Multi-scale computational homogenisation to predict the long-term durability of composite structures

TL;DR

This paper presents a multi-scale computational homogenisation framework to predict the long-term durability of fibre reinforced polymer composites under hygro-thermo-mechanical effects, incorporating degradation models and high-performance computing techniques.

Contribution

It introduces a coupled hygro-thermo-mechanical model within the Computational Homogenisation framework, including a degradation model based on experimental data, and flexible boundary condition implementation.

Findings

The model accurately predicts property evolution over time under various environmental conditions.

The framework efficiently utilizes high-performance computing for large-scale simulations.

It demonstrates applicability to textile composite RVEs with complex boundary conditions.

Abstract

A coupled hygro-thermo-mechanical computational model is proposed for fibre reinforced polymers, formulated within the framework of Computational Homogenisation (CH). At each macrostructure Gauss point, constitutive matrices for thermal, moisture transport and mechanical responses are calculated from CH of the underlying representative volume element (RVE). A degradation model, developed from experimental data relating evolution of mechanical properties over time for a given exposure temperature and moisture concentration is also developed and incorporated in the proposed computational model. A unified approach is used to impose the RVE boundary conditions, which allows convenient switching between linear Dirichlet, uniform Neumann and periodic boundary conditions. A plain weave textile composite RVE consisting of yarns embedded in a matrix is considered in this case. Matrix and yarns are considered as isotropic and transversely isotropic materials respectively. Furthermore, the computational framework utilises hierarchic basis functions and designed to take advantage of distributed memory high-performance computing.