Aerospace, Volume 11, Issue 5 (May 2024) – 86 articles

In the field of civil aviation, the nose landing gear is a critical component that is prone to damage during taxiing. With the advent of new technologies such as towing taxi-out and hub motors, the nose landing gear faces increasingly complex operational environments, thereby imposing higher performance demands. Ensuring the structural safety of the nose landing gear is fundamental for the successful application of these technologies. However, current research on aircraft nose landing gear under these new conditions is somewhat lacking, particularly in terms of reliable analysis models for real-world scenarios. This study focuses on a typical Class C aircraft, specifically the B-727 model, for which a finite element model of the nose landing gear is developed. Modal testing of the aircraft’s nose landing gear is conducted using the impact hammer method, and the results are compared with those from the simulations. The experimental data indicate that the error range for the first seven natural frequencies is between 0.23% and 9.27%, confirming the high accuracy of the developed landing gear model. Furthermore, with towing taxi-out as the primary scenario, a dynamic model of the aircraft towing system is established, and an analysis on the structural strength and topological optimization of the nose landing gear under various conditions, including high speeds and heavy loads, is performed. The results show that the developed model can effectively support the analysis and prediction of the mechanical behavior of the nose landing gear. Under high-speed, heavy-load conditions, the nose landing gear experiences significantly increased loads, with the maximum deformation primarily occurring at the lower section of the shock strut’s outer cylinder. However, no damage occurred. Additionally, under these conditions, an optimized structural design for the landing gear was identified, which, while ensuring structural strength, achieves a 22.32% reduction in the mass of the outer cylinder, also ensuring safety in towing taxi-out conditions. Full article

The positioning of civil aviation aircraft relative to a geographic reference point on Earth in a Cartesian frame is significant to detect the deviations from the desired path, especially for high-altitude airports or special airports based on performance-based navigation (PBN). To obtain these critical deviations during aircraft approach and landing, it is fundamental to estimate the continuous flight variables and discrete flight modes simultaneously with enough accuracy. With the coordinate conversion between the North, East, and Down (NED) frame and the geographic coordinate system based on World Geodetic System 1984 (WGS-84) considered, this study proposed a non-linear stochastic hybrid estimation algorithm with adaptive square-root unscented particle filtering (ASR-UPF) to estimate the true path. The probabilities of mode transition, represented by the normal cumulative density function of continuous states, determine whether to proceed with mode transitions. In addition, the adaptive update characterized by tracking variable noise and the importance sampling distributions based on the results of square-root unscented Kalman filtering (SR-UKF), as a comparative study of continuous system filtering, were used. The experiments illustrated the ASR-UPF is able to reduce the state estimation error more effectively, and more promptly track the error caused by incorrect mode estimation with adaptability compared to the SR-UKF. A further test with real flight data indicates that the proposed method gives the refined estimation of position and azimuth in NED frame. Full article

Reynolds-averaged Navier–Stokes simulations are performed for supersonic turbulent flow over a cylinder/flare with upstream surface distortion representative of structural deformation induced via fluid–structural and fluid–thermal–structural behavior. Broad parametric analysis is carried out through the generation of Kriging-response surfaces from a database of general simulations. A posteriori simulations are then carried out at parametric combinations that correspond to extrema in the Kriging response surfaces to gain deeper insights into the interaction between the surface distortion and flow responses. Upstream distortions tend to decrease, rather than increase, the peak pressure and heat flux loads on the flare compared to an undeformed cylinder. Furthermore, decreases in these quantities reach up to O(10%) compared to up to O(1%) for increases. Integrated quantities over the flare are relatively insensitive to upstream distortion. The corner separation length is the most sensitive quantity to upstream distortion, with protrusions tending to increase the separation length and recessions reducing the separation length. Modifications in the separation length of up to 40% are observed. Reductions in peak loads tend to correspond to increases in the corner separation length. The movement of the surface distortion relative to the corner indicates a negligible impact beyond 1.5 distortion lengths from the corner, and the largest impact on the corner separation length occurs when distortion is directly adjacent. These results are an important step toward understanding and quantifying the impact of surface deformations on downstream components. Full article

