| Micro air vehicles (MAVs), with wing span of 15 cm or less and flight speed around 10 m/s, have many applications in both civilian and military areas. The Reynolds number based on the given parameters is around 10 4, which often yields insufficient lift-to-drag ratio. Furthermore, one expects the unsteady effect to be noticeable for such flight vehicles. The flexible wing has been demonstrated to exhibit favorable characteristics such as passive adaptation to the flight; environment and delayed stall.; The present study focuses on developing computational and modeling capabilities to better understand the MAV aerodynamics. Both flexible wings, utilizing membrane materials, and adaptively-shaped wings, utilizing piezo-actuated flaps, have been studied. In the adaptively-shaped wing study, we use piezo-actuated flaps to actively control the flow. We assess the impacts of the flap geometry, flapping amplitude, and turbulence; modeling on the flow structure with a parallel experimental effort. The membrane wing uses a passive control mechanism to delay the stall angle and to provide a smoother flight platform. Our study focuses on the mutual interactions between the membrane wing and its surrounding viscous flow. We compare the lift-to-drag ratio and the flow structure between the flexible wing and the corresponding rigid wing. We also investigate the aerodynamic characteristics associated with the low Reynolds number and low aspect ratio wing. To assist our study, we propose an automatic and efficient moving grid technique to facilitate the fluid and structure interaction computations; we also present a dynamic membrane model to study the intrinsic large deformation of the flexible membrane wing. Solutions obtained from the three-dimensional Navier-Stokes equations are presented to highlight, the salient features of the wing aerodynamics.; Besides the aerodynamic study, we also perform shape optimization to improve the membrane wing performance. Since direct optimization of a membrane wing is too time consuming to be practical, we optimize a surrogate rigid wing model based on an integrated optimization algorithm, which consists of a Navier-Stokes solver, an automatic grid generation tool; and a gradient-based optimizer. Then, we assess the membrane wing performance based on the outcome from the surrogate model. Our numerical results confirm that the membrane wing exhibits consistent improvement in the lift-to-drag ratio with the surrogate model. |
