Alternating minimization for data-driven computational elasticity from experimental data: kernel method for learning constitutive manifold
Data-driven computing in elasticity attempts to directly use experimental data on material, without constructing an empirical model of the constitutive relation, to predict an equilibrium state of a structure subjected to a specified external load. Provided that a data set comprising stress–strain p...
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| Format: | article |
| Langue: | EN |
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Elsevier
2021
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| Accès en ligne: | https://doaj.org/article/7811f04a4abb47539f5b12f02939f59b |
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