The Chinese space station is a complex structure with large flexible appendages. Obtaining the on-orbit response characteristics of such a structure under different working conditions is a traditional and classic challenge in the field of dynamics. To address the on-orbit dynamics of the China Space Station, the basic equations for dynamic reduction, assembly and data recovery of linear and nonlinear substructures are derived based on the reduction and recovery theory, and a fast coupling analysis framework for flexible systems with nonlinear attachments is formed. This coupling analysis framework is adopted to quickly acquire the dynamic response of the China Space Station during in-orbit operation, thereby guiding the design. Taking SZ-15 radial docking to the Chinese Space Station as the object, the substructure of six nonlinear flexible arrays is reduced, the full flexible dynamic equation of the space station is assembled, and the response of each part of the flexible wing during the docking process is analyzed and recovered. By designing a reasonable and reliable flexible wing test scheme in-orbit, the acceleration at the root and top of the flexible wing during the docking of SZ-15 is obtained. The measured data in-orbit show that the acceleration analysis results of the typical parts of the flexible wing have a good agreement, which verifies the correctness of the fast coupling analysis framework of the flexible system. Hence, the dynamic coupling characteristics analysis of the main structure of the space station and the flexible wing based on this method can better guide the rationality of the design of the dynamic characteristics of the Chinese Space Station. Full article

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

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

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

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. Full article

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 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. Full article

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

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

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

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. Full article

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. Full article

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. Full article

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. Full article

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. Full article

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) $LLC$ 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

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

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

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. Full article

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. Full article

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. Full article

In the present study, a novel end-to-end automatic speech recognition (ASR) framework, namely, ResNeXt-Mssm-CTC, has been developed for air traffic control (ATC) systems. This framework is built upon the Multi-Head State-Space Model (Mssm) and incorporates transfer learning techniques. Residual Networks with Cardinality (ResNeXt) employ multi-layered convolutions with residual connections to augment the extraction of intricate feature representations from speech signals. The Mssm is endowed with specialized gating mechanisms, which incorporate parallel heads that acquire knowledge of both local and global temporal dynamics in sequence data. Connectionist temporal classification (CTC) is utilized in the context of sequence labeling, eliminating the requirement for forced alignment and accommodating labels of varying lengths. Moreover, the utilization of transfer learning has been shown to improve performance on the target task by leveraging knowledge acquired from a source task. The experimental results indicate that the model proposed in this study exhibits superior performance compared to other baseline models. Specifically, when pretrained on the Aishell corpus, the model achieves a minimum character error rate (CER) of 7.2% and 8.3%. Furthermore, when applied to the ATC corpus, the CER is reduced to 5.5% and 6.7%. Full article

The compressor serves as a crucial component that influences the performance of the gas turbine engine. Researchers have been endeavoring to explore compressor types that possess a high loading level and high-efficiency characteristics concurrently. In this study, tandem blade technology was applied to a transonic ultra-highly loaded axial compressor, and the Baseline single-blade rotor was replaced by a tandem rotor to take into account the loading level and compressor performance. Detailed investigations were carried out to identify the effects on the aerodynamic performance of the ultra-highly loaded stage and the fundamental flow mechanism within the tandem-rotor stage. This paper presents original design maps for the tandem-rotor stage, and the selection criteria for tandem parameters in tandem-rotor stage are refined. The results indicate that the peak efficiency improved by 0.83%, the stall margin increased by 2.16%, and the choke flow rate rose by 0.30% for the optimal tandem-rotor configuration. The meridional division position of the rotor primarily affects the ratio of loading of the front and rear blades, while the circumferential relative position of the tandem rotor mainly influences the channel types formed by the front and rear blades. Larger values for the meridional division position parameter and smaller values for circumferential relative position parameter should be selected for the tandem rotor design to optimize both the isentropic efficiency and total pressure ratio. This investigation offers the theoretical foundation for the design of a transonic ultra-highly loaded tandem-rotor compressor. Full article

