Modelling the effect of fiber distribution on the transverse mechanical characteristics of unidirectionally reinforced continuous-fiber composite

Abstract

This study investigates the influence of fiber spatial distribution on the transverse mechanical properties of unidirectionally reinforced continuous-fiber composites. A Swelling & Random Migration algorithm was employed to generate representative volume elements with controlled fiber arrangements, ranging from clustered to equilibrium configurations. Finite element homogenization with periodic boundary conditions was used to estimate effective elastic properties. To characterize fiber randomness and assess statistical equivalence with experimental microstructures, several descriptors are employed, including nearest neighbor distance, Ripley's K-function, pair distribution function, and local fiber volume fraction. Results reveal that, at constant fiber volume fraction, clustered fiber distributions yield significantly higher transverse stiffness but lower transverse tensile strength compared to the equilibrium distributions. For glass/epoxy composites, transverse stiffness varies by up to 20% depending on the degree of fiber clustering. A single scalar descriptor, the mean nearest neighbor distance, was shown to efficiently characterize sufficiently random fiber distributions: effective stiffness decreases, whereas transverse tensile strength increases linearly with mean nearest neighbor distance. The findings highlight the critical role of microstructural characteristics in tailoring composite performance and provide a robust framework for predictive modeling of fiber reinforced materials.