Search Results (214)

The Lambda wing UAV inevitably needs to adjust the lift coefficient and pitch moment by controlling the flap when encountering multiple flight states. Inspired by the natural morphing mechanisms of bird wings, this study draws upon bionic principles to explore a seamless morphing trailing edge (SMTE) design that mimics the smooth and continuous deformation observed in avian flight. A comparative analysis between SMTE flaps and traditional hinge flaps highlights the superior rearward stealth performance of SMTE flaps in the direction angles of 120° to 140°, along with a reduction in aerodynamic drag. During the optimization, a model based on flexible wing ribs and elastic skin was established, and statistical analysis revealed a strong linear correlation between the maximum lift coefficient provided by the flaps and the overall lift-to-drag ratio. Consequently, the optimization process omitted the enhancement of the comprehensive lift-to-drag ratio during the flap deflection. Additionally, a deep Neural Network Surrogate Model was introduced to streamline the computationally intensive aerodynamic calculations. Ultimately, an MOGA-2 optimization model incorporating local deep Neural Network Surrogate Models was utilized to achieve the comprehensive optimization of aerodynamic and stealth characteristics, through an adjustment of the wing rib and skin proportions. The UAV rearward RCS and the maximum lift coefficient provided by the flaps have decreased by 2.8% and increased by 6.6%, respectively. Full article

The legs of flying insects play a critical role in enabling seamless transitions between aerial and terrestrial environments. These appendages serve multiple functions, including landing, walking, jumping, and transitioning from jumping to flight (takeoff). Such capabilities have inspired engineers to seek similar multimodal mechanisms in Flapping-Wing Aerial Robots (FWARs) to expand their operational versatility across diverse environments. However, designing multimodal mechanisms with distinct kinematic and propulsive characteristics remains challenging, particularly in the domain of autonomous jump takeoff for FWARs, where research remains relatively sparse. In this study, inspired by the jumping takeoff strategy and hindleg kinematics of the Asian migratory locust (Locusta migratoria), we propose a functional bio-inspired jumping takeoff mechanism that extracts selected mechanical principles of the locust jumping system, including elastic energy accumulation, temporary mechanical locking, and rapid energy release. The mechanism employs a gear–crank–slider transmission system and utilizes one-way bearings to regulate the locking and disengaging states, enabling the storage and rapid release of energy for jump takeoff, thereby achieving autonomous takeoff of the robot. Adams dynamic simulations show that at a torsion spring angle of 40°, the mechanism achieves a maximum resultant velocity of 1.955 m/s, a jump height of 168.2 mm, and a horizontal displacement upon landing of 134.6 mm. Ansys Fluent (2024 R2) simulations under multiple operating conditions further confirm that the aerodynamic performance is optimal at a takeoff angle of attack(α) of 5° with a torsion spring angle(β) of 40°, yielding a lift-to-drag ratio of 3.005. This work presents a functional bio-inspired jumping takeoff mechanism based on selected mechanical principles of locust jumping, providing a potential approach for improving the autonomous takeoff capability of small-scale FWARs. Full article

Owing to its inherent flight safety, low takeoff and landing requirements, and favorable economic efficiency, the autogyro UAV, especially its electric and hybrid-electric variants, has become a core platform for low-altitude aviation missions such as transportation, inspection, and surveillance in plateau and offshore regions. However, the low air density and low Reynolds number conditions encountered in plateau regions can induce aerodynamic issues such as premature laminar flow separation, dynamic stall, and increased induced drag, which directly reduce payload capacity and endurance of small electric autogyro UAVs. In offshore environments, strong winds, turbulence, and gust disturbances intensify rotor–wake interactions, cause abrupt variations in aerodynamic loads, and reduce control margins, which severely restricts the mission reliability and flight safety of low-altitude unmanned platforms. These environmental effects collectively degrade rotor performance, including reduced aerodynamic efficiency and insufficient lift generation, and further amplify the energy constraint of electric/hybrid-electric propulsion systems. In response to bottlenecks that restrict the practical application of autogyro UAVs in extreme environments, this paper systematically reviews research progress on lift vector control for autogyro UAV rotors operating under such conditions. First, the typical aerodynamic problems encountered by autogyro UAVs in plateau and offshore environments are summarized, and their underlying physical mechanisms are analyzed from both system-level and local-flow perspectives, with a focus on how environmental factors affect the autorotation stability of unmanned platforms. Subsequently, the development of passive lift vector control technologies is reviewed, with an emphasis on the aerodynamic benefits of passive pitch mechanisms, vortex generators, and blade-tip winglets, as well as their engineering feasibility for small autogyro UAV blades. Active lift vector control technologies are then examined, including air-jet flow control, synthetic jets, and trailing-edge flaps, with discussions of their potential to delay flow separation and stall, enhance rotor aerodynamic efficiency, and an assessment of their adaptability to the energy and structural constraints of unmanned platforms. Finally, a lift vector control strategy suitable for autorotating rotors of autogyro UAVs is proposed, based on careful consideration of energy consumption, structural constraints, and control effectiveness. It provides a reference for aerodynamic optimization and flight control research on electric and hybrid-electric autogyro UAVs operating in extremely low-altitude environments. Full article

