Journal Description
Aerospace
Aerospace
is a peer-reviewed, open access journal of aeronautics and astronautics published monthly online by MDPI. The European Aeronautics Science Network (EASN), and the ECATS International Association are affiliated with Aerospace and their members receive a discount on the article processing charges.
- Open Access— free for readers, with article processing charges (APC) paid by authors or their institutions.
- High Visibility: indexed within Scopus, SCIE (Web of Science), Inspec, and other databases.
- Journal Rank: JCR - Q1 (Engineering, Aerospace) / CiteScore - Q2 (Aerospace Engineering)
- Rapid Publication: manuscripts are peer-reviewed and a first decision is provided to authors approximately 22.3 days after submission; acceptance to publication is undertaken in 2.7 days (median values for papers published in this journal in the second half of 2023).
- Recognition of Reviewers: reviewers who provide timely, thorough peer-review reports receive vouchers entitling them to a discount on the APC of their next publication in any MDPI journal, in appreciation of the work done.
- Companion journal: Astronomy.
Impact Factor:
2.6 (2022);
5-Year Impact Factor:
2.6 (2022)
Latest Articles
Experimental Investigation of Solid Rocket Scramjet Based on Central Strut
Aerospace 2024, 11(5), 410; https://doi.org/10.3390/aerospace11050410 (registering DOI) - 19 May 2024
Abstract
Scramjet based on solid propellant has become a potential choice for the development of future hypersonic vehicles. In this paper, a boron-containing solid rocket scramjet based on the central strut injection was proposed, and the ground direct-connect experiment with the equivalence ratios of
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Scramjet based on solid propellant has become a potential choice for the development of future hypersonic vehicles. In this paper, a boron-containing solid rocket scramjet based on the central strut injection was proposed, and the ground direct-connect experiment with the equivalence ratios of 0.43 to 2.4 under the flight condition of Mach 6, 25 km was carried out. The pressure and flow rate over time were measured in the experiment. The results show that the engine can realize stable supersonic mode or subsonic mode combustion by changing the gas flow rate. The engine can effectively increase the combustor pressure, reduce the unstable combustion time, and advance the strong combustion position by increasing the gas flow rate. The engine achieved high combustion efficiency when the equivalence ratio was about 1, with a maximum of 88.28%. A numerical simulation analysis was also carried out in this paper. Compared to the experimental results, the pressure error obtained by numerical simulation was less than 4%, and the typical position error was less than 3%, suggesting that the simulation model can be used to predict the behavior of scramjet.
Full article
(This article belongs to the Special Issue Advanced Chemical Propulsion and Electric Propulsion)
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Open AccessArticle
Numerical Calculation of Gas–Liquid Two-Phase Flow in Tesla Valve
by
Jie Gong, Guohua Li, Ran Liu and Zijuan Wang
Aerospace 2024, 11(5), 409; https://doi.org/10.3390/aerospace11050409 - 17 May 2024
Abstract
In this paper, the gas–liquid two-phase flow within a Tesla valve under zero-gravity conditions is numerically studied. Based on the VOF model and the inlet two-phase separation method, the forward and reverse flow patterns and pressure drop changes in a Tesla valve at
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In this paper, the gas–liquid two-phase flow within a Tesla valve under zero-gravity conditions is numerically studied. Based on the VOF model and the inlet two-phase separation method, the forward and reverse flow patterns and pressure drop changes in a Tesla valve at different inlet velocities were analyzed. At an inlet velocity of 0.1–0.2 m/s, the flow pattern was slug flow, the bubbles were evenly distributed in different positions in the Tesla valve, and the velocity difference between the main pipe and the arc branch pipe was small. When the inlet velocity was 0.4 m/s, the main flow pattern was annular flow, and there was a phenomenon of gas–liquid phase separation through different flow channels, which was related to centrifugal force. At an inlet velocity of 0.6–0.8 m/s, bubbly flow and slug flow coexisted, which was related to the uneven velocity. In the study range, the difference in the forward and reverse pressure drops of two-phase flow was smaller than that of single-phase flow, and the two-phase diodicity decreased first and then increased with the change in inlet velocity, reaching minimum values of 0.78 at 0.2 m/s and 1.44 at 0.8 m/s.
Full article
(This article belongs to the Section Astronautics & Space Science)
Open AccessArticle
Distributed Hybrid Electric Propulsion Aircraft Design Based on Convex Optimized Power Allocation Management
by
Lingfei Xiao, Yushuo Tan, Xiaole Zhang and Zirui Han
Aerospace 2024, 11(5), 408; https://doi.org/10.3390/aerospace11050408 - 17 May 2024
Abstract
In order to ensure that aircraft have medium and long-range flights, enhanced aerodynamic performance, and reduced fuel consumption, this paper presents an original Distributed Hybrid Electric Propulsion Aircraft (DHEPA) design scheme and proposes a novel power allocation management method based on convex optimization.
