Abstract

In recent years, there has been widespread interest in the design of microair vehicles (MAVs) for flapping flight with high-aspect ratio wings due to their high efficiency and energy savings. However, the flexibility of a flapping wing causes the aeroelastic effect, which remains a subject of investigation. Generally, existing research simulates active bending and twisting of flexible wings under the assumption of neglecting flapping inertia. In this research, the kinematic optimization of a bionic wing with passive deformation in forward flight while undergoing flapping and pitching is considered. To this end, a computational aeroelasticity framework, which includes the three-dimensional unsteady vortex lattice method (UVLM) and the Newmark-β method, is constructed for flapping flight. Under the assumption of linear elastic deformation, this tool is capable of simulating attached flows over a thin wing and capturing unsteady effects of wakes. A bionic numerical wing with an aspect ratio of 6.5, chord Reynolds number of 1.9 × 105, and reduced frequency less than 0.1 is investigated in kinematic optimization. The computational aeroelasticity framework is combined with a global optimization algorithm to identify the optimal kinematics that maximize the propulsive efficiency under the minimum average lift constraint. Two types of numerical wings, rigid wing and flexible wing, are considered here to compare the influence of deformation on the aerodynamics of the flapping wing. The results show that the aeroelastic effect, which increases the flapping amplitude, yields a significant improvement in terms of propulsive efficiency. In addition, the optimization algorithm maximizes the thrust efficiency while satisfying the required lift. Moreover, the optimal kinematics of both the rigid wing and the flexible wing reach the maximum flapping angle, which indicates that a larger range of motions is needed for optimal kinetics when loosening the boundary conditions.

Highlights

  • Various ornithopters have been designed and manufactured worldwide

  • To determine the coupled motion of flapping and pitching of a microflapping wing machine, Matthew et al [6] selected optimal kinematics from dozens of motion parameter combinations through experiments. is simple way to design kinematics is an alternative method in the absence of proper optimization tools

  • Razak and Dimitriadis [8] investigated the coupling effect of flapping and pitching motions on the aerodynamic characteristics of flapping wings. eir experiment explored the aerodynamic effect caused by the phase difference between flapping and pitching motions but without considering the influence of other motion parameters

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Summary

Introduction

Various ornithopters have been designed and manufactured worldwide. Such aircrafts gain lift and thrust by flapping their wings. eir weights are limited to the magnitude that flapping wings can drive, which leads to the application of flexible lightweight materials in the wing components. There is a lack of methods to optimize the kinematics of flexible flapping wings in the design stage. Nick et al [7] used symmetrical in-plane motion on a micro bat-like ornithopter without applying a kinematic optimization method to improve its aerodynamic characteristics. Razak and Dimitriadis [8] investigated the coupling effect of flapping and pitching motions on the aerodynamic characteristics of flapping wings. E current work combines a computational aeroelasticity framework with a global optimization algorithm to construct a design method for flapping wing kinematics. E computational aeroelasticity framework includes the three-dimensional unsteady vortex lattice method UVLM and the Newmark-β method to calculate the fluid-structure coupling effect caused by flexible deformation. E flapping wing kinematics have a complex design space with multiple local optima when taking specific aerodynamic characteristics as the optimization goal. The kinematic and aerodynamic results of the flexible model are discussed and compared with those of a rigid model

Wing Kinematics and Dynamics
E: O-X-Y-Z B: o-x-y-z
Unsteady Vortex Lattice Method
Global Optimization
Findings
Conclusions
Full Text
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