Spremljaj
Moritz Flaschel
Naslov
Navedeno
Navedeno
Leto
Unsupervised discovery of interpretable hyperelastic constitutive laws
M Flaschel, S Kumar, L De Lorenzis
Computer Methods in Applied Mechanics and Engineering 381, 113852, 2021
1822021
NN-EUCLID: Deep-learning hyperelasticity without stress data
P Thakolkaran, A Joshi, Y Zheng, M Flaschel, L De Lorenzis, S Kumar
Journal of the Mechanics and Physics of Solids 169, 105076, 2022
1092022
Automated discovery of generalized standard material models with EUCLID
M Flaschel, S Kumar, L De Lorenzis
Computer Methods in Applied Mechanics and Engineering 405, 115867, 2023
902023
Discovering plasticity models without stress data
M Flaschel, S Kumar, L De Lorenzis
npj Computational Materials 8 (1), 91, 2022
75*2022
Bayesian-EUCLID: Discovering hyperelastic material laws with uncertainties
A Joshi, P Thakolkaran, Y Zheng, M Escande, M Flaschel, L De Lorenzis, ...
Computer Methods in Applied Mechanics and Engineering 398, 115225, 2022
532022
A review on data-driven constitutive laws for solids
JN Fuhg, G Anantha Padmanabha, N Bouklas, B Bahmani, WC Sun, ...
Archives of Computational Methods in Engineering, 1-43, 2024
312024
Automated identification of linear viscoelastic constitutive laws with EUCLID
E Marino, M Flaschel, S Kumar, L De Lorenzis
Mechanics of Materials 181, 104643, 2023
292023
Automated discovery of interpretable hyperelastic material models for human brain tissue with EUCLID
M Flaschel, H Yu, N Reiter, J Hinrichsen, S Budday, P Steinmann, ...
Journal of the Mechanics and Physics of Solids 180, 105404, 2023
172023
Single-test evaluation of directional elastic properties of anisotropic structured materials
J Boddapati, M Flaschel, S Kumar, L De Lorenzis, C Daraio
Journal of the Mechanics and Physics of Solids 181, 105471, 2023
122023
Reduced and all-at-once approaches for model calibration and discovery in computational solid mechanics
U Römer, S Hartmann, JA Tröger, D Anton, H Wessels, M Flaschel, ...
Applied Mechanics Reviews, 1-51, 2024
102024
Automated discovery of material models in continuum solid mechanics
M Flaschel
ETH Zurich, 2023
72023
Supplementary software for “Discovering plasticity models without stress data"
M Flaschel, S Kumar, L De Lorenzis
ETH Lib, 2022
52022
FEM Data - Unsupervised discovery of interpretable hyperelastic constitutive laws
M Flaschel, S Kumar, L De Lorenzis
ETH Zurich, 2021
52021
FEM Data - Discovering plasticity models without stress data
M Flaschel, S Kumar, L De Lorenzis
ETH Zurich, 2022
42022
Calibration of material parameters based on 180° and 90° ferroelectric domain wall properties in Ginzburg–Landau–Devonshire phase field models
M Flaschel, L De Lorenzis
Archive of Applied Mechanics 90 (12), 2755–2774, 2020
32020
Discovering non-associated pressure-sensitive plasticity models with EUCLID
H Xu, M Flaschel, L De Lorenzis
Advanced Modeling and Simulation in Engineering Sciences 12 (1), 1, 2025
22025
A topology optimisation framework to design test specimens for one-shot identification or discovery of material models
S Ghouli, M Flaschel, S Kumar, L De Lorenzis
arXiv preprint arXiv:2501.12756, 2025
12025
Data‐driven methods for quantitative imaging
G Dong, M Flaschel, M Hintermüller, K Papafitsoros, C Sirotenko, ...
GAMM‐Mitteilungen, e202470014, 2024
12024
FEM Data-Automated discovery of generalized standard material models with EUCLID
M Flaschel, S Kumar, L De Lorenzis
ETH Zurich, 2022
12022
Convex neural networks learn generalized standard material models
M Flaschel, P Steinmann, L De Lorenzis, E Kuhl
Available at SSRN 5023581, 0
1
Sistem trenutno ne more izvesti postopka. Poskusite znova pozneje.
Članki 1–20