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Applying Physics-Informed Enhanced Super-Resolution Generative Adversarial Networks to Turbulent Non-Premixed Combustion on Non-Uniform Meshes and Demonstration of an Accelerated Simulation Workflow


Oct 28, 2022
Mathis Bode

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Applying Physics-Informed Enhanced Super-Resolution Generative Adversarial Networks to Finite-Rate-Chemistry Flows and Predicting Lean Premixed Gas Turbine Combustors


Oct 28, 2022
Mathis Bode

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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 Data


Oct 28, 2022
Mathis Bode, Michael Gauding, Dominik Goeb, Tobias Falkenstein, Heinz Pitsch

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Towards prediction of turbulent flows at high Reynolds numbers using high performance computing data and deep learning


Oct 28, 2022
Mathis Bode, Michael Gauding, Jens Henrik Göbbert, Baohao Liao, Jenia Jitsev, Heinz Pitsch

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* LNCS 11203, pp. 614-623, 2018 

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Pandemic Drugs at Pandemic Speed: Accelerating COVID-19 Drug Discovery with Hybrid Machine Learning- and Physics-based Simulations on High Performance Computers


Mar 04, 2021
Agastya P. Bhati, Shunzhou Wan, Dario Alfè, Austin R. Clyde, Mathis Bode, Li Tan, Mikhail Titov, Andre Merzky, Matteo Turilli, Shantenu Jha, Roger R. Highfield, Walter Rocchia, Nicola Scafuri, Sauro Succi, Dieter Kranzlmüller, Gerald Mathias, David Wifling, Yann Donon, Alberto Di Meglio, Sofia Vallecorsa, Heng Ma, Anda Trifan, Arvind Ramanathan, Tom Brettin, Alexander Partin, Fangfang Xia, Xiaotan Duan, Rick Stevens, Peter V. Coveney

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Using Physics-Informed Super-Resolution Generative Adversarial Networks for Subgrid Modeling in Turbulent Reactive Flows


Nov 26, 2019
Mathis Bode, Michael Gauding, Zeyu Lian, Dominik Denker, Marco Davidovic, Konstantin Kleinheinz, Jenia Jitsev, Heinz Pitsch

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* Submitted to Combustion Symposium 2020 

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Deep learning at scale for subgrid modeling in turbulent flows


Oct 01, 2019
Mathis Bode, Michael Gauding, Konstantin Kleinheinz, Heinz Pitsch

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A graphical heuristic for reduction and partitioning of large datasets for scalable supervised training


Jul 24, 2019
Sumedh Yadav, Mathis Bode

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* 30 pages, 25 figures, undergoing revision for publication in the Journal of Big Data 

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On the self-similarity of line segments in decaying homogeneous isotropic turbulence


Sep 20, 2018
Michael Gauding, Lipo Wang, Jens Henrik Goebbert, Mathis Bode, Luminita Danaila, Emilien Varea

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