Zero-shot RL control trained on matched channel flows reduces skin-friction drag 28.7% and total drag 10.7% on a NACA4412 wing, outperforming opposition control.
Su ´arez,et al., Active flow control for drag reduction through multi-agent reinforcement learning on a turbulent cylinder at𝑅𝑒 𝐷 =3900.Flow Turbul
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Physics-guided surrogate learning enables zero-shot control of turbulent wings
Zero-shot RL control trained on matched channel flows reduces skin-friction drag 28.7% and total drag 10.7% on a NACA4412 wing, outperforming opposition control.