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SHM for Complex Composite Aerospace Structures: A Case Study on Engine Fan Blades
SMA Torsional Actuators for Autonomous Thermal Control in Small Satellites
Comparison of Noise Impact from Aircraft Flyover Measurements and Simulations Considering Model Uncertainties
Condensing AI-Based Attitude Control Using Kolmogorov–Arnold Networks

Journal Description

Aerospace

Aerospace is a peer-reviewed, open access journal of aeronautics and astronautics, published monthly online by MDPI. The European Aerospace Science Network (EASN) and ECATS International Association are affiliated with Aerospace and their members receive a discount on the article processing charges.

Open Access— free for readers, with article processing charges (APC) paid by authors or their institutions.
High Visibility: indexed within Scopus, SCIE (Web of Science), Inspec, Ei Compendex, and other databases.
Journal Rank: JCR - Q2 (Engineering, Aerospace) / CiteScore - Q2 (Aerospace Engineering)
Rapid Publication: manuscripts are peer-reviewed and a first decision is provided to authors approximately 22.9 days after submission; acceptance to publication is undertaken in 2.4 days (median values for papers published in this journal in the second half of 2025).
Recognition of Reviewers: reviewers who provide timely, thorough peer-review reports receive vouchers entitling them to a discount on the APC of their next publication in any MDPI journal, in appreciation of the work done.
Journal Cluster of Mechanical Manufacturing and Automation Control: Aerospace, Automation, Drones, Journal of Manufacturing and Materials Processing, Machines, Robotics and Technologies.

Impact Factor: 2.2 (2024); 5-Year Impact Factor: 2.4 (2024)

Imprint Information Journal Flyer Open Access ISSN: 2226-4310

Latest Articles

15 pages, 3495 KB

Open AccessArticle

Towards More Reliable Aircraft Emission Inventories for Local Air Quality Assessment

by Kiana Sanajou and Oxana Tchepel

Aerospace 2026, 13(1), 88; https://doi.org/10.3390/aerospace13010088 (registering DOI) - 14 Jan 2026

Accurate quantification of aircraft emissions and their uncertainties is essential for well-informed policy-making, air quality management, and the development of sustainable airport strategies. This study addresses uncertainties in aircraft emission estimates implemented for local air pollutants with hourly resolution at six European airports. [...] Read more.

Accurate quantification of aircraft emissions and their uncertainties is essential for well-informed policy-making, air quality management, and the development of sustainable airport strategies. This study addresses uncertainties in aircraft emission estimates implemented for local air pollutants with hourly resolution at six European airports. Publicly available flight-tracking data were used to determine aircraft movements and types, but they typically lack detailed information on aircraft engine models, thus contributing to uncertainties in emission factors. Times-in-mode for take-off, climb-out, and approach modes followed International Civil Aviation Organization (ICAO) recommendations, while taxi times, known to vary between airports, were modeled using statistical distributions derived from Eurocontrol, and the contribution of taxi time to overall uncertainty in emission estimates was investigated. Monte Carlo simulation combined with Sobol sensitivity analysis identified the relative contribution of each uncertainty source. On average, the results indicate an uncertainty of 23% for CO, 34% for HC, 7% for NO_x, and 21% for PM across the airports analyzed. Overall, the proposed methodology introduces a novel framework utilizing publicly available, hourly resolved flight-tracking data with robust uncertainty analysis to estimate airport-level emissions with enhanced reliability, providing crucial information for local air quality assessment and policy development. Full article

(This article belongs to the Section Air Traffic and Transportation)

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39 pages, 24515 KB

Open AccessReview

Center of Mass Measurement Technology and Its Research Progress in the Aerospace Field

by Huan Wang, Qilong Jiang, Hanbin Zhu, Wenke Zhou, Chang Liu and Hongchao Zhao

Aerospace 2026, 13(1), 87; https://doi.org/10.3390/aerospace13010087 - 13 Jan 2026

The center of mass is a key parameter characterizing the mass distribution of an object, and its measurement holds significant importance in high-tech fields such as aerospace, the defense industry, and precision manufacturing. With modern engineering demanding ever-increasing spacecraft flight stability, control precision, [...] Read more.

