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Analytical model of vertical load acting on jacked pipe considering soil arching effect in cohesionless soil

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Underground space 2024年第1期14卷 263-284页

作者： Yu Zhang Lianjin Tao Xu Zhao Jun Liu Weizhang Liao Fei Guo Xiaohui Yang Ruiqin Zhong Beijing Advanced Innovation center for Future Urban Design Beijing University of Civil Engineering and ArchitectureBeijing 102627China The Key Laboratory of Urban security and Disaster Engineering Ministry of EducationBeijing University of TechnologyBeijing 100024China Beijing Municipal Construction Group Co. LtdBeijing 100045China Beijing Municipal Engineering Institute Beijing 100037China

For the project of pipe jacking in cohesionless soil,it is key to determine the vertical load on jacked pipe so as to predict the jacking force *** this paper,a new parabolic soil arching model was proposed to calculate the vertical load on jacked *** proposed analytical model was composed of parabolic soil arching zone,parabola-typed collapse zone and friction arch *** with existing literature,the key parameters(i.e.,height of parabolic soil arching,horizontal pressure coefficient and width and height of friction arch)were *** addition,considering that the trajectory of major stress is parabola,the formula of horizontal pressure coefficient was deduced in the friction *** parabolic soil arching zone is assumed as a three-hinged arch with reasonable arch axis,and the formula of load transfer was derived considering the transition effect of parabolic soil *** results of experiment,theoretical models and numerical model were adopted to verify the proposed analytical ***,the influence of the key parameters on the vertical load on jacked pipe were also discussed in *** work provides a meaningful reference for evaluating the vertical load on jacked pipe for design of pipe jacking.

关键词： Jacked pipe Soil arching effect Theoretical model Parabolic soil arching model Vertical load

A digital twins enabled underwater intelligent internet vehicle path planning system via reinforcement learning and edge computing

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Digital Communications and networks 2024年第2期10卷 282-291页

作者： Jiachen Yang Meng Xi Jiabao Wen Yang Li Houbing Herbert Song School of Electrical and Information Engineering Tianjin UniversityTianjin300072China security and Optimization for networked Globe Laboratory(SONG Lab) Embry-Riddle Aeronautical UniversityDaytona BeachFL32114USA

The Autonomous Underwater Glider(AUG)is a kind of prevailing underwater intelligent internet vehicle and occupies a dominant position in industrial applications,in which path planning is an essential *** to the complexity and variability of the ocean,accurate environment modeling and flexible path planning algorithms are pivotal *** traditional models mainly utilize mathematical functions,which are not complete and *** existing path planning algorithms depend on the environment and lack *** overcome these challenges,we propose a path planning system for underwater intelligent internet *** applies digital twins and sensor data to map the real ocean environment to a virtual digital space,which provides a comprehensive and reliable environment for path *** design a value-based reinforcement learning path planning algorithm and explore the optimal network structure *** path simulation is controlled by a closed-loop model integrated into the terminal vehicle through edge *** integration of state input enriches the learning of neural networks and helps to improve generalization and *** task-related reward function promotes the rapid convergence of the *** experimental results prove that our reinforcement learning based path planning algorithm has great flexibility and can effectively adapt to a variety of different ocean conditions.

关键词： Digital twins Reinforcement learning Edge computing Underwater intelligent internet vehicle Path planning

Steady-state Voltage security-constrained Optimal Frequency Control for Weak HVDC Sending-end AC Power Systems

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Journal of Modern Power Systems and Clean Energy 2024年第2期12卷 658-669页

作者： Qiangqiang Wang Liangzhong Yao Jian Xu Yuping Zheng Wei Li Wei Wang School of Electrical Engineering and Automation Wuhan UniversityWuhan 430072China Hubei Engineering and Technology Research center for AC/DC Intelligent Distribution network(Wuhan University) Wuhan 430072China State Key Laboratory of Smart Grid Protection and Control NARI Group Corporation(State Grid Electric Power Research Institute)Nanjing 211106China

Due to the fact that a high share of renewable energy sources(RESs)are connected to high-voltage direct current(HVDC)sending-end AC power systems,the voltage and frequency regulation capabilities of HVDC sending-end AC power systems have *** has resulted in potential system operating problems such as overvoltage and overfrequency,which occur simultaneously when block faults exist in the HVDC *** this study,a steady-state voltage security-constrained optimal frequency control method for weak HVDC sending-end AC power systems is *** integrated virtual inertia control of RESs is employed for system frequency *** dynamic reactive power compensation devices are utilized to control the voltage of all nodes meet voltage security ***,an optimization model that simultaneously considers the frequency and steady-state voltage security constraints for weak HVDC sending-end AC power systems is *** optimal control scheme with the minimum total cost of generation tripping and additional dynamic reactive power compensation required is obtained through the optimization *** are conducted on a modified IEEE 9-bus test system and practical Qing-Yu line commutated converter based HVDC(LCC-HVDC)sending-end AC power system to verify the effectiveness of the proposed method.

