activity
20202023
most citedUnsupervised discovery of interpretable hyperelastic constitutive laws

264 citations · 1.3k across the 16 of their papers we have counts for

collaborators
Showing 2023Show all

5 papers · 1 filter

cs.CE2023★ 5 cited

Enhanced Floating Isogeometric Analysis

Helge C. Hille, Siddhant Kumar, Laura De Lorenzis

The numerical simulation of additive manufacturing techniques promises the acceleration of costly experimental procedures to identify suitable process parameters. We recently propo…

cs.CE2023★ 205 cited

Unifying the design space and optimizing linear and nonlinear truss metamaterials by generative modeling

Li Zheng, Konstantinos Karapiperis, Siddhant Kumar +1

The rise of machine learning has fueled the discovery of new materials and, especially, metamaterials--truss lattices being their most prominent class. While their tailorable prope…

q-bio.QM2023★ 57 cited

Automated discovery of interpretable hyperelastic material models for human brain tissue with EUCLID

Moritz Flaschel, Huitian Yu, Nina Reiter +5

We propose an automated computational algorithm for simultaneous model selection and parameter identification for the hyperelastic mechanical characterization of human brain tissue…

cond-mat.mtrl-sci2023★ 16 cited

Single-test evaluation of directional elastic properties of anisotropic structured materials

Jagannadh Boddapati, Moritz Flaschel, Siddhant Kumar +2

When the elastic properties of structured materials become direction-dependent, the number of their descriptors increases. For example, in two-dimensions, the anisotropic behavior…

cond-mat.mtrl-sci2023★ 18 cited

Neural Cellular Automata for Solidification Microstructure Modelling

Jian Tang, Siddhant Kumar, Laura De Lorenzis +1

We propose Neural Cellular Automata (NCA) to simulate the microstructure development during the solidification process in metals. Based on convolutional neural networks, NCA can le…