The center of mass is a key parameter characterizing the mass distribution of an object, and its measurement holds significant importance in high-tech fields such as aerospace, the defense industry, and precision manufacturing. With modern engineering demanding ever-increasing spacecraft flight stability, control precision, and precision measurement requirements, the accuracy, efficiency, and adaptability of center of mass measurement have also become research hotspots. This paper systematically reviews current mainstream measurement techniques, including static and dynamic methods, while analyzing their respective advantages and sources of error. By comparing Chinese and non-Chinese achievements in center of mass measurement equipment development and engineering applications, it identifies existing challenges and issues in the field and outlines future trends in center of mass measurement technology. Full article

(This article belongs to the Special Issue Advanced Manufacturing, Assembly, and Testing Technologies for Spacecraft)

16 pages, 1705 KB

Open AccessArticle

Economic Analysis of a ROXY Pilot Plant Supporting Early Lunar Mission Architectures

by Tehya F. Birch, Achim Seidel, James E. Johnson, Georg Poehle and Uday Pal

Aerospace 2026, 13(1), 86; https://doi.org/10.3390/aerospace13010086 - 13 Jan 2026

The establishment of a sustained human presence on the Moon is critically dependent on the ability to utilize local resources, primarily the production of oxygen for life support and propellant. The ROXY (Regolith to Oxygen and metals conversion) process is a molten salt [...] Read more.

The establishment of a sustained human presence on the Moon is critically dependent on the ability to utilize local resources, primarily the production of oxygen for life support and propellant. The ROXY (Regolith to Oxygen and metals conversion) process is a molten salt electrolysis technology designed for this purpose. This paper presents an economic analysis of a ROXY pilot plant capable of producing over one ton of oxygen per year. We evaluate the economic viability by analyzing development, transportation, and operational costs against the potential revenue from selling oxygen and metals within a nascent lunar economy. A key aspect of this analysis is the perspective of an early customer in habitation life support systems preceding that of much higher propellant production demand. The analysis contextualizes this paradigm by recognizing that the primary economic driver for oxygen production is the larger future market for propellant; however, early life support demand may incentivize a paradigm-shift from Earth-based consumable resupply. Scenarios based on varying transportation costs and development timelines are evaluated to determine the internal rate of return (IRR) and time to break even (TTBE). The results indicate that the ROXY pilot plant is economically viable, particularly in near-term scenarios with higher transportation costs, achieving a positive IRR of up to 47.4% when both oxygen and metals are sold. The analysis identifies facility mass, driven by the robotics subsystem, as the primary factor for future cost-reduction efforts, concluding that ROXY is a technically and economically sound pathway toward sustainable lunar operations. Full article

(This article belongs to the Section Astronautics & Space Science)

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22 pages, 363 KB

Open AccessReview

Human Factors, Competencies, and System Interaction in Remotely Piloted Aircraft Systems

by John Murray and Graham Wild

Aerospace 2026, 13(1), 85; https://doi.org/10.3390/aerospace13010085 - 13 Jan 2026

Research into Remotely Piloted Aircraft Systems (RPASs) has expanded rapidly, yet the competencies, knowledge, skills, and other attributes (KSaOs) required of RPAS pilots remain comparatively underexamined. This review consolidates existing studies addressing human performance, subject matter expertise, training practices, and accident causation to [...] Read more.

Research into Remotely Piloted Aircraft Systems (RPASs) has expanded rapidly, yet the competencies, knowledge, skills, and other attributes (KSaOs) required of RPAS pilots remain comparatively underexamined. This review consolidates existing studies addressing human performance, subject matter expertise, training practices, and accident causation to provide a comprehensive account of the KSaOs underpinning safe civilian and commercial drone operations. Prior research demonstrates that early work drew heavily on military contexts, which may not generalize to contemporary civilian operations characterized by smaller platforms, single-pilot tasks, and diverse industry applications. Studies employing subject matter experts highlight cognitive demands in areas such as situational awareness, workload management, planning, fatigue recognition, perceptual acuity, and decision-making. Accident analyses, predominantly using the human factors accident classification system and related taxonomies, show that skill errors and preconditions for unsafe acts are the most frequent contributors to RPAS occurrences, with limited evidence of higher-level latent organizational factors in civilian contexts. Emerging research emphasizes that RPAS pilots increasingly perform data-collection tasks integral to professional workflows, requiring competencies beyond aircraft handling alone. The review identifies significant gaps in training specificity, selection processes, and taxonomy suitability, indicating opportunities for future research to refine RPAS competency frameworks and support improved operational safety. Full article

(This article belongs to the Special Issue Human Factors and Performance in Aviation Safety)

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24 pages, 14492 KB

Open AccessArticle

Impact of Groove Manufacturing Errors on Aircraft Skin-Friction Reduction

by Zhaoliang Dou, Yue Du and Fengbin Liu

Aerospace 2026, 13(1), 84; https://doi.org/10.3390/aerospace13010084 - 13 Jan 2026

This study systematically investigates the effects of manufacturing errors on the drag reduction performance of micro-grooves fabricated using roll-to-roll hot embossing technology. Numerical simulations were conducted to analyze the drag reduction characteristics of spanwise micro-grooves under a 0.4 Ma incoming flow, with a [...] Read more.

