Search Results (539)

The problem of fault-tolerant attitude tracking control for the civil aircraft with model uncertainties and actuator faults is studied. A robust multiple inversion-based incremental nonlinear dynamic inversion (RMI-INDI) fault-tolerant control method is proposed for the problem. Firstly, considering that the higher-order term is neglected in the INDI method, an RMI method is proposed to deal with the higher-order term and model uncertainties of the INDI control. Secondly, to achieve the optimal control parameters for the INDI controller, a reinforcement learning (RL) method is suggested, where a Deep Deterministic Policy Gradient (DDPG) algorithm with a smooth reward function is designed. Finally, performances of the proposed RL-RMI-INDI fault-tolerant controller are demonstrated by using two scenario simulations. Compared with the SMC control, RMI-NDI control and INDI control without RL, tracking errors and overshoots are greatly reduced by the proposed RL-RMI-INDI controller for attitude tracking missions, even under model uncertainties and actuator faults. Full article

To address the issues of safety risk analysis and conflict assessment for integrated flight of manned aircraft and fixed-wing unmanned aerial vehicles (UAVs) in low-altitude mixed-operation airspace, this study enhances the foundational Event model. By incorporating UAV characteristics such as geometric features and aerodynamic mechanisms, alongside design dimensions and onboard performance metrics, an improved collision risk model is developed—the Enhanced Event-Based Framework for Multidimensional Geometry and Quasi-Monte Carlo Analysis of Flight Performance (EMGF-M). This enhancement rectifies the limitations of the basic model regarding parameter coverage and scenario adaptability, thereby improving the reliability and validity of the computational results. Experimental results demonstrate that, in accordance with the target safety level for airspace conflicts set by the International Civil Aviation Organization (ICAO), the application of the improved Event collision model yields quantifiable assessments of safety risks and safe separation distances for integrated operations in low-altitude mixed-use airspace. Utilizing these computational results for integrated flight procedure design at a general airport in Southwest China, the study shows that the air traffic flow in the low-altitude mixed-operation airspace increased from 9.2 to 20.9 operations per hour. The practical significance of this method lies in its guidance for accurately assessing safety risks in mixed airspace operations and for determining quantifiable separation minima for integrated flight trajectory planning. Full article

Side-scan sonar (SSS) serves as the primary perceptual instrument for Autonomous Underwater Vehicles (AUVs) in large-scale marine search and rescue (SAR) operations. However, the detection of critical targets is frequently hindered by severe hydro-acoustic noise, the spatial discontinuity of wreckage, and the weak visual signatures of small targets. To surmount these challenges, this paper presents WPG-DetNet. First, we introduce a Wavelet-Embedded Residual Backbone (WERB) to reconstruct the conventional downsampling paradigm. By substituting standard pooling with the Discrete Wavelet Transform (DWT), this architecture explicitly disentangles high-frequency noise from structural information in the frequency domain, thereby achieving the adaptive preservation of edge fidelity for large human-made targets while filtering out speckle interference. Then, addressing the distinct challenge of discontinuous aircraft wreckage, the framework further incorporates a Debris Graph Reasoning Module (D-GRM). This module models scattered fragments as nodes in a topological graph to capture long-range semantic dependencies, transforming isolated instance recognition into context-aware scene understanding. Finally, to bridge the gap between AI and underwater physics, we design a Shadow-Aided Decoupling Head (SADH) equipped with a physics-informed geometric loss. By enforcing mathematical consistency between target height and acoustic shadow length, this mechanism establishes a rigorous discriminative criterion capable of distinguishing weak-echo human bodies from seabed rocks based on shadow geometry. Experiments on the SCTD dataset demonstrate that WPG-DetNet achieves a mean Average Precision ($mA{P}_{50}$) of 97.5% and a Recall of 96.9%. Quantitative analysis reveals that our framework outperforms the classic Faster R-CNN by a margin of 12.8% in $mA{P}_{50}$ and surpasses the Transformer-based RT-DETR-R18 by 5.6% in high-precision localization metrics ($mA{P}_{50:95}$). Simultaneously, WPG-DetNet maintains superior efficiency with an inference speed of 62.5 FPS and a lightweight parameter count of 16.8 M, striking an optimal balance between robust perception and the real-time constraints of AUV operations. Full article

