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Upcoming/Preprints
2023
- L. Zheng, K. Karapiperis, S. Kumar*, D.M. Kochmann*, Unifying the design space and optimizing linear and nonlinear truss metamaterials by generative modeling, Nature Communications, 14, 7563 (2023). [code] [data]
- J. Boddapati, M. Flaschel, S. Kumar, L. De Lorenzis, C. Daraio, Single-test evaluation of directional elastic properties of anisotropic structured materials, Journal of the Mechanics and Physics of Solids, 181 (2023) 105471.
- H. C. Hille, S. Kumar, L. De Lorenzis, Enhanced Floating Isogeometric Analysis, Computer Methods in Applied Mechanics and Engineering, 417 (2023), 116346.
- M. Flaschel*, H. Yu*, N. Reiter, J. Hinrichsen, S. Budday, P. Steinmann, S. Kumar, L. De Lorenzis, Automated discovery of interpretable hyperelastic material models for human brain tissue with EUCLID, Journal of the Mechanics and Physics of Solids, 180 (2023) 105404. [code]
- J. Tang, S. Kumar, L. De Lorenzis, E. Hosseini, Neural cellular automata for solidification microstructure modelling, Computer Methods in Applied Mechanics and Engineering, 414 (2023), 116197. [code]
- S. Van 't Sant*, P. Thakolkaran*, J. Martínez, S. Kumar, Inverse-designed growth-based cellular metamaterials, Mechanics of Materials, 182 (2023), 104668. [code] [data]
- R.N. Glaesener, S. Kumar, C. Lestringant, T. Butruille, C.M. Portela, D.M. Kochmann, Predicting the influence of geometric imperfections on the mechanical response of 2D and 3D periodic trusses, Acta Materialia, 254 (2023), 118918.
- E. Marino, M. Flaschel , S. Kumar, L. De Lorenzis, Automated identification of linear viscoelastic constitutive laws with EUCLID, Mechanics of Materials, 181 (2023), 104643. [code]
- M. Flaschel, S. Kumar, L. De Lorenzis, Automated discovery of generalized standard material models with EUCLID, Computer Methods in Applied Mechanics and Engineering, 405 (2023) 115867. [code] [data]
2022
- P. Thakolkaran, A. Joshi, Y. Zheng, M. Flaschel, L. De Lorenzis, S. Kumar, NN-EUCLID: deep-learning hyperelasticity without stress data, Journal of the Mechanics and Physics of Solids, 169 (2022) 105076. [code] [data]
- A. Joshi, P. Thakolkaran, Y. Zheng, M. Escande, M. Flaschel, L. De Lorenzis, S. Kumar, Bayesian-EUCLID: discovering hyperelastic material laws with uncertainties, Computer Methods in Applied Mechanics and Engineering, 398 (2022) 115225. [code] [data]
- M. Flaschel, S. Kumar, L. De Lorenzis, Discovering plasticity models without stress data, npj Computational Materials, 8 (2022), 91. [code] [data]
- J. H. Bastek, S. Kumar, B. Telgen, R. N. Glaesener, D. M. Kochmann, Inverting the structure–property map of truss metamaterials by deep learning, Proceedings of the National Academy of Sciences, 119 (1) e2111505119 (2022). [code] [data]
- H. C. Hille, S. Kumar, L. De Lorenzis, Floating Isogeometric Analysis, Computer Methods in Applied Mechanics and Engineering, 392 (2022), 114684.
- J. Voss, R. J. Martin, O. Sander, S. Kumar, D. M. Kochmann, P. Neff, Numerical approaches for investigating quasiconvexity in the context of Morrey's conjecture, Journal of Nonlinear Science, 32, 77 (2022).
- S. Kumar, D. M. Kochmann, What machine learning can do for computational solid mechanics, Current Trends and Open Problems in Computational Mechanics, Springer (2022). [Book chapter]
2021
- L. Zheng, S. Kumar, D. M. Kochmann, Data-driven topology optimization of spinodoid metamaterials with seamlessly tunable anisotropy, Computer Methods in Applied Mechanics and Engineering, 383 (2021), 113894. [code-topology] [code-ml] [data] (requires GIBBON: https://www.gibboncode.org/)
- M. Flaschel*, S. Kumar*, L. De Lorenzis, Unsupervised discovery of interpretable hyperelastic constitutive laws, Computer Methods in Applied Mechanics and Engineering, 381 (2021), 113852. [code] [data]
2020
- S. Kumar, S. Tan, L. Zheng, D. M. Kochmann, Inverse-designed spinodoid metamaterials, npj Computational Materials, 6 (2020), 73. [code-topology] [code-ml] [data] (requires GIBBON: https://www.gibboncode.org/)
- S. Kumar, A. Vidyasagar, D. M. Kochmann, An assessment of numerical techniques to find energy‐minimizing microstructures associated with nonconvex potentials, International Journal for Numerical Methods in Engineering, 121 (2020), 1595-1628 (cover article).
- S. Kumar*, A. D. Tutcuoglu*, Y. Hollenweger, D. M. Kochmann, A meshless multiscale approach to modeling severe plastic deformation of metals: Application to ECAE of pure copper, Computational Material Science, 173 (2020), 109329.
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)
2019
Before 2017
- R. Singh, S. Kumar, A. Kumar, Effect of intrinsic twist and orthotropy on extension-twist-inflation coupling in compressible circular tubes, Journal of Elasticity, 128 (2017), 175-201
- A. Kumar, S. Kumar, P. Gupta, A Helical Cauchy-Born rule for special Cosserat rod modeling of nano and continuum rods, Journal of Elasticity, 124 (2016), 81-106
Thesis: