Using deep learning to predict statistics of turbulent flows at high Reynolds numbers ⇨

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http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Preprint Bode, M. (Corresponding author)RWTH* ; Gauding, M. ; Lian, Z. ; Denker, D. ; Davidovic, M. ; Kleinheinz, K. ; Jitsev, J.FZJ* ; Pitsch, H.
Using Physics-Informed Super-Resolution Generative Adversarial Networks for Subgrid Modeling in Turbulent Reactive Flows
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http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Contribution to a conference proceedings/Contribution to a book Bode, M. ; Gauding, M. (Corresponding author) ; Göbbert, J. H.FZJ* ; Liao, B. ; Jitsev, J.FZJ* ; Pitsch, H.
Towards Prediction of Turbulent Flows at High Reynolds Numbers Using High Performance Computing Data and Deep Learning
2018High Performance Computing
International Conference on High Performance Computing, FrankfurtFrankfurt, Germany, 24 Jun 2018 - 28 Jun 20182018-06-242018-06-28 Cham : Springer International Publishing, Lecture Notes in Computer Science 11203, 614 - 623 (2018) [10.1007/978-3-030-02465-9_44] special issue: "ISC High Performance 2018 International Workshops"2018 BibTeX | EndNote: XML, Text | RIS

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