This study systematically investigates the effects of manufacturing errors on the drag reduction performance of micro-grooves fabricated using roll-to-roll hot embossing technology. Numerical simulations were conducted to analyze the drag reduction characteristics of spanwise micro-grooves under a 0.4 Ma incoming flow, with a focus on the influence mechanisms of groove array straightness error (δ) and bottom corner rounding error (σ) on aerodynamic performance. The results indicate that straightness errors induce periodic pressure pulsations, which disrupt large-scale turbulent structures and lead to a linear degradation in drag reduction performance. In contrast, bottom corner rounding errors modulate small-scale turbulence by altering the local curvature at the groove bottom. Positive deviations in particular cause an upward shift of the vortex core and enhanced energy dissipation, significantly impairing drag reduction. Based on these findings, an optimized processing window is proposed, recommending that the straightness error δ and bottom corner rounding error σ be controlled within −4% to 2% and −20% to 4%, respectively. Under these conditions, the fluctuation in the drag reduction rate can be confined within 20%. This study provides important theoretical insights and practical guidance for the precision manufacturing of drag-reducing micro-groove surfaces on aircraft. Full article

(This article belongs to the Section Aeronautics)

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21 pages, 3877 KB

Open AccessArticle

Investigation of Cavitation Inception in Aviation Hydraulic Fluid AMG-10 in a Small-Scale Rectangular Throttle Channel

by Volodymyr Brazhenko and Taras Tarasenko

Aerospace 2026, 13(1), 83; https://doi.org/10.3390/aerospace13010083 - 13 Jan 2026

Cavitation in aircraft hydraulic systems continues to pose a serious problem for the aviation industry. This paper presents a new study on cavitation in aviation hydraulic fluid AMG-10 at its inception condition, corresponding to a relative pressure drop of Δp = 0.58, [...] Read more.

Cavitation in aircraft hydraulic systems continues to pose a serious problem for the aviation industry. This paper presents a new study on cavitation in aviation hydraulic fluid AMG-10 at its inception condition, corresponding to a relative pressure drop of Δp = 0.58, within a small-scale rectangular throttle channel of specified dimensions. Numerical simulations were performed in a quasi-steady-state framework using the realizable k–ε turbulence model combined with the Enhanced Wall Treatment approach, and the results were validated against time-integrated experimental data obtained via the shadowgraphy method. Cavitation was modeled using the Zwart–Gerber–Belamri model. The validated numerical model, which showed a pressure deviation of less than 10% from experimental data on the upper and lower walls, also demonstrated good agreement in the dimensions of the cavitation regions, confirming that the upper region is consistently larger than the lower one. Quantitative analysis demonstrated that regions with high vapor concentration are highly localized, representing only 0.048% of the channel volume at a 0.8 vapor fraction threshold. The analysis reveals that the cavitation regions spatially coincide with local pressure drops to values as low as 214 and 236 Pa near the upper and lower walls. These regions are also associated with wall jets, accelerated by the flow constriction to velocities up to 41.98 m/s. Furthermore, the cavitation region corresponds to a distinct peak in the mean turbulent kinetic energy field, reaching 164.5 m²/s², which decays downstream. Full article

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36 pages, 1481 KB

Open AccessArticle

A Novel Stochastic Framework for Integrated Airline Operation Planning: Addressing Codeshare Agreements, Overbooking, and Station Purity

by Kübra Kızıloğlu and Ümit Sami Sakallı

Aerospace 2026, 13(1), 82; https://doi.org/10.3390/aerospace13010082 - 12 Jan 2026

This study presents an integrated optimization framework for fleet assignment, flight scheduling, and aircraft routing under uncertainty, addressing a core challenge in airline operational planning. A three-stage stochastic mixed-integer nonlinear programming model is developed that, for the first time, simultaneously incorporates station purity [...] Read more.

This study presents an integrated optimization framework for fleet assignment, flight scheduling, and aircraft routing under uncertainty, addressing a core challenge in airline operational planning. A three-stage stochastic mixed-integer nonlinear programming model is developed that, for the first time, simultaneously incorporates station purity constraints, codeshare agreements, and overbooking decisions. The formulation also includes realistic operational factors such as stochastic passenger demand and non-cruise times (NCT), along with adjustable cruise speeds and flexible departure time windows. To handle the computational complexity of this large-scale stochastic problem, a Sample Average Approximation (SAA) scheme is combined with two tailored metaheuristic algorithms: Simulated Annealing and Cuckoo Search. Extensive experiments on real-world flight data demonstrate that the proposed hybrid approach achieves tight optimality gaps below 0.5%, with narrow confidence intervals across all instances. Moreover, the SA-enhanced method consistently yields superior solutions compared with the CS-based variant. The results highlight the significant operational and economic benefits of jointly optimizing codeshare decisions, station purity restrictions, and overbooking policies. The proposed framework provides a scalable and robust decision-support tool for airlines seeking to enhance resource utilization, reduce operational costs, and improve service quality under uncertainty. Full article

(This article belongs to the Collection Air Transportation—Operations and Management)

25 pages, 5648 KB

Open AccessArticle

Advanced Sensor Tasking Strategies for Space Object Cataloging

by Alessandro Mignocchi, Sebastian Samuele Rizzuto, Alessia De Riz and Marco Felice Montaruli

Aerospace 2026, 13(1), 81; https://doi.org/10.3390/aerospace13010081 - 12 Jan 2026

Space Surveillance and Tracking (SST) plays a crucial role in ensuring space safety. To this end, accurate and numerous observational resources are needed to build and maintain a catalog of space objects. In particular, it is essential to develop optimal observation strategies to [...] Read more.

