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Aerospace
Volume 13
Issue 8
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Aerospace, Volume 13, Issue 8 (August 2026) – 92 articles

Cover Story (view full-size image): This paper highlights a laser-based far-field wireless power transfer system developed for UAV recharging. The research presents the architecture and experimental validation of a ground-to-air energy delivery concept combining a high-power laser source with beam pointing and receiver optical sensing. The study focuses on the subsystems that enable stable and accurate beam delivery, including coarse pointing based on global positioning, fine steering based on receiver-side optical feedback, and validation of the communication and sensing chain. The results support the feasibility of persistent UAV operations enabled by contactless energy transfer and provide an experimental basis for future developments in aerial logistics, surveillance, and defense applications. View this paper
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31 pages, 26546 KB  
Article
Collaborative Decision-Making for Departure Pushback and Taxiing to Enhance Airport Surface Efficiency
by Jiyu Tang, Guan Lian, Weizhen Luo, Wenyong Li and Yaping Zhang
Aerospace 2026, 13(8), 752; https://doi.org/10.3390/aerospace13080752 - 21 Aug 2026
Viewed by 247
Abstract
Airport surface scheduling at multi-runway airports is a complex system engineering task that balances efficiency, safety, and sustainability, making it a key research focus in the field of air traffic management. This study proposes a cosine curve-based pushback rate control strategy and a [...] Read more.
Airport surface scheduling at multi-runway airports is a complex system engineering task that balances efficiency, safety, and sustainability, making it a key research focus in the field of air traffic management. This study proposes a cosine curve-based pushback rate control strategy and a collaborative pushback and taxiing decision-making method for departure aircraft pushback and taxiing. Additionally, the Markov decision process under dynamic pushback control at dual-runway airports is analyzed. An adaptive departure operation optimization model is established. This model considers path conflicts, fuel consumption, taxiway queuing, and runway occupancy during an aircraft departure process, enhancing the operational efficiency in the temporal and spatial dimensions. In the aircraft departure process, a genetic simulated annealing algorithm with nested Markov state transitions is proposed as the optimization algorithm, utilizing a Q-learning algorithm to adaptively adjust crossover and mutation parameters. The effectiveness of the proposed model and algorithm is validated through simulation experiments at Beijing Capital International Airport. Results indicate that this approach can significantly reduce the estimated taxiing fuel-related operating cost by 17.53% in the simulated case, shorten average taxiway waiting time by 56.24%, and decrease average taxi completion time by 20.81%, thereby improving overall airport operational efficiency. Full article
(This article belongs to the Section Air Traffic and Transportation)
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30 pages, 3389 KB  
Article
Adaptive Spatial Cooperative Guidance for Impact-Speed Coordination and Two-Phase Inter-Vehicle Separation
by Shuai Yuan, Zhanpeng Gao and Wenjun Yi
Aerospace 2026, 13(8), 751; https://doi.org/10.3390/aerospace13080751 - 21 Aug 2026
Viewed by 185
Abstract
Safe cooperative interception must coordinate arrival, terminal geometry, closing speed, and internal spacing at the same time. This study formulates a spatial cooperative guidance scheme that couples range synchronization, terminal relative-speed regulation, adaptive transverse convergence, and active separation among interceptors. Along the line [...] Read more.
Safe cooperative interception must coordinate arrival, terminal geometry, closing speed, and internal spacing at the same time. This study formulates a spatial cooperative guidance scheme that couples range synchronization, terminal relative-speed regulation, adaptive transverse convergence, and active separation among interceptors. Along the line of sight (LOS), finite-time agreement of range-related states is superposed with a shared closing-speed servo, thereby separating the difference dynamics inside the multi-vehicle system from the mean radial-speed mode. In the two angular channels, the constant reaching gain is replaced with a time-, range-, and error-dependent gain that moderates the initial command peak while preserving terminal LOS-angle convergence. Collision risk is handled in two phases. During the early trajectory-reshaping phase, a smoothed neighbor-repulsion command is projected onto the transverse plane so that the radial speed loop is not perturbed. After the LOS-angle errors enter the assigned band, separated terminal approach directions are used to avoid late trajectory aggregation. Numerical tests show that the scheme removes early overload saturation and increases the minimum spacing while keeping the terminal constraints. In three deterministic cases, the terminal angle errors are on the order of 10−6, the relative impact-speed errors are on the order of 10−3, and the miss distances are approximately 0.8m. Two 200-run Monte Carlo tests with launch-condition perturbations and measurement noise give terminal angle errors on the order of 10−3, relative impact-speed errors around 0.5m/s, and miss distances concentrated near 0.5m. These results indicate that the proposed design improves command smoothness and spacing performance without sacrificing cooperative terminal accuracy under the tested engagement conditions. Full article
(This article belongs to the Special Issue Advanced Navigation, Guidance, and Control for Aerospace Vehicles)
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24 pages, 10840 KB  
Article
Orbital Impulsive Pursuit–Evasion Game in the Cislunar Space
by Xujing Zhang, Shaofeng Li and Youliang Wang
Aerospace 2026, 13(8), 750; https://doi.org/10.3390/aerospace13080750 - 21 Aug 2026
Viewed by 290
Abstract
A pursuer and an evader can exploit low-energy, non-Keplerian trajectories in cislunar space, making it difficult to obtain the saddle point for impulsive orbital pursuit–evasion games (OPEG). To address this problem, this paper first establishes a zero-sum differential game model based on the [...] Read more.
A pursuer and an evader can exploit low-energy, non-Keplerian trajectories in cislunar space, making it difficult to obtain the saddle point for impulsive orbital pursuit–evasion games (OPEG). To address this problem, this paper first establishes a zero-sum differential game model based on the circular restricted three-body problem (CR3BP), where the terminal interception time is taken as the performance objective. The necessary optimality conditions for impulsive maneuvers are then derived using Pontryagin’s Maximum Principle (PMP), which transforms the optimal control problem into multipoint boundary value problems (MPBVPs). Subsequently, to overcome the high sensitivity of the MPBVPs to initial costate vectors in shooting methods, a two-layer hybrid initial-guess strategy combining a genetic algorithm with a time-domain coarse-grid search method is proposed for the single-impulse case. Furthermore, a receding-horizon strategy is introduced to generate the initial impulse sequence guess stage by stage for multiple-impulse cases. Finally, numerical simulations demonstrate that the proposed initial-guess strategy can effectively obtain the Stackelberg equilibrium solution for representative cislunar scenarios, including distant retrograde orbits (DROs) and Halo orbits. Meanwhile, the effects of observation delay and three-dimensional orbital characteristics on the game outcomes are also discussed based on dynamic game theory. Full article
(This article belongs to the Special Issue Spacecraft Trajectory Design)
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18 pages, 4740 KB  
Article
Numerical Investigation of Aerodynamic Interactions in a Twin-Propeller Compound Helicopter
by Yutong Wang, Jiahao Song, Haomiao Xia and Qinchuan Hou
Aerospace 2026, 13(8), 749; https://doi.org/10.3390/aerospace13080749 - 20 Aug 2026
Viewed by 272
Abstract
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 [...] Read more.
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
(This article belongs to the Section Aeronautics)
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28 pages, 4611 KB  
Article
A Robust Attitude Tracking Controller for Spacecraft Based on Singularity-Free Quaternion Nonlinear Dynamic Inversion Framework
by Chang-Te Shen, Ciann-Dong Yang and Yei-Chin Chao
Aerospace 2026, 13(8), 748; https://doi.org/10.3390/aerospace13080748 - 20 Aug 2026
Viewed by 277
Abstract
This paper presents a robust attitude-tracking control architecture for rigid spacecraft subject to model mismatches and external disturbances. Quaternions are utilized for attitude representation to prevent the gimbal lock associated with Euler angles. While conventional nonlinear dynamic inversion (NDI) relies on Newtonian mechanics [...] Read more.
