Multiobjective optimization of resin transfer molding curing process for silicon‐containing arylacetylene resin‐matrix composites

Silicon‐containing arylacetylene resin (PSA)‐matrix composites hold great potential for aerospace applications due to their excellent heat resistance. In recent years, many PSAs with specific functions have been designed via materials genome approach (MGA), and appropriate resin transfer molding (RTM) curing processes need to be screened to strike a balance between low cost and high quality. In this study, a novel tool based on finite element curing simulation and multiobjective genetic algorithm was developed to optimize the RTM curing process for novel PSA‐matrix composites. The silicon‐containing fluorenylacetylene resin (PSA‐VBF) was selected as the object to systematically characterize its apparent curing kinetics. To address the problem of explosive polymerization of the resin at the injection port during the RTM process, a multiobjective optimization of the curing process using a genetic algorithm was performed to obtain the Pareto front with the maximum temperature gradient at the injection port of the resin, the maximum degree of cure gradient of the composites, and the process time as the objectives. A global sensitivity analysis was also conducted to identify the key parameters. The results demonstrate that the optimized curing process can significantly reduce the temperature gradient and the curing degree gradient with improved curing efficiency.