Space Surveillance and Tracking (SST) plays a crucial role in ensuring space safety. To this end, accurate and numerous observational resources are needed to build and maintain a catalog of space objects. In particular, it is essential to develop optimal observation strategies to maximize both the number and the quality of detections obtained from a sensor network. This represents a key step in the assessment of the network through simulations. This work presents the integrated development of sensor tasking strategies for optical systems and a track-to-track correlation pipeline within S

Ξ

NSIT, a software environment designed to simulate sensor network configurations and evaluate cataloging performance. For high-altitude low Earth orbit (HLEO) targets, which are fast-moving and widely distributed, tasking strategies emphasize systematic scans of the Earth’s shadow boundary to exploit favorable phase angles and improve observational accuracy, while medium- and geostationary-Earth orbits (MEO–GEO) rely on equatorial-plane scans. The correlation pipeline employs Two-Body Integrals, uncertainty propagation, and a

χ^{2}

-test with the Squared Mahalanobis Distance to associate tracks and perform initial orbit determination of newly detected objects. Results indicate that the integrated approach significantly enhances detection coverage, leading to greater catalog build-up efficiency and improved SST performance. Consequently, it facilitates the cataloging of numerous uncataloged objects within a reduced timeframe. Full article

(This article belongs to the Special Issue Advances in Space Surveillance and Tracking)

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27 pages, 1843 KB

Open AccessArticle

AI-Driven Modeling of Near-Mid-Air Collisions Using Machine Learning and Natural Language Processing Techniques

by Dothang Truong

Aerospace 2026, 13(1), 80; https://doi.org/10.3390/aerospace13010080 - 12 Jan 2026

As global airspace operations grow increasingly complex, the risk of near-mid-air collisions (NMACs) poses a persistent and critical challenge to aviation safety. Traditional collision-avoidance systems, while effective in many scenarios, are limited by rule-based logic and reliance on transponder data, particularly in environments [...] Read more.

As global airspace operations grow increasingly complex, the risk of near-mid-air collisions (NMACs) poses a persistent and critical challenge to aviation safety. Traditional collision-avoidance systems, while effective in many scenarios, are limited by rule-based logic and reliance on transponder data, particularly in environments featuring diverse aircraft types, unmanned aerial systems (UAS), and evolving urban air mobility platforms. This paper introduces a novel, integrative machine learning framework designed to analyze NMAC incidents using the rich, contextual information contained within the NASA Aviation Safety Reporting System (ASRS) database. The methodology is structured around three pillars: (1) natural language processing (NLP) techniques are applied to extract latent topics and semantic features from pilot and crew incident narratives; (2) cluster analysis is conducted on both textual and structured incident features to empirically define distinct typologies of NMAC events; and (3) supervised machine learning models are developed to predict pilot decision outcomes (evasive action vs. no action) based on integrated data sources. The analysis reveals seven operationally coherent topics that reflect communication demands, pattern geometry, visibility challenges, airspace transitions, and advisory-driven interactions. A four-cluster solution further distinguishes incident contexts ranging from tower-directed approaches to general aviation pattern and cruise operations. The Random Forest model produces the strongest predictive performance, with topic-based indicators, miss distance, altitude, and operating rule emerging as influential features. The results show that narrative semantics provide measurable signals of coordination load and acquisition difficulty, and that integrating text with structured variables enhances the prediction of maneuvering decisions in NMAC situations. These findings highlight opportunities to strengthen radio practice, manage pattern spacing, improve mixed equipage awareness, and refine alerting in short-range airport area encounters. Full article

(This article belongs to the Section Air Traffic and Transportation)

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25 pages, 3960 KB

Open AccessArticle

Comparison of Second-Stage Recovery Methods for Reusable Launch Vehicles Across Vehicle Scales

by Geun-Jeong Lee, Min-Seon Jo and Jeong-Yeol Choi

Aerospace 2026, 13(1), 79; https://doi.org/10.3390/aerospace13010079 - 12 Jan 2026

With the cost-saving benefits of reusable launch vehicles (RLVs), South Korea is pursuing the application of reusability technologies to KSLV-III. While SpaceX currently reuses only the first stage of Falcon 9, the Starship program aims for full-stage recovery, motivating further examination of second-stage [...] Read more.

