Search Results (902)

This study presents the design and flight demonstration of an aerobatic RC aircraft equipped with a morphing-wing using a compliant mechanism-based flexible structure. Unlike conventional hinged control surfaces, the proposed morphing wing provides an aerodynamic surface through elastic deformation, which can reduce aerodynamic discontinuities compared to conventional hinged wings. The flexible morphing rib was designed to ensure structural flexibility by combining fishbone and corrugated structures, and four flexible ribs constitute one module, making up four modules of the entire wing. Flight tests were conducted to evaluate the roll maneuverability of the UAV using roll rate and a nondimensional roll performance index. Experimental results showed that the morphing-wing UAV achieved stable and sufficient roll control performance under limited control input conditions, while demonstrating maneuverability comparable to or better than that of a conventional hinged control surface when the aileron deflection angle was limited. These results confirm the feasibility of compliant morphing wings as an alternative to traditional mechanical control surfaces and demonstrate their potential application to future high-efficiency UAV systems. Full article

Frigatebirds achieve exceptional long-endurance flight by efficiently utilizing marine atmospheric updrafts, offering a valuable biological prototype for low-energy bionic aircraft. Most existing studies focus on uniform inflow and single-axis attitudes, lacking systematic analysis of coupled-attitude aerodynamics and flow-field mechanisms in updraft environments. This work numerically investigates both clean-wing and fuselage-equipped frigatebird-inspired configurations under pitch-alone, pitch–yaw coupled, and yaw–roll coupled attitudes using the RANS/k-$\omega$ SST method. Results show that updraft effects exhibit strong pitch-angle dependence: significant drag reduction (maximum 0.0984) and lift augmentation occur within $-{12}^{\circ }<\alpha <4^{\circ }$, while above $\alpha =4^{\circ }$ updrafts suppress full-span deep stall and extend the stall angle by more than $8^{\circ }$, with a maximum lift increment of 220% near the wingtip. Under pitch–yaw coupling, a high-efficiency aerodynamic window emerges with a physically meaningful peak lift-to-drag ratio of 9.55. For yaw–roll coupling, the rolling moment is fundamentally driven by sideslip-induced asymmetric separation bubbles rather than by roll angle itself, as confirmed by surface limiting streamlines, skin friction distributions, and velocity vector plots. The bionic wing also achieves a near-elliptical spanwise lift distribution with an Oswald efficiency of approximately 0.994. This study provides key support for aerodynamic design, attitude control, and updraft energy harvesting of bird-like aerial vehicles. Full article

Flutter constrains the design of modern high-aspect-ratio wings, yet the combined influence of planform geometry, aspect ratio (AR) and structural flexibility is rarely assessed within a single consistent framework. This work presents a unified, physics-based reduced-order comparison of rectangular, trapezoidal and elliptical planforms under both rigid and flexible representations, intended as a screening tool for preliminary design rather than as a quantitatively predictive methodology for specific aircraft. A two-degree-of-freedom plunge–pitch typical section with quasi-steady (Theodorsen-based) aerodynamics is cast in state-space form, and flutter is identified through eigenvalue continuation by combined frequency coalescence and damping sign change. For rectangular and trapezoidal wings, increasing AR or reducing stiffness consistently advances flutter onset: at a fixed AR of 7.1, stiffening alone raises the critical speed by approximately 43 m/s (from 105 to 148 m/s, ≈+41%). In contrast, within the reduced-order model the elliptical planform inverts this trend: with sufficient stiffness, frequency coalescence is suppressed, and from the stiffened baseline (AR ≈ 4.75) raising AR to 5.6 keeps the wing flutter-free across the investigated velocity range, whereas lowering AR to 3.9 reintroduces hard flutter at 155 m/s. These model-based comparative tendencies indicate that AR and structural flexibility are strongly coupled design drivers and that elliptical loading is comparatively flutter-resistant, providing an efficient basis for early-stage configuration screening. Full article

