This paper introduces a new vision of data-driven structure computation taking advantage of Material Science, especially for highly nonlinear and time-dependent material behaviours. Technical solutions are also derived, in order to build internal hidden variables defining the so-called “Experimental Constitutive Manifold”.
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Pierre Ladevèze 1; David Néron 1; Paul-William Gerbaud 1
@article{CRMECA_2019__347_11_831_0, author = {Pierre Ladev\`eze and David N\'eron and Paul-William Gerbaud}, title = {Data-driven computation for history-dependent materials}, journal = {Comptes Rendus. M\'ecanique}, pages = {831--844}, publisher = {Elsevier}, volume = {347}, number = {11}, year = {2019}, doi = {10.1016/j.crme.2019.11.008}, language = {en}, }
TY - JOUR AU - Pierre Ladevèze AU - David Néron AU - Paul-William Gerbaud TI - Data-driven computation for history-dependent materials JO - Comptes Rendus. Mécanique PY - 2019 SP - 831 EP - 844 VL - 347 IS - 11 PB - Elsevier DO - 10.1016/j.crme.2019.11.008 LA - en ID - CRMECA_2019__347_11_831_0 ER -
Pierre Ladevèze; David Néron; Paul-William Gerbaud. Data-driven computation for history-dependent materials. Comptes Rendus. Mécanique, Data-Based Engineering Science and Technology, Volume 347 (2019) no. 11, pp. 831-844. doi : 10.1016/j.crme.2019.11.008. https://comptes-rendus.academie-sciences.fr/mecanique/articles/10.1016/j.crme.2019.11.008/
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