Effects of truck traffic on top-down fatigue cracking performance of flexible pavements using a new mechanics-based analysis framework

Yared H. Dinegdae*, Björn Birgisson

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

The mechanics-based analysis framework predicts top-down fatigue cracking initiation time in asphalt concrete pavements by utilising fracture mechanics and mixture morphology-based property. To reduce the level of complexity involved, traffic data were characterised and incorporated into the framework using the equivalent single axle load (ESAL) approach. There is a concern that this kind of simplistic traffic characterisation might result in erroneous performance predictions and pavement structural designs. This paper integrates axle load spectra and other traffic characterisation parameters into the mechanics-based analysis framework and studies the impact these traffic characterisation parameters have on predicted fatigue cracking performance. The traffic characterisation inputs studied are traffic growth rate, axle load spectra, lateral wheel wander and volume adjustment factors. For this purpose, a traffic integration approach which incorporates Monte Carlo simulation and representative traffic characterisation inputs was developed. The significance of these traffic characterisation parameters was established by evaluating a number of field pavement sections. It is evident from the results that all the traffic characterisation parameters except truck wheel wander have been observed to have significant influence on predicted top-down fatigue cracking performance.

Original languageEnglish
JournalRoad Materials and Pavement Design
VolumeLatest article
Early online date14 Nov 2016
DOIs
Publication statusE-pub ahead of print - 14 Nov 2016

Bibliographical note

This is an Accepted Manuscript of an article published by Taylor & Francis in Road Materials and Pavement Design on 14/11/16, available online: http://www.tandfonline.com/10.1080/14680629.2016.1251958

Keywords

  • asphalt pavement
  • axle load spectra
  • ESAL
  • fatigue
  • mechanics-based
  • Monte Carlo

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