3D Representative Volume Element Reconstruction of Fiber Composites via Orientation Tensor and Substructure Features

摘要

To provide a seamless integration of manufacturing processing simulation andfiber microstructure modeling, two new stochastic 3D microstructure reconstructionmethods are proposed for two types of random fiber composites: random short fibercomposites, and Sheet Molding Compounds (SMC) chopped fiber composites. ARandom Sequential Adsorption (RSA) algorithm is first developed to embed statisticalorientation information into 3D RVE reconstruction of random short fiber composites.For the SMC composites, an optimized Voronoi diagram based approach is developedfor capturing the substructure features of SMC chopped fiber composites. Theproposed methods are distinguished from other reconstruction works by providing away of integrating statistical information (fiber orientation tensor) obtained frommaterial processing simulation, as well as capturing the multiscale substructures of theSMC composites.