REACT reinforcement learning agent learns a state-dependent policy from experimental measurements that suppresses coherent wake structures to reduce drag with net energy savings, outperforming baselines by 2-4x and generalizing across Reynolds numbers 86400-518400 without retraining.
Annual Review of Fluid Mechanics40(1), 113–139 (2008)
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Real-time reinforcement learning for turbulent state-dependent control in a bluff-body wake
REACT reinforcement learning agent learns a state-dependent policy from experimental measurements that suppresses coherent wake structures to reduce drag with net energy savings, outperforming baselines by 2-4x and generalizing across Reynolds numbers 86400-518400 without retraining.