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Volume 11
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Aerospace, Volume 11, Issue 11 (November 2024) – 93 articles

Cover Story (view full-size image): In a worldwide scenario which sees an increasing number of small-satellite launches, novel mission concepts may be unlocked, providing spacecraft with precise and rapid maneuvering capability. This work aims to experimentally study and solve the problem of ignition for a 10N hybrid rocket fuelled by hydrogen peroxide. First, a pulsed monopropellant engine capable of functioning as a hybrid injection system was studied, and the effects of parameters such as injected mass, pressure and temperature were analyzed. Then, the objective was to find an ignition procedure that reduces propellant consumption and eliminates the need for a glow plug to reduce electrical power consumption, critical in small-satellite applications. The findings indicate that the concept of pulsed pre-heating is feasible with small propellant consumption and the fast ignition of different fuels. View this paper
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16 pages, 646 KiB  
Article
Electrodynamic Attitude Stabilization of a Spacecraft in an Elliptical Orbit
by Maksim A. Klyushin, Margarita V. Maksimenko and Alexey A. Tikhonov
Aerospace 2024, 11(11), 956; https://doi.org/10.3390/aerospace11110956 - 20 Nov 2024
Cited by 4 | Viewed by 987
Abstract
One of the fundamental problems of spacecraft dynamics related to ensuring its angular orientation in the basic coordinate system is considered. The problem of electrodynamic attitude control for a spacecraft in an elliptical near-Earth Keplerian orbit is studied. A mathematical model describing the [...] Read more.
One of the fundamental problems of spacecraft dynamics related to ensuring its angular orientation in the basic coordinate system is considered. The problem of electrodynamic attitude control for a spacecraft in an elliptical near-Earth Keplerian orbit is studied. A mathematical model describing the attitude dynamics of the spacecraft under the action of the Lorentz torque, the magnetic interaction torque, and the gravitational torque is constructed. The multipole model of the Earth’s magnetic field is used. The possibility of electrodynamic attitude control for the spacecraft’s angular stabilization in the orbital frame is analyzed based on the Euler–Poisson differential equations. The problem of electrodynamic compensation of disturbing torque due to the orbit eccentricity is solved. The control strategy for spacecraft electrodynamic attitude stabilization is presented. Electromagnetic parameters that allow stabilizing the spacecraft’s attitude position in the orbital frame are proposed. The disturbing gravity gradient torque is taken into account. The convergence of the control process is verified by computer modeling. Thus, the possibility and advisability of using the electrodynamic method for the spacecraft attitude control and its angular stabilization in the orbital coordinate system in an elliptical orbit is shown. Full article
(This article belongs to the Section Astronautics & Space Science)
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24 pages, 4561 KiB  
Article
Dual-Frequency Multi-Constellation Global Navigation Satellite System/Inertial Measurements Unit Tight Hybridization for Urban Air Mobility Applications
by Gianluca Corraro, Federico Corraro, Andrea Flora, Giovanni Cuciniello, Luca Garbarino and Roberto Senatore
Aerospace 2024, 11(11), 955; https://doi.org/10.3390/aerospace11110955 - 20 Nov 2024
Viewed by 980
Abstract
A global navigation satellite system (GNSS) for remotely piloted aircraft systems (RPASs) positioning is essential, thanks to the worldwide availability and continuity of this technology in the provision of positioning services. This makes the GNSS technology a critical element as malfunctions impacting on [...] Read more.
A global navigation satellite system (GNSS) for remotely piloted aircraft systems (RPASs) positioning is essential, thanks to the worldwide availability and continuity of this technology in the provision of positioning services. This makes the GNSS technology a critical element as malfunctions impacting on the determination of the position, velocity and timing (PVT) solution could determine safety issues. Such an aspect is particularly challenging in urban air mobility (UAM) scenarios, where low satellite visibility, multipath, radio frequency interference and cyber threats can dangerously affect the PVT solution. So, to meet integrity requirements, GNSS receiver measurements are augmented/fused with other aircraft sensors that can supply position and/or velocity information on the aircraft without relying on any other satellite and/or ground infrastructures. In this framework, in this paper, the algorithms of a hybrid navigation unit (HNU) for UAM applications are detailed, implementing a tightly coupled sensor fusion between a dual-frequency multi-constellation GNSS receiver, an inertial measurements unit and the barometric altitude from an air data computer. The implemented navigation algorithm is integrated with autonomous fault detection and exclusion of GPS/Galileo/BeiDou satellites and the estimation of navigation solution integrity/accuracy (i.e., protection level and figures of merit). In-flight tests were performed to validate the HNU functionalities demonstrating its effectiveness in UAM scenarios even in the presence of cyber threats. In detail, the navigation solution, compared with a real-time kinematic GPS receiver used as the reference centimetre-level position sensor, demonstrated good accuracy, with position errors below 15 m horizontally and 10 m vertically under nominal conditions (i.e., urban scenarios characterized by satellite low visibility and multipath). It continued to provide a valid navigation solution even in the presence of off-nominal events, such as spoofing attacks. The cyber threats were correctly detected and excluded by the system through the indication of the valid/not valid satellite measurements. However, the results indicate a need for fine-tuning the EKF to improve the estimation of figures of merit and protection levels associated to the navigation solution during the cyber-attacks. In contrast, solution accuracy and integrity indicators are well estimated in nominal conditions. Full article
(This article belongs to the Special Issue Recent Research on UAM/AAM Aircraft and Systems: Modeling, Advanced Control, and Emerging Technologies)
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26 pages, 20854 KiB  
Article
Design and Verification of Continuous Tube Forming Process Parameters for PEEK-Based Rod Aimed at Space Manufacturing Applications
by Peng Li, Shuai Tian, Yingjia Duan, Jiayong Yan and Lixin Zhang
Aerospace 2024, 11(11), 954; https://doi.org/10.3390/aerospace11110954 - 20 Nov 2024
Viewed by 883
Abstract
To meet the in-orbit construction needs of super-large spacecraft for ultra-long rod structures, this paper proposes an innovative on-orbit roll forming method for polyetheretherketone (PEEK)-based rod stock. This method ingeniously integrates temperature gradient control into a continuous deformation surface cavity design to achieve [...] Read more.
To meet the in-orbit construction needs of super-large spacecraft for ultra-long rod structures, this paper proposes an innovative on-orbit roll forming method for polyetheretherketone (PEEK)-based rod stock. This method ingeniously integrates temperature gradient control into a continuous deformation surface cavity design to achieve an efficient forming of resin rod components. A parametric model of the forming die cavity was established based on the comprehensive bending and downhill methods, and the boundary conditions for the temperature distribution gradient within the cavity were determined. Through the simulation and analysis of the PEEK rod curling and stitching forming process, the influence of the cavity configuration parameters on the forming load was determined. By constructing a test platform for the roll forming characteristics of resin rod components, the effects of different forming methods, stitching temperatures, and feed rates on forming quality and load were verified, and the main factors affecting the width of the welding zone, the roundness of the rod, and the straightness of the weld were analyzed. Experimental results show that the proposed continuous roll forming scheme can achieve an efficient and continuous forming of resin rod structures. When the length of the member is processed to 300 mm, at a formed rod diameter of 20 mm, by employing a cavity deformation zone length of 210 mm, a cavity clearance of 0.1 mm, a sheet width of 61 mm, a feed rate of 1 mm/s, and a sealing zone temperature setting of 335 °C, optimal rod forming quality can be achieved, characterized by a straightness error of 0.0133 ± 0.005 mm and a roundness error of 0.19 ± 0.07 mm. The proposal of this scheme provides a reliable basis for the continuous manufacturing of rod structures in the on-orbit construction of large space structures in terms of both the scheme and the parameter selection. Full article
(This article belongs to the Special Issue Space Sampling and Exploration Robotics)
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21 pages, 2163 KiB  
Article
Research on Check-In Baggage Flow Prediction for Airport Departure Passengers Based on Improved PSO-BP Neural Network Combination Model
by Bo Jiang, Jian Zhang, Jianlin Fu, Guofu Ding and Yong Zhang
Aerospace 2024, 11(11), 953; https://doi.org/10.3390/aerospace11110953 - 20 Nov 2024
Cited by 1 | Viewed by 1308
Abstract
Accurate forecasting of passenger checked baggage traffic is crucial for efficient and intelligent allocation and optimization of airport service resources. A systematic analysis of the influencing factors and prediction algorithms for the baggage flow is rarely included in existing studies. To accurately capture [...] Read more.
