Search Results (563)

Electric aviation and unmanned aerial vehicles (UAVs) depend on lightweight composites to preserve payload and range, yet mass reduction, recycled content, or bio-based content alone does not establish component suitability. Candidate systems must also satisfy coupled structural, thermal, fire, electrical, manufacturing, durability, repair, and circularity requirements. This structured critical narrative review evaluates thermoplastic carbon-fibre-reinforced polymer (CFRP) systems, recycled-carbon-fibre composites, natural-fibre systems, bio-based and recyclable matrices, hybrid architectures, and multifunctional composites using a component-specific framework based on source role, evidence maturity, test comparability, and failure consequence. The framework links processing and chemistry to defects, retained performance, repair and recovery, and the evidence required for defined aircraft and UAV components. Thermoplastic CFRP provides the strongest near-term pathway for secondary and semi-structural components, although weld durability, impact tolerance, fire response, and process conformity remain system specific. Recycled-carbon-fibre and natural-fibre systems are most defensible for lower-consequence covers, fairings, housings, interiors, and UAV parts when feedstock variability, moisture, porosity, and fire performance are controlled. Battery enclosures, primary structures, rotor-support members, and structural-battery systems require representative coupled-hazard and component-scale evidence. The resulting adoption pathways are bounded by component and operating conditions, with manufacturing, durability, repair, recovery, and qualification evidence specified for each application. Full article

The position of the center of mass directly affects the attitude control and flight safety of moving bodies such as unmanned aerial vehicles (UAVs). Therefore, high-precision measurement of the center of mass is required. Existing methods require changing the posture of the measured object multiple times. This introduces repeated positioning errors and suffers from poor equipment versatility. To address these issues, this paper proposes a static and dynamic combined measurement method for the center of mass based on multi-view vision. First, the relationship between the swing period and the pendulum length under the simple pendulum principle is analyzed. The basic principle of determining the direction of the center of mass using the line of gravity is also examined. Second, an under-constrained compound pendulum fixture is designed. A binocular vision system is used to track circular markers, perform FFT-based period verification, and fit the gravity line using singular value decomposition (SVD). Third, using a standard cubic iron block as the test object, the influence of pendulum length and swing angle on measurement accuracy is studied. Finally, experiments verify that the proposed method can obtain three-dimensional coordinates of the center of mass under a single suspension condition. The results show that with a pendulum length of 330 mm and an initial swing angle of 4°, the root mean square error of the center of mass measurement is 0.70 mm, and the maximum deviation over five repeated measurements is 1.45 mm. This method does not require repeated lifting or changes in posture. It can meet the need for in-situ, high-precision center of mass measurement of UAVs and other aircraft. Full article

With the increasing scale and density of low-altitude unmanned aerial vehicle (UAV) operations, safety separation between multirotor UAVs has become a critical parameter for low-altitude airspace management. Existing studies mainly consider aircraft geometry, navigation errors, trajectory deviations, and conventional collision risk models, while rotor-downwash-induced aerodynamic interference remains insufficiently addressed. This study proposes a safety separation assessment method for quadrotor UAVs by integrating computational fluid dynamics (CFD) with an improved Event collision model. A small-scale quadrotor UAV is analyzed, and its rotor downwash flow fields under vertical- and horizontal-motion conditions are simulated using the multiple reference frame method. Based on a 5 m/s crosswind-resistance capability threshold, aerodynamic-interference characteristic distances are extracted and used to construct a basic collision box. To better represent the actual aerodynamic hazard region, an I-shaped improved collision box is further developed and incorporated into the Event collision model. Under a target level of safety, the longitudinal, lateral, and vertical minimum safety separations are determined as 1.68 m, 1.72 m, and 1.08 m, respectively. The results show that the proposed CFD–Event coupled method can transform rotor downwash characteristics into collision risk parameters and provide a quantitative basis for safety separation assessment in dense low-altitude multirotor UAV operations. Full article