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In order to ensure that aircraft have medium and long-range flights, enhanced aerodynamic performance, and reduced fuel consumption, this paper presents an original Distributed Hybrid Electric Propulsion Aircraft (DHEPA) design scheme and proposes a novel power allocation management method based on convex optimization. Firstly, by taking the Tecnam P2006T general-purpose aircraft as a reference, key components of DHEPA are selected and modeled. Then, a power allocation management method for DHEPA is proposed on the basis of convex optimization, which takes the minimum fuel consumption as the performance index to realize the reasonable power allocation of the battery and engine, while avoiding sliding into the local optimum of allocation. Finally, momentum theory and numerical simulation methods are used to analyze the aerodynamic enhancement effect of the propeller on the wing in the DHEPA, and a dynamics method is utilized to calculate the dynamics performance of the aircraft at several important stages. The results show that, compared with the reference aircraft, the lift of the DHEPA is increased by 46%. Under typical sectors, the DHEPA has a higher rate of climb and maximum leveling off speed at cruise, and a significantly lower fuel consumption.
Full article
(This article belongs to the Section Aeronautics)
Open AccessArticle
Exploration and Maintenance of Homeomorphic Orbit Revs in the Elliptic Restricted Three-Body Problem
by
Kevin I. Alvarado and Sandeep K. Singh
Aerospace 2024, 11(5), 407; https://doi.org/10.3390/aerospace11050407 - 17 May 2024
Abstract
A novel station-keeping strategy leveraging periodic revolutions of homeomorphic orbits in the Elliptic Restricted Three-Body Problem within the pulsating frame is presented. A systemic approach founded on arc-length continuation is presented for the discovery, computation, and classification of periodic revolutions that morph from
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A novel station-keeping strategy leveraging periodic revolutions of homeomorphic orbits in the Elliptic Restricted Three-Body Problem within the pulsating frame is presented. A systemic approach founded on arc-length continuation is presented for the discovery, computation, and classification of periodic revolutions that morph from their traditional circular restricted three-body counterparts to build an a priori dataset. The dataset is comprehensive in covering all possible geometric architectures of the restricted problem. Shape similarity is quantified using Hausdorff distance and works as a filter for the station-keeping algorithm in relation to appropriate target conditions. Finally, an efficient scheme to quantify impulsive orbit maintenance maneuvers that minimize the total fuel cost is presented. The proposed approach is salient in its generic applicability across any elliptic three-body system and any periodic orbit family. Finally, average annual station-keeping costs using the described methodology are quantified for selected “orbits of interest” in the cis-lunar and the Sun–Earth systems. The robustness and efficacy of the approach instill confidence in its applicability for realistic mission design scenarios.
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(This article belongs to the Special Issue Spacecraft Orbit Transfers)
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Open AccessArticle
Workload Measurement Method for Manned Vehicles in Multitasking Environments
by
Chenyuan Yang, Liping Pang, Jie Zhang and Xiaodong Cao
Aerospace 2024, 11(5), 406; https://doi.org/10.3390/aerospace11050406 - 16 May 2024
Abstract
Workload (WL) measurement is a crucial foundation for human–machine collaboration, particularly in high-stress multitasking environments such as manned vehicle operations during emergencies, where operators often experience High Workload (HWL) levels, increasing the risk of human error. To address this challenge, this study introduces
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Workload (WL) measurement is a crucial foundation for human–machine collaboration, particularly in high-stress multitasking environments such as manned vehicle operations during emergencies, where operators often experience High Workload (HWL) levels, increasing the risk of human error. To address this challenge, this study introduces a novel WL measurement method that combines Task Demand Load (TDL) and Subject Load Capacity (SLC) to quantitatively assess operator workload. This method was validated through experiments with 45 subjects using the Environmental Control and Atmospheric Regeneration (ECAR) system. The statistical results showed that as the designed WL levels increased, the Average Workload (AWL), the NASA-TLX score, and the work time percentage increased significantly, while the task accuracy and the fixation duration decreased significantly. These results also revealed the impact of WL levels on human responses (such as subjective feeling, work performance, and eye movement). In addition, very strong correlations were found between AWL measurements and NASA-TLX scores (r = 0.75, p < 0.01), task accuracy (r = −0.73, p < 0.01), and work time percentage (r = 0.97, p < 0.01). Overall, these results proved the effectiveness of the proposed method for measuring WL. On this basis, this study defined WL thresholds by integrating task accuracy with AWL calculations, providing a framework for the dynamic management of task allocation between humans and machines to maintain operators within optimal WL ranges.
