Data-driven and topological design of structural metamaterials for fracture resistance

被引：35

作者：

Da, Daicong ^{[1
]}

Chan, Yu-Chin ^{[1
]}

Wang, Liwei ^{[1
]}

Chen, Wei ^{[1
]}

机构：

[1] Northwestern Univ, Dept Mech Engn, Evanston, IL 60208 USA

来源：

EXTREME MECHANICS LETTERS | 2022年 / 50卷

关键词：

Data-driven methods; Topological design; Structural metamaterials; Brittle fracture; Stress; BRITTLE-FRACTURE; OPTIMIZATION; HOMOGENIZATION; FORMULATION;

D O I：

10.1016/j.eml.2021.101528

中图分类号：

TH [机械、仪表工业];

学科分类号：

0802 ;

摘要：

Data science as a promising paradigm provides novel and diverse opportunities for structural meta-materials attaining exceptional mechanical properties. It is demonstrated here that porous structures composed of brittle constitutive materials can be strong and tough through topological optimization and data-driven techniques. We show that brittle fracture properties can be tailored through the linear control of the homogenized stress and non-periodic microstructures from a multiscale perspective. These tough advanced structural metamaterials pave the way to multiscale components with exceptional fracture resistance. (C) 2021 Published by Elsevier Ltd.

引用

页数：7

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