Scientific multi-agent reinforcement learning for wall-models of turbulent flows
Simulations of turbulent flows are relevant for aerodynamic and weather modeling, however challenging to capture flow dynamics in the near wall region. To solve this problem, the authors propose a multi-agent reinforcement learning approach to discover wall models for large-eddy simulations.
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2022-03-01
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| Series: | Nature Communications |
| Online Access: | https://doi.org/10.1038/s41467-022-28957-7 |