Insect wings can passively maintain a high angle of attack during each flapping stroke without the aid of the active pitching motion due to the torsional flexibility of the wing basal region. However, there is no clear understanding of how torsional wing flexibility should be designed for achieving optimal aerodynamic performance. In this work, a computational study was conducted to investigate the passive pitching mechanism of a fruit fly wing in hovering flight using a torsional spring model. The torsional wing stiffness was characterized by the Cauchy number, a ratio between the aerodynamic force and the structural elastic force. Different flapping patterns including zero-deviation, figure-8, and oval-shaped flapping trajectories were evaluated along a horizontal stroke plane. The aerodynamic forces and associated unsteady flow structures were simulated using an in-house immersed-boundary-method based computational fluid dynamics solver. A parametric study on the Cauchy number was performed with a Reynolds number of 300. According to the analysis of the aerodynamic performance, we found that a balance of high lift and high lift-to-power ratio can be achieved in a particular range of Cauchy numbers (0.15–0.30) for all different flapping trajectories. This range is consistent with the Cauchy number calculated based on the experimental measurements of a fruit fly in the literature. In addition, 3D wake structures generated by the passive flapping wings were analyzed in detail. The findings of this work could provide important implications for designing more efficient flapping-wing micro-air vehicles.
Insects rely on their olfactory system to forage, prey, and mate. They can sense odorant plumes emitted from sources of their interests with their bilateral odorant antennae, and track down odor sources using their highly efficient flapping-wing mechanism. The odor-tracking process typically consists of two distinct behaviors: surging upwind at higher velocity and zigzagging crosswind at lower velocity. Despite extensive numerical and experimental studies on odor guided flight in insects, we have limited understandings on the effects of flight velocity on odor plume structure and its associated odor perception. In this study, a fully coupled three-way numerical solver is developed, which solves the 3D Navier-Stokes equations coupled with equations of motion for the passive flapping wings, and the odorant convection-diffusion equation. This numerical solver is applied to resolve the unsteady flow field and the odor plume transport for a fruit fly model at different flight velocities in terms of reduced frequency. Our results show that the odor plume structure and intensity are strong related to reduced frequency. At smaller reduced frequency (larger forward velocity), odor plume is pushed up during downstroke and draw back during upstroke. At larger reduced frequency (smaller forward velocity), the flapping wings induce a shield-like air flow around the antennae which may greatly increase the odor sampling range. Our finding may explain why flight velocity is important in odor guided flight.
Insects rely on their olfactory system to forage, prey, and mate. They can sense odorant plumes emitted from sources of their interests with their bilateral odorant antennae, and track down odor sources using their highly efficient flapping-wing mechanism. The odor-tracking process typically consists of two distinct behaviors: surging upwind and zigzagging crosswind. Despite the extensive numerical and experimental studies on the flying trajectories and wing flapping kinematics during odor tracking flight, we have limited understanding of how the flying trajectories and flapping wings modulate odor plume structures. In this study, a fully coupled three-way numerical solver is developed, which solves the 3D Navier-Stokes equations coupled with equations of motion for the passive flapping wings, and the odorant convection-diffusion equation. This numerical solver is applied to investigate the unsteady flow field and the odorant transport phenomena of a fruit fly model in both surging upwind and zigzagging crosswind cases. The unsteady flow generated by flapping wings perturbs the odor plume structure and significantly impacts the odor intensity at the olfactory receptors (i.e., antennae). During zigzagging crosswind flight, the differences in odor perception time and peak odor intensity at the receptors potentially help create stereo odorant mapping to track odor source. Our simulation results will provide new insights into the mechanism of how fruit flies perceive odor landscape and inspire the future design of odor-guided micro aerial vehicles (MAVs) for surveillance and detection missions.
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