Accurate forecasting of passenger checked baggage traffic is crucial for efficient and intelligent allocation and optimization of airport service resources. A systematic analysis of the influencing factors and prediction algorithms for the baggage flow is rarely included in existing studies. To accurately capture the trend of baggage flow, a combined PCC-PCA-PSO-BP baggage flow prediction model is proposed. This study applies the model to predict the departing passengers’ checked baggage flow at Chengdu Shuangliu International Airport in China. First, in the preprocessing of the data, multiple interpolation demonstrates a better numerical interpolation effect compared to mean interpolation, regression interpolation, and expectation maximization (EM) interpolation in cases of missing data. Second, in terms of the influencing factors, unlike factors that affect the airport passenger flow, the total retail sales of consumer goods have a weak relationship with the baggage flow. The departure passenger flow and flight takeoff and landing sorties play a dominant role in the baggage flow. The railway passenger flow, highway passenger flow, and months have statistically significant effects on the changes in the baggage flow. Factors such as holidays and weekends also contribute to the baggage flow alternation. Finally, the PCC-PCA-PSO-BP model is proposed for predicting the baggage flow. This model exhibits superior performance in terms of the network convergence speed and prediction accuracy compared to four other models: BP, PCA-BP, PSO-BP, and PCA-PSO-BP. This study provides a novel approach for predicting the flow of checked baggage for airport departure passengers. Full article
(This article belongs to the Section Air Traffic and Transportation)
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22 pages, 1952 KiB  
Article
A Fully Autonomous On-Board GNC Methodology for Small-Body Environments Based on CNN Image Processing and MPCs
by Pelayo Peñarroya, Alfredo Escalante, Thomas Frekhaug and Manuel Sanjurjo
Aerospace 2024, 11(11), 952; https://doi.org/10.3390/aerospace11110952 - 19 Nov 2024
Cited by 1 | Viewed by 1171
Abstract
The increasing need for autonomy in space exploration missions is becoming more and more relevant in the design of missions to small bodies. The long communication latencies and sensitivity of the system to unplanned environmental perturbations mean autonomous methods could be a key [...] Read more.
The increasing need for autonomy in space exploration missions is becoming more and more relevant in the design of missions to small bodies. The long communication latencies and sensitivity of the system to unplanned environmental perturbations mean autonomous methods could be a key design block for this type of mission. In this work, a fully autonomous Guidance, Navigation, and Control (GNC) methodology is introduced. This methodology relies on published CNN-based techniques for surface recognition and pose estimation and also on existing MPC-based techniques for the design of a trajectory to perform a soft landing on an asteroid. Combining Hazard Detection and Avoidance (HDA) with relative navigation systems, a Global Safety Map (GSM) is built on the fly as images are acquired. These GSMs provide the GNC system with information about feasible landing spots and populate a longitude–latitude map with safe/hazardous labels that are later processed to find an optimal landing spot based on mission requirements and a distance-fromhazard metric. The methodology is exemplified using Bennu as the body of interest, and a GSM is built for an arbitrary reconnaissance orbit. Full article
(This article belongs to the Section Astronautics & Space Science)
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26 pages, 16654 KiB  
Article
Adaptive Fast Smooth Second-Order Sliding Mode Fault-Tolerant Control for Hypersonic Vehicles
by Lijia Cao, Lei Liu, Pengfei Ji and Chuandong Guo
Aerospace 2024, 11(11), 951; https://doi.org/10.3390/aerospace11110951 - 18 Nov 2024
Viewed by 684
Abstract
In response to control issues in hypersonic vehicles under external disturbances, model uncertainties, and actuator failures, this paper proposes an adaptive fast smooth second-order sliding mode fault-tolerant control scheme. First, a system separation approach is adopted, dividing the hypersonic vehicle model into fast [...] Read more.
In response to control issues in hypersonic vehicles under external disturbances, model uncertainties, and actuator failures, this paper proposes an adaptive fast smooth second-order sliding mode fault-tolerant control scheme. First, a system separation approach is adopted, dividing the hypersonic vehicle model into fast and slow loops for independent design. This ensures that the airflow angle tracking error and sliding mode variables converge to the vicinity of the origin within a finite time. A fixed-time disturbance observer is then designed to estimate and compensate for the effects of model uncertainties, external disturbances, and actuator failures. The controller parameters are dynamically adjusted through an adaptive term to enhance robustness. Furthermore, first-order differentiation is used to estimate differential terms, effectively avoiding the issue of complexity explosion. Finally, the convergence of the controller within a finite time is rigorously proven using the Lyapunov method, and the perturbation of aerodynamic parameters is tested using the Monte Carlo method. Simulation results under various scenarios show that compared with the terminal sliding mode method, the proposed method outperforms control accuracy and convergence speed. The root mean square errors for the angle of attack, sideslip angle, and roll angle are reduced by 65.11%, 86.71%, and 45.51%, respectively, while the standard deviation is reduced by 81.78%, 86.80%, and 45.51%, demonstrating that the proposed controller has faster convergence, higher control accuracy, and smoother output than the terminal sliding mode controller. Full article
(This article belongs to the Section Aeronautics)
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21 pages, 5658 KiB  
Article
Pilot Fatigue Coefficient Based on Biomathematical Fatigue Model
by Jingqiang Li, Hongyu Zhu and Annan Liu
Aerospace 2024, 11(11), 950; https://doi.org/10.3390/aerospace11110950 - 18 Nov 2024
Viewed by 1058
Abstract
The routine assessment of pilot fatigue is paramount to ensuring aviation safety. However, current designs of pilot fatigue factors often lack the comprehensiveness needed to fully account for the dynamic and cumulative nature of fatigue. To bridge this gap, this study introduces a [...] Read more.