In the present work, an alternative methodology was developed for the rapid prediction of pressure distributions over wings of low-speed aircraft. A hybrid neural network architecture, named “MARTHA” (Model for Airloads Reconstruction using a Trained Hybrid Architecture), was presented, which is composed of a Multilayer Perceptron and the decoder of an Autoencoder. Three compact representation models—Principal Component Analysis (PCA), Autoencoder (AE), and Variational Autoencoder (VAE)—were systematically evaluated to determine the optimal dimensionality reduction architecture; the AE was selected based on its superior reconstruction accuracy and training stability. The main feature of MARTHA is that it provides predictions of the differential pressure coefficient field in the form of monochrome images, where the pixel intensity directly represents the normalized pressure value. One of the main objectives of developing MARTHA was to create a rapid surrogate model that can approximate vortex lattice method (VLM) simulations in preliminary design and optimization tasks, particularly when thousands of wing configurations need to be evaluated. The key feature of the proposed model is its ability to predict the pressure distribution for trapezoidal wings of various geometries 10¹–10⁴ times faster than numerical models, while maintaining accuracy (R² = 0.9998). The data obtained are presented in a convenient format for their further use in CAE systems of strength analysis. To assess the practical utility of the proposed model, implementation cases were carried out using the finite element software ANSYS 18.2 for three wing configurations not present in the training dataset. The pressure fields predicted by MARTHA were mapped onto the wing meshes, and linear static structural analyses were performed. The obtained Von Mises stress distributions showed good agreement with the corresponding distributions obtained using numerical models. Full article

The maneuvering flight of future aircraft which employ morphing variable camber wings (VCWs) requires rapid and accurate aerodynamic regulation. However, the dynamic lift responses during fast morphing deflection exhibit unsteady hysteresis effects, hindering shape and flight control performance. This study proposes a novel modeling and feedforward compensation algorithm based on the Prandtl–Ishlinskii (PI) model to identify and mitigate such unsteady hysteresis effects from a control perspective. First, unsteady lift responses of a two-dimensional trailing-edge VCW under periodic and non-periodic morphing motions are analyzed, and the influences of morphing trajectories on lift characteristics are investigated. The results reveal that the maximum lift decreases significantly as the morphing frequency increases. Under point-to-point non-periodic morphing conditions, pronounced hysteretic lift responses are observed and are strongly influenced by the morphing trajectories. A forward model mapping “morphing trajectory-lift response” is developed using PI hysteresis operators and log(t)-creep operators, identified using time-domain data from two-dimensional computational fluid dynamics (CFD) calculations. From this, an inverse model of the “expected lift response-compensated morphing trajectory” is derived using a hysteresis compensation function. Simulations indicate that periodic lift hysteresis is effectively compensated, yielding a quasi-steady linear relationship. For fast terminal morphing, compensated trajectories enable lift to reach targets rapidly, smoothly, and stably without lag. Robustness is validated for varying lift targets and terminal times. This work offers new insights into fast morphing-wing and high-maneuverability control of future smart aircraft. Full article

High-speed compound helicopters surpass the forward-speed limits of conventional helicopters and expand the flight envelope, yet close multi-component integration induces complex aerodynamic interference, whose underlying mechanisms and evolution with flight speed must be understood to support integrated aerodynamic design. This study examines the principal aerodynamic interactions in a box-wing, twin-propeller compound helicopter at flight speeds of 30–110 m/s. Time-accurate Reynolds-averaged Navier-Stokes calculations with dynamic overset grids are performed for isolated-component, rotor-airframe, rotor-propeller, and complete configurations. At 30 m/s, direct impingement of the main-rotor wake produces highly non-uniform propeller inflow, pronounced periodic propeller-thrust fluctuations, and substantial lift losses on the advancing-side wing panels. As flight speed increases, the wake is convected downstream and direct interference weakens, although lateral asymmetry persists. When the airframe is included, the lateral propeller thrust-coefficient trend observed in the rotor-propeller configuration is reversed, while box-wing lift is redistributed unevenly among the individual panels. At 90 and 110 m/s, the main-rotor thrust-coefficient ranges in the complete configuration lie entirely below the corresponding isolated-rotor ranges. These findings clarify how flight speed and component integration jointly govern complete-configuration aerodynamics, providing a basis for reliable aerodynamic assessment and configuration optimization of high-speed compound helicopters. Full article