Full article
(This article belongs to the Special Issue Aerospace Human Machine and Environmental Control Engineering)
Open AccessArticle
A Decision Support Framework for Aircraft Arrival Scheduling and Trajectory Optimization in Terminal Maneuvering Areas
by
Dongdong Gui, Meilong Le, Zhouchun Huang and Andrea D’Ariano
Aerospace 2024, 11(5), 405; https://doi.org/10.3390/aerospace11050405 - 16 May 2024
Abstract
This study introduces a decision support framework that integrates aircraft trajectory optimization and arrival scheduling to facilitate efficient management of descent operations for arriving aircraft within terminal maneuvering areas. The framework comprises three modules designed to tackle specific challenges in the descent process.
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This study introduces a decision support framework that integrates aircraft trajectory optimization and arrival scheduling to facilitate efficient management of descent operations for arriving aircraft within terminal maneuvering areas. The framework comprises three modules designed to tackle specific challenges in the descent process. The first module formulates and solves a trajectory optimization problem, generating a range of candidate descent trajectories for each arriving aircraft. The options for descent operations include step-down descent operation, Continuous Descent Operation (CDO), and CDO with a lateral path stretching strategy. The second module addresses the assignment of conflict-free trajectories to aircraft, determining precise arrival times at each waypoint. This is achieved by solving an aircraft arrival scheduling problem. To overcome computational complexities, a novel variable neighborhood search algorithm is proposed as the solution approach. This algorithm utilizes three neighborhood structures within an extended relaxing and solving framework, and incorporates a tabu search algorithm to enhance the efficiency of the search process in the solution space. The third module focuses on comparing the total cost incurred from flight delays and fuel consumption across the three descent operations, enabling the selection of the most suitable operation for the descent process. The decision support framework is evaluated using real air traffic data from Guangzhou Baiyun International Airport. Experimental results demonstrate that the framework effectively supports air traffic controllers by scheduling more cost-efficient descent operations for arrival aircraft.
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Open AccessArticle
Characterization of the Endwall Flow in a Low-Pressure Turbine Cascade Perturbed by Periodically Incoming Wakes, Part 2: Unsteady Blade Surface Measurements Using Pressure-Sensitive Paint
by
Tobias Schubert, Dragan Kožulović and Martin Bitter
Aerospace 2024, 11(5), 404; https://doi.org/10.3390/aerospace11050404 - 16 May 2024
Abstract
Unsteady pressure-sensitive paint (i-PSP) measurements were performed at a sampling rate of 30 kHz to investigate the near-endwall blade suction surface flow inside a low-pressure turbine cascade operating at engine-relevant high-speed and low-Re conditions. The investigation focuses on the interaction of periodically incoming
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Unsteady pressure-sensitive paint (i-PSP) measurements were performed at a sampling rate of 30 kHz to investigate the near-endwall blade suction surface flow inside a low-pressure turbine cascade operating at engine-relevant high-speed and low-Re conditions. The investigation focuses on the interaction of periodically incoming bar wakes at 500 Hz with the secondary flow and the blade suction surface. The results build on extensive PIV measurements presented in the first part of this two-part publication, which captured the ’negative-jet-effect’ of the wakes throughout the blade passage. The surface pressure distributions are combined with CFD to analyze the flow topology, such as the passage vortex separation line. By analyzing data from phase-locked PIV and PSP measurements, a wake-induced moving pressure gradient negative in space and positive in time is found, which is intensified in the secondary flow region by 33% with respect to midspan. Furthermore, two methods of frequency-filtering based on FFT and SPOD are compared and utilized to associate a pressure fluctuation peak around 678 Hz with separation bubble oscillation.
