Prediction of apparent properties with uncertain material parameters using high-order fictitious domain methods and PGD model reduction

Gregory Legrain, Mathilde Chevreuil, Naoki Takano

研究成果: Article査読

2 被引用数 (Scopus)

抄録

This contribution presents a numerical strategy to evaluate the effective properties of image-based microstructures in the case of random material properties. The method relies on three points: (1) a high-order fictitious domain method; (2) an accurate spectral stochastic model; and (3) an efficient model-reduction method based on the proper generalized decomposition in order to decrease the computational cost introduced by the stochastic model. A feedback procedure is proposed for an automatic estimation of the random effective properties with a given confidence. Numerical verifications highlight the convergence properties of the method for both deterministic and stochastic models. The method is finally applied to a real 3D bone microstructure where the empirical probability density function of the effective behaviour could be obtained.

本文言語English
ページ(範囲)345-367
ページ数23
ジャーナルInternational Journal for Numerical Methods in Engineering
109
3
DOI
出版ステータスPublished - 2017 1 20

ASJC Scopus subject areas

  • 数値解析
  • 工学(全般)
  • 応用数学

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