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Aerospace
Volume 12
Issue 5
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Aerospace, Volume 12, Issue 5 (May 2025) – 77 articles

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23 pages, 2135 KiB  
Article
Lessons Learned from Official Airline Reports of Onboard Fumes and Smoke
by Judith T. L. Anderson
Aerospace 2025, 12(5), 437; https://doi.org/10.3390/aerospace12050437 (registering DOI) - 14 May 2025
Abstract
The author reviewed and classified maintenance reports that cited smoke, odor, or fumes (SOFs) that US airlines sent to the FAA over four years between 2018 and 2023. The US fleet composition was also calculated to put the number of SOF reports on [...] Read more.
The author reviewed and classified maintenance reports that cited smoke, odor, or fumes (SOFs) that US airlines sent to the FAA over four years between 2018 and 2023. The US fleet composition was also calculated to put the number of SOF reports on each aircraft type in perspective. “Fume events” (engine oil or hydraulic fluid) were the most common type of onboard SOFs reported by US airlines (43%), followed by electrical (20%), and fans (6.1%). During these years, A320fam aircraft made up 20% of the US fleet but 80% of the reported fume events. Conversely, B737fam aircraft made up 27% of the US fleet but only 3.0% of the reported fume events. Aircraft design features, airline reporting practices, and maintenance procedures that may contribute to these differences were reviewed. Pilots were most likely to document a fume event during descent (47%) and takeoff/climb (19%). The A320fam, MD80fam, A330, and ERJ140-145 aircraft were over-represented in other types of SOFs reports. Airline narratives show that the APU can be the primary source of oil/hydraulic fumes, even when it is not operating. Additionally, failure to find the source of fumes, rectify it, and clean any secondary sources of fumes can cause repeat events. Full article
(This article belongs to the Special Issue Aircraft Design (SI-7/2025))
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18 pages, 6228 KiB  
Article
Aircraft Wing Design Against Bird Strike Using Metaheuristics
by Vanessa Timhede, Silvia Timhede, Seksan Winyangkul and Suwin Sleesongsom
Aerospace 2025, 12(5), 436; https://doi.org/10.3390/aerospace12050436 - 13 May 2025
Abstract
Bird strikes pose a significant threat to aviation safety, particularly affecting the wing structures of aircraft. This research aims to design and analyze the impact of bird strikes on wing structures using response surface method and metaheuristics (MHs), which are used to explore [...] Read more.
Bird strikes pose a significant threat to aviation safety, particularly affecting the wing structures of aircraft. This research aims to design and analyze the impact of bird strikes on wing structures using response surface method and metaheuristics (MHs), which are used to explore various risk minimization and damage mitigation techniques. The optimization problem is the minimization of the maximum von Mises stress of aircraft wing structure against bird strike that is subject to displacement and stress constraints. The design variables include skin and rib thickness, as well as sweep angle. Difficulty due to embedded bird strike simulation and optimization design can be alleviated using a response surface method (RSM). The regression technique in the RSM of the data can reach our goal of model fitting with a higher R2 until 0.9951 and 0.9919 are obtained for the displacement and von Mises stress model, respectively. The response surface function of the displacement and von Mises stress are related to skin thickness, while sweep angles rather than rib thickness have a greater impact on both design variables. The optimized design of the design variables is performed using MHs, which are TLBO, JADE, and PBIL. The comparative result of MHs can conclude that the PBIL outperformed others in all descriptive statistics. The optimized design results revealed that the optimum solution can release better energy due to bird strike with the highest limit of skin thickness, moderate rib thickness, and less than half of the sweep angle. The results are in accordance with the response surface function analysis. In conclusion, the optimized design of the aircraft wing structure against bird strike can be accomplished with our proposed technique. Full article
(This article belongs to the Special Issue Environmental Influences on Aircraft Aerodynamics)
21 pages, 9421 KiB  
Article
Temporal-Sequence Offline Reinforcement Learning for Transition Control of a Novel Tilt-Wing Unmanned Aerial Vehicle
by Shiji Jin and Wenjie Zhao
Aerospace 2025, 12(5), 435; https://doi.org/10.3390/aerospace12050435 - 13 May 2025
Abstract
A newly designed tilt-wing unmanned aerial vehicle (Tilt-wing UAV) requires a unified control strategy across rotary-wing, fixed-wing, and transition modes, introducing significant challenges. Existing control strategies typically rely on accurate modeling or extensive parameter tuning, which limits their adaptability to dynamically changing flight [...] Read more.
A newly designed tilt-wing unmanned aerial vehicle (Tilt-wing UAV) requires a unified control strategy across rotary-wing, fixed-wing, and transition modes, introducing significant challenges. Existing control strategies typically rely on accurate modeling or extensive parameter tuning, which limits their adaptability to dynamically changing flight configurations. Although online reinforcement learning algorithms offer adaptability, they depend on real-world exploration, posing considerable safety and cost risks for safety-critical UAV applications. To address this challenge, we propose Temporal Sequence Constrained Q-learning (TSCQ), an offline RL framework that integrates an encoder–decoder with recurrent networks to capture temporal dependencies. The policy is further constrained within an offline dataset collected via hardware-in-the-loop simulation using a variational autoencoder, and a sequence-level prediction mechanism is introduced to ensure temporal consistency across action trajectories, thereby mitigating extrapolation error while preserving data fidelity. Experimental results demonstrate that TSCQ significantly outperforms gain scheduling, Model Predictive Control (MPC), and Batch-Constrained Q-learning (BCQ), reducing the RMSE of pitch angle by up to 53.3% and vertical velocity RMSE by approximately 33%. These findings underscore the potential of data-driven, safety-aware offline RL paradigms to enable robust and generalizable control strategies for tilt-wing UAVs. Full article
(This article belongs to the Section Aeronautics)
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26 pages, 5234 KiB  
Article
An Image and State Information-Based PINN with Attention Mechanisms for the Rapid Prediction of Aircraft Aerodynamic Characteristics
by Yiduo Kan, Xiangdong Liu and Haikuo Liu
Aerospace 2025, 12(5), 434; https://doi.org/10.3390/aerospace12050434 - 13 May 2025
Abstract
Prediction of aircraft aerodynamic parameters is crucial for aircraft design, yet traditional computational fluid dynamics methods remain time-consuming and labor-intensive. This work presents a novel model, the image and state information-based attention-enhanced physics-informed neural network (ISA-PINN), which significantly improves prediction accuracy. Our model [...] Read more.
