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

Model code and software

Used scripts and model code Robin Stoffer https://doi.org/10.5281/zenodo.4767902

microhh/microhh: 1.0.0 (Version 1.0.0) C. C. van Heerwaarden, B. J. H. van Stratum, and T. Heus https://doi.org/10.5281/zenodo.822842

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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.