Materials knowledge system for nonlinear composites

Marat I. Latypov, Laszlo S. Toth, Surya R. Kalidindi

Research output: Contribution to journalArticlepeer-review

21 Scopus citations

Abstract

In this contribution, we present a new Materials Knowledge System framework for microstructure-sensitive predictions of effective stress–strain responses in composite materials. The model is developed for composites with a wide range of combinations of strain hardening laws and topologies of the constituents. The theoretical foundation of the model is inspired by statistical continuum theories, leveraged by mean-field approximation of self-consistent models, and calibrated to data obtained from micromechanical finite element simulations. The model also relies on newly formulated data-driven linkages between micromechanical responses (phase-average strain rates and effective strength) and microstructure as well as strength contrast of the constituents. The paper describes in detail the theoretical development of the model, its implementation into an efficient computational plasticity framework, calibration of the linkages, and demonstration of the model predictions on two-phase composites with isotropic constituents exhibiting linear and power-law strain hardening laws. It is shown that the model reproduces finite element results reasonably well with significant savings of the computational cost.

Original languageEnglish (US)
Pages (from-to)180-196
Number of pages17
JournalComputer Methods in Applied Mechanics and Engineering
Volume346
DOIs
StatePublished - Apr 1 2019
Externally publishedYes

Keywords

  • Homogenization theories
  • Materials knowledge systems
  • Micromechanics
  • Multiscale modeling
  • Reduced-order models

ASJC Scopus subject areas

  • Computational Mechanics
  • Mechanics of Materials
  • Mechanical Engineering
  • Physics and Astronomy(all)
  • Computer Science Applications

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