This paper presents a robust attitude-tracking control architecture for rigid spacecraft subject to model mismatches and external disturbances. Quaternions are utilized for attitude representation to prevent the gimbal lock associated with Euler angles. While conventional nonlinear dynamic inversion (NDI) relies on Newtonian mechanics and input–output linearization—which inadvertently generates internal zero dynamics and encounters severe control derivative discontinuities at the q0=0 singularity—this study proposes a novel NDI framework derived strictly from Udwadia’s Lagrangian formulation. This approach realizes an exact input-state linearization directly on the 6-degree-of-freedom active holonomic constraint manifold, completely eliminating internal zero dynamics and mathematical singularities. To ensure robustness against physical uncertainties, the singularity-free NDI is augmented with a nonlinear disturbance observer (DOBC) and an outer-loop linear quadratic (LQ) tracking controller. A rigorous composite Lyapunov stability analysis is conducted for the complete closed-loop architecture. The analysis formally guarantees that both the isolated disturbance estimation error and the fully interconnected dual-loop NDI-DOBC system are Uniformly Ultimately Bounded (UUB), even in the presence of realistic, time-varying disturbances with non-vanishing derivatives (d˙≠0). Comprehensive numerical simulations, parameterized by a physical spherical air-bearing testbed subject to state-dependent gravitational imbalance torques, validate the architecture’s exceptional tracking precision, smooth transient response, and robust disturbance rejection. Full article
(This article belongs to the Section Astronautics & Space Science)
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30 pages, 5635 KB  
Article
Task-Based Machine Learning Model for Terminal Air Traffic Complexity Prediction
by Tea Jurinić, Biljana Juričić, Dominik Jurinić and Antonio Šajatović
Aerospace 2026, 13(8), 747; https://doi.org/10.3390/aerospace13080747 - 20 Aug 2026
Viewed by 227
Abstract
Air traffic complexity is the degree of difficulty in monitoring and managing a specific air traffic situation, and it is one of the main drivers of Air Traffic Controller (ATCO) workload. Previously developed terminal air traffic complexity models and methods require significant adjustment [...] Read more.
Air traffic complexity is the degree of difficulty in monitoring and managing a specific air traffic situation, and it is one of the main drivers of Air Traffic Controller (ATCO) workload. Previously developed terminal air traffic complexity models and methods require significant adjustment or additional data to be applied to unseen airspaces, or to be compared with ATCOs’ complexity perception. To address this gap, a terminal air traffic complexity model based on approach ATCO tasks was developed. Building on previous work, approach ATCO tasks were quantified and used as input features. A new dataset consisting of three different terminal airspaces, each containing a different number of situations, was created. Certified approach ATCOs evaluated the complexity of each situation on a scale of 1 to 5, and these values were used as ground truth for training ordinal regression models. One linear and one non-linear model were trained and evaluated, and both were tested on an airspace unseen during training. The two models achieved strong performance on the tested airspace with Quadratic Weighted Kappa (QWK) values of 0.814 and 0.873, confirming that the proposed task features can predict the complexity of a new, unseen airspace. Full article
(This article belongs to the Special Issue AI-Driven Innovations in Air Traffic Management and Aviation Safety)
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23 pages, 3472 KB  
Article
A PRTOS-Based Partitioned Runtime Architecture for Integrated Avionics of Near-Space Airships: Multicore Porting and Fault-Containment Validation
by Yong Hao, Zhaojie Li, Yanchu Yang, Jianghua Zhou and Baocheng Wang
Aerospace 2026, 13(8), 746; https://doi.org/10.3390/aerospace13080746 - 20 Aug 2026
Viewed by 268
Abstract
Integrated avionics for near-space airships increasingly consolidate multiple functions on shared multicore platforms, creating risks of cross-functional interference and fault propagation. This study develops a multicore static-partitioning architecture based on the PRTOS Type-1 hypervisor and implements static mappings among four Linux guest partitions, [...] Read more.
Integrated avionics for near-space airships increasingly consolidate multiple functions on shared multicore platforms, creating risks of cross-functional interference and fault propagation. This study develops a multicore static-partitioning architecture based on the PRTOS Type-1 hypervisor and implements static mappings among four Linux guest partitions, processor cores, independent memory regions, and devices on an Intel Atom x6425RE platform. Fault-free baseline, partition-local computational overload, 16 MiB cyclic memory access, inter-partition communication, and native-Linux multicore-propagation experiments evaluate response time, deadline misses, and communication completeness. Under PRTOS, increasing pressure causes deadline misses in the faulty partition, while the other partitions retain zero misses. Severe pressure reduces communication completeness of the faulty partition but produces no integrity error or residual backlog on the other channels. Under native Linux, one functional anomaly expands to multiple cores and causes deadline misses in all tasks. PRTOS static partitioning therefore bounds the propagation of local faults and provides an engineering basis for isolated deployment of integrated airship–avionics functions. Full article
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20 pages, 19044 KB  
Article
VFD-YOLO: A Novel Method for Vehicle Detection from a Drone Perspective
by Zongnan Liu, Yong Xu, Haoyi Xie and Zepeng He
Aerospace 2026, 13(8), 745; https://doi.org/10.3390/aerospace13080745 - 20 Aug 2026
Viewed by 260
Abstract
Vehicle detection using drone-based imagery holds significant practical value in applications such as intelligent traffic management, urban situational awareness, and emergency response coordination. It is among the core technologies for achieving coordinated air–ground intelligent monitoring. However, when viewed from the high-altitude perspective of [...] Read more.
Vehicle detection using drone-based imagery holds significant practical value in applications such as intelligent traffic management, urban situational awareness, and emergency response coordination. It is among the core technologies for achieving coordinated air–ground intelligent monitoring. However, when viewed from the high-altitude perspective of a drone, vehicle images suffer from issues such as complex backgrounds, blurriness, and low light, severely limiting the accuracy of model detection. Therefore, we propose a vehicle detection model for unmanned aerial vehicles based on YOLOv13 (VFD-YOLO). First, to address the issues of blurriness and low illumination in drone images, we designed a convolutional structure VFD-C3k2 specifically for vehicle feature extraction. It is a multi-scale feature-embedding structure based on the existing HLFD structure. We decomposed the vehicle image features into high-frequency details such as edges and textures, as well as low-frequency structural information such as global contours. Through differentiated processing, we enhanced the image restoration and detail extraction capabilities, and improved the adaptability of the model to different types of images. Afterward, to address the strong background interference from vehicle targets in drone imagery, we employed the CASAB channel and spatial attention module. This module enhances the weights of key vehicle feature channels through channel attention, focuses on the target area of the vehicle through spatial attention, effectively suppresses background noise, and strengthens the model’s ability to focus on and extract significant target features. The experimental results show that on the DroneVehicle dataset, the precision, recall rate, mAP@0.5 and mAP@0.5:0.95 of our proposed VFD-YOLO model reach 75.0%, 75.6%, 79%, and 54.7%, respectively, which represent improvements of 1.6%, 1.9%, 1.7%, and 2.4% compared with those of the baseline YOLOv13 model. In summary, the model we propose exhibits superior detection performance and can better meet the needs of practical scenarios such as intelligent transportation and urban surveillance. Full article
(This article belongs to the Section Aeronautics)
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40 pages, 8615 KB  
Article
From Sim to 6DOF: Deep Learning for Real-Time Satellite Pose Estimation from Resolved Ground-Based Imagery
by Thomas Dickinson, Dawson Friesenhahn, Justin Fletcher, Derek Walvoord, Dennis Montera and Michael Gartley
Aerospace 2026, 13(8), 744; https://doi.org/10.3390/aerospace13080744 - 19 Aug 2026
Viewed by 332
Abstract
This work presents the first complete system for automated six degrees of freedom (6DOF) satellite pose estimation from spatially resolved, ground-based, adaptive optics (AO)-corrected imagery, addressing a key challenge in Space Domain Awareness (SDA). The approach mitigates the need for human labeling by [...] Read more.
