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A two-stage surrogate model for Neo-Hookean problems based on adaptive proper orthogonal decomposition and hierarchical tensor approximation2020 Computer Methods in Applied Mechanics and Engineering article Physics and Astronomy Model Reduction and Neural Networks
Steffen Kastian, Dieter Moser, Lars Grasedyck, Stefanie Reese
18citations -
Model order reduction techniques applied to magnetodynamic T-Ω-formulation2020 COMPEL The International Journal for Computation and Mathematics in Electrical and Electronic Engineering article Physics and Astronomy Model Reduction and Neural Networks
Fabian Müller, Lucas Crampen, Thomas Henneron, Stephane Clenet, Kay Hameyer
4citations -
A hybrid enrichment strategy for the efficient construction of reduced order models by the proper generalized decomposition0citations
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A model hierarchy for predicting the flow in stirred tanks with physics-informed neural networks2024 Advances in Computational Science and Engineering article Physics and Astronomy Model Reduction and Neural Networks Open access
Veronika Trávníková, Daniel Wolff, Nico Dirkes, Stefanie Elgeti, Eric von Lieres, Marek Behr
5citations -
A multi-field decomposed model order reduction approach for thermo-mechanically coupled gradient-extended damage simulations2024 Computer Methods in Applied Mechanics and Engineering article Physics and Astronomy Model Reduction and Neural Networks Open access
Stephan Ritzert, Jian Zhang, Jannick Kehls, Stefanie Reese, Tim Brepols
22citations -
A multi-field decomposed model order reduction approach for thermo-mechanically coupled gradient-extended damage simulations2024 arXiv (Cornell University) preprint Physics and Astronomy Model Reduction and Neural Networks Open access
Qinghua Zhang, Stephan Ritzert, Jian Zhang, Jannick Kehls, Stefanie Reese, Tim Brepols
0citations -
Nonlinear parametric simulation by proper generalized decomposition on the example of a synchronous machine2022 COMPEL The International Journal for Computation and Mathematics in Electrical and Electronic Engineering article Physics and Astronomy Model Reduction and Neural Networks
Fabian Müller, Paul Baumanns, Martin Marco Nell, Kay Hameyer
4citations -
Empirical Material Sampling and Linearisation -- A Simple and Efficient Strain-Space Model Order Reduction Approach for Computational Homogenisation in Large-Deformation Hyperelasticity0citations
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Constructing the Hamiltonian from the behaviour of a dynamical system by proper symplectic decomposition2021 arXiv (Cornell University) preprint Physics and Astronomy Model Reduction and Neural Networks Open access
Nima Shirafkan, Pierre Gosselet, Franz Bamer, Abdelbacet Oueslati, Bernd A. Markert, Géry de Saxcé
1citations