Despite the rapid proliferation of unmanned aerial vehicles (UAVs) across industrial, agricultural, and scientific domains, their deployment remains constrained by limited endurance, aerodynamic inefficiency, and acoustic emissions, all mediated by a shared onboard energy budget. Existing biomimetic UAV reviews have generally treated aerodynamics, structures, sensing, control, and energy systems as parallel topics rather than as interacting components of a unified aerial architecture. Drawing primarily on literature published between 2015 and June 2026 and identified through searches of Web of Science, Scopus, and Google Scholar, this review addresses this gap by examining bio-inspired technologies across six principal domains: aeroacoustic and passive flow control, aerodynamic efficiency, multifunctional structural composites, neuromorphic sensing and control, ionic energy storage, and energy harvesting. Its principal contribution is a cross-domain synergy analysis identifying five performance couplings and one structural enabling architecture through which these domains interact physically and functionally. Representative examples include serration-based propeller geometries that can simultaneously reduce noise and power demand; morphing wing surfaces that serve as both aerodynamic structures and triboelectric harvesting substrates; and neuromorphic spiking neural networks that have been reported, in specific event-vision inference benchmarks, to reduce inference energy by three to four orders of magnitude relative to embedded graphics processing unit (GPU)-based implementations. Mechanical harvesting outputs nonetheless remain orders of magnitude below propulsion requirements and are thus positioned as supplementary. Four systemic barriers (unquantified mass–energy balance, undocumented durability, aeroelastic co-design gaps, and heterogeneous metrics) are evaluated, and the resulting synthesis indicates that advancing bio-inspired UAVs requires a transition from structural imitation to functional, system-level biomimetics. Full article

Atmospheric icing is one of the most critical meteorological hazards for unmanned aerial vehicles (UAV), whose operation under adverse conditions—high latitudes, elevated altitudes, long-endurance missions without pilot intervention—particularly exposes them to ice accumulation on aerodynamic surfaces and propellers. Unlike manned aviation, where this phenomenon has been extensively studied and regulated, a significant knowledge gap exists in the UAV domain that limits the development of effective protection systems adapted to energy constraints. This article provides an integrative review—conducted with a systematic search strategy following PRISMA reporting guidelines—of atmospheric ice formation mechanisms, their specific effects on UAV propellers, and the two most promising mitigation approaches: electrothermal modelling for the optimisation of electric heating systems and the development of functional surface materials including superhydrophobic coatings (SHC); composites with conductive nanofillers (graphene, carbon nanotubes); and piezoelectric actuators. The analysis demonstrates that hybrid systems combining passive and active strategies managed by intelligent control represent the most viable solution for extending UAV operational envelopes under known icing conditions, with a projected reduction in anti-icing system energy consumption of at least 40% relative to conventional continuous heating. This estimate is based on the most conservative published evidence: pulsed electrothermal de-icing achieves 40–60% savings versus continuous anti-icingSHC-assisted hybrid heating reduces IPS power by more than 80% on static aerofoils; and rotary-wing pulsed systems reduce mean consumption by 60–75% relative to continuous operation. Key research gaps are identified, and a prioritised future research agenda is proposed to support the development of certifiable anti-icing systems for rotary-wing UAV platforms. Full article

In-flight wingtip docking can connect multiple UAVs into a high-aspect-ratio chained-wing configuration, offering potential improvements in aerodynamic efficiency, endurance, and cruise performance. Reliable close-range 6-DoF relative pose estimation is essential for precise docking; however, existing studies have focused primarily on aerodynamic characteristics, docking mechanisms, and guidance and control, while robust monocular pose estimation under partial occlusion and image degradation remains insufficiently investigated. To address this gap, a cooperative-target-based monocular vision method is proposed for six-degree-of-freedom relative pose estimation during in-flight wingtip docking in a chained-wing UAV system. An asymmetric seven-ring planar cooperative target is designed to reduce feature-identification ambiguity and retain sufficient geometric constraints under partial occlusion. The front end combines YOLOv8n-seg instance segmentation with local inner–outer ring refinement and topology-based feature classification. According to target visibility, the back end adaptively selects seven-, five-, or four-point pose-estimation modes, refines valid solutions by minimizing reprojection error, and removes isolated suspicious candidates when necessary. The method is evaluated on a controlled indoor hardware-in-the-loop platform as a pre-flight assessment of its incremental measurement performance. In controlled incremental-response experiments, the mean absolute adjacent-increment errors do not exceed $0.08\mathrm{mm}$ in translation and $0.13°$ in rotation. The complete method achieves a pose-solving success rate of 99.07%. Experiments involving progressive wing occlusion and synthetic directional motion blur further demonstrate that the method can provide stable and continuous relative pose output under challenging observation conditions. Full article

