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Resolvent analysis of a swimming foil

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arxiv 2407.06764 v1 pith:2HR7MNGF submitted 2024-07-09 physics.flu-dyn math-phmath.MP

Resolvent analysis of a swimming foil

classification physics.flu-dyn math-phmath.MP
keywords foilanalysisswimmingresolventamplificationbodiesmathitmechanisms
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
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This study employs resolvent analysis to explore the dynamics and coherent structures in the boundary layer of a foil that swims via a travelling wave undulation. A modified NACA foil shape is used together with undulatory kinematics to represent fish-like bodies at realistic Reynolds numbers ($ \mathit{Re} = 10,000 $ and $ \mathit{Re} = 100,000 $) in both thrust- and drag-producing propulsion regimes. We introduce a novel coordinate transformation that enables the implementation of the data-driven resolvent analysis \citep{herrmann_data-driven_2021} to dissect the stability of the boundary layer of the swimming foil. This is the first study to implement resolvent analysis on deforming bodies with non-zero thickness and at realistic swimming Reynolds numbers. The analysis reinforces the notion that swimming kinematics drive the system's physics. In drag-producing regimes, it reveals breakdown mechanisms of the propulsive wave, while thrust-producing regimes show a uniform wave amplification across the foil's back half. The key thrust and drag mechanisms scale with the boundary-layer thickness, implying geometric self-similarity in this $\mathit{Re}$ regime. In addition, we identify a mechanism that is less strongly coupled to the body motion. We offer a comparison to a rough foil that reduces the amplification of this mechanism, demonstrating the potential of roughness to control the amplification of key mechanisms in the flow. The results provide valuable insights into the dynamics of swimming bodies and highlight avenues for developing opposition control strategies.

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  1. Optimized Fish Locomotion using Design-by-Morphing and Bayesian Optimization

    physics.flu-dyn 2025-09 unverdicted novelty 6.0

    A morphing-based design space explored via Bayesian optimization yields swimming profiles with 49-57% peak propulsive efficiency, 16-35% above standard anguilliform and carangiform references.