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Register a new userBio-inspired Flexible Twisting Wings Increase Lift and Efficiency of a Flapping Wing Micro Air Vehicle
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We investigate the effect of wing twist flexibility on lift and efficiency of a flapping-wing micro air vehicle capable of liftoff. Wings used previously were chosen to be fully rigid due to modeling and fabrication constraints. However, biological wings are highly flexible and other micro air vehicles have successfully utilized flexible wing structures for specialized tasks. The goal of our study is to determine if dynamic twisting of flexible wings can increase overall aerodynamic lift and efficiency. A flexible twisting wing design was found to increase aerodynamic efficiency by 41.3%, translational lift production by 35.3%, and the effective lift coefficient by 63.7% compared to the rigid-wing design. These results exceed the predictions of quasi-steady blade element models, indicating the need for unsteady computational fluid dynamics simulations of twisted flapping wings.
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Advanced and accurate modelling of a Flapping Wing Micro Air Vehicle (FW MAV) and its control is one of the recent research topics related to the field of autonomous Unmanned Aerial Vehicles (UAVs). In this work, a four wing Natureinspired (NI) FW MAV is modeled and controlled inspiring by its advanced features like quick flight, vertical take-off and landing, hovering, and fast turn, and enhanced manoeuvrability when contrasted with comparable-sized fixed and rotary wing UAVs. The Fuzzy C-Means (FCM) clustering algorithm is utilized to demonstrate the NIFW MAV model, which has points of interest over first principle based modelling since it does not depend on the system dynamics, rather based on data and can incorporate various uncertainties like sensor error. The same clustering strategy is used to develop an adaptive fuzzy controller. The controller is then utilized to control the altitude of the NIFW MAV, that can adapt with environmental disturbances by tuning the antecedent and consequent parameters of the fuzzy system.
Stretching and retracting wingspan has been widely observed in the flight of birds and bats, and its effects on the aerodynamic performance particularly lift generation are intriguing. The rectangular flat-plate flapping wing with a sinusoidally stretching and retracting wingspan is proposed as a simple model of biologically-inspired dynamic morphing wings. Direct numerical simulations of the low-Reynolds-number flows around the flapping morphing wing in a parametric space are conducted by using immersed boundary method. It is found that the instantaneous and time-averaged lift coefficients of the wing can be significantly enhanced by dynamically changing wingspan in a flapping cycle. The lift enhancement is caused not only by changing the lifting surface area, but also manipulating the flow structures that are responsible to the generation of the vortex lift. The physical mechanisms behind the lift enhancement are explored by examining the three-dimensional flow structures around the flapping wing.
The transition of the vortex pattern and the lift generated by a heaving wing in a uniform flow was investigated numerically. Motivated by insects flight maneuverability, we studied the relationship between a temporal change in the heaving wing motion and the change in the global vortex pattern. At a Strouhal number that generates an asymmetric vortex pattern, we found that temporal angular frequency reduction causes inversion of both the global vortex pattern and the lift sign. The inversion is initiated by the transfer of the leading-edge vortex, which interferes with the vortex pattern generated at the trailing edge. Successful inversion is conditioned on the starting phase and the time interval of the frequency reduction. The details of the process during the transition are discussed.
The flapping-wing aerial vehicle (FWAV) is a new type of flying robot that mimics the flight mode of birds and insects. However, FWAVs have their special characteristics of less load capacity and short endurance time, so that most existing systems of ground target localization are not suitable for them. In this paper, a vision-based target localization algorithm is proposed for FWAVs based on a generic camera model. Since sensors exist measurement error and the camera exists jitter and motion blur during flight, Gaussian noises are introduced in the simulation experiment, and then a first-order low-pass filter is used to stabilize the localization values. Moreover, in order to verify the feasibility and accuracy of the target localization algorithm, we design a set of simulation experiments where various noises are added. From the simulation results, it is found that the target localization algorithm has a good performance.
We develop a highly efficient numerical method to simulate small-amplitude flapping propulsion by a flexible wing in a nearly inviscid fluid. We allow the wings elastic modulus and mass density to vary arbitrarily, with an eye towards optimizing these distributions for propulsive performance. The method to determine the wing kinematics is based on Chebyshev collocation of the 1D beam equation as coupled to the surrounding 2D fluid flow. Through small-amplitude analysis of the Euler equations (with trailing-edge vortex shedding), the complete hydrodynamics can be represented by a nonlocal operator that acts on the 1D wing kinematics. A class of semi-analytical solutions permits fast evaluation of this operator with $O(N log N)$ operations, where $N$ is the number of collocation points on the wing. This is in contrast to the minimum $O(N^2)$ operations required by a direct 2D fluid solver. The coupled wing-fluid problem is thus recast as a PDE with nonlocal operator, which we solve using a preconditioned iterative method. These techniques yield a solver of near-optimal complexity, $O(N log N)$, allowing one to rapidly search the infinite-dimensional parameter space of all possible material distributions and even perform optimization over this space.
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