UAV-assisted VANETs are a key component of the 6G vision, yet their practical deployment is hindered by the fundamental conflict between network Quality of Service (QoS) and the high aerodynamic power required for rotary-wing flight. This paper proposes SAVIOR (Survivable Aerial-Vehicular Intelligent Optimization and Routing), a Deep Reinforcement Learning (DRL) framework that jointly optimizes multi-UAV activation and packet routing. Unlike existing approaches that rely on oversimplified linear energy models, SAVIOR integrates a rigorous three-component aerodynamic power model and introduces an M/M/1 queuing-based Survivability Score (S-score) to explicitly quantify packet delivery before Time-to-Live (TTL) expiration. Through a high-fidelity co-simulation using SUMO and Python-TraCI, the SAVIOR agent is able to handle stress-test situations where network demand is higher than capacity ($\rho >1.0$). A comparative analysis shows that SAVIOR is Pareto-optimal, with a total reward that is 65% higher than that of a static energy-saving policy and a survivability that is 24% higher. Crucially, compared to a performance-maximizing greedy policy, SAVIOR maintains comparable safety-critical QoS while reducing total energy consumption by 19.8%, thereby preventing premature battery depletion and mitigating co-channel interference. Full article

The rapid evolution of Urban Air Mobility (UAM) necessitates high-performance morphing structures capable of seamless transitions between flight and ground modes. This research presents a rigorous structural optimization framework for a wing deployment mechanism, addressing the critical challenge of minimizing stress concentrations in cantilevered revolute joints. To overcome the computational prohibitive cost of traditional multibody dynamics, a Generalized Spectral Surrogate Model (GSSM) is introduced. This novel approach maps the mechanism’s geometric parameters to its kinetic response using polynomial-modulated Fourier series, reducing the evaluation time of ${10}^5$ design configurations from 4.2 h to merely 0.8 s while maintaining a determination coefficient $R^2>0.995$. Comparative analysis demonstrates that the GSSM outperforms Artificial Neural Networks and Kriging models in capturing periodic kinematic boundaries without spurious local minima. Through a weighted topological analysis, the study identifies a global optimum ($L_2=0.5$ m, ${\theta }_2={64.2}^{\circ }$) that effectively shunts 70.3% of the aerodynamic load to the robust vehicle chassis. The proposed solution deviates from the theoretical unconstrained minimum by only 0.24%, providing a validated mathematical basis for the rapid synthesis of reliable aerospace mechanisms. Full article

Flying-wing aircraft are more susceptible to wind disturbance due to their smaller wing loading, making gust alleviation critical for flight performance and safety. Conventional control surfaces may exhibit insufficient manipulation efficiency on such configurations, motivating the adoption of active flow control, particularly circulation control (CC) due to its favorable control efficiency. This paper presents an Active Disturbance Rejection Control (ADRC) framework for gust load alleviation (GLA) of flying-wing aircraft equipped with CC actuators, which enables real-time estimation and compensation of both gust disturbance and practical uncertainties and is validated through closed-loop wind-tunnel experiments under various sinusoidal gust conditions. An unsteady aerodynamic model with experimental data is established and simulations are performed for further investigation of alleviation performance and response characteristics under a wide range of gust conditions. Results show that both ADRC and PID exhibit degraded performance at higher gust frequencies and larger gust ratios, but ADRC achieves higher alleviation efficiency across the tested conditions. Furthermore, ADRC maintains satisfactory performance with actuator delays up to 0.04 s and outperforms PID under measurement noise and Dryden turbulence. These findings validate the effectiveness and robustness of ADRC for GLA, underscoring its practical potential for active flow control systems. Full article

