An effective method to generate random fiber distributions for high-fiber volume fraction composites

This study presents an efficient methodology for generating random fiber distribution structures capable of accommodating a wide range of volume fractions. The proposed approach, an enhancement over the conventional random distribution particle swarm optimization (RDPSO) method, integrates particle swarm optimization (PSO) for initial fiber placement within a defined window, hard-core scattering to fill matrix-rich regions, and controlled random fiber deletion to obtain the representative volume element (RVE). This comprehensive procedure is termed random deletion after fiber-filling particle swarm optimization (RDAFF_PSO). The spatial statistical properties of the generated fiber distributions were rigorously evaluated and compared against those produced by RDPSO, a completely spatial randomness (CSR) pattern, and experimental data. The results demonstrate the superior performance of RDAFF_PSO in generating realistic fiber distributions. Furthermore, the elastic properties of carbon fiber-reinforced plastic (CFRP) composites were predicted using RVE models generated via the RDAFF_PSO method. The predicted mechanical properties exhibit strong agreement with experimental measurements, validating the efficacy of this approach for estimating the mechanical constants of unidirectional fiber-reinforced composites and facilitating multiscale analysis.