An efficient method to generate random distribution of fibers in continuous fiber reinforced composites

Abstract This paper presents a new method based on iterative improvement to generate the random microstructure of continuous fiber reinforced composite with high fiber volume fraction (up to 70%), overcoming the jamming limit of the traditional random sequential adsorption (RSA) method. The novelty of the proposed method lies in an iterative improvement of the generated microstructure through separating initially randomly set positions of the fibers. Without complex heuristic steps, this algorithm can generate different fiber distributions with fast speed and good randomness. The offset magnitude of the separation process is adjusted according to fiber volume fractions to speed up the generation. Statistical analysis is performed on the generated fiber distribution. Five descriptors including Voronoi polygon area, nearest neighbor distances, nearest neighbor orientation, Ripley's K function and pair distribution function are used to compare the proposed algorithm and the RSA with completely spatial random distribution for both short and far distances. Fiber distributions generated by this new algorithm are proved to have good randomness. An finite element analysis (FEA) example is also presented to predict the effective elastic property of the carbon fiber epoxy composites, and a reasonable agreement with the experimental result is achieved. The proposed algorithm provides a useful tool to generate micromechanical models that can be used to predict and understand the mechanical behavior of fiber reinforced composites.