Deep Reinforcement Learning Control of Cylinder Flow Using Rotary Oscillations at Low Reynolds Number
We apply deep reinforcement learning to active closed-loop control of a two-dimensional flow over a cylinder oscillating around its axis with a time-dependent angular velocity representing the only control parameter. Experimenting with the angular velocity, the neural network is able to devise a con...
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| Principais autores: | , , |
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| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
MDPI AG
2020-11-01
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| coleção: | Energies |
| Assuntos: | |
| Acesso em linha: | https://www.mdpi.com/1996-1073/13/22/5920 |
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