Unsupervised discovery of interpretable hyperelastic constitutive laws M Flaschel, S Kumar, L De Lorenzis Computer Methods in Applied Mechanics and Engineering 381, 113852, 2021 | 57 | 2021 |
NN-EUCLID: Deep-learning hyperelasticity without stress data P Thakolkaran, A Joshi, Y Zheng, M Flaschel, L De Lorenzis, S Kumar Journal of the Mechanics and Physics of Solids 169, 105076, 2022 | 13 | 2022 |
Discovering plasticity models without stress data M Flaschel, S Kumar, L De Lorenzis npj Computational Materials 8 (1), 91, 2022 | 11 | 2022 |
Bayesian-EUCLID: Discovering hyperelastic material laws with uncertainties A Joshi, P Thakolkaran, Y Zheng, M Escande, M Flaschel, L De Lorenzis, ... Computer Methods in Applied Mechanics and Engineering 398, 115225, 2022 | 8 | 2022 |
Automated discovery of generalized standard material models with EUCLID M Flaschel, S Kumar, L De Lorenzis Computer Methods in Applied Mechanics and Engineering 405, 115867, 2023 | 3 | 2023 |
Automated identification of linear viscoelastic constitutive laws with EUCLID E Marino, M Flaschel, S Kumar, L De Lorenzis arXiv preprint arXiv:2212.10969, 2022 | 2 | 2022 |
FEM Data - Discovering plasticity models without stress data M Flaschel, S Kumar, L De Lorenzis ETH Zurich, 2022 | 2 | 2022 |
FEM Data - Unsupervised discovery of interpretable hyperelastic constitutive laws M Flaschel, S Kumar, L De Lorenzis ETH Zurich, 2021 | 2 | 2021 |
Calibration of material parameters based on 180° and 90° ferroelectric domain wall properties in Ginzburg–Landau–Devonshire phase field models M Flaschel, L De Lorenzis Archive of Applied Mechanics 90 (12), 2755–2774, 2020 | 2 | 2020 |
FEM Data-Automated discovery of generalized standard material models with EUCLID M Flaschel, S Kumar, L De Lorenzis ETH Zurich, 2022 | | 2022 |
Experimental Validation of the EUCLID approach for Unsupervised Discovery of Hyperelastic Constitutive Laws M Ricci1a, P Carrara, M Flaschel, S Kumar, S Marfia, L De Lorenzis | | |