* Equal contribution

Upcoming/Preprints

• Y. Zheng, P. Thakolkaran, J.A. Smith, Z. Lu, S. Zheng, B.H. Nguyen*, S. Kumar*, A. Vashisth*, Inverse design of vitrimeric polymers by molecular dynamics and generative modeling, Arxiv: 2312.03690.

• S.K. Kota, S. Kumar, B. Giovanardi, A discontinuous Galerkin / cohesive zone model approach for the computational modeling of fracture in geometrically exact slender beams, Arxiv:2312.07349.

• P. Thakolkaran*, M.A. Espinal*, S. Dhulipala, S. Kumar*, C.M. Portela*, Experiment-informed finite-strain inverse design of spinodal metamaterials, Arxiv: 2312.11648

2024

• Y. Guo, S. Sharma, S. Kumar, Inverse designing surface curvatures by deep learning, Advanced Intelligent Systems, 2300789 (2024). [code] [data]

• W. Deng, S. Kumar, A. Vallone, D.M. Kochmann, J.R. Greer, AI-enabled materials design of non-periodic 3D architectures with predictable direction-dependent elastic properties, Advanced Materials, 2308149 (2024). [code-topology] [code-ml] [data]

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]

2019

• S. Kumar, K. Danas, D. M. Kochmann, Enhanced local maximum-entropy approximation for stable meshfree simulations, Computer Methods in Applied Mechanics and Engineering, 344 (2019), 858-886.

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:

• S. Kumar, An enhanced maximum-entropy-based meshfree method: theory and applications, PhD Thesis, California Institute of Technology (2019)