Probabilistic Approaches for Pavement Fatigue Cracking Prediction based on Cumulative Damage Using Miner’s Law

In mechanistic-empirical $\left(\mathrm{M}\text{-}\mathrm{E}\right)$ pavement design, pavement damage is modeled as a random variable with a pre-specified distribution (normal or lognormal). The extent of fatigue cracking in terms of percentage cracking is computed as the probability of cumulative damage exceeding unity. This paper provides a methodological framework for characterizing damage distribution under mixed traffic loading (multiple strain levels) with an improved forecast of traffic spectrum based on renewal theory. Using the linear Miner’s law for damage accumulation, analytical representation of damage distribution is obtainable owing to the proportional relationship between maximum tensile strain of pavement and traffic load under linear elasticity condition. Numerical computation shows that percent of cracking from derived damage distribution is greater than that from hypothetical normal or lognormal distributions traditionally used in the $\mathrm{M}\text{-}\mathrm{E}$ pavement design. The method developed here and the derived model can be used in pavement design and pavement management systems.