LAUSR

Abstract In this work, an improved version of the Random Sequential Absorption (RSA) algorithm, comprising of the particle re-orientation algorithm, the particle intersection checking algorithm, the particle periodicity constraint algorithm and the acceleration algorithm, is proposed to efficiently generate Representative Volume Elements (RVEs) of spheroidal particles reinforced composites with specified particle orientations. The re-orientation of the particles is realized using the gradient descent based optimization method, and the RSA algorithm is accelerated by combining with the RVE subcell method and the bounding sphere concept. Several statistical functions are introduced to analyze the distributions of the orientation and centroids of the particles in the RVEs generated by the improved algorithm. The results show that the particle orientations of the generated RVEs match well with the specified particle orientations, and the centroids of the particles in the generated RVEs are not completely randomly distributed. Based on the generated RVEs, the elastic properties and coefficients of thermal expansion of spheroidal particles reinforced composites are predicted by using the FE homogenization method, and the predicted thermo-elastic properties of the composites agree well with those of the analytical models. The advantage of the improved algorithm lies in two aspects: (1) much better computational efficiency and (2) capability of generating the RVEs with specified particle orientations.