In aerospace applications, structural vibration can cause fatigue accumulation and shorten the service life of aircraft. This makes vibration suppression based on Macro Fiber Composite (MFC) piezoelectric composites an important research topic. Considering the asymmetric high-voltage operating range of the M-8557-P1 MFC from −500 V to 1500 V and its capacitive impedance characteristics within the 1000 Hz operating frequency band, this paper designs a laboratory prototype of a high-voltage driver. The prototype adopts a voltage–current dual closed-loop structure and a current-tracking PWM control strategy. Under the tested laboratory conditions, the prototype exhibited a relatively fast transient response and a certain dynamic driving capability for capacitive loads. Based on the laboratory prototype, an auxiliary signal-conditioning module and a digital control module equipped with an active control algorithm were further developed. These modules were integrated with the laboratory prototype to form a high-voltage closed-loop control system for MFC piezoelectric sensing and actuation. Ground laboratory tests were conducted on a high-aspect-ratio unmanned aerial vehicle wing. The experimental results show that, when the dominant vibration frequency is approximately 3.6 Hz, the response converges to a steady state within 4.77 s after control is applied. In the steady state, the root-mean-square displacement decreases from 15.57 mm to 4.28 mm, corresponding to a reduction of 72.52%. This result demonstrates the effectiveness of the active vibration control system under this representative application scenario. 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

Adverse weather poses a major challenge to ground-based electro-optical (EO) aircraft surveillance. Existing parameter-efficient fine-tuning (PEFT) methods operate mainly in the spatial domain and treat weather as a generic domain shift rather than a frequency-dependent degradation. We propose Freq-LoRA, a frequency-domain PEFT method that applies the Type II Discrete Cosine Transform (DCT-II) to frozen encoder features, decomposes them into $K=4$ learned Gaussian frequency bands, and modulates the bands with an image-driven spectral gate. SpectralGate contains 140 parameters and estimates band importance from the input image’s DCT statistics, removing the need for external weather metadata at inference; weather-diverse training data are still required to learn the decomposition. On a Blender-simulated aircraft dataset covering five weather conditions, Freq-LoRA achieved a test mean Intersection-over-Union (mIoU) of 0.904, with a 95% confidence interval (CI) of [0.899, 0.908], using 559 K trainable parameters. Its point estimate differed by $-0.002$ from that of the weather-conditioned spatial method Feature-wise Linear Modulation (FiLM; 0.906), despite requiring no external weather metadata at inference. Relative to batch-size-matched Spatial LoRA (0.873; 95% CI: [0.867, 0.879]), Freq-LoRA had a 0.031 higher point estimate. Preliminary evaluation on real unmanned aerial vehicle (UAV) imagery yielded 0.421 mIoU (+13% relative to the zero-shot Segment Anything Model (SAM); one platform), and evaluation under six unseen image corruptions showed differences of at most 0.001 mIoU from the weather-oracle variant. Full article

Unmanned Aerial Vehicle (UAV) swarms are increasingly deployed in search and rescue (SAR) missions to rapidly locate survivors. However, deploying autonomous swarms in low-altitude airspace shared with crewed rescue aircraft poses significant algorithmic and safety challenges. Following PRISMA 2020 guidelines, this systematic review synthesizes 44 peer-reviewed studies (2022–2026) to evaluate the literature across algorithmic optimization, reality-gap limitations, tactical deconfliction, and validation maturity. The synthesis reveals a consistent trend toward decentralized swarms, driven by Deep Reinforcement Learning in dynamic environments and by bio-inspired metaheuristics for static coverage. Despite these algorithmic advancements, the literature exhibits a severe reality gap: approximately 86% of evaluated models rely exclusively on idealized software simulations, abstracting away critical constraints like communication denial and sensor noise. Furthermore, most models assume uncontested airspace and lack the Manned–Unmanned Teaming (MUM-T) and tactical deconfliction protocols necessary for safe coexistence with rescue helicopters. To achieve true operational readiness within the critical “Golden 72 Hours” of disaster response, the discipline must transition toward hardware-in-the-loop and physical field trials, natively integrating airspace deconfliction into core swarm optimization loops. Full article