This work presents the first complete system for automated six degrees of freedom (6DOF) satellite pose estimation from spatially resolved, ground-based, adaptive optics (AO)-corrected imagery, addressing a key challenge in Space Domain Awareness (SDA). The approach mitigates the need for human labeling by directly regressing satellite orientation and position from blurry, noisy, and deeply shadowed imagery. A multi-stage deep neural network pipeline localizes the satellite, predicts pose, and optionally applies temporal filtering. Networks are trained exclusively on fully synthetic imagery generated from a CAD model, yet generalize effectively to real data, bridging the Sim2Real domain gap. On 137 real, human-labeled test images of Seasat, the model achieved a mean rotation error of 5° and a mean image-plane translation error of 21 cm. Slant range error was quantitatively evaluated on synthetic data due to unknown real-sensor parameters. Qualitative evaluation of additional real Seasat imagery rated 177 of 199 predicted poses as “ground truth equivalent” or “high-confidence match,” with zero catastrophic failures. The system was extended to seven degrees of freedom (7DOF) for satellites with articulating components and demonstrated on real Hubble Space Telescope (HST) imagery, achieving 5.5° rotation error, 51 cm image-plane translation error, and 8° symmetry-adjusted solar array error on a 249-frame pass with causal temporal filtering. Across 586 real test images from Seasat and HST (captured over multiple decades under diverse conditions) the system consistently performed well. Full 6DOF performance was quantified on a high-fidelity wave optics (HFWO) synthetic test set of Seasat, where the model achieved 8.4° mean rotation error, 34 cm image-plane translation error, and 1.4% line-of-sight range error at r0=6 cm and 1031 km range. In a limited 200-image benchmark, the model demonstrated 48% lower mean rotation error than a single human labeler while operating ∼800× faster. It required <40 h and a single A100 GPU to generate data and train. The approach was also demonstrated for ARGOS, a smaller satellite with highly symmetric geometry. An exploratory General Image-Quality Equation-based image quality metric (AO-IQ) was introduced as an empirical correlate for pose accuracy. General-purpose models like GPT-4o and Depth Anything V2 failed across most SDA tasks, but rapid gains in vision-language models warrant continued monitoring. These results establish a new operational baseline for practical, real-time satellite pose estimation from AO SDA imagery. Full article
(This article belongs to the Section Astronautics & Space Science)
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31 pages, 11325 KB  
Article
Fuel-Supply Pressure Regulation in a Helicopter Fuel System Using a Constant-Pressure Reducing Valve
by Yecheng Nie, Xiaodong Mao, Weihua Wang, Xianze Meng and Pengyu Li
Aerospace 2026, 13(8), 743; https://doi.org/10.3390/aerospace13080743 - 19 Aug 2026
Viewed by 307
Abstract
Engine-inlet fuel pressure in helicopters can fluctuate during flight manoeuvres because load-factor variation changes both fuel distribution in the tanks and the pressure balance along the fuel-supply pipeline. This simulation-only study investigates a passive pressure-regulation scheme based on a constant-pressure reducing valve (CPRV) [...] Read more.
Engine-inlet fuel pressure in helicopters can fluctuate during flight manoeuvres because load-factor variation changes both fuel distribution in the tanks and the pressure balance along the fuel-supply pipeline. This simulation-only study investigates a passive pressure-regulation scheme based on a constant-pressure reducing valve (CPRV) for a representative five-tank helicopter fuel system. Mathematical models of the fuel tank, booster pump, jet pump, check valve, fuel-supply pipeline, and CPRV are integrated in AMESim and checked against reported tank-depletion data, fuel-centre-of-gravity data, and code-to-code benchmark results. A controlled same-model isolation check additionally compares a mobile CPRV spool with the same spool constrained at its fully open end stop while all pump, tank, line, demand, load, fluid, reference-pressure, and solver settings remain unchanged. In a longitudinal load-factor ramp to 1 g, the mobile-spool model maintains 1.8042–1.8047 barA, whereas the locked-open control gives 2.4287–2.5917 barA. Across the principal regulated simulations, the maximum absolute deviation from the 1.8 barA target is approximately 0.005 bar. These values are numerical results for the stated model and must not be interpreted as sensor-resolvable hardware accuracy or qualification evidence. Full article
(This article belongs to the Section Aeronautics)
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21 pages, 1188 KB  
Article
Robust Time-Varying Pinning Cooperative Control for Heterogeneous Air-Ground System with Switching Topologies and Uncertain Communication Links
by Jianchao Zhang, Zeng Zhao and Deyuan Liu
Aerospace 2026, 13(8), 742; https://doi.org/10.3390/aerospace13080742 - 19 Aug 2026
Viewed by 297
Abstract
In this paper, a special air-ground system consisting of multiple tail-sitters and ground vehicles are constructed under switching topologies and uncertain communication links. For the air-ground system, the ground vehicles serve as the take-off and landing platforms for the tail-sitters. A robust time-varying [...] Read more.
In this paper, a special air-ground system consisting of multiple tail-sitters and ground vehicles are constructed under switching topologies and uncertain communication links. For the air-ground system, the ground vehicles serve as the take-off and landing platforms for the tail-sitters. A robust time-varying pinning coordinated controller is developed for the heterogeneous system. The effects of parameter/link uncertainties and external disturbances are effectively attenuated via the devised control law. The robust performance of the air-ground cooperative control system with switching topologies is rigorously validated with the Lyapunov stability criterion. The steady-state tracking deviations satisfy uniform ultimate boundedness and converge within an infinitesimal region around the origin. Simulation tests are carried out to verify that the developed control scheme achieves satisfactory coordination under time-varying cases, with tracking deviations noticeably lower in comparison with conventional control schemes. Full article
(This article belongs to the Special Issue New Sights of Intelligent Robust Control in Aerospace)
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26 pages, 5211 KB  
Article
A High-Precision Adaptive Sequential Convex Programming Method for Non-Coplanar Transfer Trajectory Optimization in Constellation Aggregation
by Zihui Ma, Rong Chen and Yuzhu Bai
Aerospace 2026, 13(8), 741; https://doi.org/10.3390/aerospace13080741 - 19 Aug 2026
Viewed by 261
Abstract
With the development of constellations and satellite chains, trajectory planning for constellation satellites has gradually attracted research attention. To address the infeasibility issues of trapezoidal sequential convex programming (T-SCP) in this strong non-convexity problem, this paper proposes high-precision adaptive SCP based on the [...] Read more.
