THE DEVELOPMENT OF MODELS TO PREDICT PAVEMENT PERFORMANCE IN FROST CONDITION

This paper presents the work done to develop first generation performance models using Bayesian statistics. This work was sponsored in part by the C-SHRP under the auspices of the "Joint C-SHRP/Agency Bayesian applications" project. The performance models will be the heart of the new design approach. Bayesian statistics compensate for the lack of good quality well controlled data needed for conventional statistical analysis of pavement performance by providing a means whereby prior information (old databases and/or expert judgement) can be used to supplement the field data. The "XLBayes" statistical package, developed under the Canadian Strategic Highway Research Program (C-SHRP), will be used in the development of four distress specific models that will eventually feed the design model with information on pavement performance in freezing and thawing conditions.

Language

  • English

Media Info

  • Features: Figures; References; Tables;
  • Pagination: v.p.

Subject/Index Terms

Filing Info

  • Accession Number: 00720477
  • Record Type: Publication
  • Files: TRIS
  • Created Date: Apr 9 1996 12:00AM