The routine assessment of pilot fatigue is paramount to ensuring aviation safety. However, current designs of pilot fatigue factors often lack the comprehensiveness needed to fully account for the dynamic and cumulative nature of fatigue. To bridge this gap, this study introduces a biomathematical fatigue model (BFM) that leverages system dynamics theory, integrating a dynamic feedback mechanism for fatigue information. The novelty of this approach lies in its capability to continuously capture and model fatigue fluctuations driven by varying operational demands. A comparative analysis with international methodologies for evaluating cumulative fatigue on weekly and monthly scales demonstrates that the proposed BFM effectively reproduces variations in pilot fatigue characteristics. Moreover, the pilot fatigue coefficient derived from the model provides a robust differentiation of fatigue profiles across diverse work types, making it particularly suitable for estimating cumulative fatigue over monthly intervals. This BFM-based approach offers valuable insights for the strategic planning of flight schedules and establishes an innovative framework for utilizing BFMs in fatigue management. By employing a scientifically grounded evaluation method rooted in system dynamics and the BFM, this study rigorously assesses cumulative pilot fatigue, confirming the model’s accuracy in replicating fatigue patterns and validating the efficiency and reliability of the derived fatigue coefficient. Full article
(This article belongs to the Collection Air Transportation—Operations and Management)
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21 pages, 6865 KiB  
Article
Lessons Learned for Developing an Effective High-Speed Research Compressor Facility
by Nicholas J. Kormanik III, Douglas R. Matthews, Nicole L. Key and Aaron J. King
Aerospace 2024, 11(11), 949; https://doi.org/10.3390/aerospace11110949 - 18 Nov 2024
Cited by 2 | Viewed by 985
Abstract
Few universities in the world conduct experimental research on high-speed, high-power turbomachinery. The Purdue High-Speed Compressor Research Laboratory has a longstanding tradition of partnering with industry sponsors to perform high-TRL (technology readiness level) experiments on axial and radial compressors for aerospace applications. Early [...] Read more.
Few universities in the world conduct experimental research on high-speed, high-power turbomachinery. The Purdue High-Speed Compressor Research Laboratory has a longstanding tradition of partnering with industry sponsors to perform high-TRL (technology readiness level) experiments on axial and radial compressors for aerospace applications. Early work in the laboratory with Professor Sanford Fleeter and Professor Patrick Lawless involved aeromechanics and the addition of a multistage axial compressor facility to support compressor performance studies. This work continues today under the guidance of Professor Nicole Key. While other universities may operate a single-stage transonic compressor or a low-speed multistage compressor, the Purdue 3-Stage (P3S) Axial Compressor Research Facility provides a unique environment to understand multistage effects at speeds where compressibility is important. Over the last two decades, several areas of important research within the gas-turbine engine industry have been explored: vane clocking, stall/surge inception, tip-leakage/stator-leakage (cavity leakage) flow characterization, and forced response, to name a few. This paper addresses the different configurations of the facility chronologically so that existing datasets can be matched with correct boundary conditions and provides an overview of the different upgrades in the facility as it has developed in preparation for the next generation of small-core compressor research. Full article
(This article belongs to the Special Issue Progress in Turbomachinery Technology for Propulsion)
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17 pages, 8715 KiB  
Article
Pose Estimation for Cross-Domain Non-Cooperative Spacecraft Based on Spatial-Aware Keypoints Regression
by Zihao Wang, Yunmeng Liu and E Zhang
Aerospace 2024, 11(11), 948; https://doi.org/10.3390/aerospace11110948 - 17 Nov 2024
Viewed by 1039
Abstract
Reliable pose estimation for non-cooperative spacecraft is a key technology for in-orbit service and active debris removal missions. Utilizing deep learning techniques for processing monocular camera images is effective and is a hotspot of current research. To reduce errors and improve model generalization, [...] Read more.
Reliable pose estimation for non-cooperative spacecraft is a key technology for in-orbit service and active debris removal missions. Utilizing deep learning techniques for processing monocular camera images is effective and is a hotspot of current research. To reduce errors and improve model generalization, researchers often design multi-head loss functions or use generative models to achieve complex data augmentation, which makes the task complex and time-consuming. We propose a pyramid vision transformer spatial-aware keypoints regression network and a stereo-aware augmentation strategy to achieve robust prediction. Specifically, we primarily use the eight vertices of a cuboid satellite body as landmarks and the observable surfaces can be transformed by, respectively, using the pose labels. The experimental results on the SPEED+ dataset show that by using the existing EPNP algorithm and pseudo-label self-training method, we can achieve high-precision pose estimation for target cross-domains. Compared to other existing methods, our model and strategy are more straightforward. The entire process does not require the generation of new images, which significantly reduces the storage requirements and time costs. Combined with a Kalman filter, the robust and continuous output of the target position and attitude is verified by the SHIRT dataset. This work realizes deployment on mobile devices and provides strong technical support for the application of an automatic visual navigation system in orbit. Full article
(This article belongs to the Section Astronautics & Space Science)
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16 pages, 7121 KiB  
Article
Experimental Aerodynamics of a Small Fixed-Wing Unmanned Aerial Vehicle Coated with Bio-Inspired Microfibers Under Static and Dynamic Stall
by Dioser Santos, Guilherme D. Fernandes, Ali Doosttalab and Victor Maldonado
Aerospace 2024, 11(11), 947; https://doi.org/10.3390/aerospace11110947 - 17 Nov 2024
Cited by 1 | Viewed by 1080
Abstract
A passive flow control technique in the form of microfiber coatings with a diverging pillar cross-section area was applied to the wing suction surface of a small tailless unmanned aerial vehicle (UAV). The coatings are inspired from ‘gecko feet’ surfaces, and their impact [...] Read more.
A passive flow control technique in the form of microfiber coatings with a diverging pillar cross-section area was applied to the wing suction surface of a small tailless unmanned aerial vehicle (UAV). The coatings are inspired from ‘gecko feet’ surfaces, and their impact on steady and unsteady aerodynamics is assessed through wind tunnel testing. Angles of attack from −2° to 17° were used for static experiments, and for some cases, the elevon control surface was deflected to study its effectiveness. In forced oscillation, various combinations of mean angle of attack, frequency and amplitude were explored. The aerodynamic coefficients were calculated from load cell measurements for experimental variables such as microfiber size, the region of the wing coated with microfibers, Reynolds number and angle of attack. Microfibers with a 140 µm pillar height reduce drag by a maximum of 24.7% in a high-lift condition and cruise regime, while 70 µm microfibers work best in the stall flow regime, reducing the drag by 24.2% for the same high-lift condition. Elevon deflection experiments showed that pitch moment authority is significantly improved near stall when microfibers cover the control surface and upstream, with an increase in CM magnitude of up to 22.4%. Dynamic experiments showed that microfibers marginally increase dynamic damping in pitch, improving load factor production in response to control surface actuation at low angles of attack, but reducing it at higher angles. In general, the microfiber pillars are within the laminar boundary layer, and they create a periodic slip condition on the top surface of the pillars, which increases the near-wall momentum over the wing surface. This mechanism is particularly effective in mitigating flow separation at high angles of attack, reducing pressure drag and restoring pitching moment authority provided by control surfaces. Full article
(This article belongs to the Special Issue Aerodynamics, Flight Dynamics and Control of Advanced Air Mobility Vehicles)
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20 pages, 17929 KiB  
Article
Experimental Identification of a New Secondary Wave Pattern in Transonic Cascades with Porous Walls
by Valeriu Drăgan, Oana Dumitrescu, Mihnea Gall, Emilia Georgiana Prisăcariu and Bogdan Gherman
Aerospace 2024, 11(11), 946; https://doi.org/10.3390/aerospace11110946 - 16 Nov 2024
Cited by 1 | Viewed by 754
Abstract
Turbomachinery shock wave patterns occur as a natural result of operating at off-design points and are accountable for some of the loss in performance. In some cases, shock wave–boundary layer (SW-BLIs) interactions may even lead to map restrictions. The current paper refers to [...] Read more.
