FEM-Cluster based reduction method for efficient numerical prediction of effective properties of heterogeneous material in nonlinear range

被引:68
作者
Cheng, Gengdong [1 ]
Li, Xikui [1 ]
Nie, Yinghao [1 ]
Li, Hengyang [1 ]
机构
[1] Dalian Univ Technol, Int Res Ctr Computat Mech, Dept Engn Mech, State Key Lab Struct Anal Ind Equipment, Dalian 116023, Peoples R China
基金
中国国家自然科学基金;
关键词
Nonlinear effective properties' prediction; FEM-Cluster based reduced order method; Cluster-interaction matrix; Elasto-plastic analysis; TRANSFORMATION FIELD ANALYSIS; HOMOGENIZATION METHOD; ELASTIC PROPERTIES; COMPOSITES; IMPLEMENTATION; DECOMPOSITION; OPTIMIZATION; STIFFNESS; ELEMENT; SCHEME;
D O I
10.1016/j.cma.2019.01.019
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
A novel FEM-Cluster based reduced order method or FEM-Cluster based Analysis method (FCA) which enables efficient numerical prediction of effective properties of heterogeneous material in nonlinear range is proposed. The cluster concept initially presented in the work by WK Liu et al. is introduced and extended to derive a full FEM multi-scale formulation of the Representative Unit Cell (RUC) to circumvent the heavy burden due to huge computational efforts required for a direct numerical simulation (DNS) of the high-fidelity RUC. The proposed FEM-Cluster based reduced order method is formulated in a consistent framework of finite element method. The offline clustering process with construction of the cluster-interaction matrix derived under the assumption of the linear elasticity is carried out by the devised FE procedure of RUC. The online elasto-plastic process is performed by the incremental non-linear FE analysis using the constant cluster-interaction matrix, which plays a role in the present work conceptually similar to the initial elastic modular matrix used in the "initial stiffness method" for the traditional incremental elasto-plastic analysis. Accurate and efficient numerical prediction of effective properties of heterogeneous material in nonlinear range are developed in a consistent way. The performances of the proposed reduced order model and its numerical implementation are studied and demonstrated. Several numerical examples show its efficiency and applicability. (C) 2019 Elsevier B.Y. All rights reserved.
引用
收藏
页码:157 / 184
页数:28
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