Improving the Vector Basis Neural Network for RANS Equations Using Separate Trainings
Fuente:
arXiv
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| Autor principal: | |
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| Formato: | Preprint |
| Publicado: |
2024
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| Acceso en línea: | |
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| _version_ | 1866912047181070336 |
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| author | Oberto, Davide |
| author_facet | Oberto, Davide |
| contents | We present a new data-driven turbulence model for Reynolds-averaged Navier-Stokes equations called $ν_t$-Vector Basis Neural Network. This new model, grounded on the already existing Vector Basis Neural Network, predicts separately the turbulent viscosity $ν_t$ and the contribution of the Reynolds force vector that is not already accounted in $ν_t$. Numerical experiments on the flow in a Square Duct show the better accuracy of the new model compared to the reference one. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2409_17721 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Improving the Vector Basis Neural Network for RANS Equations Using Separate Trainings Oberto, Davide Fluid Dynamics Numerical Analysis We present a new data-driven turbulence model for Reynolds-averaged Navier-Stokes equations called $ν_t$-Vector Basis Neural Network. This new model, grounded on the already existing Vector Basis Neural Network, predicts separately the turbulent viscosity $ν_t$ and the contribution of the Reynolds force vector that is not already accounted in $ν_t$. Numerical experiments on the flow in a Square Duct show the better accuracy of the new model compared to the reference one. |
| title | Improving the Vector Basis Neural Network for RANS Equations Using Separate Trainings |
| topic | Fluid Dynamics Numerical Analysis |
| url | https://arxiv.org/abs/2409.17721 |