Turbomachinery shock wave patterns occur as a natural result of operating at off-design points and are accountable for some of the loss in performance. In some cases, shock wave–boundary layer (SW-BLIs) interactions may even lead to map restrictions. The current paper refers to experimental findings on a transonic linear cascade specifically designed to mitigate shock waves using porous walls on the blades. Schlieren visualization reveals two phenomena: Firstly, the shock waves were dissipated in all bladed passages, as predicted by the CFD studies. Secondly, a lower-pressure wave pattern was observed upstream of the blades. It is this phenomenon that the paper reports and attempts to describe. Attempts to replicate this pattern using Reynolds-averaged Navier–Stokes (RANS) calculations indicate that the numerical method may be too dissipative to accurately capture it. The experimental campaign demonstrated a 4% increase in flow rate, accompanied by minimal variations in pressure and temperature, highlighting the potential of this approach for enhancing turbomachinery performance. Full article
(This article belongs to the Section Aeronautics)
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18 pages, 12089 KiB  
Article
A Study on the Aerodynamic Impact of Rotors on Fixed Wings During the Transition Phase in Compound-Wing UAVs
by Longjin Ai, Haiting Xia, Jianting Yang, Ying He, Weibo Tang, Minglong Fan and Jinwu Xiang
Aerospace 2024, 11(11), 945; https://doi.org/10.3390/aerospace11110945 - 15 Nov 2024
Viewed by 894
Abstract
Compound-wing unmanned aerial vehicles (UAVs) are highly valued for their performance. However, during the transition from vertical take-off to the cruise phase, the rotor wake can be coupled with the fixed wing. In this study, the aerodynamic effects of a DJI 9450 rotor [...] Read more.
Compound-wing unmanned aerial vehicles (UAVs) are highly valued for their performance. However, during the transition from vertical take-off to the cruise phase, the rotor wake can be coupled with the fixed wing. In this study, the aerodynamic effects of a DJI 9450 rotor on a NACA2415 fixed wing during transition were investigated using the computational fluid dynamics (CFD) method. The rotor-to-wing distances (R/L = 0.25, 0.5, and 0.9) were varied to analyze their impact on aerodynamic performance. The results show that increasing the distance between the front rotor and the fixed wing enhances the lift and drag of the fixed wing, while increasing the distance between the rear rotor and the fixed wing decreases the lift and drag of the fixed wing. During the rotor’s rotation, the fluctuation in the lift and drag of the fixed wing changes periodically due to the rotor wake, and the smaller the distance between the rotor and the fixed wing, the larger the fluctuation. When R/L = 0.25, the fluctuation of the fixed wing is minimized. Compound-wing UAVs with rotors mounted at R/L = 0.25 during the design stage can improve the flight stability during the transition phase in UAVs. Full article
(This article belongs to the Section Aeronautics)
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17 pages, 2982 KiB  
Article
Impact of Target Surface Building Direction on the Heat Transfer Characteristics of Additive Manufactured Impingement Systems
by Tommaso Bacci, Alessio Picchi, Luca Innocenti, Francesco Morante and Bruno Facchini
Aerospace 2024, 11(11), 944; https://doi.org/10.3390/aerospace11110944 - 15 Nov 2024
Viewed by 627
Abstract
Additive manufacturing (AM) is widely recognized as a prominent tool to maximize the potential of internal cooling systems for gas turbine applications. Several past studies have been undertaken in order to assess the effect of additive manufactured components peculiar characteristics, mainly in the [...] Read more.
Additive manufacturing (AM) is widely recognized as a prominent tool to maximize the potential of internal cooling systems for gas turbine applications. Several past studies have been undertaken in order to assess the effect of additive manufactured components peculiar characteristics, mainly in the form of surface roughness, on heat transfer and pressure losses. On the other hand, impingement constitutes one of the most adopted solutions for turbine vane internal cooling; also, its heat transfer performance has been shown to be potentially improved through the use of roughened target surfaces in several studies. In this work, the effect of AM-generated roughness on the performance of impingement systems has been experimentally investigated. A lumped approach was used to test additive manufactured coupons reproducing an impingement array in 1:1 scale and retrieve an average heat transfer assessment. The Laser Powder Bed Fusion (L-PBF) technique was used for the manufacturing process. As one of the main parameters affecting AM-generated roughness, the building direction of the target surface was varied in order to highlight its impact on the overall performance comparing four different building directions with a smooth reference target plate made by standard CNC machining. Full article
(This article belongs to the Section Aeronautics)
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14 pages, 3373 KiB  
Article
Optimization of Thermal Management for the Environmental Worthiness Design of Aviation Equipment Using Phase Change Materials
by Jianjun Zhang, Minwei Li, He Li, Yun Fu and Liangxu Cai
Aerospace 2024, 11(11), 943; https://doi.org/10.3390/aerospace11110943 - 15 Nov 2024
Viewed by 905
Abstract
A phase change materials (PCM)-based heat sink is an effective way to cool intermittent high-power electronic devices in aerospace applications such as airborne electronics and aircraft external carry. Optimizing the heat sink is significant in designing a compact and efficient system. This paper [...] Read more.
A phase change materials (PCM)-based heat sink is an effective way to cool intermittent high-power electronic devices in aerospace applications such as airborne electronics and aircraft external carry. Optimizing the heat sink is significant in designing a compact and efficient system. This paper proposes an optimization procedure for the PCM/expanded graphite (EG)-based heat sink to minimize the temperature of the heat source. The numerical model is built to estimate the thermal response, and a surrogate model is fitted using the Kriging model. An optimization algorithm is constructed to predict the optimum parameters of the heat sink, and the effects of heat sink volume, heat flux, and working time on the optimal parameters of the heat sink are investigated. This shows that the numerical results agree well with the experimental data, and the proposed optimization method effectively obtains the optimal EG mass fraction and the geometric dimensions of the PCM enclosure. The optimal EG mass fraction increases with the rise in heat sink volume and decreases with the increase in heat flux and working time. The optimal ratio of the height to the length of the heat sink is 0.43. This study provides practical guidance for the optimal design of a PCM/EG-based heat sink. Full article
(This article belongs to the Special Issue Aerospace Human–Machine and Environmental Control Engineering)
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33 pages, 16970 KiB  
Article
Ontological Airspace-Situation Awareness for Decision System Support
by Carlos C. Insaurralde and Erik Blasch
Aerospace 2024, 11(11), 942; https://doi.org/10.3390/aerospace11110942 - 15 Nov 2024
Viewed by 1327
Abstract
Air Traffic Management (ATM) has become complicated mainly due to the increase and variety of input information from Communication, Navigation, and Surveillance (CNS) systems as well as the proliferation of Unmanned Aerial Vehicles (UAVs) requiring Unmanned Aerial System Traffic Management (UTM). In response [...] Read more.
