264 citations · 1.3k across the 16 of their papers we have counts for
6 papers · 1 filter
Automated identification of linear viscoelastic constitutive laws with EUCLID
Enzo Marino, Moritz Flaschel, Siddhant Kumar +1
We extend EUCLID, a computational strategy for automated material model discovery and identification, to linear viscoelasticity. For this case, we perform a priori model selection…
Automated discovery of generalized standard material models with EUCLID
Moritz Flaschel, Siddhant Kumar, Laura De Lorenzis
We extend the scope of our approach for unsupervised automated discovery of material laws (EUCLID) to the case of a material belonging to an unknown class of behavior. To this end,…
NN-EUCLID: deep-learning hyperelasticity without stress data
Prakash Thakolkaran, Akshay Joshi, Yiwen Zheng +3
We propose a new approach for unsupervised learning of hyperelastic constitutive laws with physics-consistent deep neural networks. In contrast to supervised learning, which assume…
Bayesian-EUCLID: discovering hyperelastic material laws with uncertainties
Akshay Joshi, Prakash Thakolkaran, Yiwen Zheng +4
Within the scope of our recent approach for Efficient Unsupervised Constitutive Law Identification and Discovery (EUCLID), we propose an unsupervised Bayesian learning framework fo…
Discovering plasticity models without stress data
Moritz Flaschel, Siddhant Kumar, Laura De Lorenzis
We propose a new approach for data-driven automated discovery of material laws, which we call EUCLID (Efficient Unsupervised Constitutive Law Identification and Discovery), and we…
Numerical approaches for investigating quasiconvexity in the context of Morrey's conjecture
Jendrik Voss, Robert J. Martin, Oliver Sander +3
Deciding whether a given function is quasiconvex is generally a difficult task. Here, we discuss a number of numerical approaches that can be used in the search for a counterexampl…