most citedViscoelasticty with physics-augmented neural networks: Model formulation and training methods without prescribed internal variables

2 citations · 2 across the 2 of their papers we have counts for

collaborators

2 papers

cs.CE2025

Data-efficient inverse design of spinodoid metamaterials

Max Rosenkranz, Markus Kästner, Ivo F. Sbalzarini

We create an data-efficient and accurate surrogate model for structure-property linkages of spinodoid metamaterials with only 75 data points -- far fewer than the several thousands…

cs.CE2024★ 2 cited

Viscoelasticty with physics-augmented neural networks: Model formulation and training methods without prescribed internal variables

Max Rosenkranz, Karl A. Kalina, Jörg Brummund +2

We present an approach for the data-driven modeling of nonlinear viscoelastic materials at small strains which is based on physics-augmented neural networks (NNs) and requires only…