Air Traffic Management (ATM) has become complicated mainly due to the increase and variety of input information from Communication, Navigation, and Surveillance (CNS) systems as well as the proliferation of Unmanned Aerial Vehicles (UAVs) requiring Unmanned Aerial System Traffic Management (UTM). In response to the UTM challenge, a decision support system (DSS) has been developed to help ATM personnel and aircraft pilots cope with their heavy workloads and challenging airspace situations. The DSS provides airspace situational awareness (ASA) driven by knowledge representation and reasoning from an Avionics Analytics Ontology (AAO), which is an Artificial Intelligence (AI) database that augments humans’ mental processes by means of implementing AI cognition. Ontologies for avionics have also been of interest to the Federal Aviation Administration (FAA) Next Generation Air Transportation System (NextGen) and the Single European Sky ATM Research (SESAR) project, but they have yet to be received by practitioners and industry. This paper presents a decision-making computer tool to support ATM personnel and aviators in deciding on airspace situations. It details the AAO and the analytical AI foundations that support such an ontology. An application example and experimental test results from a UAV AAO (U-AAO) framework prototype are also presented. The AAO-based DSS can provide ASA from outdoor park-testing trials based on downscaled application scenarios that replicate takeoffs where drones play the role of different aircraft, i.e., where a drone represents an airplane that takes off and other drones represent AUVs flying around during the airplane’s takeoff. The resulting ASA is the output of an AI cognitive process, the inputs of which are the aircraft localization based on Automatic Dependent Surveillance–Broadcast (ADS-B) and the classification of airplanes and UAVs (both represented by drones), the proximity between aircraft, and the knowledge of potential hazards from airspace situations involving the aircraft. The ASA outcomes are shown to augment the human ability to make decisions. Full article
(This article belongs to the Collection Avionic Systems)
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23 pages, 12326 KiB  
Article
Research on the Criteria for Determining the Starting Performance of an Inward-Turning Inlet by Integrating the Concept of the Equivalent Contraction Ratio
by Fanshuo Meng, Bo Jin, Xiaolong He, Zheng Chen, Wenhui Yan, Zhenjun Zhao and Zonghan Yu
Aerospace 2024, 11(11), 941; https://doi.org/10.3390/aerospace11110941 - 13 Nov 2024
Viewed by 1056
Abstract
The prediction of hypersonic inlet starting performance is crucial for the successful ignition of the combustion chamber, directly impacting the overall performance of the propulsion system. This challenge arises especially when freestream conditions vary. Therefore, this paper proposes the concept of the equivalent [...] Read more.
The prediction of hypersonic inlet starting performance is crucial for the successful ignition of the combustion chamber, directly impacting the overall performance of the propulsion system. This challenge arises especially when freestream conditions vary. Therefore, this paper proposes the concept of the equivalent contraction ratio, and establishes and analyzes the intrinsic correlation between the geometric contraction ratio and angle of attack on the starting performance of three-dimensional inward-turning inlet. The results indicate the following: (1) The startability index can be applied to determine the start boundary of the three-dimensional inward-turning inlet under conditions of the freestream Mach number of 6.0 and an altitude of 27 km, with a deviation of no more than 6.6% from the optimal SI = 0.087 criterion; (2) The start boundary after applying the equivalent contraction ratio shows deviations not exceeding 4.0% under positive angle-of-attack conditions compared to the startability index, while the deviation is larger under negative angle-of-attack conditions, reaching a maximum of 13.3%. After applying a correction formula, the deviations can be reduced to within 2.0%; (3) For the same equivalent contraction ratio, the differences in starting performance between different positive and negative angle-of-attack conditions may fundamentally arise from the degree of compression of the inlet. Finally, the equivalent contraction ratio theory is proven to be able to quickly and easily predict the accurate starting performance of the inward-turning inlet at different angles of attack, improving the breadth and efficiency of engineering predictions. Full article
(This article belongs to the Special Issue Innovations in Hypersonic Propulsion Systems)
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23 pages, 6475 KiB  
Article
Adaptive Two-Degree-of-Freedom Robust Gain-Scheduling Control Strategy
by Kai Yin, Zhidan Liu and Linfeng Gou
Aerospace 2024, 11(11), 940; https://doi.org/10.3390/aerospace11110940 - 12 Nov 2024
Viewed by 949
Abstract
This study introduces a novel tracking control strategy tailored to aeroengines, which are highly nonlinear and characterized by significant uncertainty. The proposed method entails a robust extended Kalman filter (REKF) enhanced by a forgetting factor for improved performance. An accompanying augmented, mixed onboard [...] Read more.
This study introduces a novel tracking control strategy tailored to aeroengines, which are highly nonlinear and characterized by significant uncertainty. The proposed method entails a robust extended Kalman filter (REKF) enhanced by a forgetting factor for improved performance. An accompanying augmented, mixed onboard adaptive model based on the REKF precisely estimates and manages engine performance degradation. This advanced model effectively counters the degradation term in the perturbation block of the engine’s uncertain model. Using this strategic approach, a robust gain-scheduling controller was constructed and was found to outperform its predecessors, marking a notable advancement in control system design. Controlling twin rotor multi-input, multi-output (MIMO) systems is a highly complex process due to model uncertainties and unpredictable external disturbances. To address these challenges, we constructed an adaptive two-degree-of-freedom robust gain-scheduling controller (ATDF-RGSC) using a mixed sensitivity approach. Rigorous performance analysis confirms that this controller offers enhanced robustness, faster tracking, and more precise disturbance attenuation compared to other methods. These advanced control strategies successfully manage uncertainties and disturbances, improving performance metrics in both simulated and experimental scenarios. The proposed method may significantly enhance the safety and reliability of aeroengines and MIMO systems in practical applications. Full article
(This article belongs to the Section Aeronautics)
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20 pages, 6585 KiB  
Article
Topology Optimization of the Bracket Structure in the Acquisition, Pointing, and Tracking System Considering Displacement and Key Point Stress Constraints
by Bo Gao, Hongtao Yang, Weining Chen and Hao Wang
Aerospace 2024, 11(11), 939; https://doi.org/10.3390/aerospace11110939 - 12 Nov 2024
Viewed by 1373
Abstract
The lightweight and displacement-stable design of the mechanical support structure within the APTS (Acquisition, Pointing, and Tracking System) is crucial for enhancing the payload capacity of remote sensing, satellite communication, and laser systems, while still meeting specified functional requirements. This paper adopts the [...] Read more.
The lightweight and displacement-stable design of the mechanical support structure within the APTS (Acquisition, Pointing, and Tracking System) is crucial for enhancing the payload capacity of remote sensing, satellite communication, and laser systems, while still meeting specified functional requirements. This paper adopts the Solid Isotropic Material with Penalization (SIMP) method to investigate the structural topology optimization of the L-shaped bracket in the APTS, aiming to minimize structural compliance while using volume, key point displacement, and maximum stress as constraints. In the optimization model, differences in the topology of the L-shaped bracket structure are explored to minimize structural compliance, which was performed under volume, key point displacement, and stress constraints, and the results are compared with the initial reinforced structure. The innovative L-shaped bracket structure obtained through topology optimization uses significantly less material than the initial reinforced design, while still meeting the displacement and stress constraints. After smoothing, rounding, and finite element analysis, the displacement and stress performance of the optimized L-shaped bracket structure satisfies the set constraints. The method proposed in this paper offers an innovative solution for the lightweight design of mechanical support structures in APTS, with significant engineering application potential. Full article
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11 pages, 1709 KiB  
Article
A Conceptual Design of Deployable Antenna Mechanisms
by Hyeongseok Kang, Bohyun Hwang, Sooyoung Kim, Hyeonseok Lee, Kyungrae Koo, Seonggun Joe and Byungkyu Kim
Aerospace 2024, 11(11), 938; https://doi.org/10.3390/aerospace11110938 - 12 Nov 2024
Viewed by 1314
Abstract
Over the last decade, large-scale antennas have been developed to enhance precise blue force tracking and improve situational awareness. In general, such large-scale antennas, ranging from 1 to up to 10 m, need a specific mechanism that can reconfigure their shapes and morphologies, [...] Read more.