In aerospace applications, the vibration of aircraft structures results in a reduction in their fatigue life. Vibration-suppression technology utilizing macro fiber composite (MFC) materials constitutes a significant research direction. Aiming at the specific requirements of the MFC actuator operating in the asymmetric high-voltage range of −500 V to 1500 V and the miniaturization of the drive system for aircraft, this study designs a compact self-tuning digital high-voltage controller which adopts a discontinuous conduction mode (DCM) flyback topology as the fundamental model for the switching power supply high-voltage controller, uses the STM32G431 chip as the main controller, and incorporates a Type-II digital compensator designed to enhance the system stability under constant parameters. A Backpropagation (BP) neural network is proposed to enable dynamic adjustment of the digital compensator control parameters, thereby achieving self-tuning, while also supporting program download and real-time data transmission. The high-voltage controller effectively addresses the size and weight constraints in vibration active control systems. Laboratory tests demonstrated its excellent transient response and robust load-driving capability. Vibration-suppression experiments on a high-aspect-ratio UAV wing achieved a 74% vibration attenuation rate, validating the effectiveness of the proposed high-voltage controller. Full article

Electrical power systems have taken on a significant role in aviation, becoming critical to solution plans driven by environmental concerns. Therefore, concepts focusing on energy efficiency and increased dependence on electrical power have gained great popularity. As electrical energy begins to replace traditional hydraulic, mechanical, and pneumatic systems in conventional aircraft, improvements in system design have become inevitable. Optimization studies are conducted to achieve weight reduction, a crucial design parameter for aircraft electrical power systems. A noteworthy target for these efforts is power cables, given their substantial contribution to the overall weight of the system. Reducing the weight of cables between distribution units and loads is related to the Load Allocation Problem (LAP). The solution to the LAP, which involves determining which loads should be powered by which distribution units, results in a significant decrease in cable weight. In this study, a method named Electrical Power System Planning Strategy (E2P2S) was developed to solve the LAP for aircraft electrical power systems, aiming for weight reduction under certain constraints. The developed method was tested using CPLEX 22.1.0 software, and a case study was conducted using the F-16 platform as a reference. The results demonstrate that the impact of weight on aircraft electrical power systems is substantially affected by the optimization, highlighting the importance of this work for future aircraft concepts that will increasingly rely on electrical energy. Full article

Aircraft noise monitoring systems deployed at major airports typically rely on scalar energy-based indicators, which primarily describe integrated sound energy but provide limited representation of the spectral–temporal structure and perceptual attributes of aircraft noise. To address this limitation, this study proposes a sensor-based psychoacoustic feature extraction and spatiotemporal analysis framework for continuous aircraft noise monitoring under high-density operational conditions. An automatic noise monitoring system compliant with ISO 20906 was deployed to synchronously acquire acoustic waveforms and ADS-B trajectory data. A cascaded spatiotemporal fusion algorithm was developed to associate noise events with aircraft flight paths, followed by a model-stratified multidimensional IQR-based data cleaning strategy to suppress environmental interference and non-stationary outliers. Based on the cleaned dataset, a suite of psychoacoustic features—including loudness, sharpness, roughness, fluctuation strength, and tonality—was extracted to characterize the perceptual structure of aircraft noise beyond conventional energy metrics. Experimental results demonstrate that, under equivalent sound exposure levels, psychoacoustic features retain substantial discriminative information that is lost in scalar energy indicators. The coefficients of variation for fluctuation strength and tonality reach 43.2% and 22.1%, respectively, corresponding to 15–69 times higher sensitivity compared to traditional energy-based metrics. Furthermore, nonlinear manifold mapping using UMAP reveals clear topological separation between new-generation and legacy aircraft models in the psychoacoustic feature space, whereas severe overlap persists in energy-based representations. Correlation analysis further indicates decoupling between macro-level physical design parameters (e.g., bypass ratio, thrust) and perceptual feature dimensions, highlighting the limitations of energy-centric monitoring schemes. The proposed framework demonstrates the feasibility of integrating psychoacoustic feature extraction into continuous sensor-based aircraft noise monitoring systems. It provides a scalable signal processing pipeline for enhancing the resolution and interpretability of aircraft noise measurements in complex operational environments. Full article