Full article
(This article belongs to the Special Issue Advanced Flow Diagnostic Tools)
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Open AccessArticle
Characterization of the Endwall Flow in a Low-Pressure Turbine Cascade Perturbed by Periodically Incoming Wakes, Part 1: Flow Field Investigations with Phase-Locked Particle Image Velocimetry
by
Tobias Schubert, Dragan Kožulović and Martin Bitter
Aerospace 2024, 11(5), 403; https://doi.org/10.3390/aerospace11050403 - 16 May 2024
Abstract
Particle image velocimetry (PIV) measurements were performed inside a low-pressure turbine cascade operating at engine-relevant high-speed and low-Re conditions to investigate the near-endwall flow. Of particular research interest was the dominant periodic disturbance of the flow field by incoming wakes, which were generated
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Particle image velocimetry (PIV) measurements were performed inside a low-pressure turbine cascade operating at engine-relevant high-speed and low-Re conditions to investigate the near-endwall flow. Of particular research interest was the dominant periodic disturbance of the flow field by incoming wakes, which were generated by moving cylindrical bars at a frequency of 500 Hz. Two PIV setups were utilized to resolve both (1) a large blade-to-blade plane close to the endwall as well as midspan and (2) the wake effects in an axial flow field downstream of the blade passage. The measurements were performed using a phase-locked approach in order to align and compare the results with comprehensive CFD data that are also available for this test case. The experimental results not only support a better understanding and even a quantification of the wake-induced over/under-turning inside and downstream of the passage, they also enable the tracing of the `negative-jet-effect’, which is widely known in the CFD branch of the turbomachinery community but is seldom visualized in experiments. The results also reveal that the bar wake periodically widens the blade wake by up to 165%, while the secondary flow is less affected and exhibits a phase lag with respect to the 2D-flow effects. The results presented here are an essential basis for the subsequent investigation of the near-endwall blade suction surface effects using unsteady pressure-sensitive paint in the second part of this two-part publication.
Full article
(This article belongs to the Special Issue Advanced Flow Diagnostic Tools)
Open AccessArticle
Stealth Aircraft Penetration Trajectory Planning in 3D Complex Dynamic Based on Radar Valley Radius and Turning Maneuver
by
Xiaoqiang Lu, Jun Huang, Jingxin Guan and Lei Song
Aerospace 2024, 11(5), 402; https://doi.org/10.3390/aerospace11050402 - 16 May 2024
Abstract
Based on the quasi-six-degree-of-freedom flight dynamic equations, considering the changes in the elevation angle caused by an increase in the rolling angle during maneuvering turns, which leads to a rise in the radar cross-section. A computational model for the radar detection probability of
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Based on the quasi-six-degree-of-freedom flight dynamic equations, considering the changes in the elevation angle caused by an increase in the rolling angle during maneuvering turns, which leads to a rise in the radar cross-section. A computational model for the radar detection probability of aircraft in complex environments was constructed. By comprehensively considering flight parameters such as turning angle, rolling angle, Mach number, and radar power factor, this study quantitatively analyzed the influence of these factors on the radar detection probability. It revealed the variation patterns of radar detection probability under different flight conditions. The results provide theoretical support for the Radar Valley Radius and Turning Maneuver Method (RVR-TM) based on decision trees, and lay the foundation for the development of subsequent intelligent decision-making models. To further optimize the trajectory selection of aircraft in complex environments, this study combines theoretical analysis with reinforcement learning algorithms to establish an intelligent decision-making model. This model is trained using the Proximal Policy Optimization (PPO) algorithm, and through precisely defining the state space and reward functions, it accomplishes intelligent trajectory planning for stealth aircraft under radar threat scenarios.
Full article
(This article belongs to the Special Issue Advanced Aircraft Technology)
Open AccessArticle
Heat Transfer Models and Measurements of Brushless DC Motors for Small UASs
by
Farid Saemi, Annalaine Whitson and Moble Benedict
Aerospace 2024, 11(5), 401; https://doi.org/10.3390/aerospace11050401 - 16 May 2024
Abstract
Heat transfer affects a motor’s sizing, its performance, and, ultimately, the overall vehicle’s range and endurance. However, the thermal literature does not have early-stage models for outrunner brushless DC (BLDC) motors found in small unmanned aerial systems (UASs). To address this gap, we
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Heat transfer affects a motor’s sizing, its performance, and, ultimately, the overall vehicle’s range and endurance. However, the thermal literature does not have early-stage models for outrunner brushless DC (BLDC) motors found in small unmanned aerial systems (UASs). To address this gap, we have developed a non-dimensional heat transfer model (Nusselt correlation). Parametric experiments of four different-sized BLDC motors under load in Reynolds-matched wind tunnel tests generated data for model correlation. The motors’ aspect ratios (diameter/length) ranged from 0.9 to 1.5. The freestream Reynolds number of the axial flow over the motors ranged from 20,000 to 40,000. The rotational Reynolds number ranged from 10,000 to 20,000. The results showed that aspect ratio had the largest influence on heat transfer, followed by rotational and freestream Reynolds numbers. A steady-state model used the correlation to predict the motor’s ambient temperature differential within 10 K of experimental data. A case study applied the correlation to predict a hypothetical motor’s continuous torque in different environments. The correlation enables conceptual designers to capture thermally-driven trade-offs in early design stages and reduce costly revisions in later stages.