Over the last decade, large-scale antennas have been developed to enhance precise blue force tracking and improve situational awareness. In general, such large-scale antennas, ranging from 1 to up to 10 m, need a specific mechanism that can reconfigure their shapes and morphologies, resulting in stowing and deploying upon the given environment. In parallel, it must be noted that such deployable mechanisms should accommodate a large aperture diameter while ensuring they are lightweight, robust, and structurally rigid to avoid undesired deformations due to the deployment. With these in mind, this work presents a large frustum-shaped deployable antenna mechanism with a large aperture diameter of 7.5 m. The deployable mechanism is composed of hierarchical bayes the radial direction at 30° intervals. Twelve bayes in total identify the overall morphology of the deployable antenna, which features a dodecagon. Specifically, the bay is composed of three linkage structures: a six-bar linkage mechanism, a V-folding mechanism, and a single pantograph mechanism. As a result of static and dynamic simulations, it is identified that the mechanism achieves an area-to-mass ratio of 5.003 m2/kg and a safety factor of 323.8 upon deployment. Conclusively, this work demonstrates a strong potential of the deployable antenna mechanism, providing high rigidity and large aperture diameter while ensuring high stability in space environments. Full article
(This article belongs to the Special Issue Space Mechanisms and Robots)
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18 pages, 2550 KiB  
Article
Machine-Learning Methods Estimating Flights’ Hidden Parameters for the Prediction of KPIs
by George Vouros, Ioannis Ioannidis, Georgios Santipantakis, Theodore Tranos, Konstantinos Blekas, Marc Melgosa and Xavier Prats
Aerospace 2024, 11(11), 937; https://doi.org/10.3390/aerospace11110937 - 12 Nov 2024
Viewed by 903
Abstract
Complex microscopic simulation models of strategic Air Traffic Management (ATM) performance assessment and decision-making are hindered by several factors. One of the most important is the existence of hidden parameters—such as aircraft take-off weight (TOW) and the selected cost index (CI)—which, if known, [...] Read more.
Complex microscopic simulation models of strategic Air Traffic Management (ATM) performance assessment and decision-making are hindered by several factors. One of the most important is the existence of hidden parameters—such as aircraft take-off weight (TOW) and the selected cost index (CI)—which, if known, would allow for more effective performance modeling methodologies for assessing Key Performance Indicators (KPIs) at various levels of abstraction/detail, e.g., system-wide, or at the level of individual flights. This research proposes a data-driven methodology for the estimation of flights’ hidden parameters combining mechanistic and advanced Artificial Intelligence/Machine Learning (AI/ML) models. Aiming at microsimulation models, our goal is to study the effect of these estimations on the prediction of flights’ KPIs. In so doing, we propose a novel methodology according to which data-driven methods are trained given optimal trajectories (produced by mechanistic models) corresponding to known hidden parameter values, with the aim of predicting hidden parameters’ values of unseen trajectories. The results show that estimations of hidden parameters support the accurate prediction of KPIs regarding the efficiency of flights: fuel consumption, gate-to-gate time and distance flown. Full article
(This article belongs to the Special Issue Advances in Air Traffic and Airspace Control and Management (2nd Edition))
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16 pages, 5597 KiB  
Article
Inverse Identification of Constituent Elastic Parameters of Ceramic Matrix Composites Based on Macro–Micro Combined Finite Element Model
by Sheng Huang, Le Rong, Zhuoqun Jiang and Yuriy V. Tokovyy
Aerospace 2024, 11(11), 936; https://doi.org/10.3390/aerospace11110936 - 12 Nov 2024
Cited by 1 | Viewed by 1238
Abstract
Accurate material performance parameters are the prerequisite for conducting composite material structural analysis and design. However, the complex multiscale structure of ceramic matrix composites (CMCs) makes it extremely difficult to accurately obtain their mechanical performance parameters. To address this issue, a CMC micro-scale [...] Read more.
Accurate material performance parameters are the prerequisite for conducting composite material structural analysis and design. However, the complex multiscale structure of ceramic matrix composites (CMCs) makes it extremely difficult to accurately obtain their mechanical performance parameters. To address this issue, a CMC micro-scale constituents (fiber bundles and matrix) elastic parameter inversion method was proposed based on the integration of macro–micro finite element models. This model was established based on the μCT scan data of a plain-woven CMC tensile specimen using the chemical vapor infiltration (CVI) process, which could reflect the real microstructure and surface morphology characteristics of the material. A BP neural network was used to predict the multiscale stiffness, considering the influence of the porous structure on the macroscopic stiffness of the material. The inversion process of the constituent elastic parameters was established using the trust-region algorithm combined with an improved error function. The inversion results showed that this method could accurately invert the CMC constituent elastic parameters with excellent robustness and anti-noise performance. Under four different degrees of deviation in the initial iteration conditions, the inversion error of all parameters was within 1%, and the maximum inversion error was only 2.16% under a 10% high noise level. Full article
(This article belongs to the Special Issue Advanced Composite Materials in Aerospace)
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12 pages, 4726 KiB  
Article
Effect of Nozzle Type on Combustion Characteristics of Ammonium Dinitramide-Based Energetic Propellant
by Jianhui Han, Luyun Jiang, Jifei Ye, Junling Song, Haichao Cui, Baosheng Du and Gaoping Feng
Aerospace 2024, 11(11), 935; https://doi.org/10.3390/aerospace11110935 - 11 Nov 2024
Cited by 1 | Viewed by 703
Abstract
The present study explores the influence of diverse nozzle geometries on the combustion characteristics of ADN-based energetic propellants. The pressure contour maps reveal a rapid initial increase in the average pressure of ADN-based propellants across the three different nozzles. Subsequently, the pressure tapers [...] Read more.
The present study explores the influence of diverse nozzle geometries on the combustion characteristics of ADN-based energetic propellants. The pressure contour maps reveal a rapid initial increase in the average pressure of ADN-based propellants across the three different nozzles. Subsequently, the pressure tapers off gradually as time elapses. Notably, during the crucial initial period of 0–5 μs, the straight nozzle exhibited the most significant pressure surge at 30.2%, substantially outperforming the divergent (6.67%) and combined nozzles (15.5%). The combustion product variation curves indicate that the contents of reactants ADN and CH3OH underwent a steep decline, whereas the product N2O displayed a biphasic behavior, initially rising and subsequently declining. In contrast, the CO2 concentration remained on a steady ascent throughout the entire combustion process, which concluded within 10 μs. Our findings suggest that the straight nozzle facilitated the more expeditious generation of high-temperature and high-pressure combustion gases for ADN-based propellants, expediting reaction kinetics and enhancing combustion efficiency. This is attributed to the reduced intermittent interactions between the nozzle wall and shock waves, which are encountered in the divergent and combined nozzles. In conclusion, the superior combustion characteristics of ADN-based propellants in the straight nozzle, compared to the divergent and combined nozzles, underscore its potential in informing the design of advanced propulsion systems and guiding the development of innovative energetic propellants. Full article
(This article belongs to the Section Astronautics & Space Science)
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20 pages, 1088 KiB  
Article
Model-Based Sequential Design of Experiments with Machine Learning for Aerospace Systems
by Tim Gerling, Kai Dresia, Jan Deeken and Günther Waxenegger-Wilfing
Aerospace 2024, 11(11), 934; https://doi.org/10.3390/aerospace11110934 - 11 Nov 2024
Viewed by 1099
Abstract
Traditional experimental design methods often face challenges in handling complex aerospace systems due to the high dimensionality and nonlinear behavior of such systems, resulting in nonoptimal experimental designs. To address these challenges, machine learning techniques can be used to further increase the application [...] Read more.
