Explore the vast range of titles available.

This paper describes the design and development of the Dove, a flapping-wing micro air vehicle (FWMAV), which was developed in Northwestern Polytechnical University. FWMAVs have attracted international attentions since the past two decades. Since some achievements have been obtained, such as the capability of supporting an air vehicle to fly, our research goal was to design an FWMAV that has the ability to accomplish a task. Main investigations were presented in this paper, including the flexible wing design, the flapping mechanism design, and the on-board avionics development. The current Dove has a mass of 220 g, a wingspan of 50 cm, and the ability of operating fully autonomously, flying lasts half an hour, and transmitting live stabilized color video to a ground station over 4 km away.

Co-flow jet (CFJ) is an active flow control technique that significantly enhances aerodynamic performance metrics such as the maximum lift and maximum lift-to-drag ratio of airfoils or wings. Currently, investigations into lift enhancement and drag reduction on three-dimensional CFJ swept wings are limited. To address this issue, we used a low-speed, high-lift NPU-LS 0515 airfoil as a baseline and designed a wind tunnel experimental model of a CFJ swept wing, with the CFJ driven by internally mounted ducted fans and guided by injection ducts. We investigated the effects of jet direction, jet momentum coefficient, and injection slot size on lift enhancement and drag reduction performance of the CFJ swept wing through wind tunnel experiments. Experimental results showed that chord-wise vortices generated by the interaction of the deflected jet flow with the main flow through shear stress effectively enhanced mixing effect and energy transfer, improving the lift coefficient of the CFJ swept wing. Compared to the baseline configuration, the CFJ swept wing achieved over a 20% increase in maximum lift coefficient and more than a 50% reduction in drag coefficient at high angles of attack. Consequently, the lift-to-drag ratio of the swept wing improved substantially.

Reliability-based design optimization (RBDO) has been an important research field with the increasing demand for product reliability in practical applications. This paper presents a new RBDO method combining adaptive surrogate model and Importance Sampling-based Modified Sequential Optimization and Reliability Assessment (IS-based modified SORA) method, which aims to reduce the number of calls to the expensive objective function and constraint functions in RBDO. The proposed method consists of three key stages. First, the samples are sequentially selected to construct Kriging models with high classification accuracy for each constraint function. Second, the samples are obtained by Markov Chain Monte Carlo in the safety domain of design space. Then, another Kriging model for the objective function is sequentially constructed by adding suitable samples to update the Design of Experiment (DoE) of the objective function. Third, the expensive objective and constraint functions of the original optimization problem are replaced by the surrogate models. Then, the IS-based modified SORA method is performed to decouple reliability optimization problem into a series of deterministic optimization problems that are solved by a Genetic Algorithm. Several examples are adopted to verify the proposed method. The optimization results show that the proposed method can reduce the number of calls to the original objective function and constraint functions without loss of precision compared to the alternative methods, which illustrates the efficiency and accuracy of the proposed method.

Unmanned aerial vehicles (UAVs) can soar like birds by harvesting natural wind energy, significantly extending flight endurance. Thermal updrafts and orographic updrafts are the two primary wind fields exploited by birds during migration and foraging, with the latter being more prevalent in mountainous terrain. Due to computational constraints of current onboard avionics, a simple yet accurate model that adequately characterizes the horizontal distribution of orographic updrafts has not yet been established, limiting existing autonomous energy-harvesting flight techniques to thermal updraft environments. This paper investigates the height-dependent horizontal distribution of vertical winds over isolated and continuous range using RANS numerical simulations. The results show that the horizontal structure of updrafts over an isolated hill closely resembles that of thermal updrafts, allowing direct adoption of existing thermal updraft models. A new horizontal distribution model for orographic updrafts is proposed, which demonstrates high precision with a maximum RMSE of only 0.088 m/s at various altitudes when compared to numerical simulation results. Compared with existing models for continuous ridges, this model significantly improves the consistency in describing the horizontal distribution patterns of orographic updrafts and provides a more reasonable characterization of the updraft distribution in regions above the ridgeline; consequently, it is well-suited for the real-time and efficient prediction of terrain-induced updrafts for small UAVs.

Many modern structural systems usually consist of multiple failure modes. One failure mode may affect other failure modes due to the same working environment and random input variables, meaning that these failure modes are not independent. The assumption of independence among failure modes simplifies the calculation of reliability of structural systems, but it adds approximation error. Different from the dependence between two failure modes, the dependence of multiple failure modes is more complicated. In this paper, on the basis of vine copula function, which is a flexible tool to describe the multivariate dependence, the dependence of multiple failure modes of the structural systems is mainly studied and analyzed. Then Rosenblatt transformation and Monte Carlo simulation method are utilized to evaluate the reliability of structural systems. Furthermore, in order to research the importance of failure modes, two indices combined with empirical copula functions are extended, which can quantitatively measure the importance of failure modes. The multiple failure modes can be ranked based on proposed importance analysis, and the ones that have greater influence on the system can be found out, thus simplifying the system analysis. Finally, in order to confirm the applicability and rationality of the proposed method, an engineering case about a mechanism system with five failure modes is presented.