With the development of constellations and satellite chains, trajectory planning for constellation satellites has gradually attracted research attention. To address the infeasibility issues of trapezoidal sequential convex programming (T-SCP) in this strong non-convexity problem, this paper proposes high-precision adaptive SCP based on the Hermite Simpson method for Low-Earth-Orbit (LEO) constellation aggregation and aimed at enhanced local reconnaissance with practical constraints, including collision avoidance. The method introduces an adaptive trust region and slack variables, which avoid convergence failures due to strong nonlinearity or large state variations over long distances and accelerate the convergence rate. Furthermore, a third-order accurate Hermite Simpson method is adopted along with a adaptive iterative collision warning mechanism, improving accuracy while reducing computational cost. Simulation results demonstrate that the proposed method improves computational efficiency by 6% and 21% compared with the T-SCP and pseudospectral method, respectively. When the number of discrete nodes is 50, it achieves position errors of 284.7 m and velocity errors of 0.33 m/s, and these errors are far lower than those of T-SCP. Monte Carlo simulations across 10,000 scenarios validate the robustness of the proposed method with a 91% overall success rate and 100% for LEO. Full article
(This article belongs to the Section Astronautics & Space Science)
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27 pages, 3720 KB  
Article
Starlink Orbit Anomaly Detection with Wavelet-Kalman Filtering and Compensated Propagation
by Jiran Wei, Fan Yang and Desheng Liu
Aerospace 2026, 13(8), 740; https://doi.org/10.3390/aerospace13080740 - 19 Aug 2026
Viewed by 286
Abstract
The rapid deployment of low-Earth-orbit mega-constellations has increased the demand for reliable and scalable orbit-anomaly monitoring. Existing methods are vulnerable to heavy-tailed measurement errors, maneuver-induced propagation drift, and the anisotropic uncertainty of short observation arcs. This study proposes an uncertainty-aware Starlink monitoring framework [...] Read more.
The rapid deployment of low-Earth-orbit mega-constellations has increased the demand for reliable and scalable orbit-anomaly monitoring. Existing methods are vulnerable to heavy-tailed measurement errors, maneuver-induced propagation drift, and the anisotropic uncertainty of short observation arcs. This study proposes an uncertainty-aware Starlink monitoring framework that combines residual-domain wavelet shrinkage with a Huber-weighted adaptive two-body extended Kalman filter to suppress non-Gaussian contamination without obscuring abrupt state changes. A linear altitude correction and a quadratic phase-time correction are introduced into Simplified General Perturbations-4 propagation to compensate for maneuver-related forecast drift. A cross-time covariance model and a joint normalized innovation squared test are further constructed for uncertainty-aware short-arc maneuver sensing, while hierarchical evidence fusion supports anomaly detection and event interpretation. Across paired experiments, the filtering chain reduces position root-mean-square error from 752.4 ± 77.7 m to 175.9 ± 9.9 m, and compensated propagation reduces the 72 h prediction error from 128.7 km to 19.6 km. The detector achieves 93.4% accuracy with a 2.7% false-alarm rate and maintains empirical short-arc false-alarm probabilities near the nominal one percent level. These results demonstrate a consistent engineering link between catalog-scale screening and uncertainty-aware short-arc maneuver sensing. Full article
(This article belongs to the Special Issue Advances in Space Surveillance and Tracking)
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28 pages, 5754 KB  
Article
Exploring a Non-Invasive Fatigue Assessment Framework for Remote Tower Scenarios: A Simulation Study
by Qingwei Zhong, Mingsiyu Pan, Xu Yan, Weijun Pan and Yingxue Yu
Aerospace 2026, 13(8), 739; https://doi.org/10.3390/aerospace13080739 - 19 Aug 2026
Viewed by 257
Abstract
Accurately assessing the fatigue levels of air traffic controllers is crucial for reducing human errors in ATC and ensuring the safe and orderly operation of the civil aviation transportation system. In remote tower scenarios, air traffic controllers’ work environments and task interaction modes [...] Read more.
Accurately assessing the fatigue levels of air traffic controllers is crucial for reducing human errors in ATC and ensuring the safe and orderly operation of the civil aviation transportation system. In remote tower scenarios, air traffic controllers’ work environments and task interaction modes differ significantly from those in traditional towers, and traditional fatigue detection approaches relying on physiological monitoring can cause intrusive disruptions to ATC operations. To overcome these limitations, this study proposes a scenario-based, non-invasive assessment framework for accurate and low-interference fatigue recognition. Taking three key scenario elements (traffic load, main operation screen brightness, and core work area illuminance) as the basis for measuring fatigue, the framework bridges the mapping from scenario elements to fatigue status, thereby enabling the transition of assessment inputs from physiological metrics to scenario features. In this mapping, fatigue labels are determined using a fusion strategy. Specifically, objective fatigue labels are derived from optimal wave features extracted from electroencephalogram data using one-way analysis of variance (OW-ANOVA), which are then fused with subjective labels based on the Karolinska Sleepiness Scale (KSS) self-reports through fuzzy C-means (FCM) clustering. Ultimately, a hybrid intelligent classification model integrating the Gannet optimization algorithm (GOA) and random forest (RF) is constructed to perform the primary assessment task. The experimental results indicate that the proposed framework achieves a recognition accuracy of 95.00%, outperforming six other commonly used classification or combination models. Ablation experiments and robustness tests validate the effectiveness of the fused labeling strategy and GOA modules, as well as the method’s excellent stability in resisting data noise. Furthermore, feature interpretability analysis reveals the quantitative influence of the three core fatigue drivers used. The research findings confirm the feasibility of non-invasive fatigue assessment for remote tower controllers leveraging scenario-based elements, which can offer intelligent decision support for controller shift scheduling, visual environment optimization, and targeted safety interventions. Full article
(This article belongs to the Section Air Traffic and Transportation)
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20 pages, 14138 KB  
Article
Energy-Efficient Anti-Icing and De-Icing of TC4 Titanium Alloy Surfaces Enabled by Laser-Patterned Microstructures and Electrothermal Heating
by Jun Rao, Hua Liang, Biao Wei, Zhi Su, Hongrui Liu and Xin Zhou
Aerospace 2026, 13(8), 738; https://doi.org/10.3390/aerospace13080738 - 19 Aug 2026
Viewed by 240
Abstract
Surface icing poses a significant risk to unmanned aerial vehicles (UAVs) and compact aerospace platforms, where limited onboard power and space require efficient anti-/de-icing surfaces. In this study, micro/nanostructures were fabricated on TC4 titanium alloy (Ti–6Al–4V) surfaces by femtosecond laser processing at different [...] Read more.
Surface icing poses a significant risk to unmanned aerial vehicles (UAVs) and compact aerospace platforms, where limited onboard power and space require efficient anti-/de-icing surfaces. In this study, micro/nanostructures were fabricated on TC4 titanium alloy (Ti–6Al–4V) surfaces by femtosecond laser processing at different scanning speeds. The effects of scanning speed on surface morphology, wettability, static freezing, dynamic droplet behavior, and electrothermal de-icing performance were systematically investigated. Increasing the scanning speed induced nonlinear changes in microstructure height and surface roughness, while variations in ablation intensity caused nonuniform material redistribution. The surface processed at 250 mm/s showed the best anti-icing performance, with a water contact angle of 157.5 ± 0.5° and a maximum freezing delay 21.5 times longer than untreated TC4. During electrothermal de-icing, melting initiated at discrete ice–substrate contact points, forming coalesced meltwater films, while interfacial stress concentration promoted crack propagation and rapid ice detachment. Compared with untreated surfaces, ice detachment time (250 mm/s) achieved complete ice detachment at approximately 152 s, whereas ice on the untreated surface remained adhered after 270 s of continuous heating, representing a de-icing time reduction of at least 44%. These results demonstrate that combining laser-fabricated microstructures with electrothermal heating effectively reduces real ice–substrate contact, providing an enhanced anti-/de-icing strategy for lightweight, long-endurance UAV applications under identical electrical input. Full article
(This article belongs to the Section Aeronautics)
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25 pages, 3850 KB  
Article
Robust Reinforcement Learning-Based Guidance Strategy Against Cyber-Attacks
by Yuting Shang and Yuanli Cai
Aerospace 2026, 13(8), 737; https://doi.org/10.3390/aerospace13080737 - 19 Aug 2026
Viewed by 286
Abstract
As electronic countermeasure techniques become increasingly sophisticated, missiles that rely on ground-based systems to generate and transmit guidance commands face the risk of cyber-attacks. Most existing guidance strategies do not account for such attacks, resulting in significant degradation of guidance performance once attacks [...] Read more.
