Aerospace doi: 10.3390/aerospace13070571

Authors: Zhuoyue Peng Qiang Shen

This paper proposes an integrated attitude control framework for flexible spacecraft subject to external disturbances, rigid–flexible dynamic coupling, and actuator faults. The control framework combines the Twin Delayed Deep Deterministic Policy Gradient (TD3) reinforcement learning algorithm with an adaptive fault-tolerant (AFT) compensator. First, a rigid–flexible coupling dynamic model is formulated using Modified Rodrigues Parameters. Second, an observer-based TD3 attitude controller is designed, where a hierarchical reward function incorporating the observer-estimated flexible modal displacement η^ is constructed to train the agent for simultaneous attitude convergence and vibration suppression. Third, a composite fault-tolerant control structure is developed by integrating the trained TD3 policy with an adaptive sliding mode compensator that handles both partial loss-of-effectiveness faults and time-varying additive faults. The proposed framework is evaluated under a progressive five-scenario uncertainty evaluation framework encompassing measurement noise, parameter mismatch, external disturbances, and actuator faults. Simulation results demonstrate that (i) the η^-augmented reward enables substantial improvements in vibration suppression over the baseline reward, achieving a better balance between pointing accuracy and vibration attenuation; (ii) under the most demanding fault scenario, the AFT compensator proves essential for precise convergence, and the composite TD3+AFT architecture achieves the best overall performance among the four compared control schemes.

Aerospace doi: 10.3390/aerospace13070570

Authors: Wang Xu He Wang

Distant Retrograde Orbits (DROs) and Near-Rectilinear Halo Orbits (NRHOs), as categories of Lagrange orbits, have been selected for the construction of future deep-space navigation constellations in the Earth-Moon space due to their unique orbital trajectories and dynamical characteristics. To obtain high-precision orbit and clock solutions, the orbit determination (OD) and time synchronization (TS) performance of DRO and NRHO based on Beidou Navigation Satellite System (BDS) L-band and Ka-band signals were analyzed. Considering the constraints of onboard resources and cost, it may be infeasible to establish Ka-band links with all BDS satellites. Therefore, multiple experiments with different link configuration schemes were designed. The results show that an orbit determination accuracy of about 500 m and the time synchronization accuracy of 50 ns can be achieved using only L-band observations. In contrast, much higher accuracy can be obtained with full Ka-band links, with orbit and clock accuracy reaching 80 m and 7 ns, respectively. Moreover, higher orbit and clock accuracies can be obtained with more Ka-band links based on L-band observations. Furthermore, with the addition of the DRO-NRHO links, the orbit determination and time synchronization performance of each scheme was further improved by 15%. And the orbit determination accuracy can be better than 65 m, while the time synchronization accuracy can be better than 5 ns. Although the analysis is based on BDS signals, the proposed framework is general in nature and can be extended to other GNSS-based or future space navigation systems, providing a reference for the design of high-precision cislunar navigation and timing architectures.

Aerospace doi: 10.3390/aerospace13070569

Authors: Jiangting Yu Minghua Hu Bing Jiang Lei Yang Zheng Zhao

The efficiency of airport resource allocation is improved through the establishment of a scientific multi-granularity configuration scheme for flight slot coordination parameters. In this study, a collaborative configuration method for hourly and 15 min coordination parameters is proposed, with Beijing Capital International Airport serving as a case study. Short-term traffic clusters are frequently omitted by traditional hourly parameters, thereby leading to sudden delay surges. First, local delays were extracted from March 2024 Automatic Dependent Surveillance-Broadcast (ADS-B) trajectory data. Subsequently, a delay prediction model was constructed through the integration of a non-stationary queuing model and a gradient boosting regression tree. Second, simulated timetables were generated via a Monte Carlo method under various parameter combinations. With a constant daily flight volume utilized as the experimental baseline, a mapping relationship was established between parameter combinations and expected local delays. Finally, feasible delay regions were delineated and interpretable configuration rules were extracted via a decision tree to maximize schedule flexibility. It was indicated by the results that at an hourly parameter of 70 flights, the target delay is maintained below 8 min by tightening the 15 min parameter to 19 flights. The findings suggest that average load is controlled by hourly parameters, while traffic clustering in high-load scenarios is effectively suppressed by 15 min parameters. A quantitative reference is provided by this method for the configuration of multi-granularity time parameters at hub airports.

Aerospace doi: 10.3390/aerospace13070567

Authors: Miguel Gabriel Cebrián Gómez Konstantinos Banitsas

Helicopter operations are often underrepresented in environmental assessments due to their relatively low number of movements and the use of aggregated indicators that do not capture their localised impacts. At the same time, rotorcraft activity typically occurs at low altitude within urban environments, where noise and emissions are directly perceptible and spatially concentrated. This creates a need for assessment approaches based on observed operations and capable of providing spatially resolved results. Automatic Dependent Surveillance-Broadcast (ADS-B) data provide high-resolution observations of aircraft trajectories and are increasingly used to analyse real-world aviation activity. However, existing approaches to ADS-B data processing have largely been developed for fixed-wing operations and do not address the specific challenges of rotorcraft activity, including low-altitude signal loss, positional artefacts, and incomplete trajectories. As a result, ADS-B data for helicopters are generally not suitable for direct use in applications requiring physically consistent and operationally defined inputs. This study proposes a methodology to condition ADS-B helicopter trajectories into a physically consistent and operationally characterised dataset suitable for downstream analysis. The approach integrates trajectory correction, reconstruction of incomplete operations, and the derivation of flight modes and associated parameters. The resulting dataset provides a complete, operation-level description of helicopter activity derived from observed data. The methodology is demonstrated through its application to helicopter operations in the Zurich area and its integration with established environmental modelling approaches, including a rotorcraft-specific noise model (NORAH2) and a flight-mode-based emissions estimation method (Rindlisbacher and Chabbey). The results produce spatially resolved maps and tabulated outputs describing environmental impacts over a defined period, enabling the identification of localised hotspots. The contribution of this work lies in providing a reproducible and integrated framework that bridges the gap between raw ADS-B rotorcraft observations and application-ready datasets for spatially explicit environmental assessment.

Aerospace doi: 10.3390/aerospace13070568

Authors: Xin Wang Mingxu Lu Yi Liu Jide Qian

Efficient detection of aircraft surface defects (ASD) is a cornerstone of aviation safety. However, ASD detection is challenged by microscopic defect scales, extremely low contrast, and severe background interference. This paper proposes the Multi-Scale Discriminative Edge Enhancement Network (DEE-Net) based on an improved YOLO11. First, to mitigate feature dissipation of tiny defects, a lossless reassembly mechanism using space-to-depth convolution (SPD-Conv) is introduced, safeguarding sub-pixel topological information through space-to-depth conversion. Second, an adaptive selective edge-enhancement (ASE) module, integrating a dual-domain selection mechanism (DSM), is designed to suppress non-target redundant information on the fuselage skin. Finally, a Wise-CIoU loss function with a non-monotonic focusing mechanism is introduced to enhance localization stability under stringent IoU thresholds. Experimental results demonstrate that DEE-Net outperforms the baseline, improving mAP50 by 7.15% and mAP50-95 by 2.43%. To provide a more reliable evaluation, a 5-fold cross-validation experiment is further conducted on the original non-augmented images, and the results are reported as mean ± standard deviation. The cross-validation results provide a more conservative estimate and indicate that the proposed method achieves competitive performance across different data partitions.

Aerospace doi: 10.3390/aerospace13070566

Authors: Radimir Y. Yanev Ingo Staack

Advances in electric flight technologies have enabled distributed electric propulsion, opening a large design space for electric vertical take-off and landing (eVTOL) aircraft with diverse configurations and mission profiles. To support rapid exploration of these trade-offs, a computationally efficient sizing and performance evaluation tool has been developed. This study focuses on the verification of the key methods within the framework. The propeller sizing and performance model is verified against conventional helicopter rotors and representative eVTOL designs, while the battery discharge model is assessed using experimental data. In addition, the overall aircraft sizing is evaluated for two configurations of NASA’s Urban Air Mobility reference vehicles and compared with results obtained using NASA’s state-of-the-art rotorcraft design tool NDARC. The results show good agreement across all levels of verification. Average deviations are within 8% for propeller performance, below 5% for battery discharge, and within 4% for maximum take-off and empty mass. Mission performance and energy consumption are predicted within approximately 10%, demonstrating the suitability of the methodology for early-stage eVTOL design.

Aerospace doi: 10.3390/aerospace13070565

Authors: Shuxia Tian Shunqiang Wang Zhenmao Chen Peng Zhang Hong-En Chen Xuan Gao Shuai Liu

Two reconstruction methods for constraint and load parameters of aero-engine pipelines based on intelligent optimization algorithms are proposed in this paper. First, a simplified finite element model (FEM) of the aero-engine pipeline structure is established, and its reliability is validated by comparing simulation data with experimental data. Second, a reconstruction algorithm for spring constraint parameters and pipeline load parameters based on the improved particle swarm optimization (IPSO) algorithm is developed on the MATLAB data analysis and ANSYS simulation platforms, which completes the reconstruction calculation of parameters such as spring constraint stiffness and applied harmonic excitation. For harmonic excitation parameter reconstruction, the maximum error of this algorithm reaches 24.9%, revealing its significant inapplicability to load parameter reconstruction. To solve this problem, a load reconstruction method based on the conjugate gradient method (CGM) is further proposed to achieve accurate reconstruction of pipeline load parameters, which mitigates the large reconstruction error of the IPSO algorithm under working conditions with multiple loads. Under 5% noise interference, the maximum error of the CGM is merely 5.16%. Finally, experimental verification of harmonic excitation amplitude reconstruction is performed using the CGM with lower reconstruction errors. Experimental results indicate that the maximum error is 14.24% for harmonic excitation amplitude reconstruction, which verifies the high applicability of the conjugate gradient algorithm to load reconstruction of aero-engine pipelines.

Aerospace doi: 10.3390/aerospace13060564

Authors: Kangkang Li Haodong Sun Chao Cheng Zhongjing Ren Jianping Yuan Mengbi Wang

This paper addresses bearing-only three-dimensional target localization using three cooperative UAVs under observation inconsistency and degraded geometry. A weighted point-to-line least-squares localization model is established to fuse multiple line-of-sight (LOS) observations derived from image measurements, camera calibration, and UAV poses. To handle unreliable measurements without ground truth, a reliability assessment mechanism is developed by combining geometric stability indicators with observation consistency metrics, enabling weak geometry and abnormal observations to be identified online. Based on this assessment, an adaptive optimization framework is introduced to perform residual-driven adaptive weighting and configuration optimization, thereby suppressing unreliable LOS measurements and improving the conditioning of cooperative geometry. Simulation results under four representative scenarios show that the proposed method consistently improves localization accuracy and robustness. The mean localization error is reduced from 0.545 m to 0.260 m under abnormal observations, from 0.355 m to 0.081 m under degraded geometry, and from 0.711 m to 0.280 m when both effects occur simultaneously. Statistical evaluations including RMSE, standard deviation, maximum error, confidence intervals, and box-plot analysis further demonstrate that the proposed framework effectively reduces error dispersion and improves robustness.

Aerospace doi: 10.3390/aerospace13060563

Authors: Khaing Phyo Zaw Sergey Vladislavovich Baranovski

Lightweight composite aircraft wing design increasingly depends on combining multidisciplinary design optimization (MDO), aeroelastic tailoring, and stacking sequence optimization. However, an overview of these interconnected fields is lacking. This study applies a PRISMA-ScR-based scoping review of 54 selected articles to map current approaches, identify emerging trends, and highlight remaining gaps. Key findings indicate six MDO architectures—with hybrid methods being increasingly preferred—and demonstrate that aeroelastic tailoring (e.g., ply angle manipulation) enhances performance while reducing weight. Manufacturing constraints (ply continuity, blending, symmetry) are addressed in a subset of the reviewed literature, with opportunities for broader integration. Critical future priorities include integrating manufacturing process models into MDO and incorporating durability considerations (fatigue, impact). This work synthesizes current approaches, identifies emerging trends, and provides a roadmap for the development of next-generation lightweight, high-performance composite wings.

Aerospace doi: 10.3390/aerospace13060562

Authors: Kunze Du Tianrun Wang Ji Chen Bin Liu Meilian Liu Haisheng Li Nan Li

High-fidelity computational fluid dynamics (CFD) remains computationally expensive for steady aerodynamic prediction under multi-condition and variable-geometry configurations, which limits rapid design iteration. To address this issue, this study proposes a data-driven surrogate framework for aircraft surface flow-field prediction on irregular meshes. The framework combines a geometry-unification strategy for variable rudder-deflection configurations with KM-GAT, a hybrid neural architecture that integrates graph attention and KAN-based nonlinear feature transformation. Geometry unification maps the surface flow fields associated with different rudder-deflection states onto a common zero-deflection reference template, thereby establishing consistent mesh correspondence and fixed prediction locations across samples while retaining the rudder angle as an operating-condition variable. The KM-GAT model further combines topology-aware message passing with localized nonlinear refinement, while the Huber loss is adopted to improve training robustness for CFD-derived data. Experiments on the F-22 research model show that the proposed framework achieves lower prediction errors and more concentrated error distributions than baseline MLP and GNN-based models. Qualitative comparisons further indicate that KM-GAT better preserves localized high-gradient structures, including pressure transitions and vortex-dominated regions. These results suggest that the proposed framework provides an effective surrogate modeling strategy for variable-geometry aerodynamic flow field prediction.

Aerospace doi: 10.3390/aerospace13060561

Authors: Lixin Li Jia Wang Lizhang Zhang Chengwei Fei Jiaqiang Li Bing Wang

The fatigue life of additively manufactured GH4169 components is strongly affected by internal defects, stress concentration, and life scatter, making reliable structural assessment difficult. In this study, a probability-based fatigue life prediction framework was developed by extending the conventional surface weakest link concept to a volume-defect weakest link formulation. Fatigue tests of smooth specimens with different build orientations were first conducted to establish baseline probabilistic fatigue relationships, and both log-normal and two-parameter Weibull distributions were considered. The proposed framework was then applied to a feature specimen representing the critical region of an aero-engine exhaust frame by combining the baseline fatigue statistics with element-wise maximum principal stress and volume information extracted from finite element analysis. The results show that the log-normal distribution provided a more stable statistical description of the smooth-specimen fatigue data than the Weibull distribution. For the feature specimens tested at 11,200 N, the measured fatigue lives ranged from 25,585 to 61,989 cycles. Compared with the conventional local stress method, the weakest link framework gave a more reasonable description of the structural fatigue life distribution, and the log-normal weakest link model showed the best overall agreement with the experimental results.

Aerospace doi: 10.3390/aerospace13060560

Authors: Hao Jiang Weili Zeng Hainuo Zhou Yannan Lu Yuheng Chen Wenbin Wei

Runway systems serve as the critical interface between airports and terminal airspace, and their efficient operation is essential for balancing air traffic demand and airport capacity. With the continuous growth of air traffic, intelligent runway demand and capacity management has become increasingly important for mitigating congestion and delays. This paper presents a comprehensive review of runway capacity–demand management from both supply-side and demand-side perspectives. On the supply side, runway configuration selection is reviewed, including runway configuration capacity envelopes, influencing factors, and existing optimization methodologies, such as prescriptive models, descriptive models, and reinforcement learning approaches. On the demand side, flight runway sequencing for arrivals, departures, and integrated arrival–departure operations is systematically analyzed. Problem analogies, operational characteristics, optimization objectives, and solution algorithms are discussed in detail. A critical comparison of existing methodologies is conducted from the perspectives of solution quality, real-time capability, human interpretability, technology readiness, trust requirements, and human–AI collaboration. Finally, future research directions are identified, including integrated runway management, multi-airport coordination, uncertainty-aware optimization, human–AI decision support, AI-enabled runway management, and integrated manned–unmanned operations. The review provides a reference for researchers, airport operators, air navigation service providers, and decision-support system developers seeking to improve runway operational efficiency and safety.

Aerospace doi: 10.3390/aerospace13060559

Authors: Donghee Lee Donggeun Lee Sungwoo Park Jungpyo Lee Heejang Moon

This study presents the preliminary development of a clustered hybrid propulsion module, and its experimental validation from static motor characterization to dynamic 1-D vertical drop tests to assess the feasibility of a hybrid propulsion system for soft-landing applications. The research progresses from preliminary design of core components (such as fuel, oxidizer supply system, engine configuration), to the performance verification of the clustering module. First, the trade-off between high regression rates and mechanical integrity was evaluated for paraffin-based fuels. However, high-density polyethylene (HDPE) was utilized as the baseline to ensure predictable combustion behavior. Second, cold flow tests of the designed multi-port manifold demonstrated a highly uniform oxidizer distribution, validating the geometric design with a maximum spatial pressure deviation of 2.44% across the four engines. Third, static fire tests confirmed robust dynamic control capabilities, successfully throttling the average chamber pressure from 100% (7.00 bar) down to 43% (3.01 bar) and back to 100% (7.01 bar) with a transient response time of approximately 0.6 s. Finally, the 1-D vertical drop test validated the operational readiness of the system; the open-loop thrust modulation successfully counteracted the module’s dynamic weight, achieving a terminal descent velocity of 1.46 m/s, which strictly satisfies planetary soft-landing safety criteria. These results demonstrate the feasibility and performance of clustered hybrid propulsion systems for planetary exploration, extending to surface launch technology for sample return missions from the Moon and Mars, and precision booster recovery for small launch vehicles.

