Data-driven self-consistent clustering analysis of heterogeneous materials with crystal plasticity

Zeliang Liu, Orion L. Kafka, Cheng Yu, Wing Kam Liu*

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingChapter

35 Scopus citations

Abstract

To analyze complex, heterogeneous materials, a fast and accurate method is needed. This means going beyond the classical finite element method, in a search for the ability to compute, with modest computational resources, solutions previously infeasible even with large cluster computers. In particular, this advance is motivated by composites design. Here, we apply similar principle to another complex, heterogeneous system: additively manufactured metals.

Original languageEnglish (US)
Title of host publicationComputational Methods in Applied Sciences
PublisherSpringer Netherland
Pages221-242
Number of pages22
DOIs
StatePublished - 2018

Publication series

NameComputational Methods in Applied Sciences
Volume46
ISSN (Print)1871-3033

ASJC Scopus subject areas

  • Civil and Structural Engineering
  • Modeling and Simulation
  • Biomedical Engineering
  • Computer Science Applications
  • Fluid Flow and Transfer Processes
  • Computational Mathematics
  • Electrical and Electronic Engineering

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