Inspired by the high performance of rotary and insect flapping wings capable of vertical takeoff and landing and hovering (VTOLH), a novel flapping wing rotor (FWR) has been developed by combining the above two types of wing motions. The FWR offers an alternative configuration for micro air vehicles (MAV) of such high flight performance. Unlike the well-studied aerodynamics of rotary and insect-like flapping wing with prescribed wing motion, the aerodynamic lift and efficiency of the FWR associated with optimal kinematics of motion has not been studied in a systematic manner before. This investigation is therefore focused on the FWR optimal kinematic motion in terms of aerodynamic lift and efficiency. Aerodynamic analysis is conducted for a FWR model of aspect ratio 3.6 and wing span 200mm in a range of kinematic parameters. The analysis is based on a quasi-steady aerodynamic model with empirical coefficients and validated by CFD results at Re~3500. For comparison purpose, the analysis includes rotary and insect-like flapping wings in hovering status with the FWR at an equilibrium rotation speed when the thrust equals to drag. The results show that the rotary wing has the greatest power efficiency but the smallest lift coefficient. Whereas the FWR can produce the greatest aerodynamic lift with power efficiency between rotary and insect-like flapping wings. The results provide a quantified guidance for design option of the three types of high performance MAVs together with the optimal kinematics of motion according to flight performance requirement.
A numerical study on the aerodynamic performance of a two-dimensional flapping wing in asymmetric stroke in hovering and forward flight is carried out. The effect of the asymmetry of the stroke on aerodynamic forces and flow structures of the wing is analyzed. It is found that for hovering flight appropriate asymmetric stroke can enhance the aerodynamic performance of the wing at low Reynolds number, but it may not be functioning at moderate and high Reynolds numbers. For forward flight the asymmetric stroke does not increase the lifting efficiency and propulsive efficiency of the wing simultaneously. However, it influences the time history of the aerodynamic force significantly, which may enhance the flight maneuverability of the wing. The present results provide physical insight into the understanding of aerodynamics and flow structures of insect flight with asymmetric stroke.
This paper proposed a multi-objective differential evolution algorithm based on max-min distance density. The algorithm proposed the definiens of maxmin distance density and a Pareto candidate solution set maintenance method, and ensured the diversity of the Pareto solution set. Using Pareto dominance relationship among individuals and max-min distance density ensured the convergence of the algorithm, realized solving multi-objective optimization problems. The proposed algorithm is applied to five ZDT test functions and compared with others multi-objective evolutionary algorithms. Experimental result and analysis show that the algorithm is feasible and efficient.
We, humans, are entering into a virtual era and indeed want to bring animals to the virtual world as well for companion. Yet, computer-generated (CGI) furry animals are limited by tedious off-line rendering, let alone interactive motion control. In this paper, we present ARTEMIS, a novel neural modeling and rendering pipeline for generating ARTiculated neural pets with appEarance and Motion synthesIS. Our ARTEMIS enables interactive motion control, real-time animation, and photo-realistic rendering of furry animals. The core of our ARTEMIS is a neural-generated (NGI) animal engine, which adopts an efficient octree-based representation for animal animation and fur rendering. The animation then becomes equivalent to voxel-level deformation based on explicit skeletal warping. We further use a fast octree indexing and efficient volumetric rendering scheme to generate appearance and density features maps. Finally, we propose a novel shading network to generate high-fidelity details of appearance and opacity under novel poses from appearance and density feature maps. For the motion control module in ARTEMIS, we combine state-of-the-art animal motion capture approach with recent neural character control scheme. We introduce an effective optimization scheme to reconstruct the skeletal motion of real animals captured by a multi-view RGB and Vicon camera array. We feed all the captured motion into a neural character control scheme to generate abstract control signals with motion styles. We further integrate ARTEMIS into existing engines that support VR headsets, providing an unprecedented immersive experience where a user can intimately interact with a variety of virtual animals with vivid movements and photo-realistic appearance. Extensive experiments and showcases demonstrate the effectiveness of our ARTEMIS system in achieving highly realistic rendering of NGI animals in real-time, providing daily immersive and interactive experiences with digital animals unseen before. We make available our ARTEMIS model and dynamic furry animal dataset at https://haiminluo.github.io/publication/artemis/.
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