Super resolution generative adversarial network for velocity fields in Large Eddy Simulations
Resumen:
This article presents an approach for generating synthetic velocity fields in Large Eddy Simulations. This is a relevant problem, considering the high computational effort required to simulate turbulent flows with fine resolution. The proposed approach applies a Generative Adversarial Network, considering relevant information about horizontal slices of turbulent velocity fields. The approach is evaluated on a realworld case study: augmenting the resolution of horizontal velocity fields downstream of a wind turbine. The main results indicate that the proposed approach is able to generate high resolution images of horizontal velocity fields given a low resolution counterpart, without the need for explicitly performing computationally expensive Large Eddy Simulations.
| 2022 | |
| Fondo sectorial de investigación a partir de datos, ANII (convocatoria 2018) | |
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Campo de velocidad de viento Superresolución Large Eddy Simulation Generative Adversarial Network |
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| Inglés | |
| Universidad de la República | |
| COLIBRI | |
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http://icsc-cities.com/
https://hdl.handle.net/20.500.12008/35395 |
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| Acceso abierto | |
| Licencia Creative Commons Atribución - No Comercial - Sin Derivadas (CC - By-NC-ND 4.0) |
