Computational Homogenization of Polycrystals

TL;DR

This paper reviews computational homogenization techniques for simulating the mechanical behavior of polycrystals, covering microstructure representation, crystal plasticity models, and multiscale approaches, with applications to strength, fatigue, and damage prediction.

Contribution

It provides a comprehensive overview of current computational homogenization methods, including mean-field and full-field approaches, and discusses their applications and future challenges.

Findings

Effective modeling of polycrystal deformation using multiscale methods.

Successful prediction of strength, fatigue life, and damage in polycrystals.

Identification of current challenges and future research directions.

Abstract

This paper reviews the current state-of-the-art in the simulation of the mechanical behavior of polycrystalline materials by means of computational homogenization. The key ingredients of this modelling strategy are presented in detail starting with the parameters needed to describe polycrystalline microstructures and the digital representation of such microstructures in a suitable format to perform computational homogenization. The different crystal plasticity frameworks that can describe the physical mechanisms of deformation in single crystals (dislocation slip and twinning) at the microscopic level are presented next. This is followed by the description of computational homogenization methods based on mean-field approximations by means of the viscoplastic self-consistent approach, or on the full-field simulation of the mechanical response of a representative polycrystalline volume element by means of the finite element method or the fast Fourier transform-based method. Multiscale frameworks based on the combination of mean-field homogenization and the finite element method are presented next to model the plastic deformation of polycrystalline specimens of arbitrary geometry under complex mechanical loading. Examples of application to predict the strength, fatigue life, damage, and texture evolution under different conditions are presented to illustrate the capabilities of the different models. Finally, current challenges and future research directions in this field are summarized.