This paper presents a generic stochastic simulation framework for evaluating the operational feasibility of solar-powered unmanned aerial vehicles (UAVs) executing an invariant trajectory in high-variability climates. Unlike conventional approaches relying on idealised irradiance conditions, the proposed framework combines a modified ASHRAE radiation model corrected for local bias and variability with a semi-Markov process modelling stochastic transitions between cloud and sunlight states using parametrised state duration times. The environmental model is further extended with diurnal temperature variation and standard atmosphere effects. UAV motion is represented using a rigid body flight dynamics model combined with a cascaded trajectory tracking controller and an energy subsystem incorporating a lithium-ion battery model. Warsaw (Dfb climate) is used as a representative Central European test case characterised by frequent radiation deficits and highly variable atmospheric conditions. The simulations quantify the influence of environmental uncertainty and selected battery capacities on mission success probability across different solar-to-wing area ratios, with the mission entry at 70% initial battery state of charge and no additional manoeuvre losses or external atmospheric perturbations. The evaluations were conducted for a fixed mission start at solar noon on 15 July and were supplemented by an optimised mission scheduling analysis to establish upper flight-time limits. The results demonstrate the strong sensitivity of solar-assisted UAV operations to stochastic cloud conditions and support the design and mission planning for low-altitude long-endurance aircraft. Full article

Low-altitude general aviation aircraft and unmanned aerial vehicles (UAVs) are widely deployed for complex operational tasks, yet low-altitude gusts and crosswind disturbances induce severe airspeed fluctuations, leading to variable lift, unstable flight altitude, and perturbed pitch attitude. Such aerodynamic fluctuations degrade flight smoothness and increase pilot control workload. To mitigate lift and altitude instability under unsteady incoming flow, this paper proposes a novel passive trailing-edge winglet configuration capable of self-regulating wing angle of attack (AOA) without active flight control systems. A quasi-static aerodynamic equilibrium analytical model based on moment balance about the wing pivot axis is established, combined with validated Computational Fluid Dynamics (CFD) simulations to characterize the passive AOA adjustment mechanism and quantify lift variations under velocity perturbations. Results demonstrate that the integrated wing-winglet layout generates passive aerodynamic feedback moments to automatically adjust the wing AOA when freestream speed varies. For airspeed disturbances within ±10% of the cruise velocity (102 m/s, 0.3 Ma), the total lift fluctuation of the wing-winglet assembly is suppressed within ±1.01%, whereas conventional fixed-wing configurations experience lift deviations between −16% and +22% under identical disturbance conditions. Notably, the present study only verifies quasi-static aerodynamic equilibrium under steady inflow; dynamic flight stability, unsteady aerodynamic effects, and stall-limit performance remain unexamined and require further investigation. The core novelty of this design lies in the passive negative-feedback aerodynamic moment generated by the trailing-edge winglet, which decouples fuselage attitude from wing pitching motion and stabilizes equilibrium lift under mild low-altitude gust perturbations. Full article

Unprovoked shark bites are one of the most recognised human–wildlife conflicts and present a significant concern for beach safety. Lethal methods of shark mitigation have previously been implemented to reduce the risk of such incidents; however, due to their destructive impacts on vulnerable marine wildlife, non-lethal approaches are increasingly preferred. In recent years, drones have emerged as an effective, minimally invasive tool for real-time shark surveillance in surf zones. Drones are also used to collect valuable data on shark ecology and behaviour in nearshore environments, which can inform evidence-based policies. This review examines the utility of drones for shark surveillance programs by identifying key operational parameters and associated challenges of drone-based methods. We investigate emerging technologies, including long-range drones, remotely operated or autonomous flight missions, and the use of artificial intelligence for shark detection and species identification. We also outline current drone licensing, laws, and regulations, noting that these vary across administrative regions (i.e., countries and states). Overall, this review provides insight into the expansion of drone-based shark surveillance in nearshore areas and its potential to enhance beach safety, support management decisions, and advance scientific knowledge without negatively impacting shark populations. Full article

