A data-driven computational homogenization method based on neural networks for the nonlinear anisotropic electrical response of graphene/polymer nanocomposites

Xiaoxin Lu; Dimitris Giovanis; Julien Yvonnet; Vissarion Papadopoulos; Fabrice Detrez; Jinbo Bai

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

1 MSSMat - Laboratoire de mécanique des sols, structures et matériaux

2 UPEM - Université Paris-Est Marne-la-Vallée

Document type :

Journal articles

Domain :

Physics [physics] / Mechanics [physics]

Complete list of metadatas

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 : Sunday, August 11, 2019 - 1:09:37 AM

A data-driven computational homogenization method based on neural networks for the nonlinear anisotropic electrical response of graphene/polymer nanocomposites

Identifiers

Collections

Citation

Export

Metrics

9

Contact

A data-driven computational homogenization method based on neural networks for the nonlinear anisotropic electrical response of graphene/polymer nanocomposites

Identifiers

Collections

Citation

Export

Share

Metrics

9

Contact