Probabilistic failure mechanisms via Monte Carlo simulations of complex microstructures
Nima Noii, Amirreza Khodadadian, Fadi Aldakheel

TL;DR
This paper introduces a stochastic framework combining phase-field fracture modeling with Monte Carlo simulations to analyze failure mechanisms in complex, heterogeneous microstructures, accounting for material and geometric uncertainties.
Contribution
It develops a novel probabilistic modeling approach for microstructure failure analysis using stochastic PDEs and Monte Carlo methods, incorporating heterogeneities in microstructural features.
Findings
Efficient Monte Carlo finite element implementation for microstructure failure prediction.
Quantitative assessment of uncertainty in failure mechanisms.
Validation through numerical examples demonstrating the method's effectiveness.
Abstract
A probabilistic approach to phase-field brittle and ductile fracture with random material and geometric properties is proposed within this work. In the macroscopic failure mechanics, materials properties and exactness of spatial quantities (of different phases in the geometrical domain) are assumed to be homogeneous and deterministic. This is unlike the lower-scale with strong fluctuation in the material and geometrical properties. Such a response is approximated through some uncertainty in the model problem. The presented contribution is devoted to providing a mathematical framework for modeling uncertainty through stochastic analysis of a microstructure undergoing brittle/ductile failure. Hereby, the proposed model employs various representative volume elements with random distribution of stiff-inclusions and voids within the composite structure. We develop an allocating strategy to…
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