Development of Fatigue Cracking Performance Prediction Models for Flexible Pavements Using LTPP Database

The main objective of this study is to develop improved fatigue cracking models for flexible pavements using the Long-Term Pavement Performance (LTPP) database. The retrieval, preparation, and cleaning of the database were carefully handled in a more systematic and automatic approach. The prediction accuracy of the existing prediction models implemented in the improved 2002 AASHTO guide was found to be inadequate. Exploratory data analysis indicated that the normality assumption with random errors and constant variance using conventional regression techniques might not be appropriate for this study. Therefore, several modern regression techniques including generalized linear model (GLM) and generalized additive model (GAM) along with the assumption of Poisson distribution and quasi-likelihood estimation method were adopted for the modeling process. The resulting mechanistic-empirical model included several variables such as yearly KESALs, pavement age, annual precipitation, annual temperature, critical tensile strain under the AC surface layer, and freeze-thaw cycle for the prediction of fatigue cracking. The goodness of the model 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.

Language

  • English

Media Info

  • Media Type: CD-ROM
  • Features: Figures; References; Tables;
  • Pagination: 14p
  • Monograph Title: TRB 86th Annual Meeting Compendium of Papers CD-ROM

Subject/Index Terms

Filing Info

  • Accession Number: 01043858
  • Record Type: Publication
  • Report/Paper Numbers: 07-1999
  • Files: TRIS, TRB
  • Created Date: Feb 8 2007 6:42PM