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(This article belongs to the Special Issue Aircraft Design (SI-5/2023))
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Open AccessArticle
Temperature Prediction of Icy Lunar Soil Sampling Based on the Discrete Element Method
by
Deming Zhao, Tianyi Peng, Weiwei Zhang, He Wang and Jinsheng Cui
Aerospace 2024, 11(5), 400; https://doi.org/10.3390/aerospace11050400 - 16 May 2024
Abstract
This study is part of the preliminary research for the Chang’e 7 project in China. The Chang’e 7 project plans to drill to penetrate the lunar polar soil and collect lunar soil samples using a spiral groove structure. Ice in the cold environment
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This study is part of the preliminary research for the Chang’e 7 project in China. The Chang’e 7 project plans to drill to penetrate the lunar polar soil and collect lunar soil samples using a spiral groove structure. Ice in the cold environment of the lunar polar region is one of the important targets for sampling. In the vacuum environment of the lunar surface, icy soil samples are sensitive to ambient temperature and prone to solid–gas phase change as the temperature increases. To predict the temperature range of lunar soil samples, this study analyzed the effect of thermal parameters on the temperature rise of lunar soil particles and the drill using discrete element simulation. The parameters included in the thermal effect analysis included the thermal conductivity and specific heat capacity of the drilling tools and lunar soil particles. The simulation showed that the temperature of the icy lunar soil sample in the spiral groove ranged from −127.89 to −160.16 °C within the thermal parameter settings. The magnitude of the value was negatively correlated with the thermal conductivity and specific heat capacity of the lunar soil particles, and it was positively correlated with those of the drilling tools. The temperature variation in the drill bit ranged from −51.21 to −132 °C. The magnitude of the value was positively correlated with the thermal conductivity and specific heat capacity of the lunar soil particles and the thermal conductivity of the drilling tool.
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(This article belongs to the Special Issue Space Sampling and Exploration Robotics)
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Open AccessArticle
Rolling Mechanism of Launch Vehicle during the Prelaunch Phase in Sea Launch
by
Deng Wang, Wenhao Xiao, Jianshuai Shao, Mingjun Li, Yuanyang Zhao and Yi Jiang
Aerospace 2024, 11(5), 399; https://doi.org/10.3390/aerospace11050399 - 16 May 2024
Abstract
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During the sea launch of a launch vehicle in low sea state, a rolling phenomenon of the launch vehicle has been observed. In rough sea conditions, launch may failure. This study utilizes dimensionality reduction-driven spatial system projection methods and virtual prototype modeling technology
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During the sea launch of a launch vehicle in low sea state, a rolling phenomenon of the launch vehicle has been observed. In rough sea conditions, launch may failure. This study utilizes dimensionality reduction-driven spatial system projection methods and virtual prototype modeling technology to reveal that the launch vehicle’s rolling is caused by differences in the motion paths of the center of mass. Additionally, during the prelaunch stage, the variation in the trajectory of the launch vehicle’s center of mass caused by the rolling and pitching motions of the transportation vessel has a significant impact on the roll motion of the launch vehicle. The motion in other degrees of freedom has minimal influence on the launch vehicle’s rolling. The minimum rocket rolling occurs when the dynamic coefficient of friction of the launchpad–launch vehicle contact is 0.05, and the dynamic coefficient of friction of the adapters and guideways is 0.4. The conclusions provide a theoretical foundation for optimizing the sea launch system and enhancing the reliability of sea launch in rough sea conditions.
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Open AccessArticle
Accurate Satellite Operation Predictions Using Attention-BiLSTM Model with Telemetry Correlation
by
Yi Peng, Shuze Jia, Lizi Xie and Jian Shang
Aerospace 2024, 11(5), 398; https://doi.org/10.3390/aerospace11050398 - 15 May 2024
Abstract
In satellite health management, anomalies are mostly resolved after an event and are rarely predicted in advance. Thus, trend prediction is critical for avoiding satellite faults, which may affect the accuracy and quality of satellite data and even greatly impact safety. However, it
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In satellite health management, anomalies are mostly resolved after an event and are rarely predicted in advance. Thus, trend prediction is critical for avoiding satellite faults, which may affect the accuracy and quality of satellite data and even greatly impact safety. However, it is difficult to predict satellite operation using a simple model because satellite systems are complex and telemetry data are copious, coupled, and intermittent. Therefore, this study proposes a model that combines an attention mechanism and bidirectional long short-term memory (attention-BiLSTM) with telemetry correlation to predict satellite behaviour. First, a high-dimensional K-nearest neighbour mutual information method is used to select the related telemetry variables from multiple variables of satellite telemetry data. Next, we propose a new BiLSTM model with an attention mechanism for telemetry prediction. The dataset used in this study was generated and transmitted from the FY3E meteorological satellite power system. The proposed method was compared with other methods using the same dataset used in the experiment to verify its superiority. The results confirmed that the proposed method outperformed the other methods owing to its prediction precision and superior accuracy, indicating its potential for application in intelligent satellite health management systems.