This study focuses on the longitudinal dynamic stability of swifts in cruising forward flight, which is critical for their high maneuverability but remains insufficiently investigated. Understanding longitudinal dynamic stability is the essential prerequisite for revealing the physical mechanism underlying their maneuverability: it is the dynamic stability characteristics that determine how the flight state responds to disturbances and control inputs, thereby laying a foundation for subsequent flight control during agile maneuvers. Conventional studies mostly adopt steady or quasi-steady assumptions, which cannot accurately reflect the influence of periodic body vibration. This study combines CFD numerical simulation and dynamic modeling to systematically analyze the unsteady dynamic stability of swifts. A bio-inspired dynamic model is established using the BE3357B airfoil with a 5° sweep angle, and the flapping-wing motion is decomposed into three degrees of freedom: sweeping, pitching, and flapping. Numerical reliability is assessed through grid independence and time-step independence verification. Aerodynamic force and moment trimming are performed on fixed-DOF and free-DOF models, where the latter considers coupled heaving–pitching motion and adjusted trim parameters. Stability analysis is conducted using three aerodynamic derivative methods: fixed velocity, forced oscillation, and Floquet. By solving small perturbation equations, eigenvalues and eigenmodes are obtained. All three methods identify two stable modes: a short-period mode with damping coefficient 0.1236–0.1870 and oscillation period 0.1121 s–0.1380 s, and a long-period mode with damping coefficient 0.2456–0.6203 and damping half-life 3.5803 s–4.8890 s, verifying stability under periodic vibration and unsteady aerodynamic coupling. Flow field results show clear distinct dynamic pressure and drag fluctuation characteristics between the downstroke and the upstroke. The unsteady stability framework provides a theoretical reference for analyzing the longitudinal stability of biomimetic flapping-wing aircraft and offers useful insight for future bird-inspired flight dynamics studies. Full article

To improve the unsteady aerodynamic response of the IAR 330 PUMA rotor, the present analysis provides a two-dimensional (2D) CFD-based framework for rotor blade sections integrated with trailing-edge flaps (TEFs). From a biomimetic perspective, the TEF is treated as an engineering abstraction of the adaptive aft-chord and camber variation observed in natural flyers, providing a controlled morphing envelope for aerodynamic-load regulation. The scientific contribution consists of an integrated assessment of the NACA 13112 section over an extended TEF deflection range, the comparison of several relative TEF chord lengths, and the transfer of the section-level framework to a four-section representation of the IAR 330 PUMA rotor. First, the effect of TEF deflection on the trajectory and strength of the dynamic stall vortex (DSV) is examined for a pitching NACA 13112 airfoil with a chord length of $c=0.6 \mathrm{m}$ and a pitching axis located at $x/c=0.25$. The pitching motion was prescribed in ANSYS Fluent through a user-defined function (UDF), imposing a hysteresis variation of the angle of attack (AoA) from $\alpha =-3°$ to $\alpha =23°$, while flap deflection angle ($\beta$) varied from $\beta =-20°$ to $\beta =8°$, corresponding to upward and downward TEF deflection, respectively. The second part of this study extends the same pitching law to real-scale rotor blade sections under hovering flight conditions. For the rotor simulations, the Multiple Reference Frame (MRF) model was used for the steady-state analysis, whereas a Sliding Mesh interface was adopted for the transient computations. A 2D pressure-based solver was employed, together with the SST k-ω turbulence model, the Unsteady Reynolds-Averaged Navier–Stokes (URANS) formulation, and a coupled pressure–velocity scheme. The rotational speed was set to $\omega =265 \mathrm{RPM}$, corresponding to a local tangential velocity of approximately $U=145 \mathrm{m}/\mathrm{s}$ at the analysed radius of $r=5.225 \mathrm{m}$ and to a local Mach number of $M\approx 0.43$. The ideal-gas assumption and energy equation were employed to account for compressibility effects. Among the investigated IAR 330 PUMA rotor-section configurations, the TEF with a chord length of $c_f=0.25c$ TEF provided the most balanced aerodynamic response, reducing the peak pitching-moment coefficient by approximately $32\%$ relative to the baseline airfoil. Full article

