| Issue |
E3S Web Conf.
Volume 459, 2023
XXXIX Siberian Thermophysical Seminar (STS-39)
|
|
|---|---|---|
| Article Number | 02005 | |
| Number of page(s) | 4 | |
| Section | Convective Flows and Heat Transfer in Single-Phase Media | |
| DOI | https://doi.org/10.1051/e3sconf/202345902005 | |
| Published online | 04 December 2023 | |
Development of explicit algebraic models of Reynolds stresses for flows in channels using gene expression programming
Kutateladze Institute of Thermophysics, Siberian Branch, Russian Academy of Sciences, 630090 Novosibirsk, Russian Federation
* Corresponding author: s.yakovenko@mail.ru
To build a data-driven approximation for the Reynolds-stress anisotropy (RSA), the symbolic regression method of gene expression programming (GEP) is applied. Two tensor-basis terms from the algebraic expansion for the RSA tensor are used in the GEP algorithm. A new RANS-GEP model is tested in several flows in channels without/with bumps at different physical and geometrical parameters, where DNS data of high fidelity involved as a target for RSA are available. The results of RANS-DNS runs are also obtained where the RSA values in the mean momentum equation are taken directly from DNS to show ability to improve the model performance versus the conventional linear eddy viscosity model (LEVM). Next, the training with carefully selected input features is performed to get an explicit non-linear algebraic model for RSA. The results of RANS-GEP study show potentials of the new tool to improve predictions.
© The Authors, published by EDP Sciences, 2023
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