A comparative study of cluster-based methods at finite strain

作     者：Yang Yang Lei Zhang Shaoqiang Tang 杨洋;张磊;唐少强

作者机构：MoE Key Laboratory of High Energy Density Physics Simulations(HEDPS)and State Key Laboratory of Turbulence and Complex Systems(LTCS)College of EngineeringPeking UniversityBeijing 100871China 

出 版 物：《Acta Mechanica Sinica》 (力学学报（英文版）)

年 卷 期：2022年第38卷第4期

页      面：104-115,I0003页

核心收录：

学科分类：08[工学] 0802[工学-机械工程] 0701[理学-数学] 0801[工学-力学（可授工学、理学学位）] 0702[理学-物理学] 080102[工学-固体力学] 

基　　金：the National Natural Science Foundation of China(Grant Nos.11832001 11521202 and 11890681) 

主　　题：Virtual clustering analysis Finite strain Homogenization Machine learning 

摘      要：Virtual clustering analysis(VCA)is a reduced-order method for numerical *** formulate VCA for finite strain problems,illustrate its implementation,and provide numerical codes for free download and *** for four test examples shows that both VCA and Self-consistent clustering analysis(SCA)excellently approximate FFT-based direct numerical simulation(DNS)results,yet at much reduced numerical *** is actually even faster in the online stage.