TY - JOUR
T1 - An advanced method for efficiently generating composite RVEs with specified particle orientation
AU - Tian, Wenlong
AU - Chao, Xujiang
AU - Fu, M. W.
AU - Qi, Lehua
N1 - Funding Information:
Supports from the National Natural Science Foundation of China (Grant no. 51134006 and 51534007), the Science Foundation of China University of Petroleum-Beijing (Grant no. LLYJ-2011-55) and the China Postdoctoral Science Foundation (Grant no. 2016M592270) are gratefully acknowledged.
Publisher Copyright:
© 2021 Elsevier Ltd
PY - 2021/3/22
Y1 - 2021/3/22
N2 - 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.
AB - 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.
KW - Improved RSA algorithm
KW - Particle composites
KW - Particle re-orientation
KW - Representative volume element
KW - Thermo-mechanical properties
UR - http://www.scopus.com/inward/record.url?scp=85099377206&partnerID=8YFLogxK
U2 - 10.1016/j.compscitech.2021.108647
DO - 10.1016/j.compscitech.2021.108647
M3 - Journal article
AN - SCOPUS:85099377206
SN - 0266-3538
VL - 205
JO - Composites Science and Technology
JF - Composites Science and Technology
M1 - 108647
ER -