Prediction of aircraft aerodynamic parameters is crucial for aircraft design, yet traditional computational fluid dynamics methods remain time-consuming and labor-intensive. This work presents a novel model, the image and state information-based attention-enhanced physics-informed neural network (ISA-PINN), which significantly improves prediction accuracy. Our model incorporates the following innovations: the designed attention module dynamically extracts hidden features from pattern data while selectively focusing on relevant dimensions of target information. Meanwhile, the image-information fusion module combines multi-scale geometric features derived from aircraft images to enhance the overall prediction accuracy. By embedding aerodynamic equations, the model maintains physical consistency while enhancing interpretability. Extensive experiments validate the effectiveness of our model for rapid aircraft aerodynamic parameter prediction, achieving a significant reduction in prediction error that improves performance by 29.25% in RMSE and 37.99% in MRE compared to existing methods. A 6.12% error increase on the test set confirms the model’s robust generalization ability. Full article
(This article belongs to the Special Issue Aerodynamics, Flight Dynamics and Control of Advanced Air Mobility Vehicles)
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16 pages, 4097 KiB  
Article
Study on Plasma-Chemical Mode of Pulsed Coaxial Dielectric Barrier Discharge Plasma Based on Mass Spectrometry
by Diankai Wang, Yongzan Zheng, Baosheng Du, Jianhui Han, Ming Wen and Tengfei Zhang
Aerospace 2025, 12(5), 433; https://doi.org/10.3390/aerospace12050433 - 13 May 2025
Abstract
This study systematically investigates the dynamic evolution of chemical regimes in pulsed coaxial dielectric barrier discharge (DBD) plasma under atmospheric pressure using mass spectrometry. An innovative real-time mass spectrometric monitoring methodology was established, enabling the dynamic tracking of the formation and consumption processes [...] Read more.
This study systematically investigates the dynamic evolution of chemical regimes in pulsed coaxial dielectric barrier discharge (DBD) plasma under atmospheric pressure using mass spectrometry. An innovative real-time mass spectrometric monitoring methodology was established, enabling the dynamic tracking of the formation and consumption processes of key reactive species such as ozone (O3) and nitrogen oxides (NOx). Energy density was the critical parameter governing the evolution of gaseous chemical components, with a quantitative elucidation of the regulatory mechanisms of air flow rate and control voltage on plasma chemical regime transition kinetics. Experimental results revealed significant parametric correlations: Under a constant control voltage of 140 V, increasing the gas flow rate from 0.5 to 5.5 L/min prolonged the transition duration from O3-NOx coexistence regime to a NOx-dominant regime from 408 s to 1210 s. Conversely, at a fixed flow rate of 3.5 L/min, elevating the control voltage from 120 V to 140 V accelerated this transition, reducing the required time from 2367 s to 718 s. Parametric sensitivity analysis demonstrated that control voltage exerts approximately 3.3 times greater influence on transition kinetics than flow rate variation. Through comprehensive analysis of the formation and consumption mechanisms of N, O, O3, and NOx species, we established a complete plasma chemical reaction network. This scheme provides fundamental insights into reaction pathways while offering practical optimization strategies for DBD systems. For aerospace applications, this work holds particular significance by demonstrating that the identified control parameters can be directly applied to plasma-assisted treatment of propellant wastewater at launch sites, where the efficient removal of nitrogen-containing pollutants is crucial. These findings advance both the fundamental understanding of atmospheric-pressure plasma chemistry and the engineering applications of plasma-based environmental remediation technologies in aerospace operations. Full article
(This article belongs to the Section Astronautics & Space Science)
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21 pages, 2865 KiB  
Perspective
Toward Sustainable Mars Exploration: A Perspective on Collaborative Intelligent Systems
by Thomas Janssen, Ritesh Kumar Singh, Phil Reiter, Anuj Justus Rajappa, Priyesh Pappinisseri Puluckul, Mohmmadsadegh Mokhtari, Mohammad Hasan Rahmani, Erik Mannens, Jeroen Famaey and Maarten Weyn
Aerospace 2025, 12(5), 432; https://doi.org/10.3390/aerospace12050432 - 13 May 2025
Abstract
Mars has long captivated the human imagination as a potential destination for settlement and scientific exploration. After deploying individual rovers, the next step in our journey to Mars is the autonomous exploration of the Red Planet using a collaborative swarm of rovers, drones, [...] Read more.
Mars has long captivated the human imagination as a potential destination for settlement and scientific exploration. After deploying individual rovers, the next step in our journey to Mars is the autonomous exploration of the Red Planet using a collaborative swarm of rovers, drones, and satellites. This concept paper envisions a sustainable Mars exploration scenario featuring energy-aware, collaborative, and autonomous vehicles, including rovers, drones, and satellites, operating around Mars. The proposed framework is designed to address key challenges in energy management, edge intelligence, communication, sensing, resource-aware task scheduling, and radiation hardening. This work not only identifies these critical areas of research but also proposes novel technological solutions drawn from terrestrial advancements to extend their application to extraterrestrial exploration. Full article
(This article belongs to the Special Issue Space Robotics and Embodied Intelligence: Advancing Autonomous Exploration)
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21 pages, 2937 KiB  
Article
SatGuard: Satellite Networks Penetration Testing and Vulnerability Risk Assessment Methods
by Jin Xiao, Buhong Wang, Ruochen Dong, Zhengyang Zhao and Bofu Zhao
Aerospace 2025, 12(5), 431; https://doi.org/10.3390/aerospace12050431 - 12 May 2025
Viewed by 52
Abstract
Satellite networks face escalating cybersecurity threats from evolving attack vectors and systemic complexities. This paper proposes SatGuard, a novel framework integrating a three-dimensional penetration testing methodology and a nonlinear risk assessment mechanism tailored for satellite security. To address limitations of conventional tools in [...] Read more.
Satellite networks face escalating cybersecurity threats from evolving attack vectors and systemic complexities. This paper proposes SatGuard, a novel framework integrating a three-dimensional penetration testing methodology and a nonlinear risk assessment mechanism tailored for satellite security. To address limitations of conventional tools in handling satellite-specific vulnerabilities, SatGuard employs large language models (LLMs) like GPT-4 and DeepSeek-R1. By leveraging their contextual reasoning and code-generation abilities, SatGuard enables semi-automated vulnerability analysis and exploitation. Validated in a simulated ground station environment, the framework achieved a 73.3% success rate (22/30 attempts) across critical ports, with an average of 5.5 human interactions per test. By bridging AI-driven automation with satellite-specific risk modeling, SatGuard advances cybersecurity for next-generation space infrastructure through scalable, ethically aligned solutions. Full article
(This article belongs to the Section Astronautics & Space Science)
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58 pages, 3864 KiB  
Review
Flow and Flame Mechanisms for Swirl-Stabilized Combustors
by Paul Palies
Aerospace 2025, 12(5), 430; https://doi.org/10.3390/aerospace12050430 - 12 May 2025
Viewed by 214
Abstract
This article reviews the physical and chemical mechanisms associated with unsteady swirl-stabilized partially or fully lean premixed combustion. The processes of flame stabilization, mode conversion, swirl number oscillation, equivalence ratio oscillation, and vortex rollup are described. The key challenges associated with flow-flame dynamics [...] Read more.