As electronic countermeasure techniques become increasingly sophisticated, missiles that rely on ground-based systems to generate and transmit guidance commands face the risk of cyber-attacks. Most existing guidance strategies do not account for such attacks, resulting in significant degradation of guidance performance once attacks occur. To address this issue, this paper proposes a robust reinforcement learning-based guidance strategy that incorporates cyber-attack factors. First, the kinematic and relative-motion models for the missile-maneuvering target engagement are established, and typical cyber-attack scenarios are analyzed. Based on these models, a robust Markov decision process incorporating cyber-attack effects is formulated, providing a theoretical framework for applying robust reinforcement learning to guidance problems. Within this framework, a robust reinforcement learning-based guidance strategy with a robust Actor–robust Critic architecture is developed. Specifically, the robust Critic updates its parameters by minimizing the mean-squared robust temporal-difference error. Meanwhile, the robust Actor updates the policy using the clipped objective of robust Proximal Policy Optimization. Together, these updates improve the robustness of the guidance policy under cyber-attacks. Extensive simulation results demonstrate that the proposed guidance strategy successfully intercepts maneuvering targets under diverse attack conditions, validating its robustness and guidance effectiveness under cyber-attacks. Full article
(This article belongs to the Special Issue New Perspective on Flight Guidance, Control and Dynamics)
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27 pages, 1633 KB  
Article
AI-Driven Semantic Processing of Notices to Air Missions for Aeronautical Information Management: Ontology-Grounded Type-Aware Extraction
by Tianyue Wei, Xin Lai, Chengwei Zhang and Yidan Liang
Aerospace 2026, 13(8), 736; https://doi.org/10.3390/aerospace13080736 - 18 Aug 2026
Viewed by 298
Abstract
Timely and accurate interpretation of Notices to Air Missions (NOTAMs) is essential for effective aeronautical information management (AIM). Although NOTAMs follow a standardized format, their abbreviated textual content and heterogeneous operational semantics make automated processing difficult. Existing methods often address type classification, information [...] Read more.
Timely and accurate interpretation of Notices to Air Missions (NOTAMs) is essential for effective aeronautical information management (AIM). Although NOTAMs follow a standardized format, their abbreviated textual content and heterogeneous operational semantics make automated processing difficult. Existing methods often address type classification, information extraction, and semantic representation independently, leaving a gap between textual interpretation and ontology-grounded information management. To address this gap, this paper presents NOTE, an AI-driven ontology-grounded type-aware extraction framework for NOTAMs. NOTE is supported by a dynamic semantic ontology that combines a shared semantic module with seven type-specific sub-ontologies. Guided by the predicted semantic type, the framework activates the corresponding ontology-aligned schema contract, extracts and validates the relevant information, and materializes the result as Resource Description Framework (RDF) triples. Experiments on 25,341 operational NOTAMs and a manually curated ontology-mapping set produced a macro-F1 of 0.9424 for type-aware routing and an F1 of 0.9053 for structured extraction, with a schema conformance rate of 0.9976. The dynamic ontology achieved slot- and relation-level F1 scores of 0.9472 and 0.9835, respectively. Compared with a scale-matched static ontology, type-specific activation improved relation mapping by 13.06 percentage points while producing semantic richness close to the human-annotated reference. These findings indicate that NOTE provides an effective connection between abbreviated NOTAM text and validated ontology-grounded representations for AIM. Full article
(This article belongs to the Special Issue AI-Driven Innovations in Air Traffic Management and Aviation Safety)
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26 pages, 8277 KB  
Article
Correcting SLD Icing Parameters: A Ridge Regression Method Fusing Icing Wind Tunnel Data and Numerical Priors
by Ning Guan, Weijian Chen, Xiang Gao and Tao Wei
Aerospace 2026, 13(8), 735; https://doi.org/10.3390/aerospace13080735 - 18 Aug 2026
Viewed by 173
Abstract
To explore the significant systematic deviations of FENSAP-ICE numerical simulations under supercooled large droplet (SLD) conditions, a ridge regression correction method that integrates numerical priors and domain-knowledge-aided features for ice shape geometric parameters is presented in this manuscript. The FENSAP-ICE predictions of eight [...] Read more.
To explore the significant systematic deviations of FENSAP-ICE numerical simulations under supercooled large droplet (SLD) conditions, a ridge regression correction method that integrates numerical priors and domain-knowledge-aided features for ice shape geometric parameters is presented in this manuscript. The FENSAP-ICE predictions of eight geometric ice shape parameters are incorporated as numerical priors into the machine learning model, transforming the learning objective from “predicting from scratch” to “correcting systematic bias.” Six engineering auxiliary features are constructed based on SLD icing physics to provide physically meaningful adjustable dimensions for small-sample modeling. A two-stage model combining Logistic Regression classification and Ridge Regression is designed for zero-ice cases on the lower-surface icing limit. Evaluated via Leave-One-Out Cross-Validation on 29 sets of NACA0012 airfoil SLD icing wind tunnel experimental data, the improved system reduces the sMAPE of total ice area from 79.47% to 34.65%, lower-surface ice horn angle from 105.19% to 28.08%, upper-surface icing limit from 61.75% to 35.48%, and average ice thickness from 42.12% to 20.89%, all compared with FENSAP-ICE predictions. Ablation experiments further reveal that the introduction of the numerical prior alone reduces prediction error by approximately 10 percentage points, serving as the primary performance driver. The proposed method features low computational cost and strong physical consistency, providing a practical bias-correction framework for SLD ice shape prediction under small-sample conditions. Furthermore, to address the potential optimistic bias arising from small-sample cross-validation, nested cross-validation together with multiple linear baseline models are additionally employed to verify the robustness and relative competitiveness of the proposed correction method. Full article
(This article belongs to the Section Aeronautics)
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32 pages, 12155 KB  
Article
Multi-Feature Fusion Based Adaptive Surge Detection Method for Aero-Engine Compressors
by Zhenyu Sun, Heli Yang and Xinqian Zheng
Aerospace 2026, 13(8), 734; https://doi.org/10.3390/aerospace13080734 - 18 Aug 2026
Viewed by 191
Abstract
Compressor surge poses a critical safety risk for aero-engines. However, conventional physics-driven detection methods—relying on single-domain features and fixed empirical thresholds—struggle to adapt across varying compressor configurations, wide operating ranges, and complex interference environments. This paper proposes a multi-feature fusion adaptive surge detection [...] Read more.