With the cost-saving benefits of reusable launch vehicles (RLVs), South Korea is pursuing the application of reusability technologies to KSLV-III. While SpaceX currently reuses only the first stage of Falcon 9, the Starship program aims for full-stage recovery, motivating further examination of second-stage reuse. This study extends the scope of the analysis to medium-class launch vehicles and evaluates the feasibility of second-stage reuse for two vehicle scales. The performance losses associated with three recovery methods—vertical landing, parachute, and fly-back—are quantitatively assessed using conceptual-level recovery system design and simplified mass modeling. For KSLV-III, a conceptual expendable medium-class launch vehicle capable of delivering a 10-ton payload to a 200 km low Earth orbit (LEO) was designed using an algebraic modeling approach. Based on this reference design, the recovery methods were evaluated for both medium-class and super-heavy-class vehicles. Results of the present order-of-magnitude conceptual trade study show that, for medium-class vehicles, the parachute provides the highest performance, followed by fly-back, while vertical landing yields the lowest. For super-heavy vehicles, the parachute remains the most effective, but vertical landing becomes the second-best option, with fly-back exhibiting the lowest performance. As the vehicle scale increases, parachute effectiveness declines, fly-back performance improves, and vertical landing shows the greatest performance gains. However, parachute becomes impractical for super-heavy vehicles due to structural limitations, making vertical landing the most viable option. In contrast, medium-class vehicles do not necessarily require vertical landing, and the optimal recovery strategy should be chosen based on vehicle structural characteristics and mission objectives. This study provides insights that support the selection of efficient recovery strategies during the early design phase of RLVs. Full article

(This article belongs to the Section Astronautics & Space Science)

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36 pages, 6026 KB

Open AccessArticle

CNN-LSTM Assisted Multi-Objective Aerodynamic Optimization Method for Low-Reynolds-Number Micro-UAV Airfoils

by Jinzhao Peng, Enying Li and Hu Wang

Aerospace 2026, 13(1), 78; https://doi.org/10.3390/aerospace13010078 - 11 Jan 2026

The optimization of low-Reynolds-number airfoils for micro unmanned aerial vehicles (UAVs) is challenging due to strong geometric nonlinearities, tight endurance requirements, and the need to maintain performance across multiple operating conditions. Classical surrogate-assisted optimization (SAO) methods combined with genetic algorithms become increasingly expensive [...] Read more.

The optimization of low-Reynolds-number airfoils for micro unmanned aerial vehicles (UAVs) is challenging due to strong geometric nonlinearities, tight endurance requirements, and the need to maintain performance across multiple operating conditions. Classical surrogate-assisted optimization (SAO) methods combined with genetic algorithms become increasingly expensive and less reliable when class–shape transformation (CST)-based geometries are coupled with several flight conditions. Although deep learning surrogates have higher expressive power, their use in this context is often limited by insufficient local feature extraction, weak adaptation to changes in operating conditions, and a lack of robustness analysis. In this study, we construct a task-specific convolutional neural network–long short-term memory (CNN–LSTM) surrogate that jointly predicts the power factor, lift, and drag coefficients at three representative operating conditions (cruise, forward flight, and maneuver) for the same CST-parameterized airfoil and integrate it into an Non-dominated Sorting Genetic Algorithm II (NSGA-II)-based three-objective optimization framework. The CNN encoder captures local geometric sensitivities, while the LSTM aggregates dependencies across operating conditions, forming a compact encoder–aggregator tailored to low-Re micro-UAV design. Trained on a computational fluid dynamics (CFD) dataset from a validated SD7032-based pipeline, the proposed surrogate achieves substantially lower prediction errors than several fully connected and single-condition baselines and maintains more favorable error distributions on CST-family parameter-range extrapolation samples (±40%, geometry-valid) under the same CFD setup, while being about three orders of magnitude faster than conventional CFD during inference. When embedded in NSGA-II under thickness and pitching-moment constraints, the surrogate enables efficient exploration of the design space and yields an optimized airfoil that simultaneously improves power factor, reduces drag, and increases lift compared with the baseline SD7032. This work therefore contributes a three-condition surrogate–optimizer workflow and physically interpretable low-Re micro-UAV design insights, rather than introducing a new generic learning or optimization algorithm. Full article

(This article belongs to the Section Aeronautics)

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19 pages, 14871 KB

Open AccessArticle

Deep Q-Network for Maneuver Planning in Beyond-Visual-Range Aerial Pursuit–Evasion with Target Re-Engagement

by Long-Jun Zhu, Kevin W. Tong and Edmond Q. Wu

Aerospace 2026, 13(1), 77; https://doi.org/10.3390/aerospace13010077 - 11 Jan 2026

Decision-making for maneuvering in the presence of long-range threats is crucial for enhancing the safety and reliability of autonomous aerial platforms operating in beyond-line-of-sight environments. This study employs the Deep Q-Network (DQN) method to investigate maneuvering strategies for simultaneously avoiding incoming high-speed threats [...] Read more.