This article reviews the physical and chemical mechanisms associated with unsteady swirl-stabilized partially or fully lean premixed combustion. The processes of flame stabilization, mode conversion, swirl number oscillation, equivalence ratio oscillation, and vortex rollup are described. The key challenges associated with flow-flame dynamics for several sources of perturbations are presented and discussed. The Rayleigh criterion is discussed. This article summarizes the scientific knowledge gained on swirling flames dynamics in terms of modeling, theoretical analysis, and transient measurements with advanced diagnostics. The following are specifically documented: (i) the effect of the swirler on swirling flames; (ii) the analytical results, computational modeling, and experimental measurements of swirling flame dynamics; (iii) the influence of flow features on flame response of swirling flames for combustion instabilities studies; and (iv) the identification and description of the combustion dynamics mechanisms responsible for swirl-stabilized combustion instabilities. Relevant elements from the literature in this context for hydrogen fuel are included. Full article
(This article belongs to the Special Issue Scientific and Technological Advances in Hydrogen Combustion Aircraft)
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17 pages, 13331 KiB  
Article
The Three-Dimensional Transient Simulation of Cross-Shaped Grains in Hybrid Rocket Motors
by Xiangyu Meng, Huihuang Huang, Yifei Chen, Mingsen Yao, Jianyuan Wang and Hui Tian
Aerospace 2025, 12(5), 429; https://doi.org/10.3390/aerospace12050429 - 12 May 2025
Viewed by 116
Abstract
The process of spacecraft entry, deceleration, landing, and ascent requires high specific impulse, high reliability, and high-precision thrust adjustments for the power system. The new hybrid rocket motor adopts a complex-shaped grain and high-energy propellant, offering high-energy characteristics, continuously adjustable thrust, a relatively [...] Read more.
The process of spacecraft entry, deceleration, landing, and ascent requires high specific impulse, high reliability, and high-precision thrust adjustments for the power system. The new hybrid rocket motor adopts a complex-shaped grain and high-energy propellant, offering high-energy characteristics, continuously adjustable thrust, a relatively simple oxidant delivery system, and high reliability, making it an ideal power choice for the above systems. However, due to changes in the characteristic structure of the three-dimensional complex flame surface degradation process, it is difficult to accurately predict the motor performance. In this study, changes in the flow field structure and performance parameters during the operation of the cross-shaped grain hybrid rocket motor are presented using fuel surface reconstruction technology based on a dynamic mesh. The spatial distribution of the fuel surface is analyzed, and the accuracy of the model is verified via firing tests. The results show that the deviations of combustion chamber pressure and thrust are less than 0.6% and 1.7%, respectively. After the test, the deviation between the simulated port area and the CT-scanned port area is less than 3.5%. The accuracy of this model is verified in terms of the above two aspects, establishing a solid foundation for predicting the performance of future hybrid rocket motors with more complex-shaped grains. Full article
(This article belongs to the Section Astronautics & Space Science)
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40 pages, 2224 KiB  
Article
Pursuit-Interception Strategy in Differential Games Based on Q-Learning-Cover Algorithm
by Yu Bai, Di Zhou and Zhen He
Aerospace 2025, 12(5), 428; https://doi.org/10.3390/aerospace12050428 - 12 May 2025
Viewed by 69
Abstract
Due to the limited difference in maneuverability between the pursuer and the evader in three-dimensional space, it is difficult for a single pursuer to capture the evader. To address this, this paper proposes a strategy where three pursuers intercept one evader and introduces [...] Read more.
Due to the limited difference in maneuverability between the pursuer and the evader in three-dimensional space, it is difficult for a single pursuer to capture the evader. To address this, this paper proposes a strategy where three pursuers intercept one evader and introduces a Q-learning-cover algorithm. Based on the motion models of the pursuers and the evader in three-dimensional space, this paper presents a region coverage scheme based on the Ahlswede ball and analyzes the convergence upper bound of the Q-learning-cover algorithm by designing an appropriate Lyapunov function. Through extensive model training, the successful capture of the evader by the pursuers in a three-on-one scenario was achieved. Finally, numerical simulation experiments and hardware-in-the-loop simulation experiments are presented, both of which demonstrate that the proposed Q-learning-cover algorithm can effectively realize the three-on-one encirclement and interception of the evading target. Full article
(This article belongs to the Section Aeronautics)
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13 pages, 2363 KiB  
Article
Spectroscopic Quantification of Metallic Element Concentrations in Liquid-Propellant Rocket Exhaust Plumes
by Siyang Tan, Song Yan, Xiang Li, Tong Su, Qingchun Lei and Wei Fan
Aerospace 2025, 12(5), 427; https://doi.org/10.3390/aerospace12050427 - 11 May 2025
Viewed by 170
Abstract
Accurate quantification of metallic contaminants in rocket exhaust plumes serves as a critical diagnostic indicator for engine wear monitoring. This paper develops a hybrid method combining atomic emission spectroscopy (AES) theory with a genetic algorithm (GA) optimized backpropagation (BP) network to quantify the [...] Read more.
Accurate quantification of metallic contaminants in rocket exhaust plumes serves as a critical diagnostic indicator for engine wear monitoring. This paper develops a hybrid method combining atomic emission spectroscopy (AES) theory with a genetic algorithm (GA) optimized backpropagation (BP) network to quantify the metallic element concentrations in liquid-propellant rocket exhaust plumes. The proposed method establishes linearized intensity–concentration mapping through the introduction of a photon transmission factor, which is derived from radiative transfer theory and experimentally calibrated via AES measurement. This critical innovation decouples the inherent nonlinearities arising from self-absorption artifacts. Through the use of the transmission factor, the training dataset for the BP network is systematically constructed by performing spectral simulations of atomic emissions. Finally, the trained network is employed to predict the concentration of metallic elements from the measured atomic emission spectra. These spectra are generated by introducing a solution containing metallic elements into a CH4-air premixed jet flame. The predictive accuracy of the method is rigorously evaluated through 32 independent experimental trials. Results show that the quantification error of metallic elements remains within 6%, and the method exhibits robust performance under conditions of spectral self-absorption, demonstrating its reliability for rocket engine health monitoring applications. Full article
(This article belongs to the Section Astronautics & Space Science)
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24 pages, 1678 KiB  
Article
An Adaptation of Nonlinear Aerodynamic Models for Non-Traditional Control Effectors
by Christian R. Bolander and Douglas F. Hunsaker
Aerospace 2025, 12(5), 426; https://doi.org/10.3390/aerospace12050426 - 10 May 2025
Viewed by 107
Abstract
This paper presents the development of a novel aerodynamic model tailored for the Bio-Inspired Rotating Empennage (BIRE), a non-traditional fixed-wing aircraft empennage inspired by avian flight. The BIRE replaces the conventional vertical stabilizer with an extra degree of freedom for the horizontal stabilizer, [...] Read more.