As a critical core component in the STOVL aircrafts, the dynamic and thermal performance of the aviation dry clutch directly determines the reliability of power transmission and the precision control, especially in high relative speed engagement and high power density conditions. Accordingly, this study proposes a 4-DOF dynamic model considering the time-varying of friction coefficient and nonlinear load characteristics, integrated with a transient thermal model incorporating the time-varying thermal parameters. The effects of pressure loading strategies and rotation speed on the dynamic and transient thermal responses are systematically analyzed. Furthermore, a novel temperature uniformity coefficient is developed to characterize the temperature field distribution. The results indicate that the pressure loading strategy fundamentally dictates the trade-off between engagement smoothness and thermal performance. Specifically, compared with other loading strategies, the linear loading strategy yields the most uniform thermal field ($U_{Tz}=0.4361$, $U_{Tr}=0.3971$) and the engagement smoothness ($J_{er}=2.353\times {10}^5{\mathrm{rad}·\mathrm{s}}^{-3}$) but increases sliding friction work (163.67 kJ). As rotation speed increases from 1500 r/min to 6000 r/min, the sliding friction work increases from 8.85 kJ to 163.67 kJ. Concurrently, the peak values of temperature, axial temperature gradient and axial temperature uniformity coefficient reach 116.557 °C, 80.622 °C and 0.4361, respectively. Consequently, an appropriate reduction in rotation speed combined with the adoption of linear loading strategy can not only facilitate the smoothness and friction loss reduction but also achieve a more uniform temperature distribution. These findings are not only essential for optimizing the thermal management and structural design of aviation dry clutches but also establish a quantitative basis for optimizing engagement strategies. Full article

Supercritical wings are widely used in large aircraft due to their excellent transonic performance, but their aerodynamic characteristics are highly sensitive to Reynolds number. To systematically study the influence of Reynolds number on the aerodynamic characteristics of a supercritical wing, cryogenic high Reynolds number pressure measurement tests were conducted in the European Transonic Wind Tunnel (ETW). A 1:17.87 scale wing-body combination model of a typical supercritical wing was employed. The Reynolds number was increased via the pressure increase and cooling technique, covering a test Reynolds number range from 2.3 × 10⁶ to 3.5 × 10⁷. Model deformation effects were isolated to obtain pressure data reflecting pure Reynolds number effects. The variation patterns of pressure distribution, lift characteristics, and pitching moment characteristics with Reynolds number were analyzed. The results indicate that, at lower speeds (Ma = 0.4 and 0.6), the supercritical wing is less affected by Reynolds number; the upper surface is more significantly influenced by Reynolds number than the lower surface; the Reynolds number effect primarily manifests in the transonic regime by delaying the onset position of the shock wave on the upper wing surface, thereby affecting aerodynamic force characteristics; several aerodynamic characteristic parameters such as ΔC_L, α₀, and C_m exhibit a linear relationship with the logarithm of Reynolds number. Experimental results obtained at low Reynolds numbers cannot be directly extrapolated to actual flight conditions, necessitating the consideration of Reynolds number effect in the aerodynamic design optimization of large aircraft. Full article

Aircraft icing prediction is crucial for aerodynamic design and airworthiness assessment. Traditional physics-based models struggle with complex multi-physical processes, while existing AI methods (function-based characterization or direct image learning) face issues like multi-valued mapping, high data dependency, or lack of physical interpretability. This study proposes a deep learning framework based on point set displacement description, transforming the icing process into airfoil boundary point movements. PCA dimensionality reduction mitigates the curse of dimensionality while retaining physical meaning. A neural network is used to map environmental parameters to low-dimensional principal components. Comparative analysis shows the 64 × 64 network achieves optimal fitting; 2000 samples reproduce complex ice shapes, and 800 low samples characterize simple ones. Balancing efficiency, accuracy, and interpretability with reduced data dependency, this method provides a new approach for rapid engineering icing prediction. Full article