Decision-making for maneuvering in the presence of long-range threats is crucial for enhancing the safety and reliability of autonomous aerial platforms operating in beyond-line-of-sight environments. This study employs the Deep Q-Network (DQN) method to investigate maneuvering strategies for simultaneously avoiding incoming high-speed threats and re-establishing tracking of a maneuvering target platform. First, kinematic models for the aerial platforms and the approaching interceptor are developed, and a DQN training environment is constructed based on these models. A DQN framework is then designed, integrating scenario-specific state representation, action space, and a hybrid reward structure to enable autonomous strategy learning without prior expert knowledge. The agent is trained within this environment to achieve near-optimal maneuvering decisions, with comparative evaluations against Q-learning and deep deterministic policy gradient (DDPG) baselines. Simulation results demonstrate that the trained model outperforms the baselines on key metrics by effectively avoiding approaching threats, re-establishing robust target tracking, reducing maneuver time, and exhibiting strong generalization across challenging scenarios. This work advances Beyond-Visual-Range (BVR) maneuver planning and provides a foundational methodological framework for future research on complex multi-stage aerial pursuit–evasion problems. Full article

(This article belongs to the Section Aeronautics)

21 pages, 3769 KB

Open AccessArticle

Response Surface Methodology-Driven Design Optimization for Ducted Fans

by Weijie Gong, Kaihua Fu and Hong Chen

Aerospace 2026, 13(1), 76; https://doi.org/10.3390/aerospace13010076 - 11 Jan 2026

Due to the complexity of aerodynamic coupling between the duct and propeller, the overall design and optimization of ducted fans often require extensive experience and time. Meanwhile, traditional design methods based on Blade Element Momentum Theory, Lifting Surface Theory, Vortex Lattice Methods, and [...] Read more.

Due to the complexity of aerodynamic coupling between the duct and propeller, the overall design and optimization of ducted fans often require extensive experience and time. Meanwhile, traditional design methods based on Blade Element Momentum Theory, Lifting Surface Theory, Vortex Lattice Methods, and Panel Method usually exhibit certain deviations between their design results and actual outcomes. This is because these approaches struggle to accurately calculate the aerodynamic coupling effects between the duct and propeller, coupled with numerous simplifications inherent in the methods themselves. Considering the strong nonlinear coupling relationship between the duct and propeller, the Response Surface Method (RSM), which enables efficient and accurate analysis of multi-variable coupling effects, was selected for the parameter design and optimization of ducted fans. Computational Fluid Dynamics (CFD) was applied to evaluate the impact of design parameters on overall aerodynamic performance. This approach addresses the limitations of traditional methods, including low design accuracy, high computational cost, and insufficient multi–objective optimization capability. It explicitly models multi-parameter coupling and nonlinear effects using a small number of experimental points, combined with the Multi-Objective Genetic Algorithm (MOGA) to find the global optimum. Compared to the baseline duct fan, the optimized duct fan achieved a 9.6% increase in overall lift and a 9.5% improvement in lift efficiency. Full article

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25 pages, 1336 KB

Open AccessArticle

Motion Accuracy and Dynamic Responses of Dual-Manipulator on Spacecraft Considering Clearance Joints

by Yiling Kuang, Zhengfeng Bai and Cheng Wei

Aerospace 2026, 13(1), 75; https://doi.org/10.3390/aerospace13010075 - 10 Jan 2026

Clearance in joints caused by assemblage, manufacturing errors, and wear is inevitable, which will affect the dynamic performance of the dual-manipulator system on spacecraft. The motion of the dual-manipulator system with clearances in imperfect joints is the motion of dual-manipulator system with ideal [...] Read more.

Clearance in joints caused by assemblage, manufacturing errors, and wear is inevitable, which will affect the dynamic performance of the dual-manipulator system on spacecraft. The motion of the dual-manipulator system with clearances in imperfect joints is the motion of dual-manipulator system with ideal joints. In this paper, the dynamic responses and motion accuracy ofdual-manipulator system on spacecraft considering clearance effects are investigated numerically. The imperfect joint with clearance is considered as contact force constraint and the mathematical model of revolute joint with clearance is established, where the normal contact force is established using nonlinear continuous contact force model and the friction effect is considered using modified Coulomb friction model. Then, a dual-manipulator system on spacecraft with clearance joints is used as the numerical example to implement the investigation. The effects of clearances on dynamic responses and motion accuracy of the dual-manipulator system are presented and discussed via different case studies. Numerical simulation results indicate that clearances present significant effects on the dynamic performances of dual-manipulator system due to contact and impact in clearance joints. The motion accuracy and stability of the dual-manipulator system are obviously reduced. The investigation in this work clearly shows the effects of clearances on dynamic performance of the dual-manipulator system on spacecraft, which is the basis for robust control system design of dual-manipulator system. Full article