This paper presents the development of a novel aerodynamic model tailored for the Bio-Inspired Rotating Empennage (BIRE), a non-traditional fixed-wing aircraft empennage inspired by avian flight. The BIRE replaces the conventional vertical stabilizer with an extra degree of freedom for the horizontal stabilizer, which is allowed to rotate about the body-fixed x axis. This empennage is similar to the tail of a bird, and allows control of both longitudinal and lateral moments. However, such a design introduces complex nonlinear longitudinal and lateral aerodynamic interactions, not typically accounted for in most fixed-wing aircraft aerodynamic models below stall. This work presents a nonlinear sinusoidal aerodynamic model that can be used for fixed-wing aircraft with this type of empennage. Although the aerodynamic model is constructed to accurately capture the degrees of freedom of this particular empennage design, similar methods could be used to develop other aerodynamic models for non-traditional control effectors. A large dataset of low-fidelity aerodynamic data was generated using a modern numerical lifting-line algorithm, and these data were fit to the nonlinear sinusoidal aerodynamic model. A method for fitting the data is demonstrated, and the results show that the nonlinear sinusoidal aerodynamic model can be fit to the data with an accuracy of less than 10% of the maximum deviation of the aerodynamic coefficients in root-mean-square error. The underlying physics of many of the longitudinal and lateral nonlinear sinusoidal aerodynamic properties of the aircraft are discussed in detail. The methodology presented here can be extended to other non-traditional control effectors, encouraging innovative approaches in aerodynamic modeling and aircraft design. In contrast, choosing to model control effectors using the traditional, linear approach can obscure key aerodynamic behaviors key for trim and control analyses. The study’s findings underscore the importance of developing adaptable aerodynamic models to support the advancement of next-generation aircraft designs and control systems. Full article
(This article belongs to the Section Aeronautics)
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30 pages, 4618 KiB  
Article
Relative Pose Estimation of an Uncooperative Target with Camera Marker Detection
by Batu Candan and Simone Servadio
Aerospace 2025, 12(5), 425; https://doi.org/10.3390/aerospace12050425 - 10 May 2025
Viewed by 169
Abstract
Accurate and robust relative pose estimation is the first step in ensuring the success of an active debris removal mission. This paper introduces a novel method to detect structural markers on the European Space Agency’s Environmental Satellite (ENVISAT) for safe de-orbiting using image [...] Read more.
Accurate and robust relative pose estimation is the first step in ensuring the success of an active debris removal mission. This paper introduces a novel method to detect structural markers on the European Space Agency’s Environmental Satellite (ENVISAT) for safe de-orbiting using image processing and Convolutional Neural Networks (CNNs). Advanced image preprocessing techniques, including noise addition and blurring, are employed to improve marker detection accuracy and robustness from a chaser spacecraft. Additionally, we address the challenges posed by eclipse periods, during which the satellite’s corners are not visible, preventing measurement updates in the Unscented Kalman Filter (UKF). To maintain estimation quality in these periods of data loss, we propose a covariance-inflating approach in which the process noise covariance matrix is adjusted, reflecting the increased uncertainty in state predictions during the eclipse. This adaptation ensures more accurate state estimation and system stability in the absence of measurements. The initial results show promising potential for autonomous removal of space debris, supporting proactive strategies for space sustainability. The effectiveness of our approach suggests that our estimation method, combined with robust noise adaptation, could significantly enhance the safety and efficiency of debris removal operations by implementing more resilient and autonomous systems in actual space missions. Full article
(This article belongs to the Special Issue New Concepts in Spacecraft Guidance Navigation and Control)
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22 pages, 4144 KiB  
Article
Wide-Range Variable Cycle Engine Control Based on Deep Reinforcement Learning
by Yaoyao Ding, Fengming Wang, Yuanwei Mu and Hongfei Sun
Aerospace 2025, 12(5), 424; https://doi.org/10.3390/aerospace12050424 - 10 May 2025
Viewed by 126
Abstract
In this paper, a controller design method based on deep reinforcement learning is proposed for a wide-range variable cycle engine with a turbine interstage mixed architecture. The PID controller is subject to limitations, including single-input single-output limitations, low regulation efficiency, and poor adaptability [...] Read more.
In this paper, a controller design method based on deep reinforcement learning is proposed for a wide-range variable cycle engine with a turbine interstage mixed architecture. The PID controller is subject to limitations, including single-input single-output limitations, low regulation efficiency, and poor adaptability when confronted with contemporary variable cycle engines that exhibit complex and multi-variable operating conditions. To solve this problem, this paper adopts a deep reinforcement learning method based on a deep deterministic policy gradient algorithm, and it applies an action space pruning technique to optimize the controller, which significantly improves the convergence speed of network training. In order to verify the control performance, two typical flight conditions are selected for simulation experiments as follows: in the first scenario, H = 0 km and Ma = 0, while in the second scenario, H = 10 km and Ma = 0.9. A comparison of the simulation results shows that the proposed deep reinforcement learning controller effectively addresses the engine’s multi-variable coupling control problem. In addition, it reduces response time by an average of 44.5%, while maintaining a similar overshoot level to that of the PID controller. Full article
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22 pages, 14643 KiB  
Article
A Method for the Life Assessment of Aero-Engine Turbine Disks Based on a Time-Varying Load Spectrum
by Shunyu Yao, Xuming Niu, Zhigang Sun and Yingdong Song
Aerospace 2025, 12(5), 423; https://doi.org/10.3390/aerospace12050423 - 9 May 2025
Viewed by 202
Abstract
The load spectrum serves as the foundation for the life analysis of aero-engine turbine disks. To enhance the accuracy of life assessments for turbine disks, this study compiles a time-varying load spectrum for turbine disks. Firstly, a surrogate model for transient processes at [...] Read more.
The load spectrum serves as the foundation for the life analysis of aero-engine turbine disks. To enhance the accuracy of life assessments for turbine disks, this study compiles a time-varying load spectrum for turbine disks. Firstly, a surrogate model for transient processes at the critical points of turbine disks is established, enabling the rapid evaluation of the transient temperature and thermal stress at these points under complex loading histories. Secondly, a performance degradation model is established based on real engine test data, explicitly describing the general trend of performance degradation characteristics with respect to the cycle number and engine power. Finally, a time-varying load spectrum for turbine disks is compiled, considering both short-term transient processes and long-term performance degradation. The life of turbine disks at the fir-tree slot root and disk bore is assessed using the Manson–Coffin equation, Wilshire equation, and linear damage accumulation rule. The results indicate that neglecting transient processes leads to conservative life assessment results while neglecting performance degradation leads to dangerous life assessment results. Compared with traditional methods, the time-varying load spectrum significantly improves the accuracy and scientific nature of turbine disk life assessment. Full article
(This article belongs to the Section Aeronautics)
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20 pages, 4137 KiB  
Article
GPU-Accelerated Eclipse-Aware Routing for SpaceWire-Based OBC in Low-Earth-Orbit Satellite Networks
by Hyeonwoo Kim, Heoncheol Lee and Myonghun Han
Aerospace 2025, 12(5), 422; https://doi.org/10.3390/aerospace12050422 - 9 May 2025
Viewed by 183
Abstract
Low-Earth-Orbit (LEO) satellite networks offer a promising avenue for achieving global connectivity, despite certain technical and economic challenges such as high implementation costs and the complexity of network management. Nonetheless, real-time routing remains challenging because of rapid topology changes and strict energy constraints. [...] Read more.