Traditional experimental design methods often face challenges in handling complex aerospace systems due to the high dimensionality and nonlinear behavior of such systems, resulting in nonoptimal experimental designs. To address these challenges, machine learning techniques can be used to further increase the application areas of modern Bayesian Optimal Experimental Design (BOED) approaches, enhancing their efficiency and accuracy. The proposed method leverages neural networks as surrogate models to approximate the underlying physical processes, thereby reducing computational costs and allowing for full differentiability. Additionally, the use of reinforcement learning enables the optimization of sequential designs and essential real-time capability. Our framework is validated by optimizing experimental designs that are used for the efficient characterization of turbopumps for liquid propellant rocket engines. The reinforcement learning approach yields superior results in terms of the expected information gain related to a sequence of 15 experiments, exhibiting mean performance increases of 9.07% compared to random designs and 6.47% compared to state-of-the-art approaches. Therefore, the results demonstrate significant improvements in experimental efficiency and accuracy compared to conventional methods. This work provides a robust framework for the application of advanced BOED methods in aerospace testing, with implications for broader engineering applications. Full article
(This article belongs to the Section Aeronautics)
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25 pages, 6322 KiB  
Article
A Convolution Auto-Encoders Network for Aero-Engine Hot Jet FT-IR Spectrum Feature Extraction and Classification
by Shuhan Du, Wei Han, Zhenping Kang, Yurong Liao and Zhaoming Li
Aerospace 2024, 11(11), 933; https://doi.org/10.3390/aerospace11110933 - 11 Nov 2024
Viewed by 615
Abstract
Aiming at classification and recognition of aero-engines, two telemetry Fourier transform infrared (FT-IR) spectrometers are utilized to measure the infrared spectrum of the areo-engine hot jet, meanwhile a spectrum dataset of six types of areo-engines is established. In this paper, a convolutional autoencoder [...] Read more.
Aiming at classification and recognition of aero-engines, two telemetry Fourier transform infrared (FT-IR) spectrometers are utilized to measure the infrared spectrum of the areo-engine hot jet, meanwhile a spectrum dataset of six types of areo-engines is established. In this paper, a convolutional autoencoder (CAE) is designed for spectral feature extraction and classification, which is composed of coding network, decoding network, and classification network. The encoder network consists of convolutional layers and maximum pooling layers, the decoder network consists of up-sampling layers and deconvolution layers, and the classification network consists of a flattened layer and a dense layer. In the experiment, data for the spectral dataset were randomly sampled at a ratio of 8:1:1 to produce the training set, validation set, and prediction set, and the performance measures were accuracy, precision, recall, confusion matrix, F1 score, ROC curve, and AUC value. The experimental result of CAE reached 96% accuracy and the prediction running time was 1.57 s. Compared with the classical PCA feature extraction and SVM, XGBoost, AdaBoost, and Random Forest classifier algorithms, as well as AE, CSAE, and CVAE deep learning classification methods, the CAE network can achieve higher accuracy and efficiency and can complete the spectral classification task. Full article
(This article belongs to the Section Aeronautics)
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13 pages, 2915 KiB  
Article
Three-Dimensional Flutter Numerical Simulation of Wings in Heavy Gas and Transonic Flutter Similarity Law Correction Method
by Zhe Hu, Bo Lu, Yongping Liu, Li Yu, Xiping Kou and Jun Zha
Aerospace 2024, 11(11), 932; https://doi.org/10.3390/aerospace11110932 - 11 Nov 2024
Cited by 1 | Viewed by 804
Abstract
Wind tunnel testing is a crucial method for studying aircraft flutter. Using heavy gas as the wind tunnel medium can mitigate the escalating issue of test models being overweight as advanced aircraft develop. This paper employs an analytical method for numerical calculations of [...] Read more.
Wind tunnel testing is a crucial method for studying aircraft flutter. Using heavy gas as the wind tunnel medium can mitigate the escalating issue of test models being overweight as advanced aircraft develop. This paper employs an analytical method for numerical calculations of three-dimensional (3D) wing flutter based on fluid–structure interaction (FSI). Flutter calculations for the Goland wing are conducted, and the results in the air medium are consistent with the literature. In contrast, significant differences in flutter behavior are observed in the heavy gas R134a medium. Compared to air, when the model reaches a critical state in R134a, the incoming flow velocity is lower, the incoming flow density is approximately 3 to 5 times air, and the incoming flow dynamic pressure is about 1.1 to 1.2 times that of air. The correction of heavy gas flutter data is crucial for wind tunnel testing. This paper proposes a correction method based on the unsteady transonic flow similarity law proposed by Bendiksen under quasi-steady conditions. Attempts are made to revise relevant published wind tunnel tests and heavy gas flutter calculation results. The transonic flutter similarity law effectively explains the flutter similarity of rigid models in both heavy gas and air media. Still, it fails in cases with highly reduced frequencies and low mass ratios, such as those encountered with flexible wings. Full article
(This article belongs to the Section Aeronautics)
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19 pages, 5848 KiB  
Article
Aerodynamic Optimization Method for Propeller Airfoil Based on DBO-BP and NSWOA
by Changjing Guo, Zhiling Xu, Xiaoyan Yang and Hao Li
Aerospace 2024, 11(11), 931; https://doi.org/10.3390/aerospace11110931 - 11 Nov 2024
Cited by 2 | Viewed by 1400
Abstract
To address the issues of tedious optimization processes, insufficient fitting accuracy of surrogate models, and low optimization efficiency in drone propeller airfoil design, this paper proposes an aerodynamic optimization method for propeller airfoils based on DBO-BP (Dum Beetle Optimizer-Back-Propagation) and NSWOA (Non-Dominated Sorting [...] Read more.
To address the issues of tedious optimization processes, insufficient fitting accuracy of surrogate models, and low optimization efficiency in drone propeller airfoil design, this paper proposes an aerodynamic optimization method for propeller airfoils based on DBO-BP (Dum Beetle Optimizer-Back-Propagation) and NSWOA (Non-Dominated Sorting Whale Optimization Algorithm). The NACA4412 airfoil is selected as the research subject, optimizing the original airfoil at three angles of attack (2°, 5° and 10°). The CST (Class Function/Shape Function Transformation) airfoil parametrization method is used to parameterize the original airfoil, and Latin hypercube sampling is employed to perturb the original airfoil within a certain range to generate a sample space. CFD (Computational Fluid Dynamics) software (2024.1) is used to perform aerodynamic analysis on the airfoil shapes within the sample space to construct a sample dataset. Subsequently, the DBO algorithm optimizes the initial weights and thresholds of the BP neural network surrogate model to establish the DBO-BP neural network surrogate model. Finally, the NSWOA algorithm is utilized for multi-objective optimization, and CFD software verifies and analyzes the optimization results. The results show that at the angles of attack of 2°, 5° and 10°, the test accuracy of the lift coefficient is increased by 45.35%, 13.4% and 49.3%, and the test accuracy of the drag coefficient is increased by 12.5%, 39.1% and 13.7%. This significantly enhances the prediction accuracy of the BP neural network surrogate model for aerodynamic analysis results, making the optimization outcomes more reliable. The lift coefficient of the airfoil is increased by 0.04342, 0.01156 and 0.03603, the drag coefficient is reduced by 0.00018, 0.00038 and 0.00027, respectively, and the lift-to-drag ratio is improved by 2.95892, 2.96548 and 2.55199, enhancing the convenience of airfoil aerodynamic optimization and improving the aerodynamic performance of the original airfoil. Full article
(This article belongs to the Section Aeronautics)
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20 pages, 4479 KiB  
Article
Prediction of Temperature Distribution on an Aircraft Hot-Air Anti-Icing Surface by ROM and Neural Networks
by Ziying Chu, Ji Geng, Qian Yang, Xian Yi and Wei Dong
Aerospace 2024, 11(11), 930; https://doi.org/10.3390/aerospace11110930 - 11 Nov 2024
Cited by 1 | Viewed by 1124
Abstract
To address the inefficiencies and time-consuming nature of traditional hot-air anti-icing system designs, reduced-order models (ROMs) and machine learning techniques are introduced to predict anti-icing surface temperature distributions. Two models, AlexNet combined with Proper Orthogonal Decomposition (POD-AlexNet) and multi-CNNs with GRU (MCG), are [...] Read more.