Aerospace doi: 10.3390/aerospace13060558

Authors: Mario Román Rodríguez Cristian Builes Cárdenas Elena Rodríguez Senín Adrián López González

Graphene is a novel material that can bring several advantages in the composite materials manufacturing field, such as improved electrical and thermal properties, and high performance. In particular, functionalizing current composite materials can bring advantages in the aerospace field in thermal management for electric aircraft engines. This paper studies the addition of graphene particles into carbon fiber composites manufactured by the Resin Transfer Molding Process (RTM). Thermal and mechanical properties are evaluated and compared with a conventional composite laminate. Major improvements were achieved on the thermal behavior of the composite material while maintaining general properties, but in particular, the addition of graphene had a negative impact on transverse tensile and mode II fracture toughness due to agglomerates present in the fiber–resin interface.

Aerospace doi: 10.3390/aerospace13060557

Authors: Jose Bernardo Padaca Leif Oliver Coronado Ulysses Ante Hannah Ramos Roider Pugal Arvin Oliver Ng Renzo Wee Marc Caesar Talampas Prince William Lim

This study investigates the application of advanced metal additive manufacturing (AM) and topology optimization for the development of a structurally efficient and lightweight 3U nanosatellite frame. Payload weight is a critical factor in space mission costs; therefore, a stock 3U CubeSat design was subjected to structural optimization using specialized Generative Design Software. The optimized model was fabricated using Powder Bed Fusion—Direct Metal Laser Sintering (PBF-DMLS) on an EOS M290 metal printer with AlSi10Mg aluminum alloy. While AlSi10Mg differs in ultimate tensile strength from traditional wrought aerospace alloys, it was selected to evaluate the baseline feasibility of this application. To evaluate manufacturability and preliminary performance, Finite Element Analysis (FEA), including structural and modal response analyses, was conducted. While the optimized design successfully achieved a 53% mass reduction (from 333 g to 155 g) and met the 30 Hz minimum fundamental frequency requirement, static analysis indicated a maximum simulated stress of 287 MPa. Because this exceeds the material’s nominal yield strength of 220 MPa, localized plastic deformation is predicted in the bare-frame configuration under maximum launch loads. This necessitates further design iterations and full-assembly simulations, incorporating the load-sharing effects of integrated panels prior to physical qualification. Post-processing successfully met JAXA dimensional and surface roughness requirements. Ultimately, this study serves as a foundational manufacturability baseline, demonstrating the applicability of PBF-DMLS for nanosatellites.

Aerospace doi: 10.3390/aerospace13060556

Authors: Xin Wang Yiran Tao Guanqiao Huang Zhongyu Wang Feimeng Diao Feng Gu

The performance of the aircraft anti-skid braking system is critical to the ground operational safety of an aircraft. Conventional Pressure Bias Modulation (PBM) can suffer from deep skidding under low runway friction coefficients or low aircraft speeds. To address these issues, a composite control strategy based on Gaussian Quantum Particle Swarm Optimization (GQPSO) is proposed. This strategy employs the GQPSO algorithm for offline Proportional–Integral–Derivative (PID) parameter optimization, followed by real-time adaptive scheduling through a lookup table to accommodate varying speed domains and runway conditions. Simultaneously, by integrating the main-wheel dynamics model and friction characteristics, a runway identification function based on a Back Propagation Neural Network (BPNN) is designed to provide runway status information. The stability of the controller is verified via phase-plane analysis and Monte Carlo simulation. Subsequently, comparative Hardware-in-the-Loop (HIL) tests are conducted among PBM, PSO-PID, and the proposed GQPSO-PID controller under various runway conditions. The experimental results demonstrate that this composite controller can adapt to different speed domains and runway conditions, stably track the target slip ratio, effectively suppress skidding, and significantly improve braking efficiency, as well as exhibiting excellent robustness and control performance.

Aerospace doi: 10.3390/aerospace13060555

Authors: Jiaxi Yan Song Wei Junkui Mao Zhiyin Yang Feng Han Longfei Wang

Accurate prediction of discharge coefficients (Cd) in rotating orifices is essential for the design of aero-engine internal air systems, yet existing correlations usually treat axial and radial orifices separately and do not fully represent intermediate wall inclination angles. In this study, steady-state RANS simulations in a rotating reference frame, supported by validation against published data and by rotating orifice experiments, are used to investigate the combined effects of wall inclination angle α and length-to-diameter ratio L/d on Cd. The numerical results show that, under typical conditions (N = 3000 rpm, Π = 1.03, L/d = 1.5), Cd increases from 0.301 to 0.340 as α increases from π/2 to π, corresponding to a 12.96% increase. Under low rotational speeds and high pressure ratios, the Coriolis force reduces the relative tangential velocity and the incidence angle, thereby increasing Cd with α; however, at high rotational speeds and low pressure ratios, the centrifugal resistance to radial inflow becomes dominant, and at N = 7000 rpm, the Cd for the α = π orifice is 38.96% lower than that for the α = π/2 orifice. Increasing L/d promotes flow redevelopment and amplifies the Coriolis-force effect, leading to a larger Cd increase for orifices with larger α. Based on these mechanisms, a generalized incidence-angle formulation incorporating Coriolis and centrifugal effects is developed, and a Cd prediction model applicable to π/2 ≤ α ≤ π and different L/d values is proposed. Experimental validation shows that the maximum prediction error is reduced to 2.37%, demonstrating the accuracy of the proposed model for rotating inclined orifices.

Aerospace doi: 10.3390/aerospace13060554

Authors: Wenjin Sun Yuan Hu Fei Fei Chao Yang Jinwen Cao Xian Meng Quanhua Sun Heji Huang

Ultra-high-speed rarefied gas wind tunnels (RGWTs) are critical for estimating the aerodynamic forces acting on spacecraft in very low Earth orbit (VLEO). These tunnels utilize nozzles with large expansion ratios to generate extreme freestream conditions (Ma>20, Kn>1). However, the large expansion ratio induces a multiscale flow within the nozzle that simultaneously spans the continuum and transitional regimes, making the investigation of such flows extremely challenging. The present work applies a multiscale particle method to investigate the RGWT nozzle flow in a unified manner. Simulations reveal that the nozzle flow is underexpanded and characterized by rarefaction effects, and can be categorized into a central core and a surrounding region comprising the shock wave and boundary layer. This surrounding region occupies a significant portion of the nozzle exit, notably degrading flow quality. The wall suction technique increases the uniform flow radius by 11% at a total pressure of 500 kPa, while its effectiveness is limited at 50 kPa due to heightened rarefaction. Finally, a wall smoothing technique is proposed to improve the quality of nozzle flow by recognizing that strongly rarefied flows are governed by gas-surface interactions.

Aerospace doi: 10.3390/aerospace13060553

Authors: Yan Zhong Xiaoyan Lu Xinbin Zhao Yi Wang Fang Fang

Tail striking is a typical safety event in the area of civil aviation, which is directly related to the aircraft pitch angle at landing. Based on 2933 A319 flights’ non-exceedance quick access recorder (QAR) data from Dali airport, the relationship between key flight parameters during the final approach and landing pitch angle is explored. Functional data analysis and the Group Lasso method are used to select the most important flight parameters, and cluster analysis and weighted logistic regression are used to identify and predict a “high-risk” flight pattern. Here, “high risk” refers to a flight pattern associated with a higher probability of large landing pitch attitude, which is used as a proxy indicator of potential tail-strike risk rather than as evidence of an actual tail-strike event. Finally, flight operation recommendations are provided. The research results indicate that the airspeed, pitch angle and engine speed are most closely related to the landing pitch angle. An unusually high-risk flight pattern is identified, characterized by “high airspeed, high attitude, low thrust” caused by improper energy management of light-load flights. About 32.4% of flights in this pattern land with “large landing attitude”, which means the landing pitch angle is larger than the 95% sample percentile. A prediction model for the high-risk pattern is established using QAR parameters at the heights of 500 ft, 450 ft, and 400 ft, with an accuracy rate of 99.7% on the test data. The prediction in advance at 400 ft can provide pilots with sufficient time to take necessary operations.

Aerospace doi: 10.3390/aerospace13060552

Authors: Peiqi Li Lingyi Sheng Dingcheng Hu Yanhua Zhang Zhe Li Haozhe Zhong Dengcheng Zhang

Accurately obtaining aircraft aerodynamic parameters is essential for improving flight performance, optimizing design and control strategies, and ensuring flight safety. In this study, the improved Northern Goshawk Optimization (SPNGO) algorithm is used to optimize the kernel parameters and regularization coefficients of the Kernel Extreme Learning Machine (KELM). To address the defects of the original NGO algorithm, such as insufficient global optimization ability and being prone to falling into local optimums, two improvement strategies are proposed. The enhanced SPNGO algorithm is verified by 14 benchmark test functions, and the proposed SPNGO-KELM model is evaluated using open-source F-16 nonlinear simulation data for longitudinal aerodynamic parameter identification. The results demonstrate its effectiveness under the considered simulation conditions, while further validation with real flight-test data is required before application to actual flight environments. Comparative analysis with KELM, NGO-KELM, SSA-KELM, and WOA-KELM models shows that a single KELM is difficult to achieve high-precision aerodynamic parameter identification, and other comparison models have obvious fitting deviations in non-steady-state and strong nonlinear regions. Notably, the SPNGO-KELM model achieves the best identification performance, with a determination coefficient (R2) of 0.96537 and a mean absolute percentage error (MAPE) as low as 3.1574%. Its comprehensive identification accuracy is 1.81% to 37.98% higher than that of the comparison models, and it can effectively suppress error oscillations in nonlinear regions. Experimental results show that the proposed algorithm has excellent identification accuracy, generalization ability, and anti-interference performance.

Aerospace doi: 10.3390/aerospace13060551

Authors: Shaofeng Bu Wenming Xie Xiaodong Peng Xuchen Shen Jingyi Ren Runnan Qin

Long-term station-keeping of stratospheric airships is challenged by strong time-varying wind fields, pronounced vertical stratification of wind speed and direction, and limited onboard energy. Existing reinforcement-learning approaches typically rely on instantaneous observations to make reactive decisions and therefore struggle to deliver foresighted control in dynamic environments. This paper proposes a Spatio-Temporal Foresight Reinforcement-Learning framework (STF-RL) that explicitly incorporates future wind information. A Transformer is introduced to model multi-step, multi-altitude forecast wind sequences, and a time–height dual positional encoding is designed to characterize both the temporal evolution and the vertical structure of the wind field. A task-conditioned attention pooling mechanism then extracts the future-wind features most relevant to the current state, which are concatenated with the airship state and fed into an actor–critic network to enable foresighted policy learning. A continuous action space supporting three-dimensional maneuvering is constructed, together with a multi-objective reward that jointly accounts for station-keeping performance, energy consumption and safety. Experimental results show that the proposed method outperforms baseline approaches in station-keeping performance, trajectory stability and energy-utilization efficiency, while exhibiting strong robustness across different wind-field conditions.

Aerospace doi: 10.3390/aerospace13060550

Authors: Fabian Nicolas Peter Marc Engelmann Meriem Fikry Michael Lüdemann Leonard Moser Christopher Warsch Rafael Balderas-Xicohtencatl Adnan Muslić Elif Erden Mirko Hornung Tobias Welsch Florian Schültke Eike Stumpf Samarth Kakkar Wolfgang Heinze Matthias Haupt Rolf Radespiel Vivian Kriewall Peters Thimo Bielsky Frank Thielecke Nicolas Moebs Andreas Strohmayer

This paper presents an integrated assessment of liquid hydrogen as an aviation energy carrier, covering fuel production, aircraft performance, and fleet-level climate impacts. The results, based on the H2Avia research project, indicate substantial potential for reducing life-cycle global warming impacts compared to conventional kerosene. The analyses conducted for the interdisciplinary assessment are presented. The analysis shows that the use of liquid hydrogen eliminates CO2 emissions during fuel burn, resulting in a significant reduction in global warming potential compared to conventional kerosene, despite remaining upstream emissions from production and transport. The aircraft application cases and the applied technologies assessment scenario are described. The modeled technologies essential for the hydrogen aircraft are discussed, and exemplary values are given. Integrated overall aircraft performance results are given and discussed. At the aircraft level, hydrogen-based aircraft require an 8–18% increase in design mission block energy compared to a 2040 kerosene baseline yet still achieve a reduction in effective global warming potential of 55–86% comparing a representative pair route between Europe and North America (6730 km). An overview of the fleet modeling approach and the applied scenarios is given. For a scenario with energy cost and climate impact as equally weighted minimization goals, the global fleet analysis yields a global warming potential reduction of 60% compared to the non-liquid hydrogen baseline scenario. Overall, the results suggest that liquid hydrogen-powered aircraft can deliver significant mission- and fleet-level reductions in global warming potential and thus represent a promising pathway for achieving long-term aviation climate targets.

Aerospace doi: 10.3390/aerospace13060549

Authors: Dajiang Song Weijun Pan Zirui Yin Boyuan Han Huafei Gao

Remote tower operations require air traffic controllers to maintain continuous visual monitoring and integrate information from panoramic displays, radar data, flight strips, and voice communication. Such screen-mediated and sustained surveillance tasks may lead to covert fatigue, which is difficult to capture using a single physiological or behavioral signal. To address this issue, this study proposes a Gated EEG–Eye Fusion Network (GEEF-Net) for window-level fatigue detection in remote tower controllers. EEG and eye-tracking signals were synchronously collected during simulated remote tower tasks and segmented into 5 s windows with a 2 s step. For each window, 53 EEG features and 47 eye-tracking features were extracted to construct a 100-dimensional multimodal representation. GEEF-Net adopts a lightweight modality-gating mechanism to adaptively weight EEG and eye-tracking representations before fatigue classification. Under the main subject-dependent validation setting, GEEF-Net achieved an Accuracy of 0.883, an F1-score of 0.788, and a ROC-AUC of 0.944, outperforming EEG-only, eye-only, and early-fusion baselines in most overall metrics. The gating analysis indicated that eye-tracking features received a higher average weight than EEG features, suggesting the importance of visual behavior in remote tower fatigue detection. Cross-subject validation showed that individual differences remain a major challenge, while few-shot subject-specific calibration improved model adaptation when limited target-subject samples were available. These findings suggest that EEG–eye-tracking fusion with lightweight modality gating is a feasible approach for fatigue detection in simulated remote tower tasks. However, larger datasets and operationally realistic validation considering shift work, circadian effects, and operational pressure are still required before the approach can be considered operationally reliable.

Aerospace doi: 10.3390/aerospace13060548

Authors: Chengyuan Pang Zongpu Li Le Ru Jiaxu Chen Fan Sun

To address the problems of state estimation bias, dynamic threat response lag, and insufficient safety margin in formation coordination caused by the mismatch between the three-dimensional continuous motion model and the discrete sampling characteristics of sensors in UAV multi-aircraft collaborative inspection missions under complex dynamic environments, this paper studies a trajectory planning method that integrates model predictive control and multi-constraint optimization. By constructing a three-dimensional continuous motion model of the UAV and discretizing it using the Euler integral method, the mapping deviation between the continuous motion characteristics and the discrete working mechanism of the airborne system is solved. Based on the model predictive control method, a patrol trajectory tracking planning model is designed, and state increment and integral augmentation strategies are introduced to transform global reference trajectory tracking into a constrained quadratic programming problem in the rolling time domain, achieving high-precision closed-loop tracking. Furthermore, a dynamic environment model coupling static terrain height field and sudden spherical threat is constructed to systematically characterize the static obstacles and random dynamic threats faced by the UAV in complex scenarios such as mountains and hills. On this basis, multiple constraints such as flight altitude, pitch angle, horizontal turning angle, terrain safety margin, and multi-aircraft collision avoidance are integrated to establish a comprehensive objective function that includes range cost, attitude penalty, and safety cost. Through a collaborative mechanism of global optimization and local online correction, a reference trajectory that meets the requirements of formation safety and flight efficiency is generated and used as the input command for the tracking planning model, forming a closed-loop architecture of global optimization generation, local closed-loop tracking, and dynamic real-time correction for trajectory planning. Experimental results show that the success rate of dynamic obstacle avoidance in complex dynamic environments is always higher than 99.9%, and the mean square error of trajectory tracking is stable in the range of 0.02–0.04 km, which verifies its significant advantages in dynamic adaptability, tracking accuracy and formation safety.

Aerospace doi: 10.3390/aerospace13060547

Authors: Dmytro Tiniakov Krittisak Limtrakul

This paper introduces a refined criterion for evaluating and optimizing the aerodynamic efficiency of compound planform wings, specifically those whose half span is formed by multiple trapezoidal segments. While elliptical lift distribution is known to minimize induced drag, practical manufacturing constraints have led to widespread adoption of tapered wings. However, conventional single-trapezoid planforms deviate significantly from the ideal elliptical distribution, resulting in increased induced drag and reduced fuel efficiency. This study proposes an adjustment to the ellipticity factor, enabling quantitative assessment of how well a multi-trapezoid wing approximates elliptical chord distribution. The methodology is validated through analysis of existing transport aircraft, identifying configurations with ellipticity factors below 5% (e.g., Lockheed C-5A, Antonov An-124) that achieve near-optimal induced drag performance. A comparative case study of a virtual 40-ton aircraft with a 100 m2 wing area quantifies trade-offs between three planform configurations. Computational fluid dynamics simulations confirm that increasing trapezoidal segmentation improves spanwise loading and delays flow separation. Results demonstrate that two-trapezoid configurations with total inverse taper ratios of 3.3–4.2 and break coordinates at 35–45% half span achieve ellipticity factors under 7%, offering an optimal balance between aerodynamic efficiency, structural feasibility, and tail surface requirements. The proposed criterion provides aircraft designers with a rapid, computationally efficient tool for planform optimization at the conceptual design stage. The proposed criterion is valid for subsonic cruise conditions (M ≤ 0.85) and does not account for wave drag or aeroelastic effects.

