An Integrated Processing–Performance Modeling Framework for Predicting the Effect of Curing on the Transverse Strength of Thermoset Composites

Abstract

The mechanical properties of fiber-reinforced polymer matrix composites are strongly influenced by manufacturing processes. In particular, curing of thermoset polymer matrices introduces residual stresses that can significantly affect microscale damage initiation and the transverse strength of composite materials. This study presents an integrated processing–performance modeling framework to predict the transverse tensile strength of thermoset composites by explicitly accounting for the microstructure and curing-induced residual stress. A discrete microscale Finite Element Analysis (FEA) model based on Representative Volume Elements (RVEs) with a random fiber distribution is developed to predict curing-induced residual stress development and damage evolution under subsequent mechanical loading. The composite curing behavior is modeled using the Cure Hardening Instantaneous Linear Elastic (CHILE) model in which the resin modulus evolves monotonically with the degree of cure (DOC). Progressive damage is captured through a fracture-energy-based Smeared Crack Approach (SCA). To enable coupled curing–damage simulations, an incremental formulation of the SCA is implemented within the FEA framework to accommodate the non-zero stress state resulting from curing. To account for the inherent variability and stochastic nature of composite microstructures, a random fiber packing algorithm is employed to generate multiple fiber distribution realizations. The influences of RVE size and matrix fracture properties on the predicted transverse tensile response are systematically investigated. This work provides a fundamental building block toward understanding how manufacturing-induced effects propagate across length scales and ultimately govern the mechanical performance of composite materials.