The safety and reliability of space connection and separation device has become a key issue due to the increasing service span of deep space exploration mission.The long-term preload relaxation(a key failure mode)of c...The safety and reliability of space connection and separation device has become a key issue due to the increasing service span of deep space exploration mission.The long-term preload relaxation(a key failure mode)of connection and separation devices is focused in this paper.A series of tests have been designed and implemented to investigate the preload relaxation regulation and a comprehensive method has been constructed to analyze and predict the reliable lifetime of the device.The two-stage preload relaxation law of the device is found and reasonably considered.Due to the different relaxation mechanism,the first-stage preload relaxation is assessed based on the working-condition test results,and the second-stage preload relaxation is characterized by accelerated test results.Finally,the service reliability and reliable life are evaluated.The experiment and assessment results demonstrate the reasonability and effectiveness of the proposed method which can achieve long-service reliability analysis for space connection and separation device within limited time.展开更多
A 3D finite element （FE） model for the Sutong cable-stayed bridge （SCB） is established based on ANSYS. The dynamic characteristics of the bridge are analyzed using a subspace iteration method. Based on recorded wi...A 3D finite element （FE） model for the Sutong cable-stayed bridge （SCB） is established based on ANSYS. The dynamic characteristics of the bridge are analyzed using a subspace iteration method. Based on recorded wind data, the measured spectra expression is presented using the nonlinear least-squares regression method. Turbulent winds at the bridge site are simulated based on the spectral representation method and the FFT technique. The influence of some key structural parameters and measures on the dynamic characteristics of the bridge are investigated. These parameters include dead load intensity, as well as vertical, lateral and torsional stiffness of the steel box girder. In addition, the influence of elastic stiffness of the connection device employed between the towers and the girder on the vibration mode of the steel box girder is investigated. The analysis shows that all of the vertical, lateral and torsional buffeting displacement responses reduce gradually as the dead load intensity increases. The dynamic characteristics and the structural buffeting displacement response of the SCB are only slightly affected by the vertical and torsional stiffness of the steel box girder, and the lateral and torsional buffeting displacement responses reduce gradually as the lateral stiffness increases. These results provide a reference for dynamic analysis and design of super-long-span cable-stayed bridges.展开更多
With the growing demand for advanced services and the rapid increase in numbers of connected devices,the development of nextgeneration wireless communication technology is being driven by the unprecedented performance...With the growing demand for advanced services and the rapid increase in numbers of connected devices,the development of nextgeneration wireless communication technology is being driven by the unprecedented performance requirements anticipated for new scenarios foreseen in the 2030 era.1 A wide range of applications,such as industrial automation,vehicle-to-everything networks,smart grids,and remote surgery,will require highly stringent and versatile capabilities to satisfy user demands in terms of quality of service.展开更多
The convergence of the Metaverse and the Internet of Things(IoT)paves the way for extensive data interaction between connected devices and digital twins;however,this simultaneously introduces considerable cybersecurit...The convergence of the Metaverse and the Internet of Things(IoT)paves the way for extensive data interaction between connected devices and digital twins;however,this simultaneously introduces considerable cybersecurity threats,including data breaches,ransomware,and device tampering.Existing intrusion detection algorithms struggle to effectively defend against emerging cyberattacks in the rapidly evolving Metaverse environment.Designing effective neural networks for intrusion detection algorithms relies heavily on expert experience,making the manual process time-consuming and often yielding suboptimal results.This paper addresses a critical gap in cybersecurity for Metaverse devices,which are often overlooked in traditional detection methods,and proposes an adaptive multiobjective evolutionary generative adversarial network(AME-GAN)as a novel,scalable solution for optimizing network intrusion detection.An inversely proportional hybrid attention-based long short-term memory GAN is proposed,combining GANs to generate minority class samples and alleviate the imbalance problem in training datasets,which has long hindered accurate intrusion detection.Additionally,an adaptive evolutionary neural architecture search algorithm for the supernet of the GAN is designed to guide the mutation direction of the supernet,enhancing the training stability.This paper further introduces a double mutation multiobjective evolutionary neural architecture search algorithm,integrating both the multiobjective evolutionary algorithm and the neural architecture search to optimize accuracy,real-time performance,and model diversity—a crucial aspect for Metaverse devices with diverse hardware constraints.Experiments conducted on 3 well-known datasets—NSL-KDD,UNSW-NB15,and CIC-IDS2017—demonstrate that AME-GAN outperforms state-of-the-art approaches,with improvements of 0.32%in accuracy,0.31%in F1 score,0.47%in precision,and 0.37%in recall.This paper offers a promising,adaptive framework to enhance cybersecurity in the Metaverse,improving detection performance and real-time applicability,and contributing to the future of network intrusion detection in next-generation digital environments.展开更多
基金supported by the National Natural Science Foundation of China(No.11872085)。
文摘The safety and reliability of space connection and separation device has become a key issue due to the increasing service span of deep space exploration mission.The long-term preload relaxation(a key failure mode)of connection and separation devices is focused in this paper.A series of tests have been designed and implemented to investigate the preload relaxation regulation and a comprehensive method has been constructed to analyze and predict the reliable lifetime of the device.The two-stage preload relaxation law of the device is found and reasonably considered.Due to the different relaxation mechanism,the first-stage preload relaxation is assessed based on the working-condition test results,and the second-stage preload relaxation is characterized by accelerated test results.Finally,the service reliability and reliable life are evaluated.The experiment and assessment results demonstrate the reasonability and effectiveness of the proposed method which can achieve long-service reliability analysis for space connection and separation device within limited time.
