Application of deep reinforcement learning in parameter optimization and refinement of turbulence models
Abstract In the field of computational fluid dynamics, the accuracy of turbulence models is crucial. The aim of this study is to improve the accuracy of simulations by optimizing turbulence model parameters, in order to address the cost and time limitations of traditional wind tunnel tests and on-si...
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2025-07-01
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| Series: | Scientific Reports |
| Subjects: | |
| Online Access: | https://doi.org/10.1038/s41598-025-00351-5 |
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