(This article belongs to the Section Astronautics & Space Science)

22 pages, 14281 KB

Open AccessArticle

An FPGADSP-Based On-Orbit Software Updating Architecture and Strategy for Satellite Payload Control Systems⁺

by Peijun Zhong, Chongru Wang, Maoxing Wen, Hongsong Qu, Yueming Wang and Tao Wang

Aerospace 2026, 13(1), 74; https://doi.org/10.3390/aerospace13010074 - 10 Jan 2026

This paper presents an architecture and strategy for on-orbit software updating of satellite payload control systems, based on a tightly coupled DSP and FPGA design. The architecture achieves tight coupling between the DSP and FPGA via the XINTF interface, integrating the DSP program [...] Read more.

This paper presents an architecture and strategy for on-orbit software updating of satellite payload control systems, based on a tightly coupled DSP and FPGA design. The architecture achieves tight coupling between the DSP and FPGA via the XINTF interface, integrating the DSP program and data into the FPGA bitstream. This enables synchronous updating of both chips with a single software package, significantly reducing both uplink data volume and update time. The system features a dual-flash redundant boot design and a mutual supervision mechanism between the DSP and FPGA, enabling cross-monitoring and autonomous reset, thereby significantly enhancing the system’s fault tolerance and reliability in orbit. Experimental results demonstrate a substantial improvement in fault recovery, with the weighted mean recovery time reduced from 27.09 s to 1.56 s, a relative improvement of 94.25% compared to conventional methods. Ground-based environmental tests confirm the system’s stability and engineering viability under extreme space conditions. Full article

(This article belongs to the Section Astronautics & Space Science)

18 pages, 5059 KB

Open AccessArticle

Decision Tree-Based Pilot Workload Prediction Through Optimized HRV Features Selection

by Carmelo Rosario Vindigni, Giuseppe Iacolino, Antonio Esposito, Calogero Orlando and Andrea Alaimo

Aerospace 2026, 13(1), 73; https://doi.org/10.3390/aerospace13010073 - 9 Jan 2026

This research explores the use of physiological signals derived from heart activity to assess mental effort during flight-related tasks. Data were collected through wearable sensors during simulations with varying cognitive demands. Specific indicators related to heart rate variability (HRV) were extracted and tested [...] Read more.

This research explores the use of physiological signals derived from heart activity to assess mental effort during flight-related tasks. Data were collected through wearable sensors during simulations with varying cognitive demands. Specific indicators related to heart rate variability (HRV) were extracted and tested in different combinations to identify those most relevant for distinguishing levels of mental workload (WL). A Random Forest (RF) ensemble method is applied to classify two conditions, and its performance is examined under various settings, including model complexity and data partitioning strategies. Results showed that certain feature pairs significantly enhanced classification accuracy. The best features settings obtained from the RF are then used to train the other two decision trees-based classifiers, namely the AdaBoost and the XGBoost. Moreover, the decision trees models output is compared with predictions from a Kriging spatial interpolation technique, showing superior results in terms of reliability and consistency. This study highlights the potential of using heart-based physiological data and advanced classification techniques for developing intelligent support systems in aviation. Full article

(This article belongs to the Section Aeronautics)

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21 pages, 3870 KB

Open AccessArticle

A Fast Robust Integrated Guidance and Control Scheme for Flight Vehicles Based on Convergence Rate Estimation Mechanism

by Tianyu Ye, Wanying Xu, Yongbin Zheng, Qingwen Ma, Peisen Zhu and Yangyang Deng

Aerospace 2026, 13(1), 72; https://doi.org/10.3390/aerospace13010072 - 9 Jan 2026

Convergence rate is a key performance index for flight vehicles, and accelerating it remains a critical open issue. In this paper, a fast robust integrated guidance and control scheme for flight vehicles based on convergence rate estimation mechanism is proposed, which improves the [...] Read more.

Convergence rate is a key performance index for flight vehicles, and accelerating it remains a critical open issue. In this paper, a fast robust integrated guidance and control scheme for flight vehicles based on convergence rate estimation mechanism is proposed, which improves the control performance and interception accuracy of flight vehicles. In the fast robust control scheme, a convergence rate indicator for integrated guidance and control systems is developed to measure the impact on convergence rate imposed by model nonlinearities and couplings within flight vehicles. Based on the indicator, the influences on convergence rate are transformed and injected into controllers to accelerate the convergence of flight vehicles. The unmatched lumped uncertainties in flight vehicle dynamics are addressed by a backstepping control method and finite-time convergence disturbance observers, which improves the robustness of the vehicle’s control system. Furthermore, the stability analysis of the closed-loop system is performed via the Lyapunov stability theorem. Extensive numerical simulations are conducted to verify the effectiveness and interception performance of the proposed method, and the comparison results confirm that it outperforms three other recently developed robust control methods. Full article

