Experimental Learning of a Hyperelastic Behavior with a Physics-Augmented Neural Network
Author:
Funder
ANR
H2020 European Research Council
Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s11340-024-01106-5.pdf
Reference51 articles.
1. Dornheim J, Morand L, Nallani HJ, Helm D (2024) Neural networks for constitutive modeling: From universal function approximators to advanced models and the integration of physics. Arch Comput Methods Eng 31(2):1097–1127
2. Neggers J, Allix O, Hild F, Roux S (2018) Big data in experimental mechanics and model order reduction: today’s challenges and tomorrow’s opportunities. Arch Comput Methods Eng 25:143–164
3. Roux S, Hild F (2020) Optimal procedure for the identification of constitutive parameters from experimentally measured displacement fields. Int J Solids Struct 184:14–23
4. Herrmann LA, Kollmannsberger S (2024) Deep learning in computational mechanics: a review. Comput Mech
5. Leygue A, Coret M, Réthoré J, Stainier L, Verron E (2018) Data-based derivation of material response. Comput Methods Appl Mech Eng 331:184–196
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