Data-Driven and Topological Design of Structural Metamaterials for Fracture Resistance

Daicong Da, Yu-Chin Chan, Liwei Wang, Wei Chen

Research output: Contribution to journalArticlepeer-review

31 Scopus citations

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.
Original languageAmerican English
JournalExtreme Mechanics Letters
Volume50
DOIs
StatePublished - Jan 2022
Externally publishedYes

Keywords

  • brittle fracture
  • data-driven methods
  • stress
  • structural metamaterials
  • topological design

EGS Disciplines

  • Biomedical Engineering and Bioengineering
  • Mechanical Engineering

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