Honeybee (Apis mellifera) flight and vertical locomotion were investigated using high-speed imaging and schlieren flow visualization. Free-flight recordings were analyzed to extract wingbeat frequency, projected stroke amplitude, wingtip trajectories, and membrane deformation. The wingtip trajectory exhibited a pronounced asymmetry between upstroke and downstroke, suggesting a dominant role of the downstroke in thrust production. Significant membrane deformation was observed near stroke reversal, indicating strong wing flexibility and dynamic modulation of wing shape during flapping. A novel support-based framework was introduced to characterize vertical locomotion through the support polygon formed by leg contact points and the displacement of its centroid relative to the body. This movement function quantified changes in support distribution and revealed adaptive leg-contact strategies during wall climbing. Schlieren visualization provided qualitative evidence of wingtip vortex formation, although finer wake structures remained difficult to resolve. These findings provide new experimental observations of honeybee flight kinematics and introduce a quantitative framework for analyzing vertical locomotion using support redistribution metrics. Full article

The Vortex Ring State (VRS) is a critical aerodynamic hazard for rotorcraft, characterized by highly unsteady fluid–structure interactions and severe low-frequency vibrations. While data-driven deep learning models have shown promise in aviation state monitoring, their inherent “black-box” nature fundamentally contradicts the stringent interpretability requirements of airworthiness certification. To address this, we propose an “AI for Science” paradigm, investigating whether advanced Vision Transformers (ViT) can autonomously discover underlying aerodynamic mechanisms without human physical priors. First, to ensure absolute data fidelity, flight test datasets of a coaxial unmanned aerial vehicle were rigorously labeled using cross-validation from high-fidelity Computational Fluid Dynamics (CFD) simulations and wind tunnel tests. One-dimensional vibration signals were then transformed into two-dimensional Continuous Wavelet Transform (CWT) spectrograms. By employing Target-Layer Gradient Adaptation (Grad-CAM) techniques, we conducted a systematic comparison between traditional Convolutional Neural Networks (ResNet50) and ViT. The results demonstrate that while CNNs suffer from diffuse attention caused by high-frequency noise, the frozen-backbone ViT model achieves a physically interpretable accuracy of $93.24\%$, while autonomously locking its global attention onto a perfectly horizontal feature band centered at $41.7$ Hz. Crucially, this autonomously discovered feature precisely aligns with the theoretically derived once-per-revolution (1P) fundamental frequency of the rotor’s flap-lag coupling response under VRS aerodynamic turbulence. This research provides direct visual evidence bridging black-box AI decisions with classical fluid mechanics, proposing a “Mechanism-Guided Verification” framework that offers a trustworthy pathway for the future certification of AI in safety-critical aerospace systems. Full article

To address the limited understanding of the aerodynamic characteristics of bird-inspired flapping-wing aircraft across different flight phases and the unclear flow field interaction mechanisms between the wings and tail, this study performs three-dimensional numerical simulations based on a self-developed prototype using ANSYS Fluent and the overset mesh method. The aerodynamic effects of key tail parameters under different flight conditions are quantitatively evaluated, and the mechanisms of bidirectional wing–tail aerodynamic coupling are investigated. The results show that tail twist has a negligible influence on instantaneous lift and thrust during level flight, with a maximum variation of only 0.2 N, but significantly affects the overall aerodynamic moments of the aircraft. When the tail twist angle increases from 15° to 20°, the pitching moment increases by 6%. In contrast, during climbing flight, the tail pitch angle has a pronounced effect on lift and thrust, and its aerodynamic influence depends strongly on the aircraft angle of attack. At an aircraft angle of attack of 15°, the difference between the maximum and minimum cycle-averaged pitching moments reaches 0.2 N·m. Further analysis of vorticity fields and pressure distributions confirms the existence of distinct wing–tail aerodynamic coupling. The tail not only directly modifies the aerodynamic forces and moments acting on the aircraft but also alters the wing-generated flow structures, while the wing wake simultaneously influences the aerodynamic effectiveness of the tail. This bidirectional wing–tail aerodynamic coupling plays a critical role in shaping the aerodynamic response of the aircraft under different flight conditions. These findings clarify the aerodynamic roles of key tail parameters and reveal the underlying flow field interaction mechanisms across different flight phases, providing a theoretical basis for motion-parameter optimization and precise attitude control of bird-inspired flapping-wing aircraft. Full article

