An Integrated Physics-Based Multiscale Modeling Framework for Advancing Thermoset Composites Manufacturing Processes

The manufacturing of composite materials presents numerous opportunities due to their superior properties, including high strength-to-weight ratios and excellent fatigue resistance, which make them ideal for advanced engineering applications. However, realizing these advantages is challenging due to complexities in manufacturing processes, which can introduce defects, residual stress, and variability. This study aims to address these challenges through the development of integrated, physics-based processing models that are capable of predicting and mitigating manufacturing defects in advanced composites. The research focuses on the integration of these physics-based models with data-driven methods such as statistical analysis, uncertainty quantification, and optimization. A significant emphasis is placed on modeling the thermo-viscoelastic (TVE) behavior of curing composites, which is often simplified in processing simulations due to computational costs, by approximating to elastic responses according to the Cure Hardening Instantaneously Linear Elastic (CHILE) model. Results show that cure-dependent TVE process simulations implemented through Finite Element Analysis (FEA) can be efficiently integrated with optimization algorithms. 570 simulations completed in 109 min on a local desktop computer. Building on these advancements, this work further investigates Automated Fiber Placement (AFP) under the context of Integrated Computational Materials Engineering (ICME), and establishes the groundwork and serves as roadmap for AFP research at Purdue University with a focus on process modeling and integration.