Low-Earth-Orbit (LEO) satellite networks offer a promising avenue for achieving global connectivity, despite certain technical and economic challenges such as high implementation costs and the complexity of network management. Nonetheless, real-time routing remains challenging because of rapid topology changes and strict energy constraints. This paper proposes a GPU-accelerated Eclipse-Aware Routing (EAR) method that simultaneously minimizes hop count and balances energy consumption for real-time routing on an onboard computer (OBC). The approach first employs a Breadth-First Search (BFS)–based K-Shortest Paths (KSP) algorithm to generate candidate routes and then evaluates battery usage to select the most efficient path. In large-scale networks, the computational load of the KSP search increases substantially. Therefore, CUDA-based parallel processing was integrated to enhance performance, resulting in a speedup of approximately 3.081 times over the conventional CPU-based method. The practical applicability of the proposed method is further validated by successfully updating routing tables in a SpaceWire network. Full article
(This article belongs to the Section Astronautics & Space Science)
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21 pages, 16482 KiB  
Article
Evaluation of Aerodynamic and Sonic Boom Performance of Supersonic Transport Aircrafts with Multiple Wing Configurations
by Wataru Yamazaki and Shu Ishida
Aerospace 2025, 12(5), 421; https://doi.org/10.3390/aerospace12050421 - 9 May 2025
Viewed by 89
Abstract
In this study, two-dimensional airfoil shapes obtained in aerodynamic optimizations are converted to three-dimensional wing models and then their aerodynamic and sonic boom performance are evaluated. The airfoil shapes analyzed are the diamond, Busemann, new supersonic biplane (NSB), and triplane airfoil configurations. The [...] Read more.
In this study, two-dimensional airfoil shapes obtained in aerodynamic optimizations are converted to three-dimensional wing models and then their aerodynamic and sonic boom performance are evaluated. The airfoil shapes analyzed are the diamond, Busemann, new supersonic biplane (NSB), and triplane airfoil configurations. The NSB is a modified version of the Busemann biplane airfoil proposed in previous studies. The triplane airfoil configuration is obtained in this study by maximizing the lift-to-drag ratio using an aerodynamic topology optimization method. Based on the obtained two-dimensional airfoil shapes, three-dimensional multiple (biplane/triplane) wing configurations are designed. The aerodynamic and sonic boom performance of these configurations is evaluated in detail through three-dimensional flow analyses as well as acoustic propagation analyses. The aerodynamic superiority of the multiple wing configurations is confirmed in this study. Full article
(This article belongs to the Special Issue Research and Development of Supersonic Aircraft)
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29 pages, 4738 KiB  
Article
AEM-D3QN: A Graph-Based Deep Reinforcement Learning Framework for Dynamic Earth Observation Satellite Mission Planning
by Shuo Li, Gang Wang and Jinyong Chen
Aerospace 2025, 12(5), 420; https://doi.org/10.3390/aerospace12050420 - 9 May 2025
Viewed by 119
Abstract
Efficient and adaptive mission planning for Earth Observation Satellites (EOSs) remains a challenging task due to the growing complexity of user demands, task constraints, and limited satellite resources. Traditional heuristic and metaheuristic approaches often struggle with scalability and adaptability in dynamic environments. To [...] Read more.
Efficient and adaptive mission planning for Earth Observation Satellites (EOSs) remains a challenging task due to the growing complexity of user demands, task constraints, and limited satellite resources. Traditional heuristic and metaheuristic approaches often struggle with scalability and adaptability in dynamic environments. To overcome these limitations, we introduce AEM-D3QN, a novel intelligent task scheduling framework that integrates Graph Neural Networks (GNNs) with an Adaptive Exploration Mechanism-enabled Double Dueling Deep Q-Network (D3QN). This framework constructs a Directed Acyclic Graph (DAG) atlas to represent task dependencies and constraints, leveraging GNNs to extract spatial–temporal task features. These features are then encoded into a reinforcement learning model that dynamically optimizes scheduling policies under multiple resource constraints. The adaptive exploration mechanism improves learning efficiency by balancing exploration and exploitation based on task urgency and satellite status. Extensive experiments conducted under both periodic and emergency planning scenarios demonstrate that AEM-D3QN outperforms state-of-the-art algorithms in scheduling efficiency, response time, and task completion rate. The proposed framework offers a scalable and robust solution for real-time satellite mission planning in complex and dynamic operational environments. Full article
(This article belongs to the Section Astronautics & Space Science)
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19 pages, 1662 KiB  
Article
Advancements in Aircraft Engine Inspection: A MEMS-Based 3D Measuring Borescope
by Jonathan Gail, Felix Kruse, Shanshan Gu-Stoppel, Ole Schmedemann, Günther Leder, Wolfgang Reinert, Lena Wysocki, Nils Burmeister, Lars Ratzmann, Thorsten Giese, Patrick Schütt, Gundula Piechotta and Thorsten Schüppstuhl
Aerospace 2025, 12(5), 419; https://doi.org/10.3390/aerospace12050419 - 8 May 2025
Viewed by 122
Abstract
Aircraft engines are regularly inspected with borescopes to detect faults at an early stage and maintain airworthiness. A critical part of this inspection process is accurately measuring any detected damage to determine whether it exceeds allowable limits. Current state-of-the-art borescope measurement techniques—primarily stereo [...] Read more.
Aircraft engines are regularly inspected with borescopes to detect faults at an early stage and maintain airworthiness. A critical part of this inspection process is accurately measuring any detected damage to determine whether it exceeds allowable limits. Current state-of-the-art borescope measurement techniques—primarily stereo camera systems and pattern projection—face significant challenges when engines lack sufficient surface features or when illumination is inadequate for reliable stereo matching. MEMS-based 3D scanners address these issues by focusing laser light onto a small spot, reducing dependency on surface texture and improving illumination. However, miniaturized MEMS-based scanner borescopes that can pass through standard engine inspection ports are not yet available. This work examines the essential steps to downsize MEMS 3D scanners for direct integration into borescope inspections, thereby enhancing the accuracy and reliability of aircraft engine fault detection. Full article
(This article belongs to the Topic Structural Health Monitoring and Non-Destructive Testing for Large-Scale Structures (2nd Edition))
24 pages, 11695 KiB  
Article
Experimental Investigation of PWM Throttling in a 50-Newton-Class HTP Monopropellant Thruster: Analysis of Pressure Surges and Oscillations
by Suk Min Choi and Christian Bach
Aerospace 2025, 12(5), 418; https://doi.org/10.3390/aerospace12050418 - 8 May 2025
Viewed by 155
Abstract
High-test peroxide (HTP) monopropellant thrusters are being considered for spacecraft lander missions due to their simplicity and reduced toxicity compared to traditional propellants. Pulse-Width Modulation (PWM) throttling is a key technique for precise thrust control in such systems. However, PWM throttling can lead [...] Read more.