Compressor surge poses a critical safety risk for aero-engines. However, conventional physics-driven detection methods—relying on single-domain features and fixed empirical thresholds—struggle to adapt across varying compressor configurations, wide operating ranges, and complex interference environments. This paper proposes a multi-feature fusion adaptive surge detection method that integrates time-domain amplitude, frequency-weighted power and slope features within a joint threshold criteria, enabling reliable and adaptive surge detection according to the statistical characteristics of the signal itself. A wavelet-based preprocessing strategy is established with the db4 wavelet and four-level decomposition identified as the optimal setting through systematic evaluation. A novel feature FWP is introduced herein, which applies frequency-dependent weighting to the power spectral density to suppress noise components while amplifying energy changes within surge-relevant bands, achieving 1.7 to 6.1 times greater magnitude variation near the surge point compared with total spectral power. The slope feature is further discovered to distinguish surge from transient interferences such as rapid valve throttling, fuel stepping and rapid acceleration. Among 100 samples, the three-feature joint detection strategy integrated with adaptive threshold criteria improves accuracy from 61% to 98%. A Bayesian optimization framework using Gaussian process surrogate models is developed for efficient cross-engine hyperparameter tuning, converging to optimal solutions within merely 11 to 13 iterations across two distinct compressors. Lastly, the method is implemented on an NI cRIO-based real-time platform and validated on two distinct ten-stage high-pressure compressors, covering surge tests across a wide speed range of 45% to 98%. Comparative tests against an industry-standard reference device demonstrate earlier warning lead times of 41 to 99 ms. The results confirm that the proposed method herein achieves high accuracy, strong robustness against operational interferences, and good cross-platform adaptability for practical application. Full article
(This article belongs to the Section Aeronautics)
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29 pages, 5228 KB  
Article
Friction-Induced Vibration Analysis of an Aircraft Electric Braking System Considering the Transmission Mechanism
by Xiaohang Hu, Ming Zhang, Bo Lei, Yapan Zhao and Xiangxi Li
Aerospace 2026, 13(8), 733; https://doi.org/10.3390/aerospace13080733 - 18 Aug 2026
Viewed by 192
Abstract
Friction-induced unstable vibration caused by nonlinear stator–rotor friction and electromechanical coupling is a critical dynamic stability issue in aircraft electric braking systems, potentially degrading braking performance and operational safety. In this study, a novel nonlinear dynamic model of an aircraft electric braking system [...] Read more.
Friction-induced unstable vibration caused by nonlinear stator–rotor friction and electromechanical coupling is a critical dynamic stability issue in aircraft electric braking systems, potentially degrading braking performance and operational safety. In this study, a novel nonlinear dynamic model of an aircraft electric braking system is developed by considering nonlinear stator–rotor friction, the nonlinear meshing force of the gear pair, and the nonlinear axial contact stiffness of the ball screw pair. The effects of braking conditions, negative friction–velocity slope, and transmission mechanism parameters on the stability and global nonlinear dynamic behavior of the system are systematically investigated. The results indicate that the negative friction–velocity slope has a critical influence on system stability. Reducing its magnitude simplifies the steady-state response and improves system stability, while the corresponding instability boundary depends on the braking conditions and system parameters. In addition, increasing the screw lead reduces the vibration intensity and simplifies the vibration modes of the system. The time-varying meshing stiffness and backlash of the transmission mechanism significantly affect the impact response and vibration intensity of the transmission mechanism, but have little influence on the vibration response of the disc brake. These findings provide theoretical guidance for vibration suppression, stability-oriented design, and parameter optimization of aircraft electric braking systems. Full article
(This article belongs to the Section Aeronautics)
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27 pages, 799 KB  
Review
Wheels-Up Landing and Its Relevance to Novel Aircraft
by Jessica Wallace, Damian Quinn, Declan Nolan, Jillian Gaskell and Evan Lawson
Aerospace 2026, 13(8), 732; https://doi.org/10.3390/aerospace13080732 - 18 Aug 2026
Viewed by 387
Abstract
The National Transport Safety Board found that Wheels-Up Landing was the second highest defining event for aircraft accidents from 2008 to 2022. The increasing push for sustainable propulsion and accompanying novel airframe architectures present new integration and safety challenges for aircraft design and [...] Read more.
The National Transport Safety Board found that Wheels-Up Landing was the second highest defining event for aircraft accidents from 2008 to 2022. The increasing push for sustainable propulsion and accompanying novel airframe architectures present new integration and safety challenges for aircraft design and development, among which is the structural integrity and crashworthiness of the aircraft under such extreme events. This paper examines the regulations and design requirements governing aircraft emergency Wheels-Up Landing scenarios, emphasising their implications for aircraft safety and structural integrity. It consolidates standards from aviation authorities, such as the FAA and EASA, which identify and define key requirements relating to occupant safety and fire prevention and protection during such events. The paper then considers the Wheels-Up Landing scenario and its design requirements within the context of future novel aircraft employing sustainable propulsion systems, from higher bypass turbofan to electric- and hydrogen-based technologies. The unique characteristics and challenges of these emerging propulsion technologies are described, highlighting how alternative structural configurations, weight distributions and powerplant architectures may influence the aircraft response under a Wheels-Up Landing event. Finally, an exploration of predictive modelling strategies and methods currently used in Wheels-Up Landing analysis was conducted. While reviewing the breadth of accurate, high-fidelity modelling methods targeting fuselage impact, it also highlighted the gap in both considering the increasingly relevant and frequent powerplant impact scenarios, and the provision of lightweight modelling approaches necessary to rapidly and adequately address the emergency Wheels-Up Landing response early in the aircraft design process. Full article
(This article belongs to the Special Issue Overall Aircraft Design for New Airframe Technologies, New Energy Systems, and New Operations—2nd Edition)
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22 pages, 4263 KB  
Article
Parallel Reconfiguration Planning for Modular Self-Reconfigurable Satellites via Multi-Agent Reinforcement Learning
by Bo Wang, Shilong Li, Jialin Yu, Dong Ye and Zhaowei Sun
Aerospace 2026, 13(8), 731; https://doi.org/10.3390/aerospace13080731 - 17 Aug 2026
Viewed by 192
Abstract
Modular self-reconfigurable satellites can adapt to diverse space missions by dynamically rearranging their configurations. Enabling multiple modules to move simultaneously enhances reconfiguration efficiency but remains constrained by existing planning algorithms. This article introduces the Parallel Reconfiguration Planner (PRP), a learning-based approach that ensures [...] Read more.
Modular self-reconfigurable satellites can adapt to diverse space missions by dynamically rearranging their configurations. Enabling multiple modules to move simultaneously enhances reconfiguration efficiency but remains constrained by existing planning algorithms. This article introduces the Parallel Reconfiguration Planner (PRP), a learning-based approach that ensures safe, concurrent module movements. PRP leverages multi-agent reinforcement learning to generate reconfiguration policies while incorporating safety constraints modeled using Linear Temporal Logic (LTL). To improve learning efficiency, PRP integrates a guarded exploration mechanism based on these safety specifications. Experiments on 3D reconfiguration scenarios demonstrate that PRP achieves more efficient reconfiguration policies in scenarios that have more moving modules compared to the baseline method. Full article
(This article belongs to the Special Issue Advanced AI and Robotic Technologies for Spacecraft Modelling, Optimization, and Decision-Making)
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26 pages, 4824 KB  
Article
Quasi-Self-Motion-Based Singularity Avoidance for Free-Floating Space Robots
by Xinghong Huang, Haiyang Li, Yuqi Song, Yubin Zhong, Tao Wu and Yingjie Zhao
Aerospace 2026, 13(8), 730; https://doi.org/10.3390/aerospace13080730 - 17 Aug 2026
Viewed by 190
Abstract
We propose a novel singularity-avoidance method for continuous path planning that maintains zero path-tracking error of a non-redundant free-floating space robot (FFSR). Singularities are a major challenge in the path planning of space robots and may lead to the failure of end-effector tracking [...] Read more.