Unmanned Air Vehicles (UAVs) are becoming increasingly popular and widely used in a variety of industries such as agriculture, construction, delivery, surveillance, rescue operations, mapping, wildlife tracking and many more. With the advancements in technology, UAVs are becoming more autonomous and able to perform tasks with minimal human intervention, rendering their use indispensable for military and law enforcement purposes. In terms of control surfaces, V-tail configurations are commonly used on UAVs due to their advantages in control and stability performance, as well as their ability to reduce drag and improve overall efficiency. However, research on V-tail design and sizing is limited, particularly for Class I mini-UAVs. The objective of this paper is to identify a methodology for the Conceptual and Preliminary sizing and design of a V-tail of a Class I Mini UAV (NATO classification). The methodology follows the design of a V-tail from the characteristics of the conventional tail of the UAV. Once the characteristics of the conventional tail are extracted, V-tail geometric characteristics are computed. The stability derivatives of the V-tail are then calculated. The methodology for the analytical aerodynamic characteristics and stability derivatives is a combination of two existing methodologies: one methodology for V-tail stability and control derivatives, which refers to the Preliminary or Detailed Design of an aircraft, and one methodology for a conventional tail design, which refers to the Conceptual and Preliminary design of an aircraft. With this combination, a V-tail Preliminary design methodology was achieved. Furthermore, the aerodynamic characteristics and stability derivatives of the designed V-tail were verified by Low Fidelity Aerodynamics simulation, and then by High Fidelity Aerodynamics by means of Computational Fluid Dynamics (CFD). Full article

Vertical take-off and landing (VTOL) configurations incur a structural weight penalty that reduces payload fraction and endurance compared to conventional fixed-wing and multirotor aircraft of comparable gross weight. To extend the endurance of VTOL UAVs, this work presents the design, analysis and control of a novel unmanned tilt trirotor aircraft with tandem wings, named Gong-H, featuring VTOL capability and high aerodynamic efficiency. A prototype of this aircraft was built with the rotor system mounted between tandem wings with a high wing coverage rate, which can achieve a more compact structure than other VTOL aircraft. The control forces and torques are provided not only by the rotor system in VTOL flight mode and the two tandem wings in cruise mode, but also by both the rotor system and wings in transition mode. Additionally, Computational Fluid Dynamics (CFD) simulations are conducted to optimize the wing configuration to improve the efficiency of cruise mode. Moreover, an airspeed-scheduled hybrid control framework based on incremental nonlinear dynamic inversion (INDI) and PID is adopted for different flight modes to improve the robustness of control and the stability of flight mode switching. Hover experiments confirm improved power efficiency compared to tilt quadrotor configuration, which extends endurance time and increases range. Additionally, complete flight cycle field experiments were conducted to demonstrate the aerodynamic feasibility of the prototype, including VTOL flight, cruise flight, and transition flight modes. Control surface redundancy tests and comparative INDI-PID validation under asymmetric disturbances further verify the practical robustness of the control framework. This work provides a design concept of VTOL aircraft and a practical solution for VTOL applications. Full article