The bionic flapping-wing aircraft has the advantages of high flexibility and strong concealment; however, in the existing flapping-wing aircraft, the platform performance is influenced by the payload capacity, endurance, and durability; additionally, the mission capability is constrained, making it challenging to put into use in real-world scenarios. In response to this issue, this article offers a thorough design approach for a large-span flapping-wing aircraft, focusing on effective flapping wings, effective flapping mechanism design, and enhancement of flapping mechanism reliability, and ultimately realizing the design and verification of a new bionic flapping-wing aircraft with a large wingspan, called “Cloud Owl”. It has a wingspan of 1.82 m and weighs 980 g. The aircraft is capable of autonomous flight and remote control, and it can carry a range of mission-specific equipment. More than 200 flights have been made by “Cloud Owl” so far in Xi’an, Beijing, Tianjin, Tibet, Ganzi, and other places. It has evolved into a flapping-wing aircraft platform with exceptional stability, payload capacity, and long endurance.

Making full use of wind energy can effectively alleviate the global energy shortage and environment contamination problems. Nevertheless, how to significantly improve the performance of the wind turbine airfoil and blade is a crucial issue. As the novel flow control method, the co-flow jet (CFJ) technology is one of the most potential methods to solve this problem. Thus, the effects of the CFJ technology on the performance enhancement of the S809 airfoil and Phase VI wind turbine blade are explored in this study. Furthermore, the effects of the injection location and jet momentum coefficient are studied, and an adaptive jet momentum coefficient strategy of the CFJ technology is proposed. Results demonstrate that the CFJ technology can significantly improve the maximum lift coefficient and maximum corrected lift-to-drag ratio of the S809 airfoil. Moreover, the power coefficient of the Phase VI wind turbine blade at the low tip speed ratio is greatly enhanced as well. In particular, the maximum lift coefficient and maximum corrected lift-to-drag ratio of the typical S809 CFJ airfoil with adaptive Cμ are improved by 119.7% and 36.2%, respectively. The maximum power coefficient of CFJ blade can be increased by 4.5%, and the power coefficient of CFJ blade can be boosted by 226.7% when the tip speed ratio is 1.52.

Wind estimation plays a crucial role in atmospheric boundary layer research and aviation flight safety. Fixed-wing UAVs enable rapid and flexible detection across extensive boundary layer regions. Traditional meteorological fixed-wing UAVs require either additional wind measurement sensors or sustained turning maneuvers for wind estimation, increasing operational costs while inevitably reducing mission duration and coverage per flight. This paper proposes a real-time wind estimation method based on an Unscented Kalman Filter (UKF) without aerodynamic sensors. The approach utilizes only standard UAV avionics—GNSS, pitot tube, and Inertial Measurement Unit (IMU)—to estimate wind fields. To validate accuracy, the method was integrated into a meteorological UAV equipped with a wind vane sensor, followed by multiple flight tests. Comparison with wind vane measurements shows real-time wind speed errors below 1 m/s and wind direction errors within 20° (0.349 rad). Results demonstrate the algorithm’s effectiveness for real-time atmospheric boundary layer wind estimation using conventional fixed-wing UAVs.

Medium and large-sized birds exhibit remarkable agility and maneuverability in flight, with their flapping motion encompassing degrees of freedom in flapping, twist, and swing, which enables them to adapt effectively to harsh ecological environments. This study proposes a flapping–twist coupled driving mechanism for large-scale flapping-wing aircraft by mimicking the motion patterns of birds. The mechanism generates simultaneous twist and flapping motions based on the phase difference of double cranks, allowing for the adjustment of twist amplitude through modifications in crank radius and phase difference. The objective of this work is to optimize the lift and thrust of the flapping wing to enhance its flight performance. To achieve this, we first derived the kinematic model of the mechanism and conducted motion simulations. To mitigate the effects of the flapping wing’s flexibility, a rigid flapping wing was designed and manufactured. Through wind tunnel experiments, the flapping wing system was tested. The results demonstrated that, compared to the non-twist condition, there exists an optimal twist amplitude that slightly increases the lift of the flapping wing while significantly enhancing the thrust. It is hoped that this study will provide guidance for the design of multi-degree-of-freedom flapping wing mechanisms.

Flexible deformation of the insect wing has been proven to be beneficial to lift generation and power consumption. There is great potential for shared research between natural insects and bio-inspired Flapping wing Micro Aerial Vehicles (FWMAVs) for performance enhancement. However, the aerodynamic characteristics and deformation process of the flexible flapping wing, especially influenced by wing membrane material, are still lacking in-depth understanding. In this study, the flexible flapping wings with different membrane materials have been experimentally investigated. Power input and lift force were measured to evaluate the influence of membrane material. The rotation angles at different wing sections were extracted to analyze the deformation process. It was found that wings with higher elastic modulus membrane could generate more lift but at the cost of more power. A lower elastic modulus means the wing is more flexible and shows an advantage in power loading. Twisting deformation is more obvious for the wing with higher flexibility. Additionally, flexibility is also beneficial to attenuate the rotation angle fluctuation, which in turn enhances the aerodynamic efficiency. The research in this paper is helpful to further understand the aerodynamic characteristics of flexible flapping wing and to design bio-inspired FWMAVs with higher performance.