Investigation of the generalization capability of a generative adversarial network for large eddy simulation of turbulent premixed reacting flows

Autor: L. Nista, C.D.K. Schumann, T. Grenga, A. Attili, H. Pitsch

Publikováno v: Nista, L, Schumann, C D K, Grenga, T, Attili, A & Pitsch, H 2022, ' Investigation of the generalization capability of a generative adversarial network for large eddy simulation of turbulent premixed reacting flows ', Proceedings of the Combustion Institute . https://doi.org/10.1016/j.proci.2022.07.244

In the past decades, Deep Learning (DL) frameworks have demonstrated excellent performance in modeling nonlinear interactions and are a promising technique to move beyond physics-based models. In this context, super-resolution techniques may present

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2214c6dd2f1e841b921e98c9310f7105
https://doi.org/10.1016/j.proci.2022.07.244

Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.