Birds actively modulate their wing and tail morphologies to achieve high aerodynamic efficiency and maneuverability, enabling long-duration gliding while retaining the ability to execute rapid maneuvers. Innovations in aircraft design and control are increasingly inspired by these avian flight characteristics through control surfaces that imitate the natural wing and tail movements of birds. This paper presents a non-flapping, unmanned aerial vehicle (UAV), called “SMART Hawk” (Shape-Morphing Artificial Red-Tailed Hawk), inspired by the flight and physical characteristics of Buteo jamaicensis, known as the Red-Tailed Hawk (RTH), which exhibits excellent soaring abilities and agility characteristic of birds of prey. To determine the design parameters required for flight, a mathematical model was developed in MachUpX, then validated and refined using Reynolds-averaged computational fluid dynamics (CFD) models in ANSYS Fluent. SMART Hawk incorporates biomimetic wing and tail morphing, including coordinated forward sweep of the mid-wing and aft sweep of the outer wing, as well as active tail pitch, roll, and feather tucking and expansion. The drone was manufactured from a combination of composite, wood, and 3D-printed components. Multiple flight tests were conducted with proof-of-concept prototypes to demonstrate the design’s effectiveness. Full article

Flapping-wing flight offers a promising solution for aerial mobility in low-density environments such as the Martian atmosphere, where conventional rotorcraft faces significant performance constraints. However, the coupled aerodynamic and structural mechanisms governing lift generation at low Reynolds numbers remain insufficiently understood. This study investigates the aeroelastic and unsteady aerodynamic behaviour of a bio-inspired flapping wing using an integrated experimental–numerical framework. High-speed imaging is employed to extract representative wing kinematics, including flapping frequency, stroke amplitude, and rotational motion. A geometrically scaled wing model is developed based on Reynolds number similitude and analysed using finite element methods to characterise its dynamic response. Aeroelastic behaviour is evaluated through modal transient simulations, while aerodynamic performance is assessed using both vortex-lattice modelling and computational fluid dynamics. The results show strong coupling between bending and torsional modes, with the structural response highly dependent on excitation frequency relative to the natural modes. Near-resonant conditions lead to amplified deformation and distinct phase relationships, while aerodynamic simulations reveal vortex-dominated lift generation. These findings provide a physics-based framework for the design and analysis of flapping-wing systems operating in low-Reynolds-number and low-density flight regimes. Full article

This paper presents the process of gathering data for a flapping-wing micro air vehicle (FWMAV) using optical tracking and force sensors for subsequent dynamic modeling and simulation purposes. Tethered and clamped experiments were performed to track the vehicle’s overall motion, wing kinematic angles, and aerodynamic force patterns, while additional properties such as mass, inertia tensor, center-of-mass position, and short-period excitation frequency were also examined. The methodology includes the testing approaches, modeling choices, and error analyses applied to the measurements. The results demonstrate that both tethered and clamped configurations introduce key limitations, particularly for steady-state flight. Additional constraints include structural fragility (hindering high-frequency testing), over-simplified CAD geometry, and controller tuning issues on the tail. Based on the identified parameters and experimental datasets, a high-fidelity simulation model was developed in MATLAB to serve as a platform for future control and flight envelope studies. Overall, the combination of optical tracking and force sensing provides a structured framework for linking experimental data to physical models, laying the foundation for future improvements in ornithopter modeling and testing. Full article