High-test peroxide (HTP) monopropellant thrusters are being considered for spacecraft lander missions due to their simplicity and reduced toxicity compared to traditional propellants. Pulse-Width Modulation (PWM) throttling is a key technique for precise thrust control in such systems. However, PWM throttling can lead to pressure surges and oscillations in the propellant feed system, potentially compromising system reliability. This study investigates the influence of PWM parameters, specifically duty cycle and frequency, on pressure surges and oscillations in a 50-newton-class HTP monopropellant thruster. The objective is to identify stable operating conditions that mitigate these effects, thereby enhancing the reliability of PWM throttling for lander applications. An experimental setup was developed, including a 50-newton-class thruster with a MnO2/La/Al2O3 catalyst and a solenoid valve for PWM control. Cold flow tests using water characterized the valve response and water hammer effects, while hot fire tests with 90 wt.% HTP were used to evaluate thruster performance under steady-state and PWM conditions. Analytical methods, including Joukowsky’s equation and power spectral density analysis, were used to interpret the data and understand the underlying mechanisms. The results showed that while surge pressures generally aligned with steady-state values, specific PWM conditions led to amplified surges, particularly at low duty cycles. Additionally, high duty cycles induced chugging instability. The natural frequencies of the feed system were found to play a crucial role in these phenomena. Stable operating conditions were identified by avoiding duty cycles that cause constructive interference of pressure waves. This research demonstrates that by carefully selecting PWM parameters based on the feed system’s dynamic characteristics, pressure surges and oscillations can be minimized, ensuring reliable operation of HTP monopropellant thrusters in PWM throttling mode. These findings contribute to the development of more efficient and safer propulsion systems for spacecraft landers. Full article
(This article belongs to the Special Issue Space Propulsion: Advances and Challenges (3rd Volume))
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21 pages, 12144 KiB  
Article
Day–Night Energy-Constrained Path Planning for Stratospheric Airships: A Hybrid Level-Set Particle Swarm Optimization (LS-PSO) Framework in Dynamic Flows
by Cheng Liu, Xiang Li, Jinggang Miao, Yu Feng and Chunjiang Bian
Aerospace 2025, 12(5), 417; https://doi.org/10.3390/aerospace12050417 - 8 May 2025
Viewed by 217
Abstract
Path planning for stratospheric airships in dynamic wind fields is challenging due to complex wind variations and strict nighttime energy constraints. This paper proposes a hybrid Level-Set Particle Swarm Optimization (LS-PSO) framework. Firstly, it employs PSO to search iteratively for a propulsion velocity [...] Read more.
Path planning for stratospheric airships in dynamic wind fields is challenging due to complex wind variations and strict nighttime energy constraints. This paper proposes a hybrid Level-Set Particle Swarm Optimization (LS-PSO) framework. Firstly, it employs PSO to search iteratively for a propulsion velocity sequence in the velocity domain, with a multi-objective fitness function that integrates reachability, energy consumption and time cost to evaluate each velocity sequence. Then, the reachability of each candidate sequence is numerically solved by the Level Set forward evolution. To improve optimization efficiency, we proposed a multi-resolution grid adaptive strategy for forward evolutions. Finally, with the optimal velocity sequence, the optimal path is generated once by the Level Set backtrack processing. To validate the resulting methodology, we used a benchmark case of a dynamic complex four-gyre flow, described by mathematical formulas, with the optimal day–night path identified by GPOPS-II. The results show the LS-PSO solution has comparable accuracy, with a trajectory deviation less than 3%. Then, we tested the methodology in the stratospheric wind flows using ERA5 reanalysis data. The results demonstrate that our path planning methodology provides a computationally efficient and optimal energy–time solution for autonomous stratospheric airships, while conforming to reachability and strict nighttime energy constraints. Full article
(This article belongs to the Special Issue Design, Characterization and Operations of Lighter-than-Air Flying Vehicles)
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28 pages, 16808 KiB  
Article
Experimental and Numerical Study on Flow and Heat Transfer Characteristics of Additively Manufactured Triply Periodic Minimal Surface (TPMS) Heat Exchangers for Micro Gas Turbine
by Xiyuan Su, Yueliang Zhang, Yu Rao, Kirttayoth Yeranee and Xintong Wang
Aerospace 2025, 12(5), 416; https://doi.org/10.3390/aerospace12050416 - 7 May 2025
Viewed by 115
Abstract
This paper proposes two compact, efficient, and lightweight heat exchangers based on triply periodic minimal surfaces (TPMSs). Designed in an annular configuration, the heat exchangers meet the requirements of micro gas turbines for compactness. Two prototypes of Diamond and Gyroid modular TPMS heat [...] Read more.
This paper proposes two compact, efficient, and lightweight heat exchangers based on triply periodic minimal surfaces (TPMSs). Designed in an annular configuration, the heat exchangers meet the requirements of micro gas turbines for compactness. Two prototypes of Diamond and Gyroid modular TPMS heat exchangers were fabricated using selective laser melting (SLM) with stainless steel. The flow and heat transfer experimental results indicate that, within a Reynolds number range of 200 to 800, the effectiveness of both heat exchangers remained above 0.62, and the average Nusselt numbers of the Diamond and Gyroid structures reached 3.60 and 4.06 times that of the printed circuit heat exchanger (PCHE), respectively. Although both heat exchangers exhibited relatively high friction factors, their overall performance surpassed that of conventional heat exchangers. Additionally, performance comparisons with existing TPMS heat exchangers revealed that smaller lattice sizes contribute to improved volume-based power density, although they result in increased pressure loss. Simulation results indicated that the “merge–split” effect present in both structures enhances heat transfer between the fluid and the wall. Furthermore, the complex channels of the TPMS structures ensure that the fluid maintains strong turbulence intensity throughout the heat exchanger. This study demonstrates that stainless steel TPMS structures can serve as excellent candidates for applications in micro gas turbines. Full article
(This article belongs to the Section Aeronautics)
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23 pages, 17577 KiB  
Article
Deep Learning Framework for Predicting Transonic Wing Buffet Loads Due to Structural Eigenmode-Based Deformations
by Rebecca Zahn, Moritz Zieher and Christian Breitsamter
Aerospace 2025, 12(5), 415; https://doi.org/10.3390/aerospace12050415 - 7 May 2025
Viewed by 88
Abstract
In the present paper, a reduced-order modeling (ROM) approach based on a hybrid neural network is presented in order to calculate wing buffet pressure distributions due to structural eigenmode-based deformations. The accurate prediction of unsteady surface pressure distributions is crucial for assessing aeroelastic [...] Read more.