Autonomous acoustic sensing systems are increasingly investigated for unmanned aerial vehicle (UAV)-based surveillance and environmental monitoring applications due to their passive operation and relatively low computational requirements. However, the integration of acoustic classification and direction-of-arrival estimation on UAV-mounted microphone arrays remains challenging, particularly because realistic flight conditions introduce propulsion noise, aerodynamic flow, vibration, and complex acoustic interference. This paper presents a static ground validation of an AI-assisted acoustic target detection and azimuth estimation framework integrated on a flying-wing vertical take-off and landing (VTOL) UAV equipped with a distributed microphone array. The proposed system combines MFCC-based chainsaw sound classification using a Random Forest model with amplitude-based and SRP-PHAT-based azimuth estimation. Four HiFiBerry measurement microphones were mounted on a 4 m wingspan flying-wing VTOL UAV and connected to a Raspberry Pi 5 processing unit. Experimental validation was conducted under controlled indoor laboratory conditions using loudspeaker playback, with the UAV propulsion system inactive and only the acoustic acquisition and processing subsystem powered. The tests included single-source angular measurements, simultaneous multi-source acoustic scenarios, and source height variation. The SRP-PHAT method achieved a mean angular error of 3.55° in the single-source tests and 4.81° in the multiple-source tests, outperforming the amplitude-based baseline. The results support the feasibility of the proposed acoustic-processing framework under static ground conditions. However, because propulsion noise and in-flight aerodynamic effects were not included in the present validation, future work must address simulated propulsion noise injection, propulsion-on static testing, outdoor validation with real chainsaw sources, and eventual in-flight experiments. Because propulsion noise, aerodynamic flow, and in-flight vibration were not included in the present experimental campaign, the results should be interpreted as baseline static ground validation results rather than evidence of in-flight robustness. Full article

An oblique wing aircraft can continuously vary its wing sweep angle, making it attractive for high-altitude unmanned aerial vehicle (UAV) relay missions that require stable attitude, altitude, and speed for antenna pointing and air-to-ground link consistency. The present work focuses on flight-platform stability as an enabling layer for UAV relay operation rather than on direct optimization of link-level communication metrics. During sweep transitions, however, sweep-dependent mass properties, aerodynamic loads, and control effectiveness introduce coupled attitude disturbances. This study develops a six-degree-of-freedom nonlinear multi-body model using Kane’s formalism to retain products of inertia, center-of-gravity variation, and sweep-dependent control effectiveness in a compact control-oriented form. A minimum-control-energy allocation method is formulated to coordinate the aileron and differential all-moving horizontal tail when aileron roll authority decreases at large sweep angles. An inner/outer-loop sliding-mode controller with auto-throttle is then designed for attitude, altitude, and speed regulation. Closed-loop simulations of 0–30° and 30–60° sweep maneuvers show that altitude and speed remain close to their commands while attitude deviations remain bounded. A 15% aerodynamic-coefficient perturbation case further indicates bounded closed-loop responses under the considered model uncertainty. Full article

Carrier-based fixed-wing UAV landing is challenged by deck motion, carrier airwake, gust disturbances, strong trajectory–attitude coupling, and actuator constraints. To address these issues, this paper proposes a Predefined-Time Direct Lift/Side-Force-Integrated Approach Landing (PTDIAL) method. An integrated direct-force architecture is constructed using the trailing-edge flap for direct lift and the spoiler for direct side force, thereby reducing the dependence of trajectory correction on angle-of-attack- and bank-angle/sideslip-mediated regulation. A preview-based reference glide slope is generated from the predicted Ideal Touch Point (ITP) sequence to improve the response to deck motion. Predefined-time control laws are developed for the cascaded position, trajectory, attitude, angular rate, and velocity loops, with prescribed-performance constraints imposed on the attitude response. A predefined-time disturbance observer is introduced to estimate the lumped aerodynamic disturbances, while an auxiliary anti-saturation mechanism compensates for the effect of trailing-edge flap saturation. Lyapunov analysis establishes the practical predefined-time stability of the closed-loop system under bounded disturbances and actuator constraints. Various simulations demonstrate that the proposed architecture improves lateral and vertical tracking while preserving the UAV attitude, and Monte Carlo simulations further confirm the robustness of PTDIAL. Full article