Insect aerial righting is a critical locomotor response to flight perturbations. However, the kinematic strategy of dragonfly (Pantala flavescens) free-fall recovery under asymmetric perturbations remains unclear. In this study, free-fall experiments were conducted using single-wing release to induce an initial asymmetric body roll, and three-dimensional kinematics were reconstructed using high-speed videography. The results show that the free-fall recovery process was divided into two phases based on body velocity: a free-fall phase with increasing downward velocity and a recovery phase marked by the cessation of this trend and a rise in horizontal velocity. During the free-fall phase, thorax roll developed and then attenuated, accompanied by relative abdominal and wing posture variations, without sustained wing flapping. Near the onset of recovery, hindwings initiated the downstroke earlier than forewings, forming a hindwing-leading flapping pattern. These findings indicate that dragonflies employ a phased kinematic strategy during asymmetric free-fall recovery, involving early body and wing posture adjustments followed by asymmetric wing flapping during the transition from gravity-dominated descent to maneuvering flight. Full article

Bio-inspired flapping-wing micro air vehicles (FWMAVs) are a research hotspot in micro air vehicles due to their high maneuverability and hovering capabilities. Accurate motion damping modeling is a prerequisite for their attitude disturbance rejection and control law design. Addressing the key issues in existing research—namely, the low computational efficiency of high-fidelity flexible-wing aerodynamic simulations and the inability of efficient rigid-wing assumptions to capture dynamic deformation of flexible wings—this paper investigates motion damping modeling for FWMAVs and its application to lateral flight stability analysis. First, an aerodynamic damping model under lateral motion parameters is established by approximating the flexible-wing surface using the spatial topology of the spar and veins. Second, numerical simulations of the flapping trajectory and motion damping are conducted. Subsequently, the validity and reliability of the model are verified through wind tunnel and turntable experiments. Finally, leveraging this model, lateral flight dynamics equations are derived to perform lateral stability analysis. The results effectively address the gap in assessing flapping-induced aerodynamic damping for flexible wings, providing an accurate analytical damping model, an efficient simulation framework, and an effective open-loop dynamics assessment method for the rapid design iteration and control algorithm development of FWMAVs. Full article

Flapping-wing drones (FWDs), owing to their compact size and operation in cluttered and unsteady airflow environments, encounter significant aerodynamic and stability challenges. Studies of avian flight reveal that falcons and other raptors actively deflect their covert feathers to mitigate gusts and maintain stable flight. Drawing inspiration from this mechanism, this study presents a peregrine falcon-inspired Active Flow Control Unit (AFCU) integrated with a Deep Deterministic Policy Gradient (DDPG)-based deep reinforcement learning (DRL) controller for real-time disturbance attenuation. The AFCU employs mechanical covert feathers (MCFs) that actuate to dissipate gust loads during high wind conditions. A reduced-order bond graph model that encapsulates the nonlinear interaction between the primary wing and the feather-based active flow control surfaces is created which is used as a dynamic training environment for the DDPG agent. Utilizing closed-loop interactions, the successfully obtained learned policy produces optimal actuator forces to reduce feather-displacement error and aerodynamic load variations. The designed controller stabilizes the internally unstable open-loop AFCU, attaining near-zero steady-state error and settling times under 1.6 s for gust magnitudes ranging from 12.5 to 20 m/s. Simulations further illustrate a reduction of up to 50% in gust-induced loads compared to traditional approaches. This integration of bio-inspired design with learning-based active flow control offers a viable avenue for the development of highly adaptive and gust-resilient flapping-wing aerial systems. Full article

This paper develops new empirical relationships to estimate FAA/EASA- and MIL-3013B-rules-compliant landing-field performance of multi-engine transport aircraft. Widely cited textbooks date from an era when inferior tire and braking capability limited aircraft performance. Today, the use of overly pessimistic conceptual design-level performance estimates may lead concept-design teams to advocate for unnecessary engineering solutions (for example, more complex flaps) to solve “problems” which do not actually exist. Moreover, today’s aircraft designer is likely to face customer-imposed wet and/or contaminated runway performance requirements, where the classic books only discussed dry-weather operations. Taken together, the design community needs a collection of revised empirical equations to estimate landing distances for dry and wet runways. The empirical relationships published here are based upon modern flight-manual data augmented by a calibrated physics-based numerical simulation applied to a wide range of possible vehicle configurations. They offer improved accuracy, compared to earlier methods. The new method, when applied to FAA rules for aircraft operating on dry runways, predicts the substantially shorter “real-world” certified landing distances attainable by modern aircraft. Full article