(This article belongs to the Special Issue Guidance and Control Systems of Aerospace Vehicles)

19 pages, 4805 KB

Open AccessArticle

Civil Airplane Safety Awareness Technology Using Virtual Flight Method

by Xiaojia Zhao, Zhanhang Gao and Hongyu Qiao

Aerospace 2026, 13(1), 71; https://doi.org/10.3390/aerospace13010071 - 9 Jan 2026

Civil airplanes encounter unpredictable safety risks due to uncertain environmental disturbances, mechanical failures, and pilot mis-operations. This paper develops a virtual flight method (VFM) consisting of a series of techniques including flight motion simulation, flight command simulation, flight control simulation, and flight environment [...] Read more.

Civil airplanes encounter unpredictable safety risks due to uncertain environmental disturbances, mechanical failures, and pilot mis-operations. This paper develops a virtual flight method (VFM) consisting of a series of techniques including flight motion simulation, flight command simulation, flight control simulation, and flight environment simulation. Moreover, a safety perception technique is established using fuzzy safety constraints, which transfers the decoupled analysis of micro-level aircraft state parameters to the coupled analysis of macro-level global system parameters. This integrated approach enables virtual flight operations and safety situation awareness for civil aircraft within the ‘Human–Machine–Environment’ triad under the influences of complex factors. The takeoff and climb scenario of the Cessna Citation 550 aircraft is selected as a case study to validate the feasibility of the proposed safety awareness technology. Results illustrate the capability to effectively capture the aircraft’s flight characteristics and safety status of the civil aircraft under various operational conditions. The safe operational envelope within specific scenarios is also determined. Full article

(This article belongs to the Section Aeronautics)

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25 pages, 2523 KB

Open AccessArticle

A Comparative Study of Liquid Film Cooling on a Flat Plate Using SPH and VOF Methods

by Edidiong Michael Umana, Huan Li, Xiufeng Yang, Dmitry Alexandrovich Uglanov and Naresh Kedam

Aerospace 2026, 13(1), 70; https://doi.org/10.3390/aerospace13010070 - 9 Jan 2026

This numerical study demonstrates the existence of a critical injection momentum threshold necessary for stable liquid film formation, highlighting that either excessive or insufficient momentum degrades cooling performance. This optimization is critical for maximizing cooling effectiveness from short injection holes in high-performance propulsion [...] Read more.

This numerical study demonstrates the existence of a critical injection momentum threshold necessary for stable liquid film formation, highlighting that either excessive or insufficient momentum degrades cooling performance. This optimization is critical for maximizing cooling effectiveness from short injection holes in high-performance propulsion systems. By comparing Smoothed Particle Hydrodynamics (SPH) and Volume of Fluid (VOF) methods, we find that the SPH method predicts a thicker, more continuous coolant film due to its superior mass conservation during interface breakup. A key design insight emerges: cooling performance peaks at a distinct, critical coolant momentum. Insufficient momentum leads to poor coverage, while excess momentum causes film separation and is counter-productive. The identified configuration—defined by a precise combination of flow rate, pressure, and geometry—promotes immediate and stable film formation. The robustness of this finding is confirmed by the agreement between the two numerical methods on film thickness and the captured physical evolution of the film from a pronounced wave to a damped state. Full article

(This article belongs to the Section Aeronautics)

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25 pages, 4978 KB

Open AccessArticle

Online Synchronous Coordinated Assignment and Planning for Heterogeneous Fixed-Wing UAVs

by Xindi Wang, Jiansong Zhang, Zhenyu Ma, Chuanshuo Cao and Hao Liu

Aerospace 2026, 13(1), 69; https://doi.org/10.3390/aerospace13010069 - 8 Jan 2026

This paper addresses the Multi-Target Reconnaissance (MTR) problem for heterogeneous Fixed-Wing Unmanned Aerial Vehicles (FW-UAVs), focusing on synchronized and time-optimal mission execution under stringent constraints. A two-stage coordinated assignment and planning framework is proposed. First, a time-balanced clustering algorithm is designed to minimize [...] Read more.

This paper addresses the Multi-Target Reconnaissance (MTR) problem for heterogeneous Fixed-Wing Unmanned Aerial Vehicles (FW-UAVs), focusing on synchronized and time-optimal mission execution under stringent constraints. A two-stage coordinated assignment and planning framework is proposed. First, a time-balanced clustering algorithm is designed to minimize the overall mission duration while balancing individual UAV workloads by jointly employing a target reallocation strategy and an improved Genetic Algorithm (GA). Subsequently, an online trajectory planning method based on differential flatness is developed, integrating a robust replanning and flight-time synchronization strategy to ensure coordinated execution. Simulation results unequivocally demonstrate that the proposed approach enhances time optimality and temporal coordination in complex scenarios. Full article

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