Forcing-informed resolvent analysis extracts data-consistent forcing and response modes for self-sustained flows by estimating input-output subspaces from nonlinear forcing snapshots.
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3 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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2026 3verdicts
UNVERDICTED 3representative citing papers
A combined SHAP-guided MARL strategy using U-net predictions of skin-friction and wall pressure achieves 34.44% drag reduction and 34.01% net energy saving with 0.43% normalized input power in turbulent channel flow.
DNS shows spanwise piezoelectric surface waves achieve up to 27.6% drag reduction in turbulent half-channel flow at Re_tau=200.
citing papers explorer
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Forcing-informed resolvent analysis: Identification of input-output relations in self-sustained flows
Forcing-informed resolvent analysis extracts data-consistent forcing and response modes for self-sustained flows by estimating input-output subspaces from nonlinear forcing snapshots.
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Direct numerical simulations of turbulent drag reduction via piezoelectric actuation
DNS shows spanwise piezoelectric surface waves achieve up to 27.6% drag reduction in turbulent half-channel flow at Re_tau=200.