We propose a novel singularity-avoidance method for continuous path planning that maintains zero path-tracking error of a non-redundant free-floating space robot (FFSR). Singularities are a major challenge in the path planning of space robots and may lead to the failure of end-effector tracking tasks. First, the singularity characteristics of FFSRs are analyzed, and a numerical method for calculating singularity surfaces is developed. The symmetry properties of the singular surface are further investigated. Subsequently, based on the nonholonomic characteristics of FFSRs, the existence of quasi-self-motion is demonstrated. A quasi-self-motion-based singularity-avoidance method is then proposed for continuous end-effector pose tracking. In addition, the workspace regions where quasi-self-motion does not exist are analytically derived. Numerical simulations verify the effectiveness of the proposed method. Compared with existing singularity-avoidance approaches, the proposed method achieves accurate path tracking while enabling both active singularity avoidance and singularity escape. Full article
(This article belongs to the Special Issue Advanced AI and Robotic Technologies for Spacecraft Modelling, Optimization, and Decision-Making)
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17 pages, 16440 KB  
Article
Rigid–Flexible Coupling Dynamic Analysis and Material Comparison for a Landing Gear Door Linkage with a Critical Flexible Link
by Fu Liu, Maosheng Zheng, Yuening Li, Jinqiang Tian and Mingbo Tong
Aerospace 2026, 13(8), 729; https://doi.org/10.3390/aerospace13080729 - 17 Aug 2026
Viewed by 238
Abstract
To address the structural deformation and mechanism jamming frequently observed in critical linkages during retraction and extension of door-coupled landing gear systems, this study proposes a rigid–flexible coupled dynamic modeling approach. A representative landing gear system was studied, and a high-fidelity rigid–flexible multibody [...] Read more.
To address the structural deformation and mechanism jamming frequently observed in critical linkages during retraction and extension of door-coupled landing gear systems, this study proposes a rigid–flexible coupled dynamic modeling approach. A representative landing gear system was studied, and a high-fidelity rigid–flexible multibody dynamics model was developed based on a conventional rigid-body framework. The left linkage, which was prone to failure, was modeled as a flexible finite element component, while the remaining parts were treated as rigid bodies. A multibody dynamics method based on nonlinear finite element was adopted, incorporating elastoplastic constitutive relations and Lagrange constraint equations. Two materials, ultra-high-strength 300M steel and high-strength 7075-T6 aluminum alloy, were evaluated to investigate the influence of structural stiffness on critical linkage stress and door kinematics during deployment. Results showed that maximum stress occurred at the hinge joint, identified as the critical region for strength assessment. The peak stress for 300M reached approximately 168 MPa, about 8.4% higher than that of 7075-T6. However, 7075-T6 exhibited lower stress oscillation frequency and superior damping performance, which helped suppress high-frequency vibration. Material selection had negligible influence on door centroid displacement, velocity, and opening angle, and the motion trajectories remained highly consistent. Full article
(This article belongs to the Section Aeronautics)
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28 pages, 8927 KB  
Article
Robust Multi-Phase Vertical Recovery Guidance for Reusable Launch Vehicles Integrated with Full-Flight Fuel Consumption Prediction
by Jiahao Gan, Yuanpeng Fang, Tie Su and Jin Zhang
Aerospace 2026, 13(8), 728; https://doi.org/10.3390/aerospace13080728 - 16 Aug 2026
Viewed by 233
Abstract
Focusing on the vertical return mission scenario of reusable launch vehicles, analytical guidance methods commonly adopted in existing research lack effective fuel prediction mechanisms, which severely restricts the mission reliability and fuel economy of vehicle vertical landing, and fails to achieve high-precision velocity [...] Read more.
Focusing on the vertical return mission scenario of reusable launch vehicles, analytical guidance methods commonly adopted in existing research lack effective fuel prediction mechanisms, which severely restricts the mission reliability and fuel economy of vehicle vertical landing, and fails to achieve high-precision velocity constraint control and stable anti-disturbance guidance in the full powered descent and terminal landing process. To address the above problems, this paper proposes a multi-phase integrated guidance framework that integrates predefined-time time-varying fractional-order sliding mode control and fuel consumption forecasting. A fuel consumption prediction model incorporating potential energy factor, kinetic energy factor and interference factor is constructed to realize full-process fuel demand prediction in the trajectory planning stage, and the proposed guidance scheme achieves high-precision and strong anti-disturbance guidance performance while satisfying strict full-stage velocity constraint requirements. Simulation results show that the proposed method can realize stable and accurate vertical soft landing under diverse disturbance conditions with minor fuel prediction errors. This method addresses the limitations of traditional analytical guidance methods in terms of mission reliability and fuel economy, improves the system robustness of vertical recovery missions, and provides an effective technical reference for precise landing guidance of reusable launch vehicles. Full article
(This article belongs to the Section Aeronautics)
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29 pages, 529 KB  
Article
Impact of Alternative Propulsion Systems on Contrail Formation and Lifetime
by Judith Rosenow, Thomas F. Geyer and Lars Enghardt
Aerospace 2026, 13(8), 727; https://doi.org/10.3390/aerospace13080727 - 14 Aug 2026
Viewed by 260
Abstract
The reduction in aviation-induced climate impacts requires not only decreasing CO2 emissions, but also mitigating non-CO2 effects such as persistent contrail cirrus. Alternative propulsion systems and fuels are therefore discussed as potential pathways toward climate-neutral aviation. However, their influence on contrail [...] Read more.
The reduction in aviation-induced climate impacts requires not only decreasing CO2 emissions, but also mitigating non-CO2 effects such as persistent contrail cirrus. Alternative propulsion systems and fuels are therefore discussed as potential pathways toward climate-neutral aviation. However, their influence on contrail formation and evolution remains insufficiently understood, particularly regarding how emission characteristics translate into contrail microphysical behavior and lifetime. This study aims to bridge this knowledge gap by systematically evaluating the contrail-forming potential of Sustainable Aviation Fuel (SAF) and hydrogen-based propulsion systems, with a clear focus on identifying the key emission parameters that govern contrail persistence. To assess the impact of reduced particle emissions on contrail evolution, scenarios with lower initial ice crystal number concentrations Nice, representative of alternative propulsion concepts, were simulated using a Gaussian plume contrail evolution model. The results demonstrate that high ice crystal number concentrations (Nice≈1014–1015 kg−1), characteristic of kerosene and many SAF combustion cases, lead to persistent contrails with lifetimes of approximately 9–12 h due to suppressed crystal growth and sedimentation. Conversely, low initial ice crystal concentrations (Nice≈109–1010 kg−1), expected for hydrogen systems under aerosol-limited nucleation conditions, promote short-lived contrails in the order of minutes. The findings indicate that contrail impacts are influenced not only by the fuel type itself, but also by combustion processes, atmospheric conditions, and the prevailing nucleation mechanisms. Consequently, the potential of SAF and hydrogen propulsion systems to mitigate contrail-related climate effects will likely depend on further technological optimization as well as additional experimental and in-flight observations to better quantify their atmospheric impacts. This work underscores the importance of linking emission measurements directly to contrail microphysics and provides a framework for evaluating future propulsion technologies based on their actual contrail-forming potential, rather than solely on fuel composition or CO2 reduction. Full article
(This article belongs to the Section Air Traffic and Transportation)
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22 pages, 2327 KB  
Review
A Review of the Current Status of Active Cooling Technology of Liquid Metal for Hypersonic Aircraft
by Haowei Li, Zhongwei Deng, Xuran Hou and Guangze Song
Aerospace 2026, 13(8), 726; https://doi.org/10.3390/aerospace13080726 - 14 Aug 2026
Viewed by 364
Abstract
Under high-Mach-number flight conditions, the combustion chambers of hypersonic vehicles encounter extreme thermal environments marked by unilateral heating, high-heat-flux density, and supercritical pressure. Traditional hydrocarbon fuel cooling often suffers from insufficient heat sinks, high-temperature cracking and coking blockages, making it difficult to meet [...] Read more.
