TY - JOUR
T1 - From microscale to mesoscale
T2 - The non-linear behavior prediction of 3D braided composites based on the SCA2 concurrent multiscale simulation
AU - He, Chunwang
AU - Ge, Jingran
AU - Gao, Jiaying
AU - Liu, Jiapeng
AU - Chen, Haosen
AU - Liu, Wing Kam
AU - Fang, Daining
N1 - Publisher Copyright:
© 2021 Elsevier Ltd
PY - 2021/9/8
Y1 - 2021/9/8
N2 - Compared with traditional phenomenological models, concurrent multiscale simulation is a powerful tool to capture the mechanical behavior of composites from different scales simultaneously. However, it is still a challenge to conduct a concurrent multiscale simulation for composites due to the huge computational costs. The aim of this paper is to solve the challenge by introducing an effective reduced order model (ROM), called the data-driven self-consistent clustering analysis (SCA). The SCA method solves the RVE problem into two stages. In the offline stage, the high-fidelity RVE of composites is compressed into a cluster-based RVE and the interaction tensor between two clusters is calculated. In the online stage, a cluster-based discrete incremental Lippmann-Schwinger equation is solved to get the local strain and stress responses. Based on SCA, a concurrent multiscale framework SCA2 from microscale to mesoscale is proposed to capture the non-linear behavior of 3D braided composites. Firstly, the SCA-based results for yarn RVE and braided RVE are compared with the finite element (FE) results to verify the accuracy of the algorithm. Then, the SCA2 framework is applied to simulate the uniaxial tension and compression of 3D braided composites, which is also validated with the experiments and shows great accuracy and high efficiency. The proposed SCA2 framework will be extended into a three-scale concurrent simulation for the macroscopic structure analysis.
AB - Compared with traditional phenomenological models, concurrent multiscale simulation is a powerful tool to capture the mechanical behavior of composites from different scales simultaneously. However, it is still a challenge to conduct a concurrent multiscale simulation for composites due to the huge computational costs. The aim of this paper is to solve the challenge by introducing an effective reduced order model (ROM), called the data-driven self-consistent clustering analysis (SCA). The SCA method solves the RVE problem into two stages. In the offline stage, the high-fidelity RVE of composites is compressed into a cluster-based RVE and the interaction tensor between two clusters is calculated. In the online stage, a cluster-based discrete incremental Lippmann-Schwinger equation is solved to get the local strain and stress responses. Based on SCA, a concurrent multiscale framework SCA2 from microscale to mesoscale is proposed to capture the non-linear behavior of 3D braided composites. Firstly, the SCA-based results for yarn RVE and braided RVE are compared with the finite element (FE) results to verify the accuracy of the algorithm. Then, the SCA2 framework is applied to simulate the uniaxial tension and compression of 3D braided composites, which is also validated with the experiments and shows great accuracy and high efficiency. The proposed SCA2 framework will be extended into a three-scale concurrent simulation for the macroscopic structure analysis.
KW - A. Textile composites
KW - B. non-linear behavior
KW - C. Computational mechanics
KW - C. Concurrent multiscale simulation
UR - http://www.scopus.com/inward/record.url?scp=85110479500&partnerID=8YFLogxK
U2 - 10.1016/j.compscitech.2021.108947
DO - 10.1016/j.compscitech.2021.108947
M3 - Article
AN - SCOPUS:85110479500
SN - 0266-3538
VL - 213
JO - Composites Science and Technology
JF - Composites Science and Technology
M1 - 108947
ER -