Articles | Volume 14, issue 6
https://doi.org/10.5194/gmd-14-3769-2021
https://doi.org/10.5194/gmd-14-3769-2021
Development and technical paper
 | 
24 Jun 2021
Development and technical paper |  | 24 Jun 2021

Development of a large-eddy simulation subgrid model based on artificial neural networks: a case study of turbulent channel flow

Robin Stoffer, Caspar M. van Leeuwen, Damian Podareanu, Valeriu Codreanu, Menno A. Veerman, Martin Janssens, Oscar K. Hartogensis, and Chiel C. van Heerwaarden

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Latest update: 05 Dec 2024
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Short summary
Turbulent flows are often simulated with the large-eddy simulation (LES) technique, which requires subgrid models to account for the smallest scales. Current subgrid models often require strong simplifying assumptions. We therefore developed a subgrid model based on artificial neural networks, which requires fewer assumptions. Our data-driven SGS model showed high potential in accurately representing the smallest scales but still introduced instability when incorporated into an actual LES.