Papers matching “physics-informed modeling” 108
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Using physics-informed enhanced super-resolution generative adversarial networks for subfilter modeling in turbulent reactive flows2021 Proceedings of the Combustion Institute article Physics and Astronomy Model Reduction and Neural Networks Open access
Mathis Bode, Michael Gauding, Zeyu Lian, Dominik Denker, Marco Davidovic, Konstantin Kleinheinz, +2 more
150citations -
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 -
Physics-informed neural network for constitutive modeling of cyclic crystal plasticity considering deformation mechanism2025 International Journal of Mechanical Sciences article Materials Science Machine Learning in Materials Science cited by 1 patent
Huanbo Weng, Franz Bamer, Cheng Luo, Bernd A. Markert, Huang Yuan
32citations -
Fast Computation of Hydrodynamic Pressure in Lubricated Contacts: Which Lp Loss is Most Suitable for Physics-Informed Neural Networks Solving the Reynolds Equation?2024 International Journal of Fluid Power article Physics and Astronomy Model Reduction and Neural Networks Open access
Faras Brumand‐Poor, Nils Plückhahn, Niklas Bauer, Katharina Schmitz
2citations -
Physics-informed neural networks for dynamic process operations with limited physical knowledge and data2024 Computers & Chemical Engineering article Physics and Astronomy Model Reduction and Neural Networks Open access
Mehmet Velioglu, Song Zhai, Sophia Rupprecht, Alexander Mitsos, Andreas Jupke, Manuel Dahmen
54citations -
Physics-Informed Neural Networks for Dynamic Process Operations with Limited Physical Knowledge and Data2024 arXiv (Cornell University) preprint Physics and Astronomy Model Reduction and Neural Networks Open access
Mehmet Velioglu, Sophia Rupprecht, Alexander Mitsos, Andreas Jupke, Manuel Dahmen
2citations -
Estimating Dense-Packed Zone Height in Liquid-Liquid Separation: A Physics-Informed Neural Network Approach2026 arXiv (Cornell University) preprint Physics and Astronomy Model Reduction and Neural Networks Open access
Mehmet Velioglu, Song Zhai, Alexander Mitsos, Adel Mhamdi, Andreas Jupke, Manuel Dahmen
0citations -
Estimating Dense-Packed Zone Height in Liquid-Liquid Separation: A Physics-Informed Neural Network Approach2026 RWTH Publications (RWTH Aachen) preprint Physics and Astronomy Model Reduction and Neural Networks Open access
Mehmet Velioglu, Song Zhai, Alexander Mitsos, Adel Mhamdi, Andreas Jupke, Manuel Dahmen
0citations -
Extrapolation of cavitation and hydrodynamic pressure in lubricated contacts: a physics-informed neural network approach2025 Advanced Modeling and Simulation in Engineering Sciences article Engineering Tribology and Lubrication Engineering Open access
Faras Brumand‐Poor, Freddy Kokou Azanledji, Nils Plückhahn, Florian Barlog, Lukas Boden, Katharina Schmitz
7citations -
Spline-PINN: Approaching PDEs without Data Using Fast, Physics-Informed Hermite-Spline CNNs2022 Proceedings of the AAAI Conference on Artificial Intelligence conference-paper Physics and Astronomy Model Reduction and Neural Networks Open access cited by 1 patent
Nils Wandel, Michael Weinmann, Michael Neidlin, Reinhard Klein
60citations -
A physics-informed meta-learning framework for the continuous solution of parametric PDEs on arbitrary geometries2026 Computers & Structures article Physics and Astronomy Model Reduction and Neural Networks Open access
Reza Najian Asl, Yusuke Yamazaki, Kianoosh Taghikhani, Mayu Muramatsu, Markus Apel, Shahed Rezaei
4citations