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The aerodynamics of hovering flight in Drosophila
Steven N. Fry, Rosalyn Sayaman, Michael H. Dickinson


Using 3D infrared high-speed video, we captured the continuous wing and body kinematics of free-flying fruit flies, Drosophila melanogaster, during hovering and slow forward flight. We then `replayed' the wing kinematics on a dynamically scaled robotic model to measure the aerodynamic forces produced by the wings. Hovering animals generate a U-shaped wing trajectory, in which large drag forces during a downward plunge at the start of each stroke create peak vertical forces. Quasi-steady mechanisms could account for nearly all of the mean measured force required to hover, although temporal discrepancies between instantaneous measured forces and model predictions indicate that unsteady mechanisms also play a significant role. We analyzed the requirements for hovering from an analysis of the time history of forces and moments in all six degrees of freedom. The wing kinematics necessary to generate sufficient lift are highly constrained by the requirement to balance thrust and pitch torque over the stroke cycle. We also compare the wing motion and aerodynamic forces of free and tethered flies. Tethering causes a strong distortion of the stroke pattern that results in a reduction of translational forces and a prominent nose-down pitch moment. The stereotyped distortion under tethered conditions is most likely due to a disruption of sensory feedback. Finally, we calculated flight power based directly on the measurements of wing motion and aerodynamic forces, which yielded a higher estimate of muscle power during free hovering flight than prior estimates based on time-averaged parameters. This discrepancy is mostly due to a two- to threefold underestimate of the mean profile drag coefficient in prior studies. We also compared our values with the predictions of the same time-averaged models using more accurate kinematic and aerodynamic input parameters based on our high-speed videography measurements. In this case, the time-averaged models tended to overestimate flight costs.

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