Data-driven and topological design of structural metamaterials for fracture resistance. (January 2022)

• Record Type: Journal Article
• Authors: Da, Daicong; Chan, Yu-Chin; Wang, Liwei; Chen, Wei
• Is Part Of: Extreme mechanics letters. Volume 50(2022)
• Publication Date: 2022-01
• Subjects: Data-driven methods -- Topological design -- Structural metamaterials -- Brittle fracture -- Stress; Mechanics -- Periodicals; Mechanics, Applied -- Periodicals; Mechanics; Electronic journals; Periodicals; 531.05
• DOI: 10.1016/j.eml.2021.101528
• Languages: English
• ISSNs: 2352-4316

Abstract

Abstract: Data science as a promising paradigm provides novel and diverse opportunities for structural metamaterials 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.