Predicting Asphalt Concrete Fatigue Life Using Artificial Neural Network Approach

The fatigue behavior of asphalt concrete is very complicated that a comprehensive fundamental theoretical model is not available. Therefore, a reliable empirical method for predicting fatigue life based on experimental data remains a desirable approach. However, the complexity of the fatigue process and the noise associated with the fatigue test results make even the traditional empirical methods, such as regression analysis, handicapped in producing a sufficiently accurate model. Artificial neural networks (ANNs) have the ability to derive considerable complex relationships and associations from experimental data while filtering out the effect of noisy data. In this study, the potential use of ANNs for fatigue life prediction was explored and the comparisons between ANN-based model predictions and predictions via multi-linear as well as other published models showed that ANN-based models provide much more accurate predictions.

Language

  • English

Media Info

  • Media Type: CD-ROM
  • Features: Figures; References; Tables;
  • Pagination: 19p
  • Monograph Title: TRB 86th Annual Meeting Compendium of Papers CD-ROM

Subject/Index Terms

Filing Info

  • Accession Number: 01043543
  • Record Type: Publication
  • Report/Paper Numbers: 07-1607
  • Files: TRIS, TRB
  • Created Date: Feb 8 2007 6:16PM