Aerospace doi: 10.3390/aerospace13060546

Authors: Yanxiang Ren Fengnan Guo Pengfei Liu Zhongyu Yuan Hui Zhu Hongfeng Ji

To address the time-consuming and labor-intensive procedures associated with traditional approaches for evaluating the integrated burning rate of wire-embedded propellants in solid rocket motors (SRMs), this study proposes an efficient and reliable prediction method. This new method is based on an improved burning-rate–initial-temperature correlation, achieved through Abaqus-Python secondary development that enables fully automated geometric modeling, transient heat-transfer analysis, and temperature-field extraction for wire-embedded propellants. The relative error between the present method and the experimental results is less than 5%. The accuracy and engineering applicability of the present method are verified. The effects of the material parameters and wire diameters on the integrated burning rate is investigated. The results indicate that wires of different materials exhibit substantial variations in burning-rate enhancement efficiency, with smaller diameters and higher thermal diffusivity producing stronger enhancement effects. When the specific heat capacity and density are held constant, the integrated burning rate increases monotonically with the wire’s thermal conductivity, though the growth trend gradually approaches saturation. In contrast, the influences of the wire’s specific heat capacity and density are comparatively weak. The integrated burning rate prediction framework developed in this study demonstrates strong versatility and scalability. It enables rapid performance evaluation of propellants embedded with wires of various sizes and thermophysical properties, providing valuable theoretical guidance and practical tools for the design and optimization of wire-embedded solid rocket motors.

Aerospace doi: 10.3390/aerospace13060545

Authors: Luanwei Chen Hua Gao Xinxin Lai Sheng Yu Zixuan Wu Junfeng Zhang

Adverse weather conditions, particularly thunderstorms, are the primary cause of flight delays and safety threats, accounting for approximately 58.7% of irregular flights in 2025. Traditional static rerouting methods often fail to adapt to the non-linear evolution of convective weather. This paper proposes a high-fidelity dynamic rerouting framework to enhance flight safety and efficiency. In the perception layer, a RainNet deep learning model is employed for short-term recursive nowcasting of radar reflectivity, which is subsequently transformed into Dynamic Avoidance Zones (DAZ) via clustering and convex hull algorithms. In the decision layer, a two-stage improved Genetic Algorithm (GA) is developed to solve the rerouting path. The first stage generates initial collaborative solutions under a receding-horizon framework, while the second stage applies a “path-straightening” module to reduce cumulative turning angles and curvature fluctuations. The comparative results in actual scenarios demonstrate a distinct dual-advantage over baseline methodologies. Compared to sampling-based strategies, the proposed model reduces the path length by 14.79%. Furthermore, when compared to heuristic algorithms, it actively trades a negligible 1% distance margin to achieve a massive 92.7% reduction in the cumulative turning angle. With a maximum single turn of only 32.51°, the trajectory completely eliminates sawtooth jitter and redundant detours. Ultimately, this research provides essential technical support for improving air traffic management efficiency and reducing controller workload during severe weather events.

Aerospace doi: 10.3390/aerospace13060544

Authors: Weijian Pang Jun Zhou Jingwen Xu Xinian Zhi

Microsatellites operate in highly dynamic thermal environments due to severe physical constraints, making temperature telemetry a critical onboard health indicator. Conventional threshold-based monitoring fails to distinguish normal operational mode transitions from genuine faults, causing excessive false alarms. To address this, we propose a two-stage framework integrating unsupervised thermal mode discovery with mode-specific deep learning prediction. Raw temperature telemetry is downsampled and segmented into orbital cycles. Unsupervised clustering identifies two nominal thermal regimes and four canonical fault-type libraries (step, spike, drift, and noise), each corresponding to distinct in-orbit failure mechanisms. For each nominal mode, a Convolutional Neural Network–Long Short-Term Memory (CNN-LSTM) is trained on 7-day historical windows to forecast 3-day temperature evolution. Post-downlink, incoming cycle mode is inferred via nearest-neighbor DTW classification; anomalies are flagged when prediction residuals exceed mode-adaptive thresholds. Validation on Macau Science Satellite-1B (MSS-1B, COSPAR 2023-069-B, NORAD 56732) in-orbit telemetry from a 41° inclination low-Earth orbit—where solar illumination dominates external thermal loading and internal heat from the data-communication module and scientific payload constitutes the primary internal thermal source—shows the method reduces anomaly flags by 96.6% and improves prediction mean absolute error by 51.3% compared to a non-classified global baseline under nominal operating conditions, correctly detecting a known operational transient while suppressing spurious alarms. A synthetic fault injection experiment with four anomaly types and five baseline methods further confirms the framework’s detection capability, achieving an overall F1 score of 0.725 vs. 0.258 for the global baseline—a 2.8× improvement driven primarily by a 4× precision gain. Sensitivity analysis reveals that the two-stage advantage is most pronounced for low-magnitude and short-duration faults, where mode-specific context is essential. This work advances microsatellite autonomous health management by providing reliable anomaly detection with quantified fault detection performance.

Aerospace doi: 10.3390/aerospace13060543

Authors: Wei Zhou Jing Zhou Yulong Zhang Peiyang Ma Zhigao Xu Shan Li Qiuyan Wang

Historically, in the initial stages of solid rocket motor (SRM) development, performance parameters, such as specific impulse, total impulse, mass, and thrust, have been prioritized, with cost considerations often treated as secondary. Consequently, SRM performance optimization under cost constraints has emerged as a central objective in aerospace propulsion. To address this gap, this study establishes a cost–performance evaluation model for SRMs. A Kriging surrogate model, the Non-dominated Sorting Genetic Algorithm II (NSGA-II), and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) are leveraged to minimize the manufacturing cost and maximize the terminal velocity of SRM engines, subject to constraints associated with the maximum operating pressure of the combustion chamber and burn time. First, a cost–performance calculation model for an SRM is developed and validated. Subsequently, Pearson correlation analysis and Sobol-based global sensitivity analysis are combined to reduce the dimensionality of the design parameters, and optimal Latin hypercube sampling is used to generate the training samples. Building on this foundation, a Kriging surrogate model is constructed. The cost–performance model of the SRM is subjected to multi-objective optimization using NSGA-II and TOPSIS to support decision-making. The results indicate that the proposed cost–performance calculation model achieves an error below 5%, demonstrating high accuracy. Among the design parameters, the combustion chamber length, nozzle outlet area, and expansion ratio significantly influence the cost and performance of SRMs. The surrogate models exhibit strong predictive accuracy, with coefficients of determination exceeding 0.9. The optimized TOPSIS scheme yields a performance improvement of 10.94% with a cost increase of 4.15% compared with the reference scheme. In summary, the cost–performance evaluation and optimization framework established in this work provides quantitative decision support for SRM design under cost constraints, and the integrated methodology can be extended to other aerospace propulsion systems or complex engineering equipment. This contributes to achieving synergistic optimization of performance and cost under resource limitations, and offers practical guidance for advancing affordability-driven design in propulsion engineering.

Aerospace doi: 10.3390/aerospace13060542

Authors: Jiao Xu Hong Tao Defu Lin

This research focuses on a cooperative guidance scenario involving multiple unmanned aerial vehicles (UAVs). The objective is to achieve a simultaneous interception of a maneuvering target while maintaining strict constraints on the relative geometry. To tackle this challenge, we introduce a distributed optimal spatial–temporal cooperative pursuit strategy. Initially, the impact angles and interception times for each UAV are analytically predicted based on the augmented ideal proportional navigation (AIPN) guidance scheme. Subsequently, we employ an optimal distributed consensus protocol to synchronize the UAVs, ensuring they converge on the target at the same time while preserving a predetermined intercept geometry. The proposed method offers significant advantages in a distributed framework, notably reducing control energy consumption by approximately 63.0% compared to an existing state-of-the-art cooperative guidance law. Comprehensive simulations are conducted to validate the energy efficiency of the approach.

Aerospace doi: 10.3390/aerospace13060541

Authors: Zhenyu Jin Zhong Ma Haibo Yang Shengbao Wu Zengqiao Tan Xiaoyu Tao

Rapid advances in on-orbit servicing technologies have driven exponential growth in micro-spacecraft on-orbit ejection missions. Post-separation attitude disturbances are the dominant factor determining mission success, requiring accurate and rapid disturbance prediction. This study develops an efficient multi-rigid-body dynamic simulation framework for on-orbit ejection based on the simulation software ADAMS. Contact parameters between the micro-spacecraft and guide rail are calibrated against high-fidelity rigid–flexible coupled simulation results from the simulation software LS-DYNA, establishing a streamlined simulation pipeline. Using this validated framework, the effects of thrust misalignment angle, thrust eccentricity, and mass eccentricity on ejection-phase attitude disturbances are systematically quantified. Results demonstrate that the calibrated ADAMS multi-rigid-body model effectively substitutes computationally intensive rigid–flexible coupled models without sacrificing predictive accuracy. Specifically, constraining the axial thrust misalignment angle to ≤0.2°, axial thrust eccentricity to ≤0.4 mm, and axial mass eccentricity to ≤0.2 mm can significantly enhance separation attitude stability. This work provides a practical and efficient engineering methodology for the rapid assessment of attitude disturbances in micro-spacecraft on-orbit ejection systems. However, this study is limited to analyzing the ejection phase of separation, neglecting attitude disturbance effects in the subsequent orbital flight and target impact phases. Future work will address these omissions by extending the model to the entire mission profile and quantifying associated uncertainties.

Aerospace doi: 10.3390/aerospace13060540

Authors: Feng Deng Jianmiao Yi Guanhua Chen Ning Qin

This paper presents the design of shock control bumps on a double-fuselage aircraft with a natural laminar flow (NLF) wing section. Both two-dimensional (2D) and three-dimensional (3D) bumps were investigated to identify the high-impact factors on both shock control and natural laminar flow for the aircraft, and to understand the associated flow physics. Firstly, two key geometric parameters, namely the bump crest location and the bump height, were optimized to trade off shock control and laminar flow. The optimized 2D bump results in 8.19% total drag reduction in the wing section, specifically, 8.61% pressure drag reduction and 6.23% viscous drag reduction. The total drag coefficient of the aircraft reduces by 8.12 counts while the lift slightly increases. Then, the robustness of the bump at off-design conditions was verified as well. Finally, the 2D bump was converted to 3D bumps according to the transonic area rule to explore more alternative designs, and it was found that the two have similar performances, confirming the effectiveness of the transonic area rule applied in the shock-control-bump design.

Aerospace doi: 10.3390/aerospace13060539

Authors: Fajia Sheng Dengxue Song Hexia Huang Huijun Tan Xiankai Li Zhiyu Zhang

To investigate the flow characteristics of three-dimensional swept interactions, 3D steady Reynolds-averaged Navier–Stokes (RANS) simulations are conducted at an incoming Mach number of 3.5 and a Reynolds number of 30,955 based on the incoming boundary-layer thickness δ0. Three independent compression configurations with a total compression angle of 18° are analyzed and compared: planar swept shocks, curved swept shocks featuring an initial 2° deflection step followed by a continuously curved compression surface, and continuous isentropic compression waves. The results demonstrate that, unlike the baseline planar case, the interactions induced by both curved swept shocks and isentropic compression waves depart from the canonical quasi-conical similarity and transcend existing topological classification frameworks. These non-planar interactions are characterized by large-scale primary vortices and small-scale corner vortices that evolve along curved trajectories downstream. Quantitatively, the curved shock interaction yields maximum normal scales of 5.4δ0 for the primary vortex and 1.8δ0 for the corner vortex—significantly more compact than the 6.7δ0 and 7.5δ0 observed in the planar-shock interaction. Furthermore, the specific modality of compression—whether by discrete shock or continuous wave—exerts a profound effect on aerodynamic performance. Under the present conditions, while isentropic compression achieves the highest compression efficiency and planar shocks provide superior mass flow capture, curved shock compression strikes a favorable balance between these competing metrics. Curved shock configurations may offer potential for improving integrated inlet performance through appropriate adjustment of the initial shock strength.

Aerospace doi: 10.3390/aerospace13060538

Authors: Rui Hong Jiahao Li Han Pan Qian Wang

Satellite object detection in space surveillance is challenged by sparse and weak targets in large-scale, structured backgrounds (e.g., star fields, clouds, and streak noise). Such interference is not random but exhibits spatial correlation and frequency regularity, causing target responses to be overwhelmed and difficult to separate within a single representation space. To address this issue, we propose a lightweight framework, termed DRSS-Net, based on the key observation that target–background separability can be enhanced across complementary representation coordinate systems. Specifically, spatial modeling captures local structural consistency, while frequency-domain processing characterizes global energy distribution and structured patterns. By alternating between these domains, the proposed method enables constraint propagation, where predictable background patterns are suppressed, and structurally inconsistent target responses are emphasized. In the spatial domain, a mutual conditioning mechanism with asymmetric channel allocation enhances the consistency between localization and semantic responses. In the frequency domain, a coupled refinement module models the interaction between energy distribution and structural configuration to distinguish structured background from anomalous targets. In addition, a scale selection strategy retains stable intermediate representations for efficient detection. Experiments on two independent space target datasets demonstrate that DRSS-Net consistently achieves superior detection performance with a compact model size under diverse observation conditions, including variations in target appearance, illumination, and structured background interference.

Aerospace doi: 10.3390/aerospace13060537

Authors: Rui Su Xiangxi Wen Shuangfeng Li Youfu Chen Wenda Yang

This paper presents a cooperative trajectory planning method for multiple aircraft avoiding thunderstorms, formulated within a game-theoretic optimal control framework. We model the multi-aircraft system as a non-cooperative game and employ an Iterative Best Response (IBR) algorithm to decompose the coupled planning problem into a series of single-agent, nonlinear optimal control subproblems. Each subproblem is solved using the CasADi framework, enabling the continuous and simultaneous optimization of both aircraft velocity and heading. This approach directly generates smooth, dynamically feasible 4D trajectories that satisfy strict on-time arrival constraints at each waypoint, addressing a key limitation of many existing methods. Our simulations show that the framework not only ensures safe separation from thunderstorms and other aircraft but also effectively manages arrival times, with errors on the order of seconds. These results demonstrate the method’s capability to produce safe, efficient, and punctual trajectories for complex multi-aircraft encounters in dynamic weather.

Aerospace doi: 10.3390/aerospace13060536

Authors: Qunting Yang Bingqing Liu Chunsheng Xie Zhang Wen

Existing unmanned aerial vehicle (UAV) urban logistics planning follows a sequential paradigm—depot siting first, routing second—that embeds a structural information loss. Straight-line distance screening systematically overestimates the feasible service radius of candidate depots, creating a blindzone of depot–demand pairs that appear reachable but prove operationally infeasible under road network distances. We term this range-feasibility blindness and derive its analytical radius Δ=Rmax(α−1)/(2α), where α is the road-to-straight-line distance ratio. Empirical measurement across three Chinese urban districts confirms α∈[1.40,1.52] and blindzone radii exceeding 2.8 km, establishing the phenomenon as a systemic property of high-density urban road geometry. To eliminate this failure by construction, we formulate a feasibility-embedded location–routing mixed-integer linear programme (MILP) that enforces road network range constraints simultaneously with depot opening decisions, making blindzone configurations implicitly inadmissible. A structure-aware Adaptive Large Neighbourhood Search (ALNS) solves the model at practical scales. Benchmark experiments on Dongli District (Tianjin) show cost reductions of 20.6–28.2% over greedy sequential baselines across three demand scenarios, with gains increasing monotonically with instance scale; cross-city experiments in Beijing and Shanghai confirm consistent improvement averaging 11.4% (Chaoyang, Beijing) and 10.2% (Pudong, Shanghai) over greedy initialisation across diverse urban morphologies. These results position joint optimisation as a necessary methodological shift for city-scale UAV infrastructure planning.

Aerospace doi: 10.3390/aerospace13060535

Authors: Massimiliano Zanin

Delays are among air transport’s main operational challenges, with significant economic, societal and environmental consequences, and many methodological alternatives have been used in their study. Here we explore the use of symbolic regression, a data-driven technique that searches a space of analytic expressions to identify compact and interpretable models explaining a given set of data. We specifically use symbolic regression to characterise delays at the busiest European airports, how they evolve in time and depend on their own past, up to how they propagate across airports. This is done with the aim of evaluating the feasibility of using this approach, and the added value when compared to standard statistical and causal models. Results of this proof of concept point to a nuanced picture: while symbolic regression demonstrates clear potential for uncovering interpretable functional relationships in delay dynamics, its applicability is hindered by the significant computational cost and its stochastic nature.

