Prediction of apparent properties with uncertain material parameters using high‐order fictitious domain methods and PGD model reduction
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- Gregory Legrain
- GeM Institute, UMR CNRS 6183, École Centrale de Nantes Université de Nantes Nantes France
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- Mathilde Chevreuil
- GeM Institute, UMR CNRS 6183, École Centrale de Nantes Université de Nantes Nantes France
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- Naoki Takano
- Department of Mechanical Engineering Keio University 3‐14‐1 Hiyoshi Yokohama 223‐8522 Japan
抄録
<jats:title>Summary</jats:title><jats:p>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. Copyright © 2016 John Wiley & Sons, Ltd.</jats:p>
収録刊行物
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- International Journal for Numerical Methods in Engineering
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International Journal for Numerical Methods in Engineering 109 (3), 345-367, 2016-05-27
Wiley
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詳細情報 詳細情報について
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- CRID
- 1360567180195544320
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- DOI
- 10.1002/nme.5289
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- ISSN
- 10970207
- 00295981
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- データソース種別
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- Crossref
- KAKEN