In the present paper, a reduced-order modeling (ROM) approach based on a hybrid neural network is presented in order to calculate wing buffet pressure distributions due to structural eigenmode-based deformations. The accurate prediction of unsteady surface pressure distributions is crucial for assessing aeroelastic stability and preventing structural failure, but full-order simulations are computationally expensive; the proposed ROM provides a fast and efficient alternative with a sufficient level of accuracy. The hybrid ROM is defined by a series connection of a convolutional autoencoder (CNN-AE) and a long short-term memory (LSTM) neural network. As a test case, the NASA Common Research Model (CRM) configuration for the transonic buffet condition is applied. Forced-motion computational fluid dynamics (CFD) simulations are conducted in order to obtain the aerodynamic responses induced by the eigenmode-based deformations. For the unsteady simulations, the triangular adaptive upwind (TAU) solver of the German Aerospace Center (DLR), is used. Based on a selected structural model, symmetric and asymmetric eigenmode-based deformations of the wing structure are implemented and considered for performance evaluation. Comparing the pressure loads modeled by the hybrid ROM and the reference full-order numerical solution, an overall good prediction performance is indicated with mean squared error (MSE) values mostly below 3%, reaching local maxima of about 12%, due to strong pressure gradients associated with pronounced shock oscillations. Full article
(This article belongs to the Section Aeronautics)
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14 pages, 10798 KiB  
Article
Flexible Surface Reflector Antenna for Small Satellites
by Dong-Seok Kang, Dong-Hun Keum, Jun-Hyeong Choi, Min-Hyuk Lee, Kitae Park, Hwa-Young Jung, Deok-Soo Kang, Ji-Hyeon Yun, Jae-Wook Lee and Jin-Ho Roh
Aerospace 2025, 12(5), 414; https://doi.org/10.3390/aerospace12050414 - 7 May 2025
Viewed by 117
Abstract
A novel deployable reflector antenna for small satellites has been designed, fabricated, and experimentally validated. The reflector utilizes a doubly curved flexible surface manufactured from a triaxially woven fabric-reinforced silicone (TWFS) composite. By leveraging high-strain composite materials, the design enables a highly compact [...] Read more.
A novel deployable reflector antenna for small satellites has been designed, fabricated, and experimentally validated. The reflector utilizes a doubly curved flexible surface manufactured from a triaxially woven fabric-reinforced silicone (TWFS) composite. By leveraging high-strain composite materials, the design enables a highly compact stowed configuration while maintaining precise surface accuracy upon deployment. The deployment mechanism is proposed to accommodate a 0.6 m diameter parabolic reflector within a minimal stowed volume, optimizing space efficiency for satellite integration. To validate this concept, a prototype of the reflector antenna has been fabricated and demonstrated the feasibility and effectiveness of the proposed approach. Full article
(This article belongs to the Special Issue Advanced Aerospace Composite Materials and Smart Structures)
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29 pages, 8569 KiB  
Article
Optimization of Flight Scheduling in Urban Air Mobility Considering Spatiotemporal Uncertainties
by Lingzhong Meng, Minggong Wu, Xiangxi Wen, Zhichong Zhou and Qingguo Tian
Aerospace 2025, 12(5), 413; https://doi.org/10.3390/aerospace12050413 - 7 May 2025
Viewed by 118
Abstract
The vigorous development of urban air mobility (UAM) is reshaping the urban travel landscape, but it also poses severe challenges to the safe and efficient operation of dense and complex airspace. Potential conflicts between flight plans have become a core bottleneck restricting its [...] Read more.
The vigorous development of urban air mobility (UAM) is reshaping the urban travel landscape, but it also poses severe challenges to the safe and efficient operation of dense and complex airspace. Potential conflicts between flight plans have become a core bottleneck restricting its development. Traditional flight plan adjustment and management methods often rely on deterministic trajectory predictions, ignoring the inherent temporal uncertainties in actual operations, which may lead to the underestimation of potential risks. Meanwhile, existing global optimization strategies often face issues of inefficiency and overly broad adjustment scopes when dealing with large-scale plan conflicts. To address these challenges, this study proposes an innovative flight plan conflict management framework. First, by introducing a probabilistic model of flight time errors, a new conflict detection mechanism based on confidence intervals is constructed, significantly enhancing the ability to foresee non-obvious conflict risks. Furthermore, based on complex network theory, the framework accurately identifies a small number of “critical flight plans” that play a core role in the conflict network, revealing their key impact on chain reactions of conflicts. On this basis, a phased optimization strategy is adopted, prioritizing the adjustment of spatiotemporal parameters (departure time and speed) for these critical plans to systematically resolve most conflicts. Subsequently, only fine-tuning the speeds of non-critical plans is required to address remaining local conflicts, thereby minimizing interference with the overall operational order. Simulation results demonstrate that this framework not only significantly improves the comprehensiveness of conflict detection but also effectively reduces the total number of conflicts. Additionally, the proposed phased artificial lemming algorithm (ALA) outperforms traditional optimization algorithms in terms of solution quality. This work provides an important theoretical foundation and a practically valuable solution for developing robust and efficient UAM dynamic scheduling systems, holding promise to support the safe and orderly operation of large-scale urban air traffic in the future. Full article
(This article belongs to the Section Air Traffic and Transportation)
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19 pages, 516 KiB  
Article
Validation of a Machine Learning Model for Certification Using Symbolic Regression and a Behaviour Envelope
by Moritz Neumaier, Marcel Anselment and Stephan Rudolph
Aerospace 2025, 12(5), 412; https://doi.org/10.3390/aerospace12050412 - 7 May 2025
Viewed by 83
Abstract
Aviation is highly regulated with a strong focus on safety. If machine learning models are to be used in aviation, their correctness must be proven as part of the certification process. As the number of data points is limited in real-world applications, a [...] Read more.