Aerospace doi: 10.3390/aerospace13060534

Authors: Qi Wang Zhe Hu Tianyi Wang Shusen Yuan Lei Zhang Wenjun Yi

To address the limitations of existing sliding mode-based integrated guidance and control (IGC) schemes, such as chattering, input saturation, and insufficient robustness, this paper proposes a three-dimensional IGC design method incorporating both terminal angle and attitude angle constraints. First, a control-oriented six-degrees-of-freedom model is established based on three-dimensional relative motion and vehicle dynamics, and the control objectives for maneuvering target interception under multiple constraints are clarified. Subsequently, a finite-time terminal sliding mode guidance law based on time-to-go (TGO) is integrated with dynamic surface control to construct the IGC framework. In this design, command filters are introduced to overcome the “explosion of complexity”, while amplitude saturation functions are employed to constrain system states and control inputs. Meanwhile, a generalized super-twisting extended state observer (GSTESO) is incorporated to estimate and compensate for lumped uncertainties in the system. Finally, by combining Lyapunov stability theory with an integral barrier Lyapunov (IBL) function, it is proven that the closed-loop system is uniformly ultimately bounded and satisfies the terminal angle constraints. Comparative simulations under multiple disturbance scenarios demonstrate that the proposed method meets the accuracy requirements in terms of miss distance and LOS angle error. Moreover, it alleviates high-frequency chattering and prevents control-input saturation, showing improved robustness and disturbance rejection capability compared with the baseline methods. Therefore, the proposed approach provides a valuable reference for engineering applications of three-dimensional IGC in maneuvering target interception.

Aerospace doi: 10.3390/aerospace13060533

Authors: Jia Peng Yarong Wu Chenjie Wei Yang Ou Hao Wang Miaomiao Zhu

Multi-runway sequencing of unmanned aerial vehicles (UAVs) at temporary disaster relief aerodromes presents a priority-heterogeneous scheduling problem under class-asymmetric wake turbulence constraints. We formulate this as a priority-weighted Markov decision process with a deliberately minimalist reward—per-step class weights for completed landings, with no shaping or hand-crafted safety logic—and extend it with per-UAV operational deadlines (encoding en-route endurance consumption) and per-runway queue capacity constraints that produce a non-trivial action mask. We train a Proximal Policy Optimisation (PPO) agent and benchmark it against six baselines spanning deterministic optimisation (Joint-LA-1), stochastic lookahead (Stochastic-LA), and online tree search (MCTS). Across 100 paired evaluation episodes, PPO matches the operational standard Priority-FCFS within 2.7% (p = 0.124, not significant); Joint-LA-1, the strongest non-learned baseline, outperforms PPO by 3.2% (p = 0.043). Despite near-identical aggregate throughput, PPO autonomously develops a runway specialisation pattern—concentrating 60% of high-priority landings on a single strip while routing 93% of emergency arrivals to the remaining strips—that emerges entirely from the reward signal. Under looser deadlines, the PPO–PFCFS gap narrows to −0.5%, and wake symmetry ablation reveals that PPO outperforms Priority-FCFS by 46.5% when the asymmetric wake structure is removed. These results demonstrate that priority-aware capacity reservation can emerge without embedded domain knowledge, and that simple heuristics are near-optimal under tight operational constraints—a finding with direct implications for autonomous scheduling in disaster relief aviation.

Aerospace doi: 10.3390/aerospace13060532

Authors: Wencheng Ma Shuai Jiang Zhengzheng Yin

Over the course of long-term operation, wear to moving parts can significantly affect the dynamic behavior, reliability and service life of landing gear retraction and extension systems. The primary innovation of this paper is the proposal of a multi-body rigid-body dynamics modeling method for LGRES that accounts for irregular wear clearances, along with an analysis of its dynamic response under different system parameters. First, an exact dynamic model of the LGRES with joint clearance is developed. Secondly, the Archard wear model is introduced to characterize the wear evolution of the joint surfaces. Finally, the dynamic behavior of the mechanism under different wear cycles, initial clearance values, and drive speeds is compared to analyze the impact of these system parameters on wear characteristics. The results indicate that as these system parameters increase, wear significantly amplifies the impact forces on the joint and further exacerbates wear between the hinge pin and the bearing, as well as motion errors.

Aerospace doi: 10.3390/aerospace13060531

Authors: Shijie Zhai Wenhua Cheng Tinghua Zhang

The high-precision celestial positioning of space targets is constrained by star point centroid errors, star identification errors, and residual distortions in wide-field imaging. To improve the positioning accuracy and robustness under complex stellar-field conditions, this study focuses on improving star point centroid extraction and star identification. For star point centroid extraction, an improved effective point spread function (ePSF) fitting method is adopted to construct an ePSF model consistent with the actual imaging process, which characterizes the instrumental response, pixel sampling, and stellar intensity distribution, thereby improving the accuracy of sub-pixel centroid extraction. For star identification, a two-level matching method combining the inradius of star triangles and angular-distance constraints is proposed. Candidate screening, angular-distance constraints, and posterior validation based on a theoretical reference star map are used to reduce redundant matches and mismatching risks. Experiments on simulated star images show that the star identification success rate of the proposed method reaches 97.32%, outperforming traditional algorithms. In real star images, the star identification precision, star identification completeness, and F1 score are 93.59%, 90.14%, and 91.83%, respectively. When the 20-constant plate model is adopted, the average positioning errors of simulated and real star images are reduced to 0.86″ and 1.10″, respectively. Further increasing the model to 30 constants provides limited accuracy gain, which is insufficient to fully offset the cost of increased model complexity and parameter stability. The results show that the proposed method achieves a favorable balance among positioning accuracy, identification reliability, and model complexity.

Aerospace doi: 10.3390/aerospace13060530

Authors: Hanxin Lin Bing Yu Jia Guo Hongjian Zhang Caishan Liu

Clamp band separation mechanisms are widely used in spacecraft interfaces, and the clamp band preload is a key factor governing both connection reliability and separation performance. The conventional torque-control method is susceptible to friction-induced preload non-uniformity in clamp band separation mechanisms. To overcome this limitation, thermal preloading has been proposed as an alternative installation method. In this paper, a thermo-mechanical analytical model is established for clamp band separation mechanisms during thermal preloading based on curved-beam and thin-shell theories. Theoretical analysis shows that the preload distribution can be divided into three characteristic zones: a stick zone, a slip zone, and a separation zone. In the stick zone, the preload remains constant and is mainly governed by thermal stress and structural relative stiffness. In the slip zone, friction dominates the load transfer, leading to a non-uniform preload distribution. In the separation zone, local disengagement occurs near the clamp band joint end due to the eccentricity-induced bending moment. The proposed model is validated by finite element simulations, and parametric studies are conducted to reveal the effects of friction coefficient and structural geometric parameters on preload distribution. Based on the theoretical model, a zoned-heating method is proposed to improve preload uniformity, providing a useful reference for optimizing the thermal preloading method.

Aerospace doi: 10.3390/aerospace13060529

Authors: Yuntao Hua Ning Zhang Yingyong Shen Shengxin Sun Hutao Cui Wenlai Ma

Extreme cyclic temperature fluctuations (−200 °C to 200 °C) and inherent clearance nonlinearity in deployment hinges severely threaten the on-orbit deployment accuracy and dynamic stability of large variable-geometry spacecraft antennas for geosynchronous Earth orbit applications. However, current modeling approaches suffer from three critical limitations: single-configuration models requiring manual switching, there are inherent geometric nonlinear errors from conventional floating frame formulations, and incomplete thermo-mechanical coupling neglects the temperature effects on contact stiffness and friction. To address these gaps, we propose a unified high-fidelity dynamic model based on the Absolute Nodal Coordinate Formulation (ANCF). This model eliminates geometric errors and mesh mismatch, enables seamless multi-configuration deployment without switching, and fully incorporates temperature-dependent material properties and nonlinear contact forces. An improved Hilber–Hughes–Taylor-α implicit integration algorithm with second-order accuracy and unconditional stability is adopted to solve the strongly nonlinear differential-algebraic equations. Numerical results demonstrate that the proposed model achieves a calculation error below 3% against experimental data, significantly outperforming the traditional floating frame of reference formulation with an error of 15–22%. Non-uniform temperature fields increase thermally induced vibration amplitudes by 32–45%, and every 0.1 increase in the friction coefficient raises the impact force at the clearance hinge by 15–20%. The proposed unified modeling framework provides a solid theoretical basis for deployment stability prediction and the on-orbit control optimization of large variable-geometry spacecraft antennas.

Aerospace doi: 10.3390/aerospace13060528

Authors: Ryota Kinjo Sota Watanabe Ananda Rafi Dhaifan Masashi Wakita Harunori Nagata

This study experimentally investigated the effect of characteristic chamber length, L∗, on combustion efficiency and stability in CAMUI-type hybrid rockets using 70 wt% and 80 wt% hydrogen peroxide under non-catalytic spray-injection conditions. Combustion tests were conducted by systematically varying L∗ through changes in the nozzle throat diameter while maintaining the combustor volume constant. For both oxidizer concentrations, the characteristic exhaust velocity efficiency, ηc∗, increased with increasing L∗. The 70 wt% cases required a larger L∗ than the 80 wt% cases to achieve comparable efficiency, and flame blowoff occurred in the low-L∗ region. The normalized RMS pressure fluctuation was also larger for the 70 wt% cases, particularly in the low-L∗ region, indicating lower combustion stability. These results indicate that reducing the hydrogen peroxide concentration increases the L∗ required to maintain stable and efficient combustion. As a key outcome of this study, stable and efficient combustion of 70 wt% hydrogen peroxide was demonstrated without catalytic assistance when a sufficiently large L∗ was provided. These results demonstrate the capability of the CAMUI-type combustor to extend stable operation toward lower oxidizer concentrations and experimentally clarify the concentration-dependent L∗ requirement as a practical design guideline for catalyst-free hydrogen peroxide hybrid rockets.

Aerospace doi: 10.3390/aerospace13060527

Authors: Devansh Joshi Timothy Newson Gordon R. Osinski

Recent technological advances and the reinvigoration of NASA’s Artemis program have increased the feasibility of lunar habitats and supporting infrastructure, necessitating the development of specialized foundation systems capable of maintaining stability under transferred structured loads. Site investigation techniques, including in situ testing, sampling, and geophysical mapping, must therefore be adapted for lunar conditions, while construction using regolith requires an improved understanding of lunar soil mechanics. Foundations must also endure extreme thermal fluctuations, reduced gravity, radiation exposure, micrometeoroid impacts, and lunar seismicity to ensure long-term performance. Consequently, enhanced knowledge of the monotonic and cyclic geotechnical behavior of lunar soils is essential. Owing to the limited availability of in situ testing opportunities and returned lunar materials, high-fidelity simulants that replicate regolith behavior are required for experimental studies. This research investigates the static behavior of several contemporary lunar simulants and compares their responses with terrestrial benchmark soils. The results indicate that the overall stress–strain trends of lunar simulants broadly resemble those of terrestrial soils; however, the particle morphology and distinctive mineralogical compositions, including basaltic and anorthositic constituents, yield higher values of certain geomechanical parameters. Comparison with terrestrial datasets further suggests that carefully selected benchmark soils may facilitate the development of a next generation of lunar simulants with improved fidelity to lunar regolith.

Aerospace doi: 10.3390/aerospace13060526

Authors: Jaewan Choi Younghoon Choi

In modern battlefields, the rapid advancement of Counter-UAV (C-UAV) technologies has made single-UAV missions increasingly difficult. This highlights the need for distributed swarm systems that can operate reliably under such threats. Among various swarm coordination methods, hierarchical leader–follower structures have been actively studied for battlefield environments with high risk of agent loss and limited communication. The Virtual Leader-based Formation System (VLFS), which follows this structure, enables formation through a virtual leader. It also introduces a novel collision avoidance approach that allows followers to avoid obstacles during formation flight. However, the conventional VLFS suffers from long convergence time with severe oscillations. In addition, it does not consider inter-UAV collisions and has demonstrated avoidance only in simple obstacle environments. To address these limitations, this paper proposes the VLFS-RF method, which directly integrates a repulsive function into the VLFS. The proposed method consists of four control modes that perform formation tracking, inter-UAV collision avoidance, and obstacle avoidance simultaneously according to the situation. Software-In-The-Loop (SITL) simulations were conducted in a ROS-Gazebo environment using V-shaped and hexagonal formations. The results show that the formation tracking error is reduced by approximately 59% compared to the conventional VLFS. In addition, inter-UAV collisions are prevented during initial convergence, and obstacles are successfully avoided in narrow passages and gaps between two obstacles. These results demonstrate that VLFS-RF is a practical formation control method for UAV swarms in complex environments.

Aerospace doi: 10.3390/aerospace13060525

Authors: Michał Szcześniak Robert Rogólski Aleksander Olejnik

The identification of natural vibration modes in turbomachinery components is essential to ensure safe and reliable operation, particularly with respect to resonance avoidance. In lightweight structures such as bladed disks, conventional contact-based measurement techniques may alter the dynamic response of the system. This study presents an experimental comparison of one-dimensional (1D) and three-dimensional (3D) laser Doppler vibrometry for non-contact modal analysis of a miniature turbofan engine rotor. The investigation focuses on measurement accuracy, experimental complexity, and the practical applicability of both approaches. Experimental tests were conducted on an isolated rotor of the DGEN-380 engine using a scanning laser vibrometer system. The obtained natural frequencies and mode shapes were compared for both techniques. The results indicate that, for vibration modes dominated by axial motion, the differences between 1D and 3D measurements are typically below 1%. At the same time, the 1D approach significantly simplifies the experimental setup and reduces measurement time. These findings suggest that 1D vibrometry can be effectively used in selected engineering applications, while 3D measurements remain necessary for the full spatial characterization of complex vibration modes.

Aerospace doi: 10.3390/aerospace13060524

Authors: Wei Xu Yuyang Liu Jie Ji Ye Tian Yachen Sun Wenhui Guo Jiahang Zhang Weilong Wang Jialin Zhang Weiwei Zhang Yafang Liu

The complex composition and extremely harsh, uncertain surface conditions on Mars impose stringent requirements on the coring performance and fault tolerance of a coring sampler. To satisfy the drilling and coring requirements of Martian soil–rock composite strata, a coring sampler capable of multiple repeated sampling operations is designed, which enables reliable acquisition and preservation of core samples. Drilling and coring experiments are conducted on simulated Martian soil with different particle size distributions and relative densities, as well as basalt specimens. The coring efficiency of the developed bit for Martian soil and rock under diverse working conditions, together with its wear characteristics during repeated coring, is systematically investigated. The results indicate that the proposed coring sampler structure is well adaptable to Martian soil–rock composite drilling. The coring mass of simulated Martian soil increases with increasing advance-to-rotation ratio and relative density, as well as decreasing median particle size. The coring mass of specimens with 91.7% relative density is significantly higher than that of 72.8%, and the maximum single coring mass of fine-grained pure regolith specimens reaches 19.32 g. During basalt coring, higher rotational speeds lead to more severe bit wear and more pronounced temperature elevation, with a peak temperature of 372.4 °C at 120 r/min. A rotational speed of 110 r/min achieves the best compromise between core integrity and bit service life, exhibiting excellent long-term operational stability and favorable cutting–rock-breaking matching performance. The results of this research provide a reference scheme and data support for future Martian soil–rock composite coring and drilling exploration missions.

Aerospace doi: 10.3390/aerospace13060523

Authors: Qian Wang Chong Jiang Shunli Li

To address the robustness of autonomous proximity trajectories in asteroid exploration missions under model uncertainties and external disturbances, this paper proposes a tube-based model predictive control (TBMPC) framework with disturbance identification for a six-degree-of-freedom nonlinear model. Specifically, the inner layer employs a sequential convex optimization-based nonlinear MPC framework to solve the nominal trajectory optimization problem, while the outer layer dynamically estimates the disturbance set using real-time measurement information through an online exogenous input identification mechanism and adaptively adjusts the size of the disturbance-invariant tube, thereby effectively reducing the conservatism caused by the fixed disturbance bounds in conventional TBMPC. In addition, a sensitivity analysis of the forgetting factor parameter is conducted to investigate the influence of different forgetting factor values on system performance. Finally, 100 Monte Carlo simulations are performed to further verify the robustness and stability of the proposed method under randomly bounded disturbances. The results show that all actual trajectories remain within the disturbance-invariant tube, demonstrating the good engineering applicability of the proposed method.

Aerospace doi: 10.3390/aerospace13060522

Authors: Anthony Freeman Reza Karimi John Elliott Damon Landau Matteo Clark Steven Zusack Alfred Nash Kelley Case Lizbeth B. De La Torre Jonathan Murphy Rashied Amini Mathieu Choukroun Carol Raymond Art Chmielewski

Sample return missions are among the most difficult tasks for robotic spacecraft in exploring our solar system. However, the samples they return to Earth have significantly high value for the planetary science community. Thus far, we have only acquired samples from the Moon, three asteroids, a comet’s tail, and the solar wind at the Earth–Sun Lagrange Points. The National Academy’s most recent decadal survey of planetary science at NASA emphasized the value of samples returned to Earth for analysis and called for NASA to prioritize samples returned from Mars, the Moon’s South Pole, a Jupiter-family comet, and Ceres. Currently available rockets and propulsion technology impose severe, and possibly insurmountable, limits to where we can send robot explorers and return samples within a reasonable timescale. Now, the advent of large new rockets offers the potential for very high C3 (characteristic energy) Earth escape trajectories. Parallel developments in Nuclear Propulsion yield much higher ISP than chemical propulsion and can operate far away from the Sun. Our novel trajectory modeling results and mission architecture analysis show that, by combining these technologies, sample return from across the solar system becomes feasible within the career lifetime of a planetary scientist.