Fast and reliable aerodynamic predictions are crucial in the early phases of aircraft design, where a quick assessment of various configurations is required. In this context, the Vortex Lattice Method (VLM) is widely adopted due to its computational efficiency; however, its predictive accuracy is highly sensitive to panel discretization strategies, which are often determined heuristically. This study proposes a bio-inspired optimization framework for VLM panel discretization and evaluates it through a systematic case study on a representative wing geometry. A grid-convergence analysis was initially carried out to ensure solution independence across various spanwise-to-chordwise panel ratios. Subsequently, a novel Hybrid Response Surface Methodology (HRSM), integrating Box–Behnken and Central Composite experimental designs, was employed to enable a more comprehensive exploration of the factor space while quantifying the effects of clustering parameters at the leading-edge, trailing-edge, root, and tip regions of the wing. The HRSM dataset was further utilized to train Ensemble Machine-Learning surrogate models, which were coupled with bio-inspired Crayfish and Aquila optimization algorithms, alongside a classical Genetic Algorithm (GA) as a performance benchmark, to identify the optimal discretization strategy and to enable a comparative assessment of their convergence behavior and robustness against the numerical noise of the ensemble-based landscape. Compared to base (i.e., uniform) panel distribution, the optimally clustered discretization enhanced overall aerodynamic prediction accuracy by approximately 33%, particularly at low angles of attack, while maintaining robust performance at higher angles. Both algorithms converged to similar minima; however, the Aquila algorithm achieved higher solution consistency, whereas the Crayfish algorithm exhibited greater dispersion despite faster convergence, revealing a multimodal optimization landscape. The variance decomposition revealed that trailing-edge clustering dominated aerodynamic accuracy at low angles of attack, contributing up to 90% of the total variance, whereas tip clustering became increasingly influential at higher angles, exceeding 30%, highlighting the need for adaptive discretization strategies to ensure reliable VLM-based aerodynamic analyses. Full article

With the increasing complexity of the space electromagnetic environment, traditional omnidirectional antenna-aided communication and networking techniques can no longer meet the collaboration requirements of aircraft clusters. To achieve goals such as anti-jamming, anti-interception, and enhanced spatial multiplexing, an increasing number of aircraft are being equipped with high-gain directional antennas. However, modeling of directional antenna-constrained Flying Ad Hoc Networks (FANETs) is far more complex than modeling of omnidirectional antenna-aided networks. The former task is highly dependent on the real-time flight state and the spatial topology of the network. In response to the communication challenges posed by directional networking of highly-dynamic aircraft clusters, this study proposes an antenna selection and beam pointing control algorithm, which is deeply integrated with the aircraft’s Guidance, Navigation, and Control (GNC) system. By introducing parameters that characterize dynamic flight state, such as position and attitude information, and combining them with high-precision multi-coordinate system transformations and spatial geometric analysis methods, the proposed algorithm enables the real-time optimization of antenna selection and beam pointing under the relative motion trends of aircraft. It effectively maintains high-quality connections between flying nodes. Digital simulation and physical experiment results demonstrate that the proposed method can accurately calculate the appropriate antenna selection and determine precise beam pointing directions based on the position data of flying nodes. This provides an important reference for the design of optimized communication strategies used in directional networking of highly-dynamic aircraft clusters. Full article

Aircraft functions under extreme environmental circumstances, encompassing both elevated and diminished temperatures, influence the material characteristics and inflation pressure of aircraft tires. This results in modifications to the tire’s cornering, affecting the shock absorption efficacy of the landing gear and maneuvering stability during cornering. This study examines the cornering characteristics of aircraft tires at four ambient temperatures: −60 °C, −40 °C, 25 °C, and 50 °C. The analysis of stress–strain findings of rubber materials at varying temperatures assessed the impact of ambient temperature on rubber properties. Based on this, a numerical model for tire cornering was constructed using ABAQUS to examine the impact of ambient temperature on the tire’s cornering characteristics. The model considers the intricate friction dynamics between the tire and road surface and the convergence tolerance parameter of ABAQUS. The precision of this model and methodology was confirmed through experimental testing. The findings demonstrate that ambient temperature significantly affects the lateral force and self-aligning torque of aircraft tires, hence impacting cornering stiffness considerably. The influence of radial force and rolling speed on cornering differs with varying ambient temperatures. These results offer significant insights into the design of aircraft tire environmental adaptability and aircraft ground handling systems. Full article

