Utility of 2D Finite Element Simulations for Predicting Effective Thermomechanical Properties of Particle-Reinforced Composites

Abstract

In the last two decades, researchers have implemented two-dimensional (2D) Finite Element (FE) simulations of particle-reinforced composites for various purposes, including prediction of effective properties and failure modes. The present work aspires to examine the validity of the hypothesis that 2D FE simulations can provide accurate predictions for various thermomechanical properties of high volume fraction (VF) particle-reinforced composites. For this purpose, the random sequential adsorption (RSA) algorithm is implemented to generate FE simulations of various composites. The uniqueness in the methodology of the present work is in the generation of FE simulation of composites with more than two material types as reinforcement, as well as thorough and concurrent comparison of multiple thermal and mechanical properties. The adequacy of the simulations is verified statistically, and the results are compared to predictions from established schemes as well as certain experimental findings. These comparisons show that the predictive power of 2D FE simulations is lower for elastic properties, and higher for coefficient of thermal expansion (CTE) and thermal conductivity of particle-reinforced composites. The findings of this research can guide the researchers in making better decisions for implementing Finite Element Method (FEM) for designing high VF composites.