.png){kind=icon}
Return
Optimizing flapping foil dynamics: A data-driven framework for motion optimization
.png){kind=icon}
PRE
AI
DOI：10.1016/j.oceaneng.2025.122990.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
• We propose a data-driven framework for non-parametric flapping foil optimization, with the objective of performing multi-objective optimization on thrust coefficient and propulsive efficiency. • Our approach combines Gaussian process regression for parametric motion prediction with reinforcement learning for non-parametric motion optimization, yielding motions that outperform the Pareto frontier obtained via brute force search.
Journal
IF:
5.5
Papers:
7.5K
Citations:
7.6W
Organization
Cited Papers
Effects of Reynolds number and thickness on an undulatory self-propelled foil.png)
PHYSICS OF FLUIDS
PHYSICS OF FLUIDSIF4.3
PREAI
ShareSave
ShareSaveEffects of non-sinusoidal pitching motion on energy extraction performance of a semi-active flapping foilRENEWABLE ENERGY
RENEWABLE ENERGYIF9.1
PREAI
ShareSaveNumerical investigation on energy extraction of flapping hydrofoils with different series foil shapesENERGY
ENERGYIF9.4
PREAI
ShareSaveDeep reinforcement transfer learning of active control for bluff body flows at high Reynolds number
PREAI
ShareSave
View more