Aviation is highly regulated with a strong focus on safety. If machine learning models are to be used in aviation, their correctness must be proven as part of the certification process. As the number of data points is limited in real-world applications, a new approach is needed to ensure that the behaviour between the test points is correct. Due to the complexity, it is unlikely that a method for a complete evaluation with a reasonable runtime will be found. It is demonstrated in this methodology study how, in addition to the data set, the expected behaviour of the system the model is designed for can be considered. Using domain knowledge, a specific “behaviour envelope” defines the area the model is expected to stay within. In case the model stays within the behaviour envelope, which can be mathematically evaluated, it can be ensured that the behaviour between the test points is always physically meaningful. Since the effort for the evaluation increases with the complexity, it is proposed to use symbolic regression, a method where a search procedure combines elementary functions to create a compact symbolic model. This shifts the effort more towards model creation and simplifies the subsequent validation. Full article
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24 pages, 9711 KiB  
Article
A Deep Reinforcement Learning-Based Cooperative Guidance Strategy Under Uncontrollable Velocity Conditions
by Hao Cui, Ke Zhang, Minghu Tan and Jingyu Wang
Aerospace 2025, 12(5), 411; https://doi.org/10.3390/aerospace12050411 - 6 May 2025
Viewed by 213
Abstract
We present a novel approach to generating a cooperative guidance strategy using deep reinforcement learning to address the challenge of cooperative multi-missile strikes under uncontrollable velocity conditions. This method employs the multi-agent proximal policy optimization (MAPPO) algorithm to construct a continuous action space [...] Read more.
We present a novel approach to generating a cooperative guidance strategy using deep reinforcement learning to address the challenge of cooperative multi-missile strikes under uncontrollable velocity conditions. This method employs the multi-agent proximal policy optimization (MAPPO) algorithm to construct a continuous action space framework for intelligent cooperative guidance. A heuristically reshaped reward function is designed to enhance cooperative guidance among agents, enabling effective target engagement while mitigating the low learning efficiency caused by sparse reward signals in the guidance environment. Additionally, a multi-stage curriculum learning approach is introduced to smooth agent actions, effectively reducing action oscillations arising from independent sampling in reinforcement learning. Simulation results demonstrate that the proposed deep reinforcement learning-based guidance law can successfully achieve cooperative attacks across a range of randomized initial conditions. Full article
(This article belongs to the Section Aeronautics)
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26 pages, 9803 KiB  
Article
Research on Surrogate Model of Variable Geometry Turbine Performance Based on Backpropagation Neural Network
by Liping Deng, Hu Wu, Yuhang Liu and Qi’an Xie
Aerospace 2025, 12(5), 410; https://doi.org/10.3390/aerospace12050410 - 6 May 2025
Viewed by 95
Abstract
To meet the increasingly stringent performance indicators of gas turbines, the turbine inlet temperature has increased, and variable geometry turbine technology is widely applied. Therefore, this study developed a quasi-two-dimensional (quasi-2D) method for variable geometry turbine performance considering cooling air mixing based on [...] Read more.
To meet the increasingly stringent performance indicators of gas turbines, the turbine inlet temperature has increased, and variable geometry turbine technology is widely applied. Therefore, this study developed a quasi-two-dimensional (quasi-2D) method for variable geometry turbine performance considering cooling air mixing based on the elementary blade method and the cooling airflow mixing model. To address the high-dimensional, multi-variable data fitting problem of variable geometry turbines considering the effects of cooling air, this study adopted a BP neural network to further establish a surrogate model for variable geometry turbine performance. A sensitivity analysis of a single-stage turbine was conducted. The variable geometry cooling performance of a single-stage turbine and an E3 five-stage low-pressure air turbine were calculated, and the corresponding surrogate models were established. The relative errors between the calculated mass flow rate and efficiency of the single-stage turbine and the experimental values were no more than 0.70% and 4.44%, respectively; for the five-stage air turbine, the maximum relative errors in mass flow rate and efficiency were no more than 1.67% and 1.385%, respectively. When the throat area of the single-stage turbine nozzle changed by ±30%, the maximum relative errors between the calculated mass flow rate and efficiency and their experimental values were 3.602% and 4.228%, respectively; thus, the determination coefficients of the constructed BP neural network model for the training samples were all greater than 0.999, indicating that the surrogate model has high prediction accuracy and strong generalization ability and can quickly predict variable geometry turbine cooling performance. Full article
(This article belongs to the Section Aeronautics)
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31 pages, 11029 KiB  
Article
Adapting e-Genius for Next-Level Efficient Electric Aerotow with High-Power Propulsion and Automatic Flight Control System
by Stefan Zistler, Dalong Shi, Walter Fichter and Andreas Strohmayer
Aerospace 2025, 12(5), 409; https://doi.org/10.3390/aerospace12050409 - 6 May 2025
Viewed by 116
Abstract
Aiming to reduce energy demand and carbon footprint, minimize noise impact, and enhance flight safety and efficiency during aerotow operations, this study integrates an electric propulsion system and an automatic flight control system (AFCS) into the electric research aircraft e-Genius. An advanced propulsion [...] Read more.
Aiming to reduce energy demand and carbon footprint, minimize noise impact, and enhance flight safety and efficiency during aerotow operations, this study integrates an electric propulsion system and an automatic flight control system (AFCS) into the electric research aircraft e-Genius. An advanced propulsion system is developed using high-performance batteries and available electric drive components, while the AFCS is designed following a systematic process of developing flight control algorithms. Flight tests are then conducted to evaluate the performance of individual components and the overall system. The test results demonstrate that the upgraded propulsion system provides sufficient power to launch sailplanes, even with the maximum takeoff mass, while significantly reducing energy demand when compared to contemporary fossil fueled towplanes. Additionally, the AFCS proves to be stable and robust, successfully following specified commanded states, executing path tracking, and performing aerotow operations. Full article
(This article belongs to the Special Issue 14th EASN International Conference on Innovation in Aviation & Space towards Sustainability Today & Tomorrow)
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21 pages, 3777 KiB  
Article
On Dynamics of a Copter-Slung Spherical Payload Partially Filled with Liquid
by Yury Selyutskiy, Marat Dosaev, Boris Lokshin and Gusztáv Fekete
Aerospace 2025, 12(5), 408; https://doi.org/10.3390/aerospace12050408 - 6 May 2025
Viewed by 101
Abstract
The motion of a copter with a suspended payload in a vertical plane is considered. The payload has a spherical shape and contains a concentric spherical cavity partially filled with ideal liquid. The system is subjected to horizontal stationary wind. The aerodynamic load [...] Read more.
The motion of a copter with a suspended payload in a vertical plane is considered. The payload has a spherical shape and contains a concentric spherical cavity partially filled with ideal liquid. The system is subjected to horizontal stationary wind. The aerodynamic load on the payload is described within the framework of a quasi-steady approach. The dynamics of the liquid are simulated using the phenomenological pendulum model. The points of this study are the controllability and observability of a stationary flight of a copter with the payload. A control strategy is proposed, which aims to bring the system from a certain initial state to a certain final state, such that the center of mass of the copter moves along a given sufficiently smooth curve. The control is designed to ensure the suppression of oscillations of the payload and the liquid along the entire trajectory. Full article
(This article belongs to the Special Issue Flight Dynamics, Control & Simulation (2nd Edition))
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