17 citations · 23 across the 6 of their papers we have counts for
5 papers · 1 filter
On limitations of polyconvexity
Dominik K. Klein, Rogelio Ortigosa, Heinrich T. Roth +4
Polyconvex constitutive modeling is attractive as it guarantees stability of numerical simulations and can improve the generalization behavior of material models. However, in certa…
Advances in polyconvex anisotropic hyperelasticity
Dominik K. Klein, Karl A. Kalina, Rogelio Ortigosa +3
A key challenge in material theory is the formulation of models that satisfy all common mechanical constitutive conditions while retaining sufficient flexibility. In this context,…
Neural networks meet hyperelasticity: A monotonic approach
Dominik K. Klein, Mokarram Hossain, Konstantin Kikinov +3
We apply physics-augmented neural network (PANN) constitutive models to experimental uniaxial tensile data of rubber-like materials whose behavior depends on manufacturing paramete…
Physics-augmented neural networks for constitutive modeling of hyperelastic geometrically exact beams
Jasper O. Schommartz, Dominik K. Klein, Juan C. Alzate Cobo +1
We present neural network-based constitutive models for hyperelastic geometrically exact beams. The proposed models are physics-augmented, i.e., formulated to fulfill important mec…
Nonlinear electro-elastic finite element analysis with neural network constitutive models
Dominik K. Klein, Rogelio Ortigosa, Jesús Martínez-Frutos +1
In the present work, the applicability of physics-augmented neural network (PANN) constitutive models for complex electro-elastic finite element analysis is demonstrated. For the i…