Aerospace最新文献_第10页

Stealth Aircraft Penetration Trajectory Planning in 3D Complex Dynamic Based on Radar Valley Radius and Turning Maneuver 基于雷达波谷半径和转弯操纵的隐形飞机三维复杂动态穿透轨迹规划

IF 2.6 3区工程技术

Aerospace Pub Date : 2024-05-16 DOI: 10.3390/aerospace11050402

Xiaoqiang Lu, Jun Huang, Jingxin Guan, Lei Song

{"title":"Stealth Aircraft Penetration Trajectory Planning in 3D Complex Dynamic Based on Radar Valley Radius and Turning Maneuver","authors":"Xiaoqiang Lu, Jun Huang, Jingxin Guan, Lei Song","doi":"10.3390/aerospace11050402","DOIUrl":"https://doi.org/10.3390/aerospace11050402","url":null,"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 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.","PeriodicalId":48525,"journal":{"name":"Aerospace","volume":null,"pages":null},"PeriodicalIF":2.6,"publicationDate":"2024-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140970447","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Accurate Satellite Operation Predictions Using Attention-BiLSTM Model with Telemetry Correlation 利用具有遥测相关性的注意力-BiLSTM 模型准确预测卫星运行情况

IF 2.6 3区工程技术

Aerospace Pub Date : 2024-05-15 DOI: 10.3390/aerospace11050398

Yi Peng, ShuZe Jia, Lizi Xie, Jian Shang

{"title":"Accurate Satellite Operation Predictions Using Attention-BiLSTM Model with Telemetry Correlation","authors":"Yi Peng, ShuZe Jia, Lizi Xie, Jian Shang","doi":"10.3390/aerospace11050398","DOIUrl":"https://doi.org/10.3390/aerospace11050398","url":null,"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 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.","PeriodicalId":48525,"journal":{"name":"Aerospace","volume":null,"pages":null},"PeriodicalIF":2.6,"publicationDate":"2024-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140975665","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Beyond Static Obstacles: Integrating Kalman Filter with Reinforcement Learning for Drone Navigation 超越静态障碍：将卡尔曼滤波器与强化学习整合用于无人机导航

IF 2.6 3区工程技术

Aerospace Pub Date : 2024-05-15 DOI: 10.3390/aerospace11050395

Francesco Marino, Giorgio Guglieri

{"title":"Beyond Static Obstacles: Integrating Kalman Filter with Reinforcement Learning for Drone Navigation","authors":"Francesco Marino, Giorgio Guglieri","doi":"10.3390/aerospace11050395","DOIUrl":"https://doi.org/10.3390/aerospace11050395","url":null,"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) 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.","PeriodicalId":48525,"journal":{"name":"Aerospace","volume":null,"pages":null},"PeriodicalIF":2.6,"publicationDate":"2024-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140976236","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Investigation of High-Speed Rubbing Behavior of GH4169 Superalloy with SiC/SiC Composites 用碳化硅/碳化硅复合材料研究 GH4169 超合金的高速摩擦行为

IF 2.6 3区工程技术

Aerospace Pub Date : 2024-05-15 DOI: 10.3390/aerospace11050397

Zhaoguo Mi, Kanghe Jiang, Yicheng Yang, Zhenhua Cheng, Weihua Yang, Zhigang Sun

{"title":"Investigation of High-Speed Rubbing Behavior of GH4169 Superalloy with SiC/SiC Composites","authors":"Zhaoguo Mi, Kanghe Jiang, Yicheng Yang, Zhenhua Cheng, Weihua Yang, Zhigang Sun","doi":"10.3390/aerospace11050397","DOIUrl":"https://doi.org/10.3390/aerospace11050397","url":null,"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 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.","PeriodicalId":48525,"journal":{"name":"Aerospace","volume":null,"pages":null},"PeriodicalIF":2.6,"publicationDate":"2024-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140975459","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A High Step-Down SiC-Based T-Type LLC Resonant Converter for Spacecraft Power Processing Unit 用于航天器动力处理单元的基于碳化硅的高降压 T 型 LLC 谐振转换器

IF 2.6 3区工程技术

Aerospace Pub Date : 2024-05-15 DOI: 10.3390/aerospace11050396

Wenjie Ma, Hui Li

{"title":"A High Step-Down SiC-Based T-Type LLC Resonant Converter for Spacecraft Power Processing Unit","authors":"Wenjie Ma, Hui Li","doi":"10.3390/aerospace11050396","DOIUrl":"https://doi.org/10.3390/aerospace11050396","url":null,"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 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.","PeriodicalId":48525,"journal":{"name":"Aerospace","volume":null,"pages":null},"PeriodicalIF":2.6,"publicationDate":"2024-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140973534","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Improved A* Algorithm for Path Planning Based on CubeSats In-Orbit Electromagnetic Transfer System 基于立方体卫星在轨电磁传输系统的改进型 A* 路径规划算法