Under high-Mach-number flight conditions, the combustion chambers of hypersonic vehicles encounter extreme thermal environments marked by unilateral heating, high-heat-flux density, and supercritical pressure. Traditional hydrocarbon fuel cooling often suffers from insufficient heat sinks, high-temperature cracking and coking blockages, making it difficult to meet long-endurance thermal protection requirements. Liquid metal, due to its extremely high thermal conductivity, wide liquid phase temperature range, low Prandtl number and electromagnetic pump driving capability, has become a key technology for breaking through the bottleneck of high-heat-flux thermal protection. Apart from the magnitude of heat flux, the heat-transfer time scale (such as the characteristic thermal response time of the wall and the fluid) is also crucial. During hypersonic flight, transient thermal loads can change within milliseconds, requiring rapid thermal response. Liquid metals, due to their high thermal diffusivity, have a shorter thermal diffusion time compared to hydrocarbon fuels. This review employs a systematic literature review of approaches using gallium-indium-tin alloy, GaInSn, focusing on three core directions: the flow and heat-transfer characteristics of liquid metals, the optimization of cooling micro-channels, and the application of thermal protection systems. It summarizes the research progress at home and abroad, compares and analyzes the performance differences and applicable scenarios of typical liquid-metal working fluids, and summarizes the advantages and disadvantages of existing models, structural designs, and system schemes. The research shows that liquid metals can significantly alleviate thermal stratification and eliminate coking, and deep, narrow, tree-shaped, and biomimetic micro-channels can effectively enhance heat transfer. The liquid-metal-fuel dual-channel waste heat recovery and thermoelectric power generation system has demonstrated engineering application potential. Currently, the field still faces key challenges, such as unclear heat-transfer mechanisms under extreme conditions, the lack of general heat-transfer correlation formulas, insufficient compatibility with high-temperature materials, poor miniaturization and vibration resistance of electromagnetic pumps, and low system integration. In the future, efforts should be focused on developing multi-field coupled heat-transfer models under extreme thermal environments using engineered micro-channel structures, corrosion-resistant materials, and lightweight electromagnetic pumps, promoting the research and development of integrated thermal protection, heating and power generation systems, and providing support for the development of advanced thermal management systems for hypersonic aircraft and aviation engines. Full article
(This article belongs to the Section Aeronautics)
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30 pages, 31100 KB  
Article
Gust Load Alleviation Based on Active Disturbance Rejection Control for a Flying-Wing Aircraft with Circulation Control Actuators
by Xueqi Liao, Weilin Zhang, Zhiwei Shi, Pengyu Guo, Xing Tian and Rui Li
Aerospace 2026, 13(8), 725; https://doi.org/10.3390/aerospace13080725 - 14 Aug 2026
Viewed by 352
Abstract
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 [...] Read more.
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
(This article belongs to the Section Aeronautics)
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34 pages, 3043 KB  
Article
Detailed Sensitivity and Multi-Level Design Studies on a Hydrogen-Hybrid Dual-Fuel Regional Aircraft Retrofit
by Ulrich Carsten Johannes Rischmüller, Alexandros Lessis, Patrick Egerer, Rafael Balderas-Xicohtencatl and Mirko Hornung
Aerospace 2026, 13(8), 724; https://doi.org/10.3390/aerospace13080724 - 13 Aug 2026
Viewed by 268
Abstract
Current research in commercial aviation is exploring numerous propulsion and aircraft technologies to mitigate its environmental impact. While purely hydrogen-powered aircraft face manifold challenges, combining hydrogen and conventional fuel may facilitate the introduction of hydrogen-based flight. This study dives into the conceptual design [...] Read more.
Current research in commercial aviation is exploring numerous propulsion and aircraft technologies to mitigate its environmental impact. While purely hydrogen-powered aircraft face manifold challenges, combining hydrogen and conventional fuel may facilitate the introduction of hydrogen-based flight. This study dives into the conceptual design of a parallel-hybrid dual-fuel regional aircraft retrofit based on the D328eco. The assessed retrofit approach aims to extend airframe service life and reduce emissions by incorporating a novel propulsion system. By integrating high-temperature fuel cells (FCs) to assist conventional turboshaft engines, the powertrain reduces fuel consumption. Utilizing the Bauhaus Luftfahrt Aircraft Design Environment, various aircraft-level sensitivities and hybridization strategies were assessed. The fuel/payload ratio was identified as a key metric, and enabling FC support during diversion climb while minimizing that ratio shifted the corresponding hybridization degree from 20.3% to 37.2%. Retaining the reference turboshaft-engine for reduced retrofit development costs, a hybridization degree of 20.2% was attainable while the minimum allowable payload was carried aboard. Subsequent off-design mission analysis revealed a decrease in transport efficiency for reduced mission ranges, underlining the importance of market-tailored aircraft designs. The main studies were complemented by a higher-level emission and climate impact assessment to set the basis for more generalized retrofit statements. Full article
(This article belongs to the Special Issue Power Management for Hybrid Electric Aircraft)
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23 pages, 3354 KB  
Article
Research on Air Traffic Situation Prediction Methods in Multi-Airport Terminal Areas
by Rundong Miao, Xiangxi Wen, Yaobo Shang and Chuanlong Zhang
Aerospace 2026, 13(8), 723; https://doi.org/10.3390/aerospace13080723 - 13 Aug 2026
Viewed by 188
Abstract
Accurate assessment and forecasting of air traffic conditions in multi-airport terminal areas are essential for improving early-warning capabilities, mitigating flight conflicts, and alleviating air-route congestion. Accordingly, this study develops an air traffic situation prediction approach that combines an air route–flight state interdependent network [...] Read more.
Accurate assessment and forecasting of air traffic conditions in multi-airport terminal areas are essential for improving early-warning capabilities, mitigating flight conflicts, and alleviating air-route congestion. Accordingly, this study develops an air traffic situation prediction approach that combines an air route–flight state interdependent network with an Optimal Training Sample Online Fuzzy Least-Squares Support Vector Machine (OTSOF-LSSVM). An interdependent network model is first established. The Analytic Hierarchy Process (AHP) is then employed to combine three network indicators, namely node degree, weighted clustering coefficient, and node strength, thereby producing a comprehensive air traffic situation value and its corresponding evolutionary time series. Considering the time-varying and long-periodic properties of this series, an OTSOF-LSSVM-based prediction method is developed. Training samples are selected according to their temporal and spatial proximity to the prediction moment. In addition, block-matrix operations are introduced during model updating to streamline the computational procedure and improve algorithmic efficiency. The proposed approach is validated using actual flight data from the multi-airport terminal area of the Guangdong–Hong Kong–Macao Greater Bay Area. The results demonstrate that the proposed assessment method can effectively characterize the prevailing air traffic situation. Moreover, in comparison with several existing prediction techniques, the proposed method achieves the best overall performance, yielding a mean absolute error of only 0.0111. Full article
(This article belongs to the Section Air Traffic and Transportation)
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