| Inverse-designed spinodoid metamaterials S Kumar, S Tan, L Zheng, DM Kochmann npj Computational Materials 6 (1), 1-10, 2020 | 96* | 2020 |
| 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 |
| Data-driven topology optimization of spinodoid metamaterials with seamlessly tunable anisotropy L Zheng, S Kumar, DM Kochmann Computer Methods in Applied Mechanics and Engineering 383, 113894, 2021 | 52 | 2021 |
| A helical Cauchy-Born rule for special Cosserat rod modeling of nano and continuum rods A Kumar, S Kumar, P Gupta Journal of Elasticity 124 (1), 81-106, 2016 | 29 | 2016 |
| Inverting the structure–property map of truss metamaterials by deep learning JH Bastek, S Kumar, B Telgen, RN Glaesener, DM Kochmann Proceedings of the National Academy of Sciences 119 (1), e2111505119, 2022 | 23 | 2022 |
| Enhanced local maximum-entropy approximation for stable meshfree simulations S Kumar, K Danas, DM Kochmann Computer Methods in Applied Mechanics and Engineering 344, 858-886, 2019 | 21 | 2019 |
| Effect of Intrinsic Twist and Orthotropy on Extension–Twist–Inflation Coupling in Compressible Circular Tubes R Singh, S Kumar, A Kumar Journal of Elasticity 128 (2), 175-201, 2017 | 16 | 2017 |
| 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 |
| An assessment of numerical techniques to find energy‐minimizing microstructures associated with nonconvex potentials S Kumar, A Vidyasagar, DM Kochmann International Journal for Numerical Methods in Engineering 121 (7), 1595-1628, 2020 | 12 | 2020 |
| A meshless multiscale approach to modeling severe plastic deformation of metals: Application to ECAE of pure copper S Kumar, AD Tutcuoglu, Y Hollenweger, DM Kochmann Computational Materials Science 173, 109329, 2020 | 12 | 2020 |
| Discovering plasticity models without stress data M Flaschel, S Kumar, L De Lorenzis npj Computational Materials 8 (1), 1-10, 2022 | 11 | 2022 |
| What machine learning can do for computational solid mechanics S Kumar, DM Kochmann Current Trends and Open Problems in Computational Mechanics, 275-285, 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 |
| Numerical approaches for investigating quasiconvexity in the context of Morrey's conjecture J Voss, RJ Martin, O Sander, S Kumar, DM Kochmann, P Neff arXiv preprint arXiv:2201.06392, 2022 | 4 | 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 |
| Floating Isogeometric Analysis HC Hille, S Kumar, L De Lorenzis Computer Methods in Applied Mechanics and Engineering 392, 114684, 2022 | | 2022 |
| An Enhanced Maximum-Entropy Based Meshfree Method: Theory and Applications S Kumar California Institute of Technology, 2019 | | 2019 |
Dennis KochmannETH ZurichBestätigte E-Mail-Adresse bei ethz.ch