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Open AccessArticle
Investigation of High-Speed Rubbing Behavior of GH4169 Superalloy with SiC/SiC Composites
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Zhaoguo Mi, Kanghe Jiang, Yicheng Yang, Zhenhua Cheng, Weihua Yang and Zhigang Sun
Aerospace 2024, 11(5), 397; https://doi.org/10.3390/aerospace11050397 - 15 May 2024
Abstract
The silicon carbide fiber-reinforced silicon carbide matrix (SiC/SiC), ceramic matrix composite (CMC) and nickel-based superalloy GH4169 can be utilized in high-temperature applications due to their high-temperature performance. The SiC/SiC composites are commonly used in turbine outer rings, where they encounter friction and wear
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The silicon carbide fiber-reinforced silicon carbide matrix (SiC/SiC), ceramic matrix composite (CMC) and nickel-based superalloy GH4169 can be utilized in high-temperature applications due to their high-temperature performance. The SiC/SiC composites are commonly used in turbine outer rings, where they encounter friction and wear against the turbine blades. This high-speed rubbing occurs frequently in aircraft engines and steam turbines. To investigate the tribological behavior of these materials, rubbing experiments were conducted between the SiC/SiC and the GH4169 superalloy. The experiments involved varying the blade tip speeds ranging from 100 m/s to 350 m/s and incursion rates from 5 μm/s to 50 μm/s at room temperature. Additionally, experiments were conducted at high temperatures to compare the tribological behavior under ambient conditions. The results indicated that the GH4169 superalloy exhibited abrasive furrow wear during rubbing at both room temperature and high temperature. Furthermore, at elevated temperatures, some of the GH4169 superalloy adhered to the surface of the SiC/SiC. The analysis of the experiments conducted at ambient temperatures revealed that the friction coefficient increased with higher blade tip velocities (100~350 m/s). However, the coefficient was lower at high temperatures compared to room temperature. Furthermore, significant temperature increases were observed during rubbing at room temperature, whereas minimal temperature changes were detected on the rubbing surface at high temperatures.
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Open AccessArticle
A High Step-Down SiC-Based T-Type LLC Resonant Converter for Spacecraft Power Processing Unit
by
Wenjie Ma and Hui Li
Aerospace 2024, 11(5), 396; https://doi.org/10.3390/aerospace11050396 - 15 May 2024
Abstract
A spacecraft power processing unit (PPU) is utilized to convert power from solar arrays or electric batteries to the payload, including electric propulsion, communication equipment, and scientific instruments. Currently, a high-voltage converter is widely applied to the spacecraft PPU to improve power density
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A spacecraft power processing unit (PPU) is utilized to convert power from solar arrays or electric batteries to the payload, including electric propulsion, communication equipment, and scientific instruments. Currently, a high-voltage converter is widely applied to the spacecraft PPU to improve power density and save launch weight. However, the high voltage level poses challenges such as high step-down ratios and high power losses. To achieve less conduction loss, a SiC-based T-type three-level (TL) resonant converter is proposed. To further broaden the gain range and achieve high step-down ratios, a variable frequency and adjustable phase-shift (VFAPS) modulation scheme is proposed. Meanwhile, the steady-state time-domain model is established to elaborate the operation principles and boundary conditions for soft switching. Furthermore, the optimal resonant element design considerations have been elaborated to achieve wider gain range and facilitate easier soft switching. Furthermore, the numerical solutions for switching frequency and phase shift (PS) angle under each specific input could be figured out. Finally, the effectiveness of this theoretical analysis is demonstrated via a 500-W experimental prototype with 650∼950-V input and constant output of 48-V/11-A.