IF 2.6 3区工程技术

Aerospace Pub Date : 2024-05-15 DOI: 10.3390/aerospace11050394

Duo Xu, Honghao Yue, Yong Zhao, Fei Yang, Jun Wu, Xueting Pan, Tao Tang, Yuhao Zhang

{"title":"Improved A* Algorithm for Path Planning Based on CubeSats In-Orbit Electromagnetic Transfer System","authors":"Duo Xu, Honghao Yue, Yong Zhao, Fei Yang, Jun Wu, Xueting Pan, Tao Tang, Yuhao Zhang","doi":"10.3390/aerospace11050394","DOIUrl":"https://doi.org/10.3390/aerospace11050394","url":null,"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 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.","PeriodicalId":48525,"journal":{"name":"Aerospace","volume":null,"pages":null},"PeriodicalIF":2.6,"publicationDate":"2024-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140973787","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Enhancing Small Object Detection in Aerial Images: A Novel Approach with PCSG Model 增强航空图像中的小物体检测：利用 PCSG 模型的新方法

IF 2.6 3区工程技术

Aerospace Pub Date : 2024-05-14 DOI: 10.3390/aerospace11050392

Kang An, Huiping Duanmu, Zhiyang Wu, Yuqiang Liu, Jingzhen Qiao, Qianqian Shangguan, Yaqing Song, Xiaonong Xu

{"title":"Enhancing Small Object Detection in Aerial Images: A Novel Approach with PCSG Model","authors":"Kang An, Huiping Duanmu, Zhiyang Wu, Yuqiang Liu, Jingzhen Qiao, Qianqian Shangguan, Yaqing Song, Xiaonong Xu","doi":"10.3390/aerospace11050392","DOIUrl":"https://doi.org/10.3390/aerospace11050392","url":null,"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 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.","PeriodicalId":48525,"journal":{"name":"Aerospace","volume":null,"pages":null},"PeriodicalIF":2.6,"publicationDate":"2024-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140979965","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

ARCnet: A Multi-Feature-Based Auto Radio Check Model ARCnet：基于多种特征的自动无线电检查模型

IF 2.6 3区工程技术

Aerospace Pub Date : 2024-05-14 DOI: 10.3390/aerospace11050391

Weijun Pan, Yidi Wang, Yumei Zhang, Boyuan Han

{"title":"ARCnet: A Multi-Feature-Based Auto Radio Check Model","authors":"Weijun Pan, Yidi Wang, Yumei Zhang, Boyuan Han","doi":"10.3390/aerospace11050391","DOIUrl":"https://doi.org/10.3390/aerospace11050391","url":null,"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 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.","PeriodicalId":48525,"journal":{"name":"Aerospace","volume":null,"pages":null},"PeriodicalIF":2.6,"publicationDate":"2024-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140980185","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

An Anomaly Detection Method for UAV Based on Wavelet Decomposition and Stacked Denoising Autoencoder 基于小波分解和堆叠去噪自动编码器的无人飞行器异常检测方法

IF 2.6 3区工程技术

Aerospace Pub Date : 2024-05-14 DOI: 10.3390/aerospace11050393

Shenghan Zhou, Zhao He, Xu Chen, Wenbing Chang

{"title":"An Anomaly Detection Method for UAV Based on Wavelet Decomposition and Stacked Denoising Autoencoder","authors":"Shenghan Zhou, Zhao He, Xu Chen, Wenbing Chang","doi":"10.3390/aerospace11050393","DOIUrl":"https://doi.org/10.3390/aerospace11050393","url":null,"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 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.","PeriodicalId":48525,"journal":{"name":"Aerospace","volume":null,"pages":null},"PeriodicalIF":2.6,"publicationDate":"2024-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140979892","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Speech Recognition for Air Traffic Control Utilizing a Multi-Head State-Space Model and Transfer Learning 利用多头状态空间模型和迁移学习进行空中交通管制语音识别

IF 2.6 3区工程技术

Aerospace Pub Date : 2024-05-14 DOI: 10.3390/aerospace11050390

Haijun Liang, Hanwen Chang, Jianguo Kong

{"title":"Speech Recognition for Air Traffic Control Utilizing a Multi-Head State-Space Model and Transfer Learning","authors":"Haijun Liang, Hanwen Chang, Jianguo Kong","doi":"10.3390/aerospace11050390","DOIUrl":"https://doi.org/10.3390/aerospace11050390","url":null,"abstract":"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%.","PeriodicalId":48525,"journal":{"name":"Aerospace","volume":null,"pages":null},"PeriodicalIF":2.6,"publicationDate":"2024-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140980756","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0