Aerospace doi: 10.3390/aerospace13060519

Authors: Imanol Iriarte Estela Nieto Ramos Iñaki Iglesias Josu Del Río Joseba Lasa Santi Vilardaga Sergi Lucas Basilio Sierra

This article discusses a novel aircraft coordination algorithm for automated vertiport operation. New applications of Innovative Air Mobility (IAM) including inspection, logistics and security UAVs, Urban Air Mobility (UAM) or Regional Air Mobility (RAM) present a coordination challenge, especially near vertiports, as large numbers of vehicles with different characteristics share the airspace, and so avoiding collisions, optimizing resource usage and operating with low human intervention is important.In this paper, this problem is addressed by proposing a new formulation of the aircraft coordination problem that makes use of a discretized airspace to detect potential conflicts and collisions between cooperative and non-cooperative aircraft in the surroundings of a vertiport. The proposed algorithm not only considers the cells traversed by the aircraft, but also the set of adjacent cells, making the algorithm more conservative and robust than other algorithms found in the literature, and achieving a 100% conflict-detection rate. A mathematical model of aircraft dynamics is employed to turn high-level flight plans into detailed aircraft trajectories, using those trajectories to detect potential collisions. The deconfliction problem is formulated as a mixed-integer optimization program that computes orders of pass for every conflict while minimizing the divergence between requested time of arrival (RTA) and estimated time of arrival (ETA). This problem is implemented in OR-Tools to be solved by means of the CP-SAT solver. The validity of the solution is tested by extensive simulation, showing tactical coordination of up to 25 aircraft landing on a vertiport.

Aerospace doi: 10.3390/aerospace13060521

Authors: Manuel González Sandra Amarillo Alex Sanchis Juan Vicente Balbastre

The rapid expansion of Unmanned Aircraft Systems (UAS) operations has created an urgent need for scalable strategic conflict resolution methods within the U-space framework. When requested 4D flight plans overlap with previously authorised ones, the Flight Authorisation Service denies the request and can provide the UAS operator with an alternative, conflict-free route. While traditional pathfinding algorithms ensure optimal routes, their computational cost creates a critical bottleneck during the flight activation phase or emergency missions, which demand near-instantaneous responses. To address this, we propose a three-stage framework. First, an Octree spatial partitioning discretises the airspace to identify occupied cells. Second, both A* and JPS algorithms are implemented to establish an optimal reference route. Finally, a standard Deep Reinforcement Learning (DRL) model, trained on realistic PX4 Simulator trajectories and using a well-adjusted reward function, generates alternative paths that optimise distance and energy. Results demonstrate that this DRL architecture achieves near-optimal routing behaviour. Crucially, it reduces computation time by several orders of magnitude compared to traditional algorithms, solving complex conflicts in milliseconds rather than seconds. We conclude that simple, well-tuned DRL architectures overcome latency limitations of classical pathfinding while achieving optimal results, ensuring rapid, safe, and efficient conflict resolution for high-density U-space.

Aerospace doi: 10.3390/aerospace13060520

Authors: Gabriele Milanese Silvia Crosa Massimo Rivarolo Loredana Magistri

A validation study has been done to provide evidence on the reliability of Reynolds-averaged simulations for supersonic ejectors operating in the single-choked condition. The existing works show that the simulation accuracy for a given turbulence model strongly depends on ejector geometry and the working conditions. In addition, the performance of different turbulence models is usually presented by comparing the results without discussing the origins of their failures. Part 1 of the present work highlights the importance of properly modeling the turbulence response to the varying shear intensity that characterizes the ejector flow-field. The key elements related to this point have been analyzed for commonly used eddy viscosity models and for a new K−ε model. The models described in Part 1 are tested here on two complementary test cases. A free jet with detailed turbulence measurements in the initial region is used to provide information on the models’ behavior, data which could hardly be obtained directly for ejectors. The simulation of a supersonic ejector is then presented, comparing the results with the measured velocity and pressure distributions. The assessed validity of the new eddy viscosity model is exploited to give insightful considerations on ejector flow-field development.

Aerospace doi: 10.3390/aerospace13060518

Authors: Boris Benedikter Roberto Furfaro Vishnu Reddy Tanner Campbell Bill Gray

Orbit determination from optical observations remains a challenging problem due to the absence of direct range measurements and the presence of sparse, noisy, and irregularly sampled data. This work presents TRACER (Tracking, Recognition, and Analysis for Celestial Ephemerides Retrieval), a robust and fully automated framework for angles-only orbit determination. The proposed approach integrates probabilistic and deterministic strategies within a unified, decision-driven architecture. In particular, statistical ranging is employed for short-arc regimes to explore admissible solutions, while deterministic methods, including modified Gauss and Väisälä techniques, are used for longer arcs and refinement. Candidate solutions are evaluated through a unified scoring function that combines observational consistency with physically motivated penalties. A key contribution of TRACER is the introduction of a randomized subset-selection outer loop, which repeatedly solves the orbit determination problem on different observation subsets and validates solutions against the full dataset, enhancing robustness in challenging scenarios. Additional mechanisms for adaptive subarc selection, recovery from failure, and progressive data assimilation further improve reliability. The resulting framework enables fully autonomous orbit determination without manual intervention, bridging the gap between individual algorithms and operational pipelines for real-world astrometric data processing.

Aerospace doi: 10.3390/aerospace13060517

Authors: Adnan Muslić Elif Erden Rafael Balderas-Xicohtencatl Fabian Nicolas Peter Mirko Hornung

This paper presents the main results of a fleet-level assessment of H2-powered aircraft defined within the H2Avia research project, focusing on their energy performance and climate impact. The assessment is based on a global, long-term fleet evolution framework using scenario-based inputs for an in-house model which applies linear optimization to minimize the energy component of direct operating costs and the climate impact of a global fleet. Different transition scenarios from fossil-based aviation toward an H2-powered aviation system are evaluated. The main findings show that H2-based scenarios result in up to 15% higher block energy consumption at the fleet level compared with an SAF-based baseline in 2050, while providing the highest potential for a climate impact reduction of up to 60% relative to the same baseline. However, this benefit depends strongly on the inclusion and modeling of non-CO2 effects for hydrogen, as well as on the weighting between energy cost and climate impact-driven objectives. The findings demonstrate the added value of an integrated assessment framework for capturing long-term fleet evolution and enabling rapid evaluation of emerging aircraft technologies in support of climate-neutral aviation strategies.

Aerospace doi: 10.3390/aerospace13060516

Authors: Xiao Chang Jianliang Ai

Shipboard helicopter landing in the near-deck region requires stable attitude regulation and high-precision deck-relative motion control under substantial model uncertainty and environmental disturbances, conditions under which conventional model-based controllers may lose performance or become overly conservative. This paper proposes a task-oriented, learning-enhanced control algorithm for ship-relative near-deck station keeping and landing by integrating a model-based baseline controller with residual reinforcement learning in a deck-relative closed-loop framework. The algorithmic contribution is the deck-relative baseline–residual control architecture: a split-channel incremental nonlinear dynamic inversion (INDI) outer loop and a reduced-order dynamic inversion (DI) inner loop provide the nominal baseline pathway, while a bounded residual Proximal Policy Optimization (PPO) policy supplies compensation in the same physical outer-loop command channels to suppress unmodeled nonlinearities and time-varying disturbances. Simulation results show that Residual PPO improves hover robustness and landing performance relative to the baseline controller and Pure PPO. With approximately 20–30% residual authority, it achieved 90.0% Desired landing rates in both tested descent-and-landing scenes.

Aerospace doi: 10.3390/aerospace13060515

Authors: Chenming Zheng Cheng Zhang Jun Wang Jiayu Bao Zhangyao Zheng

Under severe flight conditions such as high Mach number and large angle of attack, the aerodynamic environment of guided rockets exhibits highly nonlinear and strongly coupled characteristics. Significant dynamic coupling effects exist among the pitch, yaw, and roll channels, and aerodynamic parameters are subject to considerable uncertainties due to shocks, flow separation, and other factors. These issues collectively pose serious challenges to traditional control design methods based on linearized models. To address these challenges, this paper proposes a variable-gain adaptive decoupling control method. First, based on the classical feedforward decoupling concept, a decoupling controller is designed to preliminarily suppress inter-channel coupling effects. To further cope with aerodynamic parameter perturbations and model uncertainties, a model reference adaptive control framework is introduced, and an online parameter compensation mechanism is constructed to adjust controller parameters in real time according to changes in the aerodynamic environment. Additionally, by defining and estimating a system coupling degree in real time, a variable-gain adaptive law based on coupling degree is designed. This allows the decoupling effort to be dynamically adjusted according to the coupling degree, ensuring effective decoupling while avoiding performance degradation due to over-compensation. Simulation experiments conducted under typical high-dynamic flight scenarios demonstrate that, compared to traditional methods, the proposed approach effectively suppresses inter-channel coupling disturbances and significantly enhances system stability and robustness under parameter uncertainties and external disturbances. This provides a feasible technical solution for controlling guided rockets under extreme aerodynamic conditions.

Aerospace doi: 10.3390/aerospace13060514

Authors: Aman Batra Reiko Raute Robert Camilleri

This paper presents an Improved Range Equation (IRE) for fully fueled aircraft that incorporates climb, cruise, and descent phases within a single analytical framework. Unlike the classical Bréguet equation, which assumes steady cruise and neglects non-cruise segments, the proposed formulation introduces phase-dependent fuel fractions to account for mission-wide fuel consumption. The model is validated against (i) a forward–backward iterative numerical method based on BADA data and (ii) real flight trajectories obtained via waypoint reconstruction (which is also the ground truth). Three aircraft types—ATR72-600, B737-800, and B777-300—were analyzed across nine routes ranging from 155 km to 7538 km. Results show that the IRE reduces the relative error compared to measured waypoint distance/s by approximately 26–77% compared with the classical Bréguet equation, depending on aircraft class. Here, the reported percentages represent the reduction in percentage error relative to the Bréguet-based estimates using waypoint-reconstructed trajectories as ground truth. For short-haul flights (ATR72-600),, improvements of nearly 60–73% were observed, while for medium- and long-haul aircraft, improvements of 26–77% were observed. The proposed model also closely matches the numerical method, with differences typically below 70–80 km from the original value, again depending on aircraft class. These results demonstrate that incorporating climb and descent phases significantly improves range prediction accuracy, particularly for short-haul missions where non-cruise segments represent a substantial portion of total flight distance. The IRE retains the analytical simplicity of the Bréguet formulation while achieving accuracy comparable to computationally intensive numerical methods.

Aerospace doi: 10.3390/aerospace13060513

Authors: Taewon Choi Daehee Won Byung-Rok So Dong-Hyuk Lee

In this paper, an engineering model (EM) of a multi-joint space gripper for on-orbit servicing (OOS) is proposed. OOS missions demand robotic systems capable of reliable physical interactions under dynamic uncertainties and harsh space environments. While prior space-qualified grippers have demonstrated dexterous manipulation through anthropomorphic, high-DoF configurations, this work adopts a design direction widely established in industrial applications: a three-finger, lower-DoF configuration that balances grasp versatility, structural simplicity, and system integration for OOS missions. The developed gripper features a tendon-driven mechanism with a structural design optimized for space-environment compatibility and mechanical compliance. The kinematic characteristics of the mechanism are analyzed, while workspace and manipulability analyses are conducted to evaluate its operational limits. To verify the functional feasibility of the proposed design, representative grasping experiments were performed using a fabricated EM. The mechanical reliability and grasping performance were evaluated through a series of empirical experiments. The results indicate that the proposed design achieves a practical balance among grasp versatility, structural simplicity, and system integration for OOS missions, with a shielding-oriented structural configuration adopted as a design baseline. Its functional feasibility is supported by kinematic analysis, repeatability verification, and grasping experiments. This study provides a basis for the design and evaluation of three-finger robotic grippers in future OOS missions.

Aerospace doi: 10.3390/aerospace13060512

Authors: Suhan Ko Hasang Jeon Sungjune Kim Iksoo Park Jungpyo Lee Heejang Moon

Solid fuel ramjets (SFRJs) are air-breathing propulsion systems with a high specific impulse, but their sudden expansion combustors often exhibit axially nonuniform fuel regression because of the distinct recirculation, reattachment, and downstream turbulent diffusion flame regions. However, previous studies have primarily focused on the average regression rate, with limited attention to local combustion characteristics. This study applied a photogrammetry-based three-dimensional shape reconstruction technique to obtain the post-combustion internal port geometry of a sudden-expansion SFRJ combustor burning high-density polyethylene fuel under different chamber pressure and air mass flux conditions. This geometry was employed to determine the axial distributions of the local regression rates. The analysis procedure was validated against the corresponding space–time averaged regression rate obtained from fuel mass loss, showing suitable agreement with relative errors of 1.7–5.7%. The axial distributions consistently exhibited low values in the upstream, increased rapidly in the middle region, and sustained high or gradually decreasing in the downstream. In addition, an empirical expression for the space–time averaged regression rate indicated greater sensitivity to air mass flux than chamber pressure. These results confirm that photogrammetry is an effective tool for resolving the axially nonuniform regression behavior and informing spatial insights beyond the average regression rate alone.

Aerospace doi: 10.3390/aerospace13060511

Authors: Boyang Jiang Zhongjing Ren Xicai Li Aibin Yang

Aerial manipulation tasks performed by multirotor unmanned aerial vehicles (UAVs) are often constrained by rotor-induced downwash, which generates a concentrated high-momentum axial core capable of destabilizing lightweight manipulators and payloads. This paper proposes a downwash-aware design framework for a long-reach, three-degree-of-freedom (3-DOF) aerial manipulator explicitly optimized to mitigate aerodynamic disturbances. The framework integrates CFD-based characterization of the rotor downwash, forward-kinematic modeling, workspace reconstruction, and experimental validation under controlled and real-flight conditions to ensure that the end-effector operates outside the strong-disturbance zone. Link lengths of 0.40 m and 0.80 m were selected to balance operational reach, aerodynamic safety, and platform stability. A controlled measurement setup was established for validation of the CFD numerical model, where the UAV was laterally fixed on a rigid support frame to eliminate flight-induced motion. The experimental results on the velocities at targeted locations show a good agreement with the CFD-predicted velocity profiles, confirming the reliability of the flow-field prediction model. A prototype integrated with a six-rotor UAV was experimentally validated under real flight conditions, demonstrating stable takeoff, manipulator deployment, and retraction, with a visually observable reduction in end-effector oscillation tendency. Several representative grasping configurations where the airflow velocity at the end-effector remained below the threshold of 1 m/s, or a weak-disturbance region, were identified and achieved via manipulation of the UAV system. We envision promising applications of the downwash-aware design of multirotor UAVs with aerial manipulator in high-altitude sampling, precision harvesting, and other contact-intensive aerial manipulation tasks.

Aerospace doi: 10.3390/aerospace13060510

Authors: Zhousheng Huang Zichao Yue Weizhen Tang Tianjiao Wang Xu Zhang

Currently, improving runway utilization under operational safety constraints has become a critical concern for small and medium airports. Existing research focuses primarily on landing-phase runway occupation time, while predictive studies on the takeoff phase remain limited. Analysis of 1749 Quick Access Recorder (QAR) records from ten airports reveals that departure runway occupation time is strongly correlated with ground speed at liftoff (0.72) and airport elevation (0.67) but weakly correlated with aircraft weight and meteorological conditions, providing guidance for feature engineering. To address the prediction of departure runway occupation time, this study proposes a TCN-FEP hybrid model. The model employs an enhanced Temporal Convolutional Network (TCN) module with multi-scale convolutions (kernel sizes 3, 5, 7) and dilated convolutions (rates 2, 4, 8) to capture multi-scale feature interactions, alongside a Feature Enhancement Projection (FEP) module that maps local features into a high-dimensional latent space for implicit relationship mining and global information integration. Experimental results demonstrate that the proposed TCN-FEP model achieves an MSE of 90.20, RMSE of 9.49, MAE of 5.84 s, MAPE of 3.80%, and R2 of 0.97, outperforming Informer (MSE 117.95), Longformer (MSE 132.11), XGBoost (MSE 92.30), and LightGBM (MSE 91.45). Under 5% outlier injection, MSE increases by 7.9%, compared to 24.3% for LSTM and 18.4% for Informer. With 94% of prediction errors within ±5 s, the model’s accuracy may offer a useful reference for runway resource optimization at small and medium airports.

