264 citations · 926 across the 20 of their papers we have counts for
5 papers · 1 filter
Benchmarking data-driven material models on the classic Treloar dataset
Hagen Holthusen, Moritz Flaschel, Denisa Martonová +1
Machine learning is rapidly reshaping constitutive modeling, offers new ways to learn material behavior directly from experimental data, and challenges long-established modeling pa…
Neural operators solve inverse problems for constitutive model discovery
Moritz Flaschel, Burigede Liu, Ellen Kuhl
Characterizing the mechanical response of materials traditionally requires solving optimization problems in which model parameters are calibrated or trained to minimize the discrep…
Adaptive Material Fingerprinting for the fast discovery of polyconvex feature combinations in isotropic and anisotropic hyperelasticity
Moritz Flaschel, Hagen Holthusen, Denisa Martonová +1
We recently proposed a method called Material Fingerprinting for the rapid discovery of mechanical material models that avoids solving continuous optimization problems. Material Fi…
Infinite-Dimensional Closed-Loop Inverse Kinematics for Soft Robots via Neural Operators
Carina Veil, Moritz Flaschel, Ellen Kuhl +1
For fully actuated rigid robots, kinematic inversion is a purely geometric problem, efficiently solved by closed-loop inverse kinematics (CLIK) schemes that compute joint velocitie…
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…