Recently, continuous improvements in aircraft manoeuvrability and fuel consumption reduction have led researchers to investigate additional wing configurations based on morphing concepts. Morphing is also a potential solution for noise level reduction and may therefore represent an additional benefit. The advantages of morph-type schemes over traditional control surfaces during specific manoeuvres become a key parameter in the preliminary design stage. In this work, three types of airfoil morphing applied to a typical basic wing are considered and analysed: leading-edge morphing, trailing-edge morphing, and rib twist. The aerodynamic performance of each configuration is evaluated through a numerical procedure combining a panel method and a vortex lattice method. Drag reduction in morphed versus conventional wings under identical flight conditions is quantified, allowing the identification of the most efficient configuration. The analyses consider both roll manoeuvres and high-lift flight phases by evaluating changes in design parameters—such as chord-wise hinge positions, span-wise morph distribution, and morphing angles—which are compared and discussed. For the rolling manoeuvre, increasing the span-wise morphing region improves drag reduction, but not by more than 5%. When shifting the hinge position from 60% to 80% of the chord, similar drag reduction levels can be achieved, although the required morph angle differs under the same conditions. The effect of different drag components is also assessed, showing that the induced drag component is predominant for low aspect ratio wings, whereas parasite drag becomes significant at higher aspect ratios. Optimal geometrical configurations are presented and discussed for both manoeuvres. For the rolling, hinge positions yielding typical rolling moment coefficients (i.e., −0.05, −0.06, and −0.08) lie between 65% and 75% of the chord, with span-wise morphing ranges 40% < y_rib < 60% producing drag reduction up to 40% compared with a conventional wing. For the high-lift conditions, configurations between 65% < x_hinge < 80% and 50% < y_rib < 90% allow a drag reduction which can go up to 60%. Another beneficial effect is also observed for the yawing moment coefficient C_n with a reduction of more than 20% for larger aileron surfaces. Full article

Vertical takeoff and landing (VTOL) aircraft must balance the conflicting demands of hover and cruise performance. To address the lack of integrated design methodologies in the existing literature, a unified design-optimization framework is presented, coupling high-fidelity CFD simulations with a genetic algorithm to refine a gas-driven thrust fan (GDTF) VTOL nacelle. Key geometric parameters—fan pressure ratio pressure ratio, fan tilt, nozzle angle, tail inclination, and tip shape—were varied in a comprehensive parametric study to maximize lift-to-drag ratio and maintain constant mass flow. The optimization reveals that a nearly horizontal fan axis maximizes cruise efficiency (${\displaystyle \frac{L}{D}}\approx 2.98$), a nozzle angle of about $22°$ offers the best lift-vs-drag compromise during transition, and refining the tip geometry yields a $10$–$20\%$ performance boost. To validate the numerical predictions, a 1:1.05 scale VTOL nacelle model (fan diameter $D = 0.42 \mathrm{m}$) was fabricated and tested in a low-speed wind tunnel at $52 {\displaystyle \frac{\mathrm{m}}{\mathrm{s}}}$ ($Re \approx 5 \times {10}^6$, turbulence intensity ≈ 2%). Total-pressure probes at the intake exit plane and static taps along the inner cowl wall provided detailed pressure distributions, from which exit Mach number, velocity and the equivalent flow coefficient φ (≈0.68 under test conditions) were derived. Oil-flow visualization on the external cowl surface confirmed smooth, attached streamlines with no large separation bubbles. This dual validation combining surface-flow visualization and pressure-recovery mapping demonstrates the accuracy and reliability of the proposed simulation methodology. By successfully bridging detailed CFD with genetic-algorithm-driven design and validating against comprehensive wind-tunnel measurements, this integrated approach paves the way for next-generation VTOL configurations with longer range and lower fuel consumption. Full article

Hypersonic aircraft represent a cutting-edge technology in aerospace engineering, where the shock angle serves as a critical aerodynamic parameter. However, existing studies remain limited by significant prediction errors for the shock angle. This study employs a combination of numerical simulation and wind tunnel test techniques to analyze the shock angle characteristics of hypersonic wide-speed-range cruise aircraft. Consequently, a numerical simulation analysis model for the shock angle of such aircraft was established. Shock angle measurement tests were conducted at various Mach numbers in a pulsed combined high-enthalpy wind tunnel. Comparing the simulation results to the wind tunnel results revealed a numerical error of 4.08%, validating the accuracy of the numerical model. Shock angles at Mach numbers 6, 7, 8, 9, 10, 12, 15 and 20 were analyzed in the numerical simulations, and a nonlinear fitting method was used to determine the functional relationship between the shock angle and Mach number. The results indicate that as the Mach number increases, the shock angle progressively decreases, and its attenuation rate diminishes. The shock angle exhibits an exponentially decreasing relationship with the Mach number, approaching 10.708° as the Mach number approaches infinity. This study provides methodological support and data references for predicting shock wave characteristics and designing aerodynamic hypersonic aircraft. Full article