Fatigue Failure Criteria of Asphalt Binders and Asphalt Mixtures: A Comprehensive Review

This study presents a systematic review of fatigue analysis methodologies and failure criteria for asphalt binders and mixtures employed in various cyclic fatigue testing configurations. The investigation focuses on three principal predictive approaches: phenomenological models, mechanistic frameworks, and artificial neural network implementations, which are commonly utilized to forecast asphalt pavement fatigue life based on experimental data from different fatigue tests. A critical evaluation is conducted on the diverse failure criteria integrated within these analytical approaches, with particular emphasis on their respective merits and limitations. Current research findings reveal a notable absence of consensus regarding the precise definition of fatigue failure criteria for asphalt materials. Furthermore, critical parameters including accuracy assessment, reliability verification, and sensitivity analysis of these failure criteria are identified as requiring enhanced research attention. The review proposes several innovative methodologies and criteria formulations that could potentially advance theoretical understanding in this field. This comprehensive analysis of fatigue failure mechanisms in asphalt composites aims to inform strategic refinements for future research trajectories and enhance durability-oriented pavement design practices.