Aerospace doi: 10.3390/aerospace13060509

Authors: Yanzhe Yang Zhiping Chen An Zhu Xiaodong Fu Haiping Ai

In this paper, a nonsingular fixed-time terminal sliding mode control (NFTSMC) strategy based on a fixed-time adaptive sliding mode disturbance observer (FASMDOB) is proposed for a space robot in the presence of dynamic uncertainties and external disturbance. Firstly, based on fixed-time theory, a novel FASMDOB is designed to mitigate the impacts of the lumped disturbance including dynamic uncertainties and external disturbance, improving the robustness of the control system and utilizing an adaptive technique to reduce chattering. Additionally, compared to finite-time disturbance observers (FTDOB), FASMDOB converges estimation errors to zero within a fixed time, regardless of the information about the initial states of the system. Next, a nonsingular fixed-time terminal sliding mode (NFTSM) surface is developed for the following control system design. By replacing the high-order fractional term with a piecewise function, the singularity problem in conventional terminal sliding mode control is effectively avoided. Combining FASMDOB and NFTSM surface, a FASMDOB-based NFTSMC strategy is developed, which guarantees the fixed-time convergence of the sliding mode surface and tracking errors. Notably, the proposed NFTSMC method utilizes the arctangent function to construct the reaching law, improving the performance of the control system. Lastly, based on Lyapunov theory, the fixed-time stability of the proposed control system is rigorously proven. With several comparative simulations being conducted, the feasibility and effectiveness of the proposed FASMDOB-based NFTSMC strategy are verified and highlighted.

Aerospace doi: 10.3390/aerospace13060508

Authors: Yu Lai Yong Chen Yang Yang Jialong Jian Yuanfei Liu

In close-range dynamic UAV tracking, the sharp decrease in relative distance and rapidly changing relative-motion conditions require UAVs to execute highly dynamic maneuvers. Traditional autonomous decision-making systems struggle with the curse of dimensionality in continuous action spaces or suffer from strategy-level rigidity when using predefined discrete maneuver primitives. This paper aims to resolve these limitations by developing a dimension-reduced yet highly continuous decision-making framework. We propose a hierarchical deep reinforcement learning architecture based on a geometric pursuit-strategy action space. The top-level Proximal Policy Optimization agent evaluates the relative-motion state to output discrete guidance-mode commands: lag pursuit, lead pursuit, or pure pursuit. A mid-level guidance translator converts these intents into continuous flight reference commands based on angular geometry and energy maneuverability. The bottom-level guidance translator utilizes a high-fidelity JSBSim fixed-wing aircraft flight-dynamics model for precise aerodynamic control. Monte Carlo simulations and comparative experiments across representative initial postures show that the proposed framework improves training convergence compared with a conventional continuous-control PPO baseline and achieves more stable high-level guidance-mode selection than a Double-DQN baseline. In simulation tests under predefined geometric tracking-success criteria, the model achieved a 91.5% success rate in initially favorable configurations and a 64.0% success rate when starting from a challenging configuration. By abstracting complex maneuvers into geometric pursuit strategies, this hierarchical framework lowers exploration dimensionality while maintaining the continuous kinematic logic of flight trajectories, providing an interpretable and simulation-validated decision-making framework for UAV close-range dynamic tracking and autonomous flight control.

Aerospace doi: 10.3390/aerospace13060507

Authors: Chenxi Sun Huiqi Ren Zailin Yang Renjie Wang

With the advancement of aerospace technology, full-scale wind tunnel testing has become a crucial approach to overcoming bottlenecks in hypersonic technology. The design of ultra-large, high-performance nozzles stands out as one of the core challenges. This paper focuses on a profiling design method for supersonic/hypersonic nozzles with interchangeable throats at the 6 m outlet scale, addressing issues such as significant boundary layer effects and difficulties in achieving variable Mach numbers due to the large dimensions. An empirical boundary layer correction method is proposed to efficiently compensate for viscous effects. By parameterizing and controlling the Mach number distribution along the nozzle axis using cubic B-spline curves and applying the method of characteristics for accurate inviscid supersonic flow field computation, the nozzle profile is optimized. To enable multi-Mach-number operation, a design strategy is adopted, where the high-Mach-number profile serves as the baseline, and the low-Mach-number throat section is inversely designed to ensure a smooth transition between multi-Mach nozzles and a shared expansion section. Using this approach, nozzle profiles for Mach numbers 4, 5, and 6 were successfully designed and validated through fully viscous CFD simulations. Results demonstrate that under all design conditions, a wide and uniform core flow region forms at the nozzle exit, with no strong shock waves present in the flow field. This study confirms the effectiveness and reliability of the integrated design method for large-scale interchangeable-throat nozzles, providing important theoretical foundation and technical support for the future development of advanced large-scale hypersonic wind tunnels.

Aerospace doi: 10.3390/aerospace13060506

Authors: Yaowei Yu Meilong Le

Collaborative 3D path planning for multiple unmanned aerial vehicles (UAVs) in dense urban airspace is difficult, which does not come from one factor alone. Buildings, flight restrictions, moving obstacles, and inter-UAV coupling all act together, and the search space grows quickly as the scene becomes more crowded. In such cases, a standard swarm optimizer may still find a path, but it often struggles with early feasibility, later-stage refinement, and local replanning after the environment changes. To deal with these issues, this paper develops a spatio-temporal collaborative improved multi-strategy dung beetle optimization algorithm, called STC-IMSDBO, for urban multi-UAV path planning. The framework combines five linked components: feasible-airspace population initialization, spatio-temporal variable-step search, multi-factor adaptive weighting, local game-based conflict handling, and rolling-horizon replanning. A normalized multi-objective cost is used to balance flight efficiency, smoothness, obstacle avoidance, airspace compliance, and cooperative safety. The method is tested in four simulated urban scenarios and compared with six representative methods. In the tested cases, the STC-IMSDBO generates shorter feasible routes, uses less energy, converges in fewer iterations, and maintains better cooperative safety than the comparison methods. These results suggest that the method is a useful planning option for dense urban missions such as logistics, inspection, and emergency response. That said, larger-swarm runtime tests and field validation are still needed.

Aerospace doi: 10.3390/aerospace13060505

Authors: Ekaterina Kudryashova Diana Rakhimova Artur Andronov Andrei Shumeiko

The desire to use space in the most rational and efficient way to address contemporary challenges leads to the necessity of creating multi-purpose space missions capable of solving a wide range of diverse tasks. This creates a demand for propulsion systems that can provide high maneuverability for modern and future spacecraft. One potential solution to increase the maneuverability of satellites is the use of electrodeless plasma thrusters with magnetic thrust-vectoring (MTVEPT). Their simple design and acceptable thrust-to-power characteristics can improve the cost-effectiveness of a space mission, increase its reliability and operational lifetime, and enable the required orbital maneuvers. This paper presents an experimental study on the ignition thresholds of a radiofrequency discharge in an electrodeless plasma thruster utilizing argon. The study is conducted over a gas flow rate range of 20 to 210 sccm, with solenoid currents from 0 to 5 A, for two magnetic field directions and two diameters of the exhaust orifice, which is varied using a diaphragm. It is found that a 93% relative reduction in the channel diameter leads to an average twofold decrease in the discharge ignition threshold, reaching a minimum value of 2.5 × 103 V/m at a flow rate of 100 sccm. This can be used to reduce the thruster’s power consumption for the repetitive discharge ignitions when the propellant reserves are limited. Furthermore, four distinct discharge ignition regions are identified, depending on the solenoid current. The existence of a minimum threshold electric field for the discharge ignition of 4.0 × 103 V/m is demonstrated for a multidirectional electrodeless plasma thruster without changing the discharge channel geometry within the studied parameter range, occurring at a solenoid current of I = 2 A.

Aerospace doi: 10.3390/aerospace13060504

Authors: Qian Zhao Yue Yu Carlo E. D. Riboldi

This study presents a reinforcement learning (RL)-based framework for the aerodynamic optimization of the Lotte airship, combining mid-fidelity dynamic simulations with adaptive learning strategies. To address the complex nonlinear coupling between the hull shape and tail configuration, a staged, data-driven optimization strategy is developed. In the first stage, single-parameter RL experiments are conducted to independently analyze the aerodynamic sensitivity of key design variables. This conceptual stage isolates pure aerodynamic potential, focusing on the unconstrained optimization of the hull’s Bézier parameterized profile, alongside the individual sensitivities of empennage area, longitudinal shift, lift slope factor, and efficiency. These experiments yield a comprehensive sensitivity map, clarifying each parameter’s independent influence on the average lift-to-drag ratio (L/D¯) of the airship. In the second stage, the obtained sensitivities are utilized to structure an integrated multi-parameter optimization scenario. Crucially, this unified environment integrates the hull and tail while enforcing rigorous longitudinal trim constraints via a dynamic bisection search. This forces the RL agent to balance system-level aerodynamic recovery against inevitable trim drag penalties. The proposed framework is implemented in MATLAB R2023b using the SILCROAD airship dynamics environment and trained by the Deep Deterministic Policy Gradient (DDPG) algorithm. Results demonstrate that the initial single-parameter sensitivity extraction not only accelerates algorithmic convergence but also significantly improves the interpretability and physical validity of the final trimmed full airship configuration. This hierarchical approach establishes a systematic path from isolated parameter understanding to holistic, physics-informed aerodynamic design, offering a transferable methodology for future autonomous airship optimization.

Aerospace doi: 10.3390/aerospace13060503

Authors: Shixuan Zhang Jie Ma

Distributed optimal design brings significant solutions for experiment optimization in complex engineering design problems. A Kriging-based augmented Lagrangian Method is proposed with the help of the Multi-fidelity Hamiltonian Kriging (MHK) surrogate model. The Multi-fidelity Hamiltonian Kriging-based Augmented Lagrangian Method (MHK-ALM) uses subsystem surrogate models constructed from multi-fidelity data to speed up the inner loop solution of ALM, while also reducing the iterations of the outer loop of ALM. The MHK-ALM is illustrated with one numerical simulation of a multi-fidelity constrained NASA speed reducer problem, demonstrated with a multidisciplinary design optimization of a solid-propellant ballistic missile. The engineering application of the multidisciplinary design optimization (MDO) problem shows that the proposed method can perform precisely over certain advanced surrogate-based optimization frameworks. The MHK-ALM can be applied for any other distributed optimal design problems where one need complex subsystem decomposition.

Aerospace doi: 10.3390/aerospace13060502

Authors: Pablo Hernández David Marroquí Ausiàs Garrigós Ferdinando Tonicello

The increase in small satellites demands the integration of commercial components to reduce costs and development time. However, the lack of standardized system-level methodologies to mitigate radiation-induced degradation limits their adoption. Although majority-carrier technologies such as MOSFET transistors dominate space power electronics, modern commercial off-the-shelf BJT transistors present a robust and cost-effective alternative. This paper evaluates the viability of the new-generation commercial off-the-shelf BJT transistors in space radiation environments by analyzing their response to total ionizing dose (measured at the circuit level) and single-event effects (inferred from component-level data). A fault-tolerant design methodology is proposed based on the strict definition of the safe operating area: the collector-emitter voltage is limited to safe values to mitigate single-event burnout, and an overdrive margin, specifically a 5× worst-case factor, is applied to compensate for the parametric degradation of the current gain. These strategies are empirically validated through two circuits: a voltage clamp and a proportional base driver operating in the 5 W to 40 W range. Experimental tests on the voltage clamp demonstrate stable operation up to one hundred kilorads, exceeding the 50 krad mission requirement by 100%. This indirectly supports the proportional base driver through shared mitigation principles, which rely on base current over-dimensioning to compensate for TID degradation. In conclusion, by applying appropriate derating rules, commercial off-the-shelf BJT transistors constitute a viable and robust alternative for small satellite power systems, mitigating the need for expensive radiation-hardened components.

Aerospace doi: 10.3390/aerospace13060501

Authors: Hongmin Li Shuo Huang Shuanglong Rong Cheng Qian Baiyang Zheng

Lightweight alloys in aerospace precision structures undergo slow but cumulative creep deformation during long-term storage, wherein strain accumulation over years can compromise dimensional stability and operational reliability. However, continuum damage mechanics (CDM) constitutive models, while physically grounded, require extensive parameter calibration and exhibit degraded accuracy during the primary creep stage. Meanwhile, purely data-driven approaches are impractical for the sparse datasets typical of accelerated creep testing, wherein as few as 14 data points may be available per condition. Although physics-informed neural networks (PINNs) have shown promise in computational mechanics, existing PINN-based creep studies predict only scalar life quantities rather than the full strain–time curve ε(t), and none embed damage evolution equations as differential constraints. This study proposes a damage-coupled PINN framework (termed DC-PINN) that predicts the complete creep strain evolution ε(t) by embedding CDM damage evolution ordinary differential equations (ODEs) as hierarchical differential constraints within the learning process. The framework couples the predicted strain rate dε/dt with the damage state D(t) through material-specific constitutive ODEs, supplemented by monotonicity enforcement and boundary conditions. Alloy-specific formulations are developed for 2A12-T4 aluminum (Arrhenius kinetics, no damage) and ZM6 magnesium (Sandström dislocation model with Ostwald-ripening-driven grain coarsening damage). Validated on 13 experimental conditions spanning both alloys (50–100 °C, 20–60 MPa, 14–100 points per condition), DC-PINN achieves R2>0.99 for 2A12-T4 and R2>0.97 for ZM6 across all tested conditions. Ablation studies show that the total physics-driven R2 improvement is 5.8 times larger for the data-sparse ZM6 (14–34 points) than for the data-rich 2A12-T4 (∼100 points), with the CDM damage coupling alone accounting for 22% of the improvement in ZM6. To the best of our knowledge, this represents the first integration of CDM damage evolution ODEs as differential constraints within PINNs for creep strain modeling, providing a physically consistent and data-efficient tool for the storage life assessment of aerospace structures.

Aerospace doi: 10.3390/aerospace13060500

Authors: Alex Pollitt Daan Vlaskamp James Blundell Annemarie Landman

For almost fifty years, Crew Resource Management (CRM) has been a cornerstone of aviation safety and training. This narrative review examines the current state of CRM training and identifies key directions for future development, including the integration of artificial intelligence, increasing attention on mental health and resilience, and workforce diversity. While there is evidence of gradual evolution in CRM practices, reflected in updated regulatory frameworks, competency-based approaches, and a growing community of human factors and aviation psychology specialists, progress remains uneven across the industry. We argue that many aviation operators and training organizations still lack robust institutional mechanisms to systematically translate emerging scientific evidence into training design and delivery. As a result, advances in research on teaching and learning methods and human performance are not consistently brought forward into everyday training practices. The review concludes with a set of practical recommendations aimed at strengthening knowledge exchange between researchers and operational stakeholders, enhancing evidence-informed training, and supporting the modernization of CRM in a rapidly changing operational environment.

Aerospace doi: 10.3390/aerospace13060499

Authors: Tao Sui Dechen Sun Zhishuo Ji Jingqi Li Xiuzhi Liu

To address the challenges of time-dependent error divergence in Strapdown Inertial Navigation Systems (SINS) and the insufficient accuracy of traditional terrain matching algorithms in feature-sparse flat terrain environments, this paper proposes an intelligent terrain-aided navigation method integrating an Improved Osprey Optimization Algorithm (IOOA), Distribution Estimation, and Q-learning. Utilizing terrain information entropy as a robust matching metric, the algorithm establishes a two-phase evolutionary framework comprising Lévy flight-based random search (exploration phase) and elite-guided Gaussian Estimation of Distribution (exploitation phase). By introducing a Q-learning mechanism to adaptively regulate exploration parameters, an intelligent balance between population diversity and convergence speed is achieved. Under a unified computational benchmark, systematic multi-scenario simulations were conducted using datasets from simulated moderately undulating foothill terrain, the Libyan Sahara, and the real Digital Elevation Model (DEM) of the Junggar Basin in Xinjiang, China. Experimental results demonstrate that, compared to traditional TERCOM and mainstream swarm intelligence algorithms, the proposed algorithm drastically reduces positioning errors in the aforementioned complex terrains and significantly enhances matching accuracy. Robustness and real-time performance tests indicate that the algorithm achieves an average single-match processing time of only 0.08 s and maintains error variability as low as ±0.83 m under random perturbations. Furthermore, an ablation study confirms the necessity of the multi-strategy fusion mechanism in suppressing local optima entrapment and non-convergent oscillations. This study validates the engineering feasibility of the algorithm under conditions of low computational dependency, providing an effective technical approach for high-precision autonomous navigation in GPS-denied environments.

Aerospace doi: 10.3390/aerospace13060498

Authors: Feng Yang Geng Tian Ziheng Cheng Kai Liu

To address the efficiency problem of traditional sequential convex optimization (SCO) methods with uncertain terminal time for long-range hypersonic vehicle reentry, this paper proposes an improved method with neural network-based terminal time prediction strategy, which has distinctly higher computational efficiency than the traditional one. In the improved method, a neural network is used to fit the mapping between the vehicle’s current state and the terminal time, thereby replacing the parametric computation in the optimization process and thus improving efficiency. For network training, a large number of sample trajectories are first generated using the traditional sequential convex optimization method. Then, a multi-layer feedforward neural network is employed to approximate the mapping from the reentry vehicle’s flight states to the terminal time, thus completing the offline training. The simulation results demonstrate that the proposed algorithm reduces computation time by more than 50% compared to the SCO algorithm, satisfies the requirements for online trajectory generation, and can also adapt to special cases where the initial and terminal positions vary.

