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Applying physics-informed enhanced super-resolution generative adversarial networks to turbulent premixed combustion and engine-like flame kernel direct numerical simulation data2023 Proceedings of the Combustion Institute article Physics and Astronomy Model Reduction and Neural Networks Open access
Mathis Bode, Michael Gauding, Dominik Goeb, Tobias Falkenstein, Heinz G. Pitsch
31citations -
Applying Physics-Informed Enhanced Super-Resolution Generative Adversarial Networks to Turbulent Premixed Combustion and Engine-like Flame Kernel Direct Numerical Simulation Data2022 arXiv (Cornell University) preprint Physics and Astronomy Model Reduction and Neural Networks Open access
Mathis Bode, Michael Gauding, Dominik Goeb, Tobias Falkenstein, Heinz G. Pitsch
0citations -
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
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