Non-intrusive data learning based computational homogenization of materials with uncertainties - Archive ouverte HAL
Article Dans Une Revue Computational Mechanics Année : 2019

Non-intrusive data learning based computational homogenization of materials with uncertainties

Résumé

This paper is devoted to the study of the influence of variabilities and uncertainties when homogenizing the effective behavior of elastic heterogeneous media. A new non-intrusive approach is proposed connecting computational homogenization schemes and reduced order models. The effect of the local material variabilities and uncertainties on the overall behavior is studied using a high dimensional parametric approach.
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Dates et versions

hal-04661660 , version 1 (25-07-2024)

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Nawfal Blal, Anthony Gravouil. Non-intrusive data learning based computational homogenization of materials with uncertainties. Computational Mechanics, 2019, 64 (3), pp.807-828. ⟨10.1007/s00466-019-01682-7⟩. ⟨hal-04661660⟩
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