Aerospace doi: 10.3390/aerospace13060497

Authors: Chenghao Wang Kaiqiang Feng Jie Li Li Qin Xi Zhang Junlong Li Songhao Zhang Yanchun Suo

Owing to their reliance on detailed mathematical modeling, traditional control methods encounter challenges such as high control complexity and low precision when applied to high-speed flight vehicle control under strongly disturbed atmospheric conditions. To address this limitation, this study introduces a data-driven neural network mapping approach into the field of flight vehicle control. By excavating the underlying patterns in operational data and leveraging the nonlinear mapping capability of neural networks, accurate prediction and generation of control commands are achieved, thereby eliminating the dependence on precise mathematical models and offering a novel solution for complex control problems. Building on this foundation, a self-organizing map (SOM) radial basis function (RBF) neural network is proposed. Leveraging the competitive learning mechanism of SOM, it performs adaptive clustering on input samples, dynamically optimizes the number of clusters to determine the number of hidden-layer nodes in RBF, and adopts the SOM cluster centers as the centers of RBF basis functions. This design enables the one-click data-driven determination of both the number of nodes and their corresponding center vectors, significantly simplifying the network structure design process. Meanwhile, to address inherent limitations of this network, such as suboptimal output weights, unoptimized width functions, and the inherent drawbacks of the traditional Moth-Flame Optimization (MFO) algorithm, an Adaptive Enhanced Moth-Flame Optimization (AEMFO) algorithm is developed, drawing inspiration from biological swarm intelligence. By integrating strategies such as adaptive spiral update and elite opposition-based learning, it balances the global exploration and local exploitation capabilities, and performs targeted optimization of the RBF width parameters and output-layer weights. This optimization significantly enhances the accuracy of the network in mapping attitude-control commands in strongly disturbed environments, providing robust support for the stable attitude control of high-speed flight vehicles. Finally, simulation results demonstrate that the proposed method achieves high control accuracy for flight vehicle attitude control under strongly disturbed environments.

Aerospace doi: 10.3390/aerospace13060496

Authors: Bin Qi Siyuan Gao Lejie Yang Peng Qiao Dawei Liu Hai Du Guoshuai Li Jifei Wu

Shock buffet is one of the critical issues affecting the aerodynamic performance, flight quality, and flight safety of large aircraft. To overcome the limitations of traditional experimental measurement methods, such as insufficient capability in capturing flow features and high cost, an integrated experimental system tailored for extreme cryogenic and high-Reynolds-number conditions is developed based on the conventional tuft technique. This system comprises “preparation of low-flow-disturbance fluorescent mini-tufts, high-efficiency large-area tuft taping, automatic generation of digital streamline, and flow topology analysis”. Furthermore, a technique for assessing the transonic shock buffet onset using dynamic flow visualization with fluorescent mini-tufts is proposed. This paper takes a typical supercritical airfoil as the research object. First, through high-precision numerical simulations, it reveals that low-energy, unstable boundary-layer separation is the core driving force for the development and maintenance of shock buffet, and that flow separation characteristics serve as an important basis for determining the shock buffet onset. Subsequently, experimental validation is conducted in a 0.3 m high-Reynolds-number transonic wind tunnel. Using a dual-excitation-band composite light source, simultaneous measurements of pressure-sensitive paint (PSP) and fluorescent mini-tuft patterns are realized. The experimental results show that under extreme conditions, characterized by a wide total temperature range of 110 K to 280 K and strong scouring at Mach numbers from 0.6 to 0.9, the fluorescent mini-tufts (approximately 0.05 mm in diameter) exhibit excellent flow-following capability without any detachment. The digitized flow patterns of the fluorescent mini-tufts, obtained via computer image recognition algorithms, clearly reveal the location and area of boundary-layer separation. The trends show good agreement with the cryogenic PSP results, providing an important reference for determining the shock buffet onset.

Aerospace doi: 10.3390/aerospace13060495

Authors: Luz del Carmen García-Rodríguez Mario Alberto Mendoza-Barcenas Javier Díaz-Carmona Agustín Sancén-Plaza Luis Enrique Chinea-Mujica Francisco Javier Pérez-Pinal Alejandro Espinosa-Calderón

Electronic components play a fundamental role in critical missions, performing functions such as data processing, measurement of physical variables, data storage, communication, power generation and storage, and algorithm computation. However, their performance can be compromised in harsh environments like those encountered in aerospace applications, where components are exposed to extreme conditions including radiation, temperature variations, and vibrations. To ensure reliability, electronic components used in aerospace missions must comply with strict specifications, typically requiring space- or military-grade standards. These components are significantly more expensive than commercial alternatives and often involve long development and design times for custom platforms. The use of COTS (Commercial-Off-The-Shelf) components has emerged as a viable solution for aerospace applications where cost and development time are critical factors. This paper presents a state-of-the-art review of COTS components used in aerospace missions. After an extensive literature review and document screening process, the results indicate that COTS components are commonly employed in critical missions, representing 44% of the studies analyzed. Furthermore, approximately 81% of the reviewed projects focused on space applications, with validation performed in space (22%), ground (75%), and air (3%) environments. Among the systems validated for space missions, half used CubeSat-based payload structures, while the rest relied on other platforms. Most launches were conducted using spacecraft (96%), with the remainder using balloons.

Aerospace doi: 10.3390/aerospace13060494

Authors: Larry Catalasan Tianyi He Weihua Su

This paper presents a method of data-driven parametric dynamic mode decomposition (p-DMD) to derive a linear parameter-varying reduced-order model (LPV-ROM) and predictive control for the nonlinear aeroelasticity of highly flexible aircraft. It directly uses the data snapshots obtained at varying flight conditions and encodes a nonlinear model’s polynomial dependency on flight conditions to produce a polynomial-dependent LPV-ROM. The modeling method can handle not only equilibrium flight conditions but also continuously varying flight conditions. In numerical studies, the proposed data-driven p-DMD modeling is applied to a highly flexible cantilever wing perturbed around equilibrium conditions and a flexible aircraft with time-varying angles of attack in dynamic maneuvers. The numerical results demonstrate that the current p-DMD model can capture the non-equilibrium (or transient) aeroelastic and flight dynamic behaviors of highly flexible aircraft in both time and frequency domains with over 95% accuracy in the simulated representative cases. Accuracy is quantified by the normalized root mean square error (NRMSE) in the time domain and the normalized error between the frequency responses over the frequency range of interest. The data-driven reduced-order model is further implemented in predictive control to suppress the vibrations excited by Dryden gust disturbances. The simulation results demonstrate that for a Dryden gust profile, data-driven predictive control can suppress the strains by 18.34% as quantified by the reduction in the root mean square of strains compared to the uncontrolled case.

Aerospace doi: 10.3390/aerospace13060493

Authors: Lorenz Losensky Tobias Rabus Nicolas Fota Maria Buzatu Christopher Brain Augustin Udristioiu

The expected rise in space operations challenges the European Air Traffic Management (ATM), as traditional static airspace segregation causes operational inefficiencies. To mitigate this, a new function within the European Network Manager Operations Centre (NMOC), supported by the novel Network Real-time Mission Monitoring (N-RMM) tool, and complemented by ad hoc Debris Response Areas (DRAs), are being developed. This paper introduces the safety assessment of this approach using the Expanded Safety Reference Material (E-SRM) methodology. By developing specialised Accident Incident Models (AIMs) for mid-air collisions with space debris, we quantify safety barrier efficiencies and define a Risk Classification Scheme (RCS). The results indicate that by developing dedicated AIMs for the proposed dynamic airspace-management concept, the derived safety criteria, under the stated assumptions, are compatible with the targeted safety thresholds. The potential reduction in segregated airspace volume and duration remains an expected operational benefit to be quantified in subsequent validation work.

Aerospace doi: 10.3390/aerospace13060492

Authors: Ketan Vasudeva M. Reza Emami

This paper outlines the system engineering of a Lunar Robotic Construction System (LRCS) for the bagging and manipulation of Regolith Containment Units (RCUs) on the lunar surface. The lunar regolith is the most readily available material on the Moon’s surface, which can be utilized for the protection of structures, machines, and equipment from projectiles, thermal variations, and radiation. A mission scenario of employing the LRCS for the creation of a blast berm for landing pads is presented, and the subsystems are subsequently designed in detail. Structural and physical modeling of the LRCS is performed, including simulations of the regolith intake mechanism. An analysis of LRCS mass, power, and cost is also studied, completing its system engineering.

Aerospace doi: 10.3390/aerospace13060491

Authors: Ming Li Mingying Huo Tianchen Wang Yisen Ma Xiyan Zhao Naiming Qi

To address the nonlinear orbit determination problem under multi-satellite cooperative observation, this paper proposes an orbit determination method integrating a plane-constrained observation model with adaptive robust filtering. Based on angular measurements from multiple observation nodes, a linearized observation model is constructed using spatial geometric constraints. The Maximum Correntropy Criterion is then introduced to adaptively weight each measurement component, and a hybrid kernel function is employed to suppress the effects of non-Gaussian noise and outliers. Meanwhile, an adaptive factor based on the covariance matching principle is designed to adjust the process noise intensity online, thereby improving the robustness of the Cubature Kalman Filter in state prediction and update. Simulation results under severe non-Gaussian noise show that the proposed adaptive robust cubature Kalman filter (ARCKF) reduces the position RMSE from 95.3 m for CKF to 30.8 m, corresponding to an improvement of approximately 67.7%, while increasing the computation time from 6.52 s to 7.35 s. These results indicate that the proposed method can achieve improved accuracy and robustness under uncertain measurement statistics and dynamic disturbances, making it suitable for space-based angles-only orbit determination, although further computational optimization is still required for onboard applications.

Aerospace doi: 10.3390/aerospace13060490

Authors: Guiye Wen Meihong Liu Junjie Lei

Brush seals, as a fundamental dynamic sealing technology in the aerospace and energy propulsion industries, require performance enhancement through instantaneous adjustment of the friction coefficient and force analysis of brush filaments. This paper establishes an instantaneous friction coefficient correction method based on the open volume between bristles and the backing plate. The downstream section of the double-row brush wire (2.6 mm) was quantitatively identified as the maximum leakage point, and it was found that the vortex characteristic length in the downstream area is approximately 1–3 times the bristle gap, with an increasing pressure ratio enhancing downstream turbulence and reducing gas leakage. A cantilever beam structural model was developed to assess the motion, force, and hysteresis properties of a single filament. Additionally, a porous medium model was utilized to elucidate the flow field and temperature distribution within the seal. The results suggest that the lag angle increases linearly over the first one-third of the brush wire’s length from the free end to the fixed end and is directly proportional to the pressure difference ΔP, reaching a maximum of 10.18°. The viscous drag causes the radial force y-component Fxy to increase and then decrease near the free end. The rear baffle contact force, Fb, shows variable peaks at two-thirds of the filament length. The displacement at the brush filament’s free end, the deflection angle, and the bending moment are directly proportional to the pressure differential. As pressure increases, the deformed region propagates toward the fixed end, and the maximum displacement at the free end of the brush wire reaches 13.04 mm. The leakage rate increases nearly linearly with ΔP and its deformation, reaching a maximum of 0.00849 m2/s. The pressure gradient growth rates of 164%, 73%, and 29% at the front baffle corner demonstrate that adding pressure chambers on front and rear baffles is optimal for high-pressure scenarios (ΔP > 0.3 MPa), while the formation of vortices between bristles and rotor reduces tip friction force and front-row turbulent disturbance, providing design guidance for extending seal service life.

Aerospace doi: 10.3390/aerospace13060489

Authors: Zijie Wu Baoxing Li Kun Wang Ronggang Wei Chengfeng Wu Shaoqing Hu

Oblique detonation engines have been proposed for hypersonic propulsion because detonation-based heat addition can, in principle, provide rapid energy release with reduced total-pressure penalties. We investigate non-premixed injection/mixing of an RP-3 aviation-kerosene surrogate in a constrained supersonic channel and its impact on oblique-detonation initiation, stabilization, and static pressure gain. Numerical simulations are performed for a Mach 8 inflow representative of a 30 km altitude condition using an OpenFOAM v7-based reacting-flow solver. We analyze the pressure-gain process following detonation onset, quantify the effects of the inducer-ramp angle, and qualitatively assess the predicted initiation/stabilization trends against direct-connect hot-fire experiments. The results show that non-premixed injection into a supersonic crossflow yields limited mixing over the available mixing length and results in a strongly stratified inflow to the combustor. In the constrained passage, a train of reflected shocks forms and progressively reduces the total-pressure recovery factor along the mixing section, which asymptotically approaches ~0.49. In the combustor, the inducer-ramp angle controls whether and how a stabilized oblique detonation can be established. For a 25° ramp, no self-sustained ODW is obtained under the present conditions, whereas stabilized ODWs are observed for 30° and 35° ramps, exhibiting abrupt and smooth topologies, respectively. These initiation thresholds and stabilized morphologies show qualitative consistency with the direct-connect observations. Due to fuel stratification, pressure gain varies among streamlines but consistently follows a “primary compression–plateau–secondary pressure rise” sequence; the secondary stage contributes approximately 17.54–27.98% of the static pressure rise.

Aerospace doi: 10.3390/aerospace13060488

Authors: Yunlong Ge Yinjie Du Linchang Han Liming Yang

In this work, a partitioned coupling algorithm is developed by integrating the improved discrete velocity method (IDVM) with the lattice Boltzmann flux solver (LBFS) to address conjugate heat transfer (CHT) in microscale systems across all flow regimes. Specifically, the flow field is solved by the IDVM, generating a heat flux that acts as a Neumann boundary condition at the interface for the solid domain. Subsequently, the LBFS calculates the thermal distribution inside the solid, and the updated temperature at the interface is then applied to the fluid computations as a Dirichlet condition. The proposed framework effectively combines the strengths of the IDVM in modeling rarefied gas flows with the advantages of the LBFS in handling heat conduction in complex geometries. Crucially, the current approach implicitly captures temperature jump discontinuities at the conjugate boundary, bypassing the requirement for supplementary jump conditions. To evaluate its performance, several CHT test cases involving rarefied gas in microchannels were conducted. Computational evidence suggests that the scheme is robust across diverse flow regimes.

Aerospace doi: 10.3390/aerospace13060487

Authors: Mengna Quan Bin Lan Shike Long Yongjun Wang Shanlin Sun

This paper investigates the output consensus problem in heterogeneous multi-agent systems. To address the challenges of traditional analytical methods in handling unknown dynamics and disturbances, a control framework is proposed that combines known model structures with a data-driven adaptive mechanism. The framework uses a distributed internal model to compensate for system heterogeneity and incorporates an event-triggered mechanism to reduce communication burden. To improve transient tracking performance, a reinforcement learning strategy based on centralized training and decentralized execution is introduced to adaptively optimize local feedback gains. Simulation results show that the proposed method effectively bounds closed-loop signals, achieves relatively fast convergence, and demonstrates some robustness and communication efficiency under process noise.

Aerospace doi: 10.3390/aerospace13060486

Authors: Haitao Li Yunhong Bai Yawen Wang Mengyang Zhang Yikang Zhang Lijun Yang Chi Ma Jie Li

Impinging injectors are extensively utilized in liquid rocket engines, characterized by a large number of paired inclined injection orifices. The diameter and axis alignment deviation of these orifices directly influence propellant flow distribution, atomization and mixing behavior, and engine operational stability. To address the challenges associated with micro-sized orifices, inclined axes, large quantities, spatial intersection, and the low detection efficiency of conventional approaches, this paper proposes a dual-line laser 3D point cloud reconstruction-based method for measuring the diameter and impact alignment deviation of injector orifices. A dual-line laser measurement system is established to capture surface point clouds on both sides of the orifice inlets. Through system calibration and point cloud registration, the 3D point cloud data of the injector orifices within a unified coordinate system are reconstructed. Cross-sectional mapping, boundary extraction, and geometric fitting techniques are applied to determine the diameter and axis parameters of the orifices, and the spatial alignment deviation of paired orifices is subsequently calculated. To validate the feasibility of the proposed method, experimental investigation is conducted on test specimens with both 8 pairs of Φ2 mm through-holes and Φ0.5 mm micro-orifices. For the Φ2 mm specimen, the diameter measurement results are compared with industrial computed tomography (CT) data, while the alignment deviation results are verified using a combination of pin gauges and coordinate measuring machine (CMM) measurements. For the Φ0.5 mm micro-orifices, both diameter and alignment deviation results are verified using a 3D coaxial line confocal sensor. After system calibration, the fitting residuals of three Φ8 mm standard spheres are all maintained within 0.08 mm. The diameter measurement results of 8 selected Φ2 mm orifices show good overall agreement with industrial CT data: the maximum absolute deviation is 22 μm, the average absolute deviation is 15 μm, the maximum relative error is 1.09%, and the average relative error is 0.74%. The diameter and alignment deviation results of Φ0.5 mm micro-orifices show good consistency with the 3D coaxial line confocal sensor: the maximum absolute deviation is 13 μm for diameter and 0.047° for alignment deviation, with maximum relative errors of 2.41% and 0.058%, respectively. The alignment deviation results of 8 pairs of Φ2 mm orifices indicate that the proposed dual-line laser method is generally consistent with the combined pin gauge and CMM approach: the maximum absolute deviation is 0.170°, the average absolute deviation is 0.125%, the maximum relative error is 0.284%, and the average relative error is 0.125%. The results demonstrate that the proposed method enables non-contact and high-efficiency measurement of the diameter and alignment angle of injector orifices in impinging injectors for both conventional Φ2 mm orifices and micro Φ0.5 mm orifices, with high measurement accuracy and promising engineering application potential, thereby providing a new technical approach for the geometric parameter inspection of multi-scale micro-injection orifices.

