Ricardo Vinuesa
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126
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ML×1AI×1physics.flu-dyn×1
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2026
Explainable deep reinforcement learning reveals energy-efficient control strategies for turbulent drag reduction
The paper proposes an energy-efficient drag reduction strategy for turbulent flows by combining Multi-Agent Deep Reinforcement Learning with SHAP-guided explainable deep learning, achieving superior performance with significantly reduced actuation power.
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