(Peer-Reviewed) Clustering Solver for Displacement-based Numerical Homogenization
Shaoqiang Tang 唐少强, Xi Zhu 朱熙
HEDPS, CAPT and LTCS, College of Engineering, Peking University, Beijing 100871, China
北京大学工学院
Abstract
Based on strain-clustering via k-means, we decompose computational domain into clusters of possibly disjoint cells. Assuming cells in each cluster take the same strain, we reconstruct displacement field. We further propose a new way to condensate the governing equations of displacement-based finite element method to reduce the complexity while maintain the accuracy.
Numerical examples are presented to illustrate the efficiency of the clustering solver. Numerical convergence studies are performed for the examples. Avoiding complexities which is common in existing clustering analysis methods, the proposed clustering solver is easy to implement, particularly for numerical homogenization using commercial softwares.
Multi-photon neuron embedded bionic skin for high-precision complex texture and object reconstruction perception research
Hongyu Zhou, Chao Zhang, Hengchang Nong, Junjie Weng, Dongying Wang, Yang Yu, Jianfa Zhang, Chaofan Zhang, Jinran Yu, Zhaojian Zhang, Huan Chen, Zhenrong Zhang, Junbo Yang
Opto-Electronic Advances
2025-01-22