Aerospace doi: 10.3390/aerospace13050485

Authors: Yutao Liu Jihan Feng Yifan Wang

In this paper, we investigate secrecy energy efficiency (SEE) maximization in a rate-splitting multiple access (RSMA)-enabled UAV communication system, which consists of a communication UAV serving legitimate ground users (GUs) and a cooperative jamming UAV transmitting jamming signals to degrade the channel of the eavesdropper (Eve). Taking into account the propulsion energy consumption of fixed-wing UAVs, we formulate a non-convex SEE maximization problem by jointly optimizing communication scheduling, CUAV transmit power, and the trajectories of both UAVs. To tackle the non-convex problem, an iterative optimization algorithm combined with the Dinkelbach method and successive convex approximation (SCA) is developed to obtain a suboptimal solution. Simulation results demonstrate the convergence of the proposed algorithm and show the proposed joint optimization scheme significantly improves SEE compared with benchmark schemes.

Aerospace doi: 10.3390/aerospace13050484

Authors: Huatong Liu Peng Cao Huiqian Hao Zhifei Tan

Large-aperture steerable reflector antennas are pivotal for deep-space exploration and satellite communication, but their high-frequency performance is often compromised by wind-induced structural deformations. This study employs a high-fidelity fluid–structure interaction (FSI) framework, coupling Computational Fluid Dynamics (CFD) and the Finite Element Method (FEM), to investigate the dynamic response of an 18 m Square Kilometre Array (SKA) antenna under transient wind loads. The structural FEM is validated against experimental modal data, ensuring the capture of essential vibration characteristics. We evaluate steady-state wind pressure coefficients (Cp) and transient responses under a simulated Davenport wind spectrum across the antenna’s full operational elevation range. Surface accuracy degradation is rigorously quantified using the Root Mean Square Error (RMSE) of the best-fit paraboloid. The results demonstrate a significant correlation between peak deformation and surface error, pinpointing 15° and 90° pitch angles as the most critical configurations for profile degradation due to the “air pocket effect” and asymmetric pressure distributions, respectively. These insights establish a robust theoretical basis for structural optimization and the development of active surface control strategies for next-generation aerospace signal acquisition infrastructure.

Aerospace doi: 10.3390/aerospace13050483

Authors: Youhong Yuan Zetao Guo Wenqiang Gao Zengjie Zhou Qinglin Niu

Infrared radiation spectra produced by vibration–rotation transitions in multicomponent gases within the vacuum plume of attitude and orbital control engines constitute crucial radiation sources for optical target identification and space maneuver recognition, and rapid prediction of these signatures is essential for real-time forecasting. This study introduces an axisymmetric vacuum plume flow field model based on a simplified point-source approach that accommodates multicomponent combustion gases. Using the Maxwellian velocity distribution and a velocity–position angle algorithm, normalized number density, velocity, and temperature distributions are derived. A plume–freestream interaction model founded on noncentral fully elastic collision theory is incorporated, and overall plume properties are obtained via density-weighted averaging. Neglecting non-equilibrium radiation effects, the high-temperature gas absorption coefficient is calculated using a statistical narrowband model and radiative transfer is solved via the line-of-sight method. The model is validated against direct simulation Monte Carlo results for single-gas and MBB bipropellant plumes and confirmed using infrared spectral data in the 2.0–4.5 μm band. The proposed framework achieves 102–103-fold higher computational efficiency than conventional DSMC approaches. Freestream effects on plume diffusion and momentum exchange diminish with increasing altitude, as does the freestream velocity’s enhancement of radiation intensity, whereas greater plume expansion at higher altitudes increases overall radiation intensity.

Aerospace doi: 10.3390/aerospace13050482

Authors: Ding Chen Jonty Veitch Jonathan Petticrew Anne Samaras Oliver Saint-Pe Jo Shien Ng Chee Hing Tan

To realise high-speed free-space optical communication links in harsh space environments, it is crucial to consider the link’s operating wavelength, the performance of the optical receiver, and the radiation hardness of the avalanche photodiode (APD)—optical detectors in the optical receivers. In this work, we experimentally evaluated the radiation hardness of 2.5 Gb/s receivers based on InGaAs/AlGaAsSb APDs integrated with Ommic CGY2102UH/C2 transimpedance amplifiers. Proton energy (62 MeV) and fluence (up to 3.8 × 1010 p/cm2) representative of space environments were used to irradiate multiple receivers, ensuring rigour. After irradiation, the receivers maintained their avalanche gain and photocurrent, while exhibiting bandwidths exceeding 1.5 GHz. Despite a slight increase in APD’s dark current at high reverse bias, there was no degradation of the receiver’s bit error rate. At 2.5 Gb/s data rate and 1550 nm wavelength, the irradiated receivers achieved a bit error rate of 10−9 with an average optical power of −38.2 dBm, outperforming selected commercial receivers by ~3 dB. Since the displacement damage dose induced by the proton radiation levels used in this work are representative of those in Low Earth, Geostationary and Global Positioning System orbits, we demonstrated that InGaAs/AlGaAsSb APDs have sufficient radiation hardness to be employed as optical detectors of high-speed optical links in harsh space environments.

Aerospace doi: 10.3390/aerospace13050480

Authors: Timothy T. Takahashi

This paper arises from an ARPA-E-sponsored project seeking design opportunities to retrofit existing aircraft with hybrid electric propulsion systems. Engineers typically configure aircraft to fly a given payload over a long range, which is subject to field performance constraints. In practice, operators fly transport aircraft (civilian and military) in a manner where dispatch consciously trades payload and/or range to enable safe operations to and from short runways. This work describes a simple yet novel analytical process suitable for inclusion in conceptual design or technology portfolio trade study evaluations to assess the impacts of weight-restricted dispatch upon usable payloads. We find that options that increase low-speed thrust may maintain or improve the useful payload even if it substantially increases aircraft fixed weight. Conversely, otherwise desirable technologies that decrease low-speed thrust may severely impact the useful payload of aircraft operating to and from short runways.

Aerospace doi: 10.3390/aerospace13050481

Authors: Naiming Qi Long He Rui Zhou Kaiyuan Liu Xu Wang Li Yao

To meet the high-precision and automated requirements for the insertion assembly between large-scale components and non-cooperative outer shells, an impedance-controlled large-component insertion assembly technology, namely compliant insertion assembly technology, is proposed. This paper explains the working principle of the technology from a theoretical perspective, elaborates on two key technical aspects—pose control and force-following control based on a parallel mechanism—and conducts horizontal insertion assembly simulation for components. The simulation results demonstrate that force-following control via the parallel mechanism can reduce the axial pose accuracy error between the component and the shell by more than 85%, meeting the pose accuracy requirements for insertion assembly. It is also verified that force-following control can adjust the pose of the shell in real time based on the coaxiality between the component and the shell, satisfying the minor deformation requirements during the insertion assembly process.

Aerospace doi: 10.3390/aerospace13050479

Authors: Wenlei Liu Minghua Hu Wen Tian Jinghui Sun

To address peak-period congestion in high-density air route networks and the high cost and limited precision of traditional global control methods, this study proposes a congestion mitigation method based on pinning control theory. First, a comprehensive evaluation index system for critical waypoints is constructed from complex-network structural characteristics, traffic flow characteristics, and congestion-state information. Pearson correlation analysis is used to examine redundancy among candidate indicators, and the entropy-weighted TOPSIS method is then employed to evaluate waypoint importance and identify critical pinning nodes. Second, a GA-PID pinning control optimization model is established to realize closed-loop optimization of network congestion by dynamically regulating a small number of critical nodes. Finally, simulation experiments are conducted using actual operational trajectory data from the Yangtze River Delta airspace. The results show that the proposed method reduces the network congestion coefficient from 176 to 137, representing a decrease of 22.16%, and increases airspace resource utilization from 70.76% to 84.41%, representing an improvement of 19.29%. Compared with the baseline GA method, the proposed method achieves better optimization performance and requires adjustments at only 13 waypoints, whereas the baseline GA method requires adjustments at 25 waypoints, demonstrating lower control costs and higher regulation efficiency.

Aerospace doi: 10.3390/aerospace13050478

Authors: Gabriele Milanese Edward Canepa Massimo Rivarolo Loredana Magistri

The use of computational fluid dynamics provides an important tool for the design of supersonic ejectors. Within Reynolds/Favre-averaged simulations, the turbulence model plays an essential role in determining results’ reliability. Existing validation studies show general accuracy problems, whose relevance, partially masked in the double-choked regime, becomes fully evident for the single-choked regime. For this flow regime, errors reported in the literature are strongly erratic, reaching magnitudes higher than 50% in terms of global performance. The absence of clear, unified conclusions by different authors motivates the present work, focused on single-choked ejectors. In the first part, the main ejector flow features are discussed, highlighting the importance of adequately reproducing the turbulence response to different shear intensities. To properly address this point, an original analysis is conducted, exploiting data from previous studies on jets and basic shear flows. The developed analysis explains how the prediction of an ejector jet is influenced by the constitutive relationship of eddy viscosity models and by the modelled balance of the turbulent-dissipation rate. The modelling failures of these two elements are discussed for existing models in common use and addressed through the development of a new Consistent Realizable K − ε model. In Part 2, the analyzed models are used to simulate two test cases, with detailed measurements available.

Aerospace doi: 10.3390/aerospace13050477

Authors: Feng Yang Ziheng Cheng Chengyu Zhao

In this paper, a radial basis function (RBF) neural network based trajectory generation strategy is proposed to solve the online rapid generation of initial reference trajectory for low-cost hypersonic glide vehicles (HGV) under initial state perturbation. Firstly, the feasible trajectories that constitute the sample sets are offline generated by pseudospectral method according to the possible distribution of heights and velocities. Then, the sample set is randomly divided into training subset and test subset, by which the RBF neural network is trained and verified. Moreover, the input of the RBF neural network is a vector comprised by height and velocity from the initial state, whereas the output is a discrete state-control sequence which represents the trajectory from the current state to the expected final state. The simulation results validate that the proposed method has high confidence and small errors, which can improve the on-line generation efficiency of the trajectory.

Aerospace doi: 10.3390/aerospace13050476

Authors: Ce Zhang Hexiang Wang Daxin Liao Dawei Liu Xiping Kou Siyuan Gao Guoshuai Li Yang Tao

Boundary layer suction is a critical technique in hybrid laminar flow control (HLFC) for delaying transition and reducing drag. While the effectiveness of suction is well-established, systematic studies on the parametric optimization of suction hole diameter, location, and coefficient for two-dimensional airfoils remain scarce. This study addresses this gap through numerical investigations using the validated γ-Re~θt transition model. The research systematically analyzes the synergistic effects of suction coefficient (Cq), location (5%, 10%, and 15% chord), and suction hole diameter (0.2 mm, 0.6 mm, and 1.0 mm) on transition characteristics and aerodynamic performance. The results reveal that suction location predominantly governs the viscous drag coefficient (CDv), whereas suction hole diameter primarily influences the pressure drag coefficient (CDp). Consequently, suction location selection proves more critical for drag reduction than suction hole diameter. The maximum drag reduction (11.9% decrease in CD) and optimal transition delay (11.8% chord shift) are achieved using a small suction hole (0.2 mm) located at an aft position (15% chord) with a high suction coefficient. Furthermore, an optimal matching range exists between suction location and coefficient, which widens with decreasing suction hole diameter. Based on these findings, this study proposes an energy-efficient design strategy: employing small apertures across the suction region while gradually increasing suction rates toward the trailing edge to achieve significant drag reduction with minimal energy penalty.

Aerospace doi: 10.3390/aerospace13050475

Authors: Alexa-Andreea Crisan Mircea Moraru Daniel-Eugeniu Crunteanu Alina Bogoi

Effective thermal insulation of cryogenic liquid hydrogen (LH2) storage tanks remains a critical engineering challenge, as conventional vacuum-based or monolithic systems are constrained by manufacturing complexity, mechanical vulnerability, and poor geometric adaptability. This study presents the design and numerical verification of a four-layer octagonal composite thermal shield fabricated via additive manufacturing: an AA5083 structural layer (5 mm), a boron nitride-doped ceramic plate (1 mm), up to 290 stacked graphene sheets in a sealed compartment, and an outer Fe3S4-TiO2 nanocomposite layer (~30 µm). Steady-state and transient FEA in ANSYS evaluated three convective boundary conditions (h = 10, 15, and 20 W/m2·K), with the inner wall fixed at 20 K. Temperature distributions remained essentially invariant across all cases (20 K inner, ~20.12 K outer), confirming that thermal performance is governed by the multilayer architecture rather than convective intensity. The shield achieved a mean heat flux of 1684 W/m2, R_total ≈ 0.163 m2K/W, and a boil-off rate of 13.9 g/hour. Comparative FEA against NASA US9617069 (q = 193.35 W/m2) and JP2018-119634A (q = 37.975 W/m2) highlights the compactness advantage of the proposed 6 mm shield; the coupled thermo-structural assessment yielded a safety factor of 64,182, confirming elastic-regime operation at 20 K.

Aerospace doi: 10.3390/aerospace13050474

Authors: Yanzhao Li Xiaoyi Du Wenlong Niu Xiaodong Peng Yun Li Siqi Li

Deep space exploration missions may encounter opportunities to visit previously unplanned small bodies, which require timely and reliable observation planning under complex engineering constraints. However, traditional manual planning is labor-intensive and difficult to adapt to multi-objective flyby scenarios, while fully autonomous systems still face reliability limitations. To address these challenges, this study proposes SB-ObsGen, a framework for flyby small-body observation plan generation that integrates large language models (LLMs) with physics-informed tools. The framework follows a Generate-and-Optimize paradigm: an Observation Plan Generation Module decomposes tasks and invokes domain-specific tools to derive feasible observation information, and a Plan Optimization Module iteratively refines the initial plan through discriminator-guided feedback. Experiments on 80 mission scenarios show that SB-ObsGen achieves strong performance across different LLM backbones, with the best configurations reaching over 85% plan consistency with reference recommendation plans. Comparative experiments against classical planning methods further show that the proposed framework is competitive on structured planning tasks while offering additional advantages in tool use, flexible constraint handling, and end-to-end planning from heterogeneous inputs. Ablation studies confirm the critical role of the Plan Optimization Module in improving final plan quality.

Aerospace doi: 10.3390/aerospace13050473

Authors: Zhenyu Sun Heli Yang Jiashuai Zhou Huijie Jin Lei Jin Xinqian Zheng

Compressor surge detection, as a critical issue of aero-engines, often faces limitations with physics-based methods due to their reliance on expert-driven feature engineering and empirical thresholding rules. While deep learning offers superior feature extraction, it is hindered by low interpretability and high computational demands for real-time deployment. This paper aims to resolve these issues by proposing a novel framework that integrates a Lightweight Deep Support Vector Data Description (LWDSVDD) network with an Enhanced layer-wise relevance propagation (Enhanced-LRP) structure and dynamic threshold strategy. This new Enhanced-LIP algorithm identifies top-ranking temporal and spectral features by evaluating relevance score along with sensitivity for the surge phenomenon, ensuring precise and minimal extraction of critical features. Subsequently, these features are processed by the LWDSVDD which essentially embeds depthwise separable convolutions into traditional Deep Supported Vector Description, decomposing standard convolutions to depthwise and pointwise operations to achieve lightweight design. The joint effect of enhanced-LRP and LWDSVDD design enables a significant reduction in computational cost with minimal impact on detection accuracy. The proposed model was validated on several types of full-scale multi-stage compressors by deploying it in a portable edge-computing system, successfully demonstrating not only robustness to external interferences but also real-time surge warning capability with substantial lead time for reliable active anti-surge control.

Aerospace doi: 10.3390/aerospace13050471

Authors: Liang Ma Zhanwu Li Juntao Zhang You Li Shijie Deng

Flight dynamics modeling is a fundamental cornerstone of aircraft design, simulation, and control. Traditional approaches rely on aerodynamic look-up tables for numerical integration, which suffer from high data-acquisition costs, poor extrapolation capability, and difficulty in assimilating flight test data. This paper proposes an architectural integration of physics-informed neural networks (PINNs), graph neural networks (GNNs), and known flight mechanics equations for flight dynamics modeling. Without requiring aerodynamic coefficient labels, the method predicts flight state derivatives using state-transition data. The approach encodes the structural knowledge of flight mechanics equations into graph topology and a physics computation layer (PhysicsLayer), so that the neural network only needs to learn the unknown aerodynamic coefficients while all remaining physical relationships are computed by the governing equations. Using an F-16 fighter six-degree-of-freedom model as the verification platform, an ablation study involving Direct-MLP, PINN, PIGNN, and GNN is conducted. Results show that the PIGNN architecture improves single-step derivative prediction accuracy by 86.6% over Direct-MLP, 60.9% over pure PINN, and 90.8% over GNN. In 499-step (approximately 5 s) rollout state prediction, the PIGNN Core RMSE is 1.1554, with approximately linear error growth within the first 100 steps indicating well-controlled short-range error accumulation. The graph-structural prior enables the network to learn aerodynamic coefficients that closely match the F-16 reference aerodynamic database without aerodynamic coefficient supervision. The results demonstrate that combining graph-based dependency modeling with hard physical constraints is effective for interpretable flight dynamics surrogate modeling.