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A data-driven computational homogenization method based on neural networks for the nonlinear anisotropic electrical response of graphene/polymer nanocomposites
Xiaoxin Lu
1
Dimitris Giovanis
Julien Yvonnet
2, *
Vissarion Papadopoulos
Fabrice Detrez
Jinbo Bai
1
*
Corresponding author
Xiaoxin Lu 1
Author
Dimitris Giovanis
Author
Julien Yvonnet 2
Correspondent author IdHAL : j-yvonnet
Vissarion Papadopoulos
Author
Fabrice Detrez
Author IdHAL : fabrice-detrez
Jinbo Bai 1
Author
1
MSSMat - Laboratoire de mécanique des sols, structures et matériaux (CentraleSupélec - Bâtiment Eiffel - 3 rue Joliot Curie - 91190 GIF-SUR-YVETTE - France)
- CentraleSupélec (3, rue Joliot Curie, Plateau de Moulon, 91192 GIF-SUR-YVETTE Cedex - France)
- CNRS - Centre National de la Recherche Scientifique : UMR8579 (France)
2
UPEM - Université Paris-Est Marne-la-Vallée (5 boulevard Descartes - Champs-sur-Marne - 77454 Marne-la-Vallée Cedex 2 - France)
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Journal articles
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https://hal-upec-upem.archives-ouvertes.fr/hal-02265344
Contributor : J. Yvonnet <>
Submitted on : Friday, August 9, 2019 - 2:13:01 PM
Last modification on : Wednesday, July 8, 2020 - 11:10:22 AM
Contributor : J. Yvonnet <>
Submitted on : Friday, August 9, 2019 - 2:13:01 PM
Last modification on : Wednesday, July 8, 2020 - 11:10:22 AM
Identifiers
- HAL Id : hal-02265344, version 1
- DOI : 10.1007/s00466-018-1643-0
Citation
Xiaoxin Lu, Dimitris Giovanis, Julien Yvonnet, Vissarion Papadopoulos, Fabrice Detrez, et al.. A data-driven computational homogenization method based on neural networks for the nonlinear anisotropic electrical response of graphene/polymer nanocomposites. Computational Mechanics, Springer Verlag, 2019, 64 (2), pp.307-321. ⟨10.1007/s00466-018-1643-0⟩. ⟨hal-02265344⟩
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