13 citations · 16 across the 5 of their papers we have counts for
4 papers · 1 filter
Learning finite viscoelasticity with DAVIS: A supervised framework for generalized standard materials
Simon Wiesheier, Paul Steinmann, Miguel Angel Moreno-Mateos
This work revisits the recently proposed data-adaptive viscoelasticity (DAVIS) framework, a spline-based formulation of finite viscoelasticity within the generalized standard mater…
Learning ultra-compressible hyperelasticity with splines: Constitutive asymmetries and non-unique representations
Miguel Angel Moreno-Mateos, Simon Wiesheier, Paul Steinmann +1
Highly compressible solids, such as foams, exhibit complex responses, including pronounced tension-compression asymmetry. Capturing such behaviors within unified hyperelastic frame…
Data-adaptive spline surfaces for non-separable hyperelastic energy functions
Simon Wiesheier, Miguel Angel Moreno-Mateos, Paul Steinmann
Invariant-based models for incompressible isotropic hyperelasticity are typically formulated as functions of the first and second invariants, . A widel…
Unsupervised Material Fingerprinting: Ultra-fast hyperelastic model discovery from full-field experimental measurements
Moritz Flaschel, Miguel Angel Moreno-Mateos, Simon Wiesheier +2
Material Fingerprinting is a lookup table-based strategy to discover material models from experimental measurements, which completely avoids the need to solve an optimization probl…