Full article
(This article belongs to the Special Issue Advanced Chemical Propulsion and Electric Propulsion)
Open AccessArticle
Beyond Static Obstacles: Integrating Kalman Filter with Reinforcement Learning for Drone Navigation
by
Francesco Marino and Giorgio Guglieri
Aerospace 2024, 11(5), 395; https://doi.org/10.3390/aerospace11050395 - 15 May 2024
Abstract
Autonomous drones offer immense potential in dynamic environments, but their navigation systems often struggle with moving obstacles. This paper presents a novel approach for drone trajectory planning in such scenarios, combining the Interactive Multiple Model (IMM) Kalman filter with Proximal Policy Optimization (PPO)
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Autonomous drones offer immense potential in dynamic environments, but their navigation systems often struggle with moving obstacles. This paper presents a novel approach for drone trajectory planning in such scenarios, combining the Interactive Multiple Model (IMM) Kalman filter with Proximal Policy Optimization (PPO) reinforcement learning (RL). The IMM Kalman filter addresses state estimation challenges by modeling the potential motion patterns of moving objects. This enables accurate prediction of future object positions, even in uncertain environments. The PPO reinforcement learning algorithm then leverages these predictions to optimize the drone’s real-time trajectory. Additionally, the capability of PPO to work with continuous action spaces makes it ideal for the smooth control adjustments required for safe navigation. Our simulation results demonstrate the effectiveness of this combined approach. The drone successfully navigates complex dynamic environments, achieving collision avoidance and goal-oriented behavior. This work highlights the potential of integrating advanced state estimation and reinforcement learning techniques to enhance autonomous drone capabilities in unpredictable settings.
Full article
(This article belongs to the Special Issue Aerodynamics, Flight Dynamics and Control of Advanced Air Mobility Vehicles)
Open AccessArticle
Improved A* Algorithm for Path Planning Based on CubeSats In-Orbit Electromagnetic Transfer System
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Duo Xu, Honghao Yue, Yong Zhao, Fei Yang, Jun Wu, Xueting Pan, Tao Tang and Yuhao Zhang
Aerospace 2024, 11(5), 394; https://doi.org/10.3390/aerospace11050394 - 15 May 2024
Abstract
For future large-scale CubeSat applications in orbit, the deployer must accommodate a greater number of CubeSats and facilitate cluster releases. This paper introduces an improved A* algorithm tailored for CubeSat in-orbit transfer path planning. Unlike the traditional A* algorithm, this enhanced version incorporates
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For future large-scale CubeSat applications in orbit, the deployer must accommodate a greater number of CubeSats and facilitate cluster releases. This paper introduces an improved A* algorithm tailored for CubeSat in-orbit transfer path planning. Unlike the traditional A* algorithm, this enhanced version incorporates a path coordination strategy to manage congestion caused by the simultaneous transfer of many CubeSats, ensuring they reach their designated release positions smoothly and thus significantly boosting the efficiency of CubeSat transfers. Additionally, the algorithm develops a cost model for attitude disturbances on the electromagnetic conveying platform and crafts an improved cost function. It strategically balances the reduction in attitude disturbances caused by CubeSat transfers with the efficiency of these transfers. The primary goal is to minimize platform disturbances while optimizing the number of steps CubeSats need to reach their intended positions. The effectiveness of this algorithm is demonstrated through detailed case studies, which confirm that during the CubeSat transfer process, the platform’s attitude remains stable, and the transfer efficiency is well-managed, achieving efficient path planning for the in-orbit transfer of numerous CubeSats.
Full article
(This article belongs to the Topic Techniques and Science Exploitations for Earth Observation and Planetary Exploration)
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Open AccessArticle
An Anomaly Detection Method for UAV Based on Wavelet Decomposition and Stacked Denoising Autoencoder
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Shenghan Zhou, Zhao He, Xu Chen and Wenbing Chang
Aerospace 2024, 11(5), 393; https://doi.org/10.3390/aerospace11050393 - 14 May 2024
Abstract
The paper proposes an anomaly detection method for UAVs based on wavelet decomposition and stacked denoising autoencoder. This method takes the negative impact of noisy data and the feature extraction capabilities of deep learning models into account. It aims to improve the accuracy
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The paper proposes an anomaly detection method for UAVs based on wavelet decomposition and stacked denoising autoencoder. This method takes the negative impact of noisy data and the feature extraction capabilities of deep learning models into account. It aims to improve the accuracy of the proposed anomaly detection method with wavelet decomposition and stacked denoising autoencoder methods. Anomaly detection based on UAV flight data is an important method of UAV condition monitoring and potential abnormal state mining, which is an important means to reduce the risk of UAV flight accidents. However, the diversity of UAV mission scenarios leads to a complex and harsh environment, so the acquired data are affected by noise, which brings challenges to accurate anomaly detection based on UAV data. Firstly, we use wavelet decomposition to denoise the original data; then, we used the stacked denoising autoencoder to achieve feature extraction. Finally, the softmax classifier is used to realize the anomaly detection of UAV. The experimental results demonstrate that the proposed method still has good performance in the case of noisy data. Specifically, the Accuracy reaches 97.53%, the Precision is 97.50%, the Recall is 91.81%, and the F1-score is 94.57%. Furthermore, the proposed method outperforms the four comparison models with more outstanding performance. Therefore, it has significant potential in reducing UAV flight accidents and enhancing operational safety.