To address the inefficiencies and time-consuming nature of traditional hot-air anti-icing system designs, reduced-order models (ROMs) and machine learning techniques are introduced to predict anti-icing surface temperature distributions. Two models, AlexNet combined with Proper Orthogonal Decomposition (POD-AlexNet) and multi-CNNs with GRU (MCG), are proposed by comparing several classic neural networks. Design variables of the hot-air anti-icing cavity are used as inputs of the two models, and the corresponding surface temperature distribution data serve as outputs, and then the performance of these models is evaluated on the test set. The POD-AlexNet model achieves a mean prediction accuracy of over 95%, while the MCG model reaches 96.97%. Furthermore, the proposed model demonstrates a prediction time of no more than 5.5 ms for individual temperature samples. The proposed models not only provide faster predictions of anti-icing surface temperature distributions than traditional numerical simulation methods but also ensure acceptable accuracy, which supports the design of aircraft hot-air anti-icing systems based on optimization methods such as genetic algorithms. Full article
(This article belongs to the Special Issue Deicing and Anti-Icing of Aircraft (Volume IV))
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29 pages, 18002 KiB  
Article
Planning and Evaluation of Water-Dropping Strategy for Fixed-Wing Fire Extinguisher Based on Multi-Resolution Modeling
by Xiyu Wang, Yuanbo Xue, Yongliang Tian, Hu Liu and Zhiyong Cai
Aerospace 2024, 11(11), 929; https://doi.org/10.3390/aerospace11110929 - 10 Nov 2024
Viewed by 1608
Abstract
The deployment of fixed-wing aircraft in fire-extinguishing operations represents a significant advancement in the domain of aviation emergency rescue. Addressing the challenge of enhancing firefighting efficacy, this study delves into the water-dropping strategies of fixed-wing extinguishers and provides a methodological framework for the [...] Read more.
The deployment of fixed-wing aircraft in fire-extinguishing operations represents a significant advancement in the domain of aviation emergency rescue. Addressing the challenge of enhancing firefighting efficacy, this study delves into the water-dropping strategies of fixed-wing extinguishers and provides a methodological framework for the strategic planning and assessment of water-dropping tactics, employing multi-resolution modeling. The formulation of the planning algorithm and the structure of the effectiveness evaluation index system are explained accordingly. The corresponding prototype system was designed, comprising four subsystems that utilized distinct resolution models: fire environment simulation, water-dropping point scheme planning, approaching path planning, and mission evaluation simulation. Case studies validate the system’s capability to forecast fire and smoke propagation, plan a water-dropping trajectory based on the fire line, optimize flight paths based on the trajectory, and simulate as well as evaluate the whole firefighting mission process. The above research comprehensively constructs the model, finishes the iterative optimization, and evaluates the water-dropping strategy by simulation. The technical path and methodological framework of studying water-dropping strategies are established. The outcomes of this study provide invaluable support for the parameter inversion design of the fixed-wing extinguisher, offering decision-making assistance to commanders and supplying training scenarios for new aviation crews. Full article
(This article belongs to the Section Aeronautics)
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19 pages, 3453 KiB  
Article
Autonomous UAV Chasing with Monocular Vision: A Learning-Based Approach
by Yuxuan Jin, Tiantian Song, Chengjie Dai, Ke Wang and Guanghua Song
Aerospace 2024, 11(11), 928; https://doi.org/10.3390/aerospace11110928 - 9 Nov 2024
Cited by 1 | Viewed by 858
Abstract
In recent years, unmanned aerial vehicles (UAVs) have shown significant potential across diverse applications, drawing attention from both academia and industry. In specific scenarios, UAVs are expected to achieve formation flying without relying on communication or external assistance. In this context, our work [...] Read more.
In recent years, unmanned aerial vehicles (UAVs) have shown significant potential across diverse applications, drawing attention from both academia and industry. In specific scenarios, UAVs are expected to achieve formation flying without relying on communication or external assistance. In this context, our work focuses on the classic leader-follower formation and presents a learning-based UAV chasing control method that enables a quadrotor UAV to autonomously chase a highly maneuverable fixed-wing UAV. The proposed method utilizes a neural network called Vision Follow Net (VFNet), which integrates monocular visual data with the UAV’s flight state information. Utilizing a multi-head self-attention mechanism, VFNet aggregates data over a time window to predict the waypoints for the chasing flight. The quadrotor’s yaw angle is controlled by calculating the line-of-sight (LOS) angle to the target, ensuring that the target remains within the onboard camera’s field of view during the flight. A simulation flight system is developed and used for neural network training and validation. Experimental results indicate that the quadrotor maintains stable chasing performance through various maneuvers of the fixed-wing UAV and can sustain formation over long durations. Our research explores the use of end-to-end neural networks for UAV formation flying, spanning from perception to control. Full article
(This article belongs to the Section Aeronautics)
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23 pages, 2017 KiB  
Article
Numerical Modeling, Trim, and Linearization of a Side-by-Side Helicopter in Hovering Conditions
by Francesco Mazzeo, Marilena D. Pavel, Daniele Fattizzo, Emanuele L. de Angelis and Fabrizio Giulietti
Aerospace 2024, 11(11), 927; https://doi.org/10.3390/aerospace11110927 - 9 Nov 2024
Viewed by 920
Abstract
In the present paper, a flight dynamics model is adopted to represent the trim and stability characteristics of a side-by-side helicopter in hovering conditions. This paper develops a numerical representation of the rotorcraft behavior and proposes a set of guidelines for trimming and [...] Read more.
In the present paper, a flight dynamics model is adopted to represent the trim and stability characteristics of a side-by-side helicopter in hovering conditions. This paper develops a numerical representation of the rotorcraft behavior and proposes a set of guidelines for trimming and linearizing the highly coupled rotor dynamics derived by the modeling approach. The trim algorithm presents two nested loops to compute a solution of the steady-state conditions averaged around one blade’s revolution. On the other hand, a 38-state-space linear representation of the helicopter and rotor dynamics is obtained to study the effects of flap, lead–lag, and inflow on the overall stability. The results are compared with an analytical framework developed to validate the rotorcraft stability and compare different modeling approaches. The analysis showed that non-uniform inflow modeling led to a coupled longitudinal inflow–phugoid mode which made the vehicle prone to dangerous instabilities. The flap and lead–lag dynamics introduced damping in the system and can be considered beneficial for rotor dynamics. Full article
(This article belongs to the Special Issue Vertical Lift: Rotary- and Flapping-Wing Flight)
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