A robust data-driven model for flapping aerodynamics under different hovering kinematics
نویسندگان
چکیده
Flapping Wing Micro Air Vehicles (FWMAV) are highly manoeuvrable, bio-inspired drones that can assist in surveys and rescue missions. wings generate various unsteady lift enhancement mechanisms challenging the derivation of reduced models to predict instantaneous aerodynamic performance. In this work, we propose a robust CFD data-driven, quasi-steady (QS) Reduced Order Model (ROM) drag coefficients within flapping cycle. The model is derived for rigid ellipsoid wing with different parameterized kinematics hovering conditions. proposed ROM built via two-stage regression. first stage, defined as `in-cycle' (IC), computes parameters regression linking state. second `out-of-cycle' (OOC), links IC weights features define motion. training test dataset were generated high-fidelity simulations using overset method, spanning wide range Reynolds numbers kinematics. regressor combines Ridge Gaussian Process (GP) provide estimates uncertainties. shows accurate predictions widely varying performs best smooth stable Leading Edge Vortex (LEV). Remarkably also observed dynamic scenarios where LEV partially shed, non-circulatory forces considerable, encounters its own wake.
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ژورنال
عنوان ژورنال: Physics of Fluids
سال: 2023
ISSN: ['1527-2435', '1089-7666', '1070-6631']
DOI: https://doi.org/10.1063/5.0139020