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(This article belongs to the Special Issue Computing Methods for Aerospace Reliability Engineering)
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Open AccessArticle
Enhancing Small Object Detection in Aerial Images: A Novel Approach with PCSG Model
by
Kang An, Huiping Duanmu, Zhiyang Wu, Yuqiang Liu, Jingzhen Qiao, Qianqian Shangguan, Yaqing Song and Xiaonong Xu
Aerospace 2024, 11(5), 392; https://doi.org/10.3390/aerospace11050392 - 14 May 2024
Abstract
Generalized target detection algorithms perform well for large- and medium-sized targets but struggle with small ones. However, with the growing importance of aerial images in urban transportation and environmental monitoring, detecting small targets in such imagery has been a promising research hotspot. The
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Generalized target detection algorithms perform well for large- and medium-sized targets but struggle with small ones. However, with the growing importance of aerial images in urban transportation and environmental monitoring, detecting small targets in such imagery has been a promising research hotspot. The challenge in small object detection lies in the limited pixel proportion and the complexity of feature extraction. Moreover, current mainstream detection algorithms tend to be overly complex, leading to structural redundancy for small objects. To cope with these challenges, this paper recommends the PCSG model based on yolov5, which optimizes both the detection head and backbone networks. (1) An enhanced detection header is introduced, featuring a new structure that enhances the feature pyramid network and the path aggregation network. This enhancement bolsters the model’s shallow feature reuse capability and introduces a dedicated detection layer for smaller objects. Additionally, redundant structures in the network are pruned, and the lightweight and versatile upsampling operator CARAFE is used to optimize the upsampling algorithm. (2) The paper proposes the module named SPD-Conv to replace the strided convolution operation and pooling structures in yolov5, thereby enhancing the backbone’s feature extraction capability. Furthermore, Ghost convolution is utilized to optimize the parameter count, ensuring that the backbone meets the real-time needs of aerial image detection. The experimental results from the RSOD dataset show that the PCSG model exhibits superior detection performance. The value of mAP increases from 97.1% to 97.8%, while the number of model parameters decreases by 22.3%, from 1,761,871 to 1,368,823. These findings unequivocally highlight the effectiveness of this approach.
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Open AccessArticle
ARCnet: A Multi-Feature-Based Auto Radio Check Model
by
Weijun Pan, Yidi Wang, Yumei Zhang and Boyuan Han
Aerospace 2024, 11(5), 391; https://doi.org/10.3390/aerospace11050391 (registering DOI) - 14 May 2024
Abstract
Radio checks serve as the foundation for ground-to-air communication. To integrate machine learning for automated and reliable radio checks, this study introduces an Auto Radio Check network (ARCnet), a novel algorithm for non-intrusive speech quality assessment in civil aviation, addressing the crucial need
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Radio checks serve as the foundation for ground-to-air communication. To integrate machine learning for automated and reliable radio checks, this study introduces an Auto Radio Check network (ARCnet), a novel algorithm for non-intrusive speech quality assessment in civil aviation, addressing the crucial need for dependable ground-to-air communication. By employing a multi-scale feature fusion approach, including the consideration of audio’s frequency domain, comprehensibility, and temporal information within the radio check scoring network, ARCnet integrates manually designed features with self-supervised features and utilizes a transformer network to enhance speech segment analysis. Utilizing the NISQA open-source dataset and the proprietary RadioCheckSpeech dataset, ARCnet demonstrates superior performance in predicting speech quality, showing a 12% improvement in both the Pearson correlation coefficient and root mean square error (RMSE) compared to existing models. This research not only highlights the significance of applying multi-scale attributes and deep neural network parameters in speech quality assessment but also emphasizes the crucial role of the temporal network in capturing the nuances of voice data. Through a comprehensive comparison of the ARCnet approach to traditional methods, this study underscores its innovative contribution to enhancing communication efficiency and safety in civil aviation.
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(This article belongs to the Special Issue Space-Air-Ground-Integrated Communications in the New Era: Applications, Challenges, and Countermeasures)
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