Stochastic multiscale modeling of crack propagation in random heterogeneous media

Abstract

SummaryA stochastic approach to model crack propagation in random heterogeneous media, using mesoscopic representations of elastic and fracture properties, is presented. In order to obtain reference results, Monte‐Carlo simulations are first conducted on microstructural samples in which a pre‐existing crack is propagated by means of a phase‐field approach. These computations are used to estimate the subscale‐induced randomness on the macroscopic response of the domain. Mesoscopic descriptors are then introduced to investigate scale transition. Elasticity tensor random fields are specifically defined, at that stage, through a moving‐window upscaling approach. The mesoscopic fracture toughness, which is assumed homogeneous and deterministic, is identified by solving an inverse problem involving the macroscopic peak force. A stochastic model is subsequently constructed in which the mesoscopic elasticity is described as a non‐Gaussian random field. This model allows the multiscale‐informed elastic counterpart in the phase‐field formulation to be sampled without resorting to computational homogenization. The results obtained with the sample‐based and model‐based mesoscopic descriptions are finally compared with those corresponding to the full‐scale microscopic model. It is shown, in particular, that the mesoscopic elasticity‐phase‐field formulation associated with statically uniform boundary conditions enables the accurate predictions of the mean elastic response and mean peak force.