Stratospheric solar-powered unmanned aerial vehicles (UAVs), commonly operated as High-Altitude Pseudo-Satellites (HAPS), promise satellite-like persistence for Earth observation, communications and remote sensing, but their feasibility is governed by a tight coupling between solar energy availability and onboard energy demand. This study presents an energy-balance simulation framework that predicts the diurnal charge–discharge behaviour and endurance of solar-powered UAVs. The framework couples a physics-based environmental irradiance model—astronomical solar position, an air-mass and pressure-scaled broadband atmospheric transmission and an eccentricity-corrected extraterrestrial irradiance—with a wing-geometry photovoltaic collection model that reduces the airfoil camber, planform, dihedral and cell layout of a real wing to three scalar coefficients, replacing the flat-plate assumption common in solar-UAV sizing. The closed-form collection coefficient captures the full dependence of collected power on sun position and aircraft heading and admits an exact orbit-averaging result for circular loiter. The model is implemented as a reproducible, modular tool with single-day, annual and global analysis modes. It is validated against a ground-based photovoltaic charging campaign conducted on the as-built Aurora solar UAV demonstrator (5.6 m span, 8 kg) over three clear-sky days spanning a 90-day seasonal range: predicted and measured wing-collected power agree with a Pearson correlation of 0.998, a coefficient of determination of 0.993, an RMS error of 6.0% and a daily-energy agreement within 3.5%. A structured residual identifies an unmodelled photovoltaic temperature effect bounded at the 6% level. The framework provides HAPS designers and operators with a transparent, validated tool for feasibility screening, component selection and mission planning across latitude and season. Full article

Typhoon-eye sensing places unmanned aerial vehicle (UAV) swarms in a setting where the wind field that carries the target signal also displaces aircraft, drains energy, weakens links, and increases failure risk. A rule that improves only routing or only motion can therefore move the swarm into another failure mode. This paper proposes a risk-driven cross-layer coordination scheme for such missions. A bounded risk index, computed from isolation, connectivity loss, and wind intensity, acts as a supervisory variable for multi-hop reachability maintenance, isolated-node recovery, and layered altitude adaptation. For evaluation, graph reachability is separated from useful data return through a degraded multi-hop aggregation model that includes distance loss, wind-dependent reliability, rain-induced packet loss, relay forwarding loss, and mothership collection capacity. The simulator combines a bounded Holland-type storm field, stochastic turbulence, nonlinear propulsion energy consumption, and wind-dependent structural failure. Against three literature-inspired baselines, two AI-inspired comparators, and six ablation variants, the method keeps a balanced profile across connectivity, isolation, wind exposure, data collection, and survival. In 30-run steady-state robustness tests under heavy-rain attenuation, the full strategy showed clear gains over routing-only and multi-agent reinforcement learning (MARL)-routing comparators in connectivity and isolation, but did not uniformly dominate topology reconstruction or the multi-agent deep deterministic policy gradient–artificial potential field (MADDPG-APF) recovery comparator. The results indicate that, in storm-dominated swarm sensing, resilience comes mainly from coordinating exposure reduction with topology stabilization, rather than from optimizing a single layer. Full article

Ground vibration testing (GVT) plays a key role in the validation of numerical models and the assessment of aeroelastic stability in lightweight aircraft structures. This study presents an experimental and numerical investigation of a full-scale composite flying wing unmanned aerial vehicle (UAV) intended for vertical take-off and landing operations. Due to its low structural mass and highly integrated configuration, the aircraft exhibits increased sensitivity to modeling assumptions, boundary conditions, and measurement uncertainties. A finite element model was developed in Ansys, incorporating detailed laminate definitions and the internal sandwich structure. Experimental modal testing was performed under free-free boundary conditions using an electrodynamic shaker and a distributed measurement consisting of 94 response locations. Frequency Response Functions (FRFs), coherence analysis, and the Complex Mode Indication Function (CMIF) were employed to identify the dominant structural modes. Particular attention was given to the bending and torsional modes that govern aeroelastic behavior. Comparison of experimental and numerical results showed good agreement in mode shapes, while discrepancies in natural frequencies ranged from 10.4% to 20.1%. The results demonstrate that the model adequately captures the dynamic behavior of the aircraft and provides a reliable basis for future aeroelastic and flutter analyses of lightweight composite flying wing. Full article