The ablation impulse of typical asteroid simulants irradiated by a nanosecond pulsed laser has been investigated in a vacuum environment. A torsional pendulum measurement system was constructed to calculate the impulse of laser ablation. A 10 ns pulsed laser was used, with a 1064 nm wavelength, a 900 mJ maximum pulse energy, and a millimeter-scale ablation spot diameter. Impulsive coupling characteristics of six typical targets that imitate the substance of asteroids with various laser fluences were analyzed. Furthermore, the impulse coupling coefficient curves of different materials were fitted. The results reveal that the minimum laser fluence corresponding to a measurable ablation impulse is approximately 2.5 J/cm², and the optimum laser fluence corresponding to the maximum impulse coupling coefficient is approximately 14.0 J/cm². The trends of the laser ablation impulse coupling curves are roughly consistent for the six materials. Impulse coupling characteristics of the six typical materials can be represented by the same polynomial within a 95% confidence interval, so a unified rule has been given. In actual deflection tasks of asteroids, the unified impulse coupling characteristic can be used to implement laser deflection techniques, especially when the material of the asteroid cannot be accurately judged in time. Full article

This paper presents a summary of and introduction to research on high-altitude and subatmospheric combustion concerning turbine and scramjet engines. The investigation includes theoretical analysis, experimental studies, and numerical simulations. The analysis encompasses the flow field structure, fuel atomization, and combustion performance. Subsequently, recent research on the combustion performance of liquid fuels, solid fuels, and gaseous fuels under high-altitude and low-pressure plateau environments is reviewed. This includes an evaluation of flame height, flame temperature, combustion rate, fire spread rate, and heat radiation flux. Additionally, combustion performance prediction models for high-altitude environments based on experimental and theoretical analysis have been introduced. Lastly, issues in subatmospheric combustion in the aerospace and plateau fire fields are presented based on the current research. Full article

Satellite computing represents a recent computational paradigm in the development of low Earth orbit (LEO) satellites. It aims to augment the capabilities of LEO satellites beyond their current transparent relay functions by enabling real-time processing, thereby providing low-latency computational services to end users. In LEO constellations, a significant deployment of computationally capable satellites is orchestrated to offer enhanced computational resources. Challenges arise in the optimal allocation of terminal services to the most suitable satellite due to overlapping coverage among neighboring satellites, compounded by constraints on satellite energy and computational resources. The satellite service allocation (SSA) problem is recognized as NP-hard, yet assessing allocation methods through results allows for the application of deep reinforcement learning (DRL) to obtain improved solutions, partially addressing the SSA challenge. In this paper, we introduce a satellite computing capability model to quantify satellite computational resources. A DRL model is proposed to address service demands, computational resources, and resolve service allocation conflicts, strategically placing each service on appropriate servers. Through simulation experiments, numerical results demonstrate the superiority of our proposed method over baseline approaches in service allocation and satellite resource utilization, showcasing advancements in this field. Full article

In the present study, a passive flow device is considered for drag reduction purposes through implementation in a transonic high-power rocket. The high-power rocket serves as a reference platform that, apart from the operating conditions, enforces several constraints in terms of available volume and placement locations. A step-by-step methodology is suggested, where the unit is initially broken down into an inlet and an outlet component. The flow field is investigated by means of computational modeling (CFD), where the Reynolds-averaged Navier–Stokes equations are solved coupled with turbulence models that vary depending on the design phase and the individual component. In the first design phase, the best alternative configuration is selected for each component by comparing mass flow rates and discharge coefficients. In the second design phase, each component is analyzed in greater detail based on the first phase results. Indicatively, the protruding inlet diffuser-type channel is converted into a protruding inlet nozzle-type channel to avoid choked flow phenomena, and a nozzle geometry is selected as the outlet amongst the other considered scenarios. The two components are eventually integrated into a common base bleed unit and a final assessment is made. The computational results are used to predict the performance and trajectory of the rocket through a well-established trajectory software. The overall methodology is validated against full-scale test flight data. The results show that the base bleed unit developed in the framework of this study yields a drag reduction of approximately 15% at transonic speeds without impacting the rocket mass and stability. Full article