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.
Cremades,et al., Identifying regions of importance in wall-bounded turbulence through explainable deep learning.Nat
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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.