Modelling of fatigue crack propagation using Piecewise Deterministic Markov Processes

Fatigue crack propagation is a stochastic phenomenon in nature due to the inherent uncertainties coming from material properties, environmental conditions and loads. Stochastic processes offer an appropriate framework for modelling crack propagation since it is intended to include sources variabilities. In this work, we propose to model crack propagation mechanism with Piecewise Deterministic Markov Process (PDMP) using usual random crack laws. A new modelling is proposed that consists in using more than one law as each one is more suitable for a specific phase during crack propagation. Regime-switching models seem very attractive and with our modelling assessed crack growth rates and crack lengths are very close to experimental values