant effects and reasonable physical interpretations in the model, various tentative performance prediction models were developed. The resulting mechanistic-empirical model included several variables such as pavement age, yearly ESALs, bearing stress, annual precipitation, base type, subgrade type, annual temperature range, joint spacing, modulus of subgrade reaction, and freeze-thaw cycle for the prediction of joint faulting. The goodness of fit was further examined through the significant testing and various sensitivity analyses of pertinent explanatory parameters. The tentatively proposed predictive models appeared to reasonably agree with the pavement performance data although their further enhancements are possible and recommended.

Topic Category 工程學 > 土木與建築工程
工程學 > 道路與鐵路工程
  1. FHWA (2003). Distress Identification Manual for the Long-Term Pavement Performance Program, Publication No. FHWA-RD-03-031, Federal Highway Administration, Department of Transportation, Washington, DC, USA.
  2. FHWA (2000). Improved Prediction Models for PCC Pavement Performance-Related Specifications, Volume Ι: Final Report, Publication No. FHWA-RD-00-130, Federal Highway Administration, Department of Transportation, Washington, DC, USA.
  3. Khazanovich, L., Darter, M.I., and Yu, H.T. (2004). Mechanistic-Empirical Model to Predict Transverse Joint Faulting, Transportation Research Record, No. 1896, pp.34-45.
  4. Ker, H.W., Lee, Y.H., and Lin, C.H. (2008). Prediction Models for Transverse Cracking of Jointed Concrete Pavements: Development with Long-Term Pavement Performance Database, Transportation Research Record, No. 2068, pp. 20-31.
  5. Nelder, J.A. and Wedderburn, R.W.M. (1972). Generalized Linear Models, Journal of the Royal Statistical Society (Series A), 135, pp. 370-384.
  6. Darter, M.I., Becker, J.M., and Snyder, M.B. (1985). Concrete Pavement Evaluation System (COPES). NCHRP Report No. 277, NCHRP Project 1-19, Washington, DC, USA.
  7. Simpson, A.L., Rauhut, J.B., Jordahl, P.R., Owusu-Antwi, E., Darter, M.I., Ahmad, R., Pendleton, O.J., and Lee, Y.H. (1993). Early Analyses of LTPP General Pavement Studies Data, Volume 3, Sensitivity Analyses for Selected Pavement Distresses, Report No. SHRP-P-393, Strategic Highway Research Program, Washington, DC, USA.
  8. AASHTO (1998). Supplement to the AASHTO Guide for Design of Pavement Structures, Part II, - Rigid Pavement Design & Rigid Pavement Joint Design, American Association of State Highway and Transportation Officials, Washington, DC, USA.
  9. ARA, Inc., ERES Consultants Division (2004). Guide for Mechanistic- Empirical Design of New and Rehabilitated Pavement Structures, NCHRP 1-37A Report, Transportation Research Board, Washington, DC, USA.
  10. FHWA (2004). Long-Term Pavement Performance Information Management System: Pavement Performance Database Users Reference Guide, Publication No. FHWA-RD-03-088, Federal Highway Administration, Department of Transportation, Washington, DC, USA.
  11. Lin., C.H. (2007). Development of Performance Prediction Models for Rigid Pavements Using LTPP Database, Unpublished Master Thesis, Tamkang University, Taiwan (in Chinese).
  12. FHWA (2001). Backcalculation of Layer Parameters for LTPP Test Sections - Slab on Elastic Solid and Slab on Dense-Liquid Foundation Analysis of Rigid Pavements, FHWA-RD-00-086, Federal Highway Administration, Department of Transportation, Washington, DC, USA.
  13. Insightful Corp. (2003). S-Plus 6.2 for Windows: User’s Manual, Language Reference, Seattle, Washington, USA.
  14. Lee, Y.H. and Darter, M.I. (1995). Development of Performance Prediction Models for Illinois Continuously Reinforced Concrete Pavements, Transportation Research Record, No. 1505, pp.75-84.
  15. Venables, W.N. and Ripley, B.D. (2002). Modern Applied Statistics with S. 4th ed., Springer-Verlag, New York, USA.