基金The National Science Foundation of China under Grant No.51378111the Program for New Century Excellent Talents in University of Ministry of Education of China under Grant No.NCET-13-0128+2 种基金the Fok Ying-Tong Education Foundation for Young Teachersin the Higher Education Institutions of China under Grant No.142007the Fundamental Research Funds for the Central Universities under Grant No.2242012R30002the Open Fund of Jiangsu Key Laboratory of Environmental Impact and Structural Safety in Engineering under Grant No.JSKL2011YB02
文摘A 3D finite element （FE） model for the Sutong cable-stayed bridge （SCB） is established based on ANSYS. The dynamic characteristics of the bridge are analyzed using a subspace iteration method. Based on recorded wind data, the measured spectra expression is presented using the nonlinear least-squares regression method. Turbulent winds at the bridge site are simulated based on the spectral representation method and the FFT technique. The influence of some key structural parameters and measures on the dynamic characteristics of the bridge are investigated. These parameters include dead load intensity, as well as vertical, lateral and torsional stiffness of the steel box girder. In addition, the influence of elastic stiffness of the connection device employed between the towers and the girder on the vibration mode of the steel box girder is investigated. The analysis shows that all of the vertical, lateral and torsional buffeting displacement responses reduce gradually as the dead load intensity increases. The dynamic characteristics and the structural buffeting displacement response of the SCB are only slightly affected by the vertical and torsional stiffness of the steel box girder, and the lateral and torsional buffeting displacement responses reduce gradually as the lateral stiffness increases. These results provide a reference for dynamic analysis and design of super-long-span cable-stayed bridges.
文摘With the growing demand for advanced services and the rapid increase in numbers of connected devices,the development of nextgeneration wireless communication technology is being driven by the unprecedented performance requirements anticipated for new scenarios foreseen in the 2030 era.1 A wide range of applications,such as industrial automation,vehicle-to-everything networks,smart grids,and remote surgery,will require highly stringent and versatile capabilities to satisfy user demands in terms of quality of service.
基金supported by the National Key R&D Program of China under grant no.2023YFB4503000supported in part by the National Natural Science Foundation of China(NSFC)under grant no.62473129+3 种基金the Natural Science Fund of Hebei Province for Distinguished Young Scholars under grant no.F2021202010the Science and Technology Project of Hebei Education Department under grant no.JZX2023007the S&T Program of Hebei under grant no.225676163GHthe Interdisciplinary Postgraduate Training Program of Hebei University of Technology under grant no.HEBUT-Y-XKJC-2022116.
文摘The convergence of the Metaverse and the Internet of Things(IoT)paves the way for extensive data interaction between connected devices and digital twins;however,this simultaneously introduces considerable cybersecurity threats,including data breaches,ransomware,and device tampering.Existing intrusion detection algorithms struggle to effectively defend against emerging cyberattacks in the rapidly evolving Metaverse environment.Designing effective neural networks for intrusion detection algorithms relies heavily on expert experience,making the manual process time-consuming and often yielding suboptimal results.This paper addresses a critical gap in cybersecurity for Metaverse devices,which are often overlooked in traditional detection methods,and proposes an adaptive multiobjective evolutionary generative adversarial network(AME-GAN)as a novel,scalable solution for optimizing network intrusion detection.An inversely proportional hybrid attention-based long short-term memory GAN is proposed,combining GANs to generate minority class samples and alleviate the imbalance problem in training datasets,which has long hindered accurate intrusion detection.Additionally,an adaptive evolutionary neural architecture search algorithm for the supernet of the GAN is designed to guide the mutation direction of the supernet,enhancing the training stability.This paper further introduces a double mutation multiobjective evolutionary neural architecture search algorithm,integrating both the multiobjective evolutionary algorithm and the neural architecture search to optimize accuracy,real-time performance,and model diversity—a crucial aspect for Metaverse devices with diverse hardware constraints.Experiments conducted on 3 well-known datasets—NSL-KDD,UNSW-NB15,and CIC-IDS2017—demonstrate that AME-GAN outperforms state-of-the-art approaches,with improvements of 0.32%in accuracy,0.31%in F1 score,0.47%in precision,and 0.37%in recall.This paper offers a promising,adaptive framework to enhance cybersecurity in the Metaverse,improving detection performance and real-time applicability,and contributing to the future of network intrusion detection in next-generation digital environments.
