Stochastic multiscale computational framework for fibrous composites considering many physical and geometrical random parameters

Naoki Takano, Akio Ohtani, Asami Nakai

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

One of the authors have developed the first-order perturbation based stochastic homogenization (FPSH) method to predict the macroscopic properties considering the geometrical and physical uncertainties at the microscale. The feature of our formulation lies in the use of many physical random parameters, whose verification is shown in this paper by comparison with Monte Carlo simulation using 10,000 sampling points. This method is extended in this paper to predict the microscoipc strain when the RVE (representative volume element) model is under given macroscopic strain condition. This enabled us to predict the damage occurance and also the damage propagation in a stochastic way. Many examples are included in this paper. First, the parameterization of the geometrical uncertainty is described for a GFRP woven fabric reinforced laminate. The idea was extended to a 3D woven ceramic matrix composites and initial damage occurance in the fiber bundles was predicted. Finally, a demonstrative example of a RVE model with single short fiber is presented to show the stochastic prediction of damage propagation in the interphase between fiber and matrix.

Original languageEnglish
Title of host publicationECCM 2018 - 18th European Conference on Composite Materials
PublisherApplied Mechanics Laboratory
ISBN (Electronic)9781510896932
Publication statusPublished - 2020 Jan 1
Event18th European Conference on Composite Materials, ECCM 2018 - Athens, Greece
Duration: 2018 Jun 242018 Jun 28

Publication series

NameECCM 2018 - 18th European Conference on Composite Materials

Conference

Conference18th European Conference on Composite Materials, ECCM 2018
CountryGreece
CityAthens
Period18/6/2418/6/28

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Keywords

  • Damage prediction
  • Finite element method
  • First-order perturbation method
  • Stochastic homogenization method
  • Uncertainty

ASJC Scopus subject areas

  • Ceramics and Composites

Cite this

Takano, N., Ohtani, A., & Nakai, A. (2020). Stochastic multiscale computational framework for fibrous composites considering many physical and geometrical random parameters. In ECCM 2018 - 18th European Conference on Composite Materials (ECCM 2018 - 18th European Conference on Composite Materials). Applied Mechanics Laboratory.