关键词： Renewable energy source(RES) high-voltage direct current(HVDC) AC power system optimal frequency control steady-state voltage security dynamic reactive power compensation

Spatial Distribution Feature Extraction network for Open Set Recognition of Electromagnetic Signal

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Computer Modeling in Engineering & Sciences 2024年第4期139卷 279-296页

作者： Hui Zhang Huaji Zhou Li Wang Feng Zhou The Ministry Key Laboratory of Electronic Information Countermeasure and Simulation Xidian UniversityXi’an710071China Science and Technology on Communication Information security Control Laboratory Jiaxing314033China

This paper proposes a novel open set recognition method,the Spatial Distribution Feature Extraction network(SDFEN),to address the problem of electromagnetic signal recognition in an open *** spatial distribution feature extraction layer in SDFEN replaces convolutional output neural networks with the spatial distribution features that focus more on inter-sample information by incorporating class center *** designed hybrid loss function considers both intra-class distance and inter-class distance,thereby enhancing the similarity among samples of the same class and increasing the dissimilarity between samples of different classes during ***,this method allows unknown classes to occupy a larger space in the feature *** reduces the possibility of overlap with known class samples and makes the boundaries between known and unknown samples more ***,the feature comparator threshold can be used to reject unknown *** signal open set recognition,seven methods,including the proposed method,are applied to two kinds of electromagnetic signal data:modulation signal and real-world *** experimental results demonstrate that the proposed method outperforms the other six methods overall in a simulated open ***,compared to the state-of-the-art Openmax method,the novel method achieves up to 8.87%and 5.25%higher micro-F-measures,respectively.

关键词： Electromagnetic signal recognition deep learning feature extraction open set recognition

Inelastic Scattering of Dark Matter with Heavy Cosmic Rays

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Research in Astronomy and Astrophysics 2024年第6期24卷 68-80页

作者： Keyu Lu Yue-Lin Sming Tsai Qiang Yuan Le Zhang School of Physics and Astronomy Sun Yat-sen UniversityZhuhai 519082China Key Laboratory of Dark Matter and space Astronomy Purple Mountain ObservatoryChinese Academy of SciencesNanjing 210023China School of Astronomy and space Science University of Science and Technology of ChinaHefei 230026China CSST Science center for the Guangdong-Hong Kong-Macao Greater Bay Area SYSUZhuhai 519082China Peng Cheng Laboratory Shenzhen 518000China

We investigate the impact of inelastic collisions between dark matter(DM)and heavy cosmic ray(CR)nuclei on CR *** approximate the fragmentation cross-sections for DM-CR collisions using collider-measured proton-nuclei scattering cross-sections,allowing us to assess how these collisions affect the spectra of CR boron and *** derive new CR spectra from DM-CR collisions by incorporating their cross-sections into the source terms and solving the diffusion equation for the complete network of reactions involved in generating secondary *** a specific example with a coupling strength of b_(χ)=0.1 and a DM mass of m_(χ)=0.1 GeV,considering a simplified scenario where DM interacts exclusively with oxygen,a notable modification in the boron-to-carbon spectrum due to the DM-CR interaction is ***,the peak within the spectrum,spanning from 0.1 to 10 GeV,experiences an enhancement of approximately 1.5 ***,in a more realistic scenario where DM particles interact with all CRs,this peak can be amplified to twice its original *** the latest data from AMS-02 and DAMPE on the boron-to-carbon ratio,we estimate a 95%upper limit for the effective inelastic cross-section of DM-proton as a function of DM *** findings reveal that at m_(χ)?2 MeV,the effective inelastic cross-section between DM and protons must be less than O(10^(-32))cm^(2).

关键词： elementary particles nuclear reactions nucleosynthesis abundances scattering astroparticle physics (cosmology:)dark matter

On m-ovoids of finite classical polar spaces with an irreducible transitive automorphism group

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Science China Mathematics 2024年第3期67卷 683-712页

作者： Tao Feng Weicong Li Ran Tao School of Mathematical Sciences Zhejiang UniversityHangzhou 310027China Department of Mathematics and National center for Applied Mathematics Shenzhen Southern University of Science and TechnologyShenzhen 518055China Key Laboratory of Cryptologic Technology and Information security Ministry of EducationShandong UniversityQingdao 266237China School of Cyber Science and Technology Shandong UniversityQingdao 266237China

In this paper, we classify the m-ovoids of finite classical polar spaces that admit a transitive automorphism group acting irreducibly on the ambient vector space. In particular, we obtain several new infinite familie... 详细信息

关键词： transitive m-ovoids irreducible action finite classical polar spaces primitive divisor

Salinity fronts shape spatial patterns in zooplankton distribution in Hangzhou Bay

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Acta Oceanologica Sinica 2024年第6期43卷 96-106页

作者： Yepeng Xu Yiqi Wang Lin Zhan Yijun Ou Kangning Jia Ming Mao Xuyu Zhu Zhibing Jiang Yuanli Zhu Wei Huang Ping Du Jiangning Zeng Lu Shou Feng Zhou Key Laboratory of Marine Ecosystem Dynamics Second Institute of OceanographyMinistry of Natural ResourcesHangzhou 310012China Key Laboratory of Nearshore Engineering Environment and Ecological security of Zhejiang Province Hangzhou 310012China State Key Laboratory of Satellite Ocean Environment Dynamics Ministry of Natural ResourcesHangzhou 310012China Nantong Marine Environmental Monitoring center Ministry of Natural ResourcesNantong 226002China Key Laboratory of Ocean space Resource Management Technology Ministry of Natural ResourcesHangzhou 310012China Observation and Research Station of Marine Ecosystem in the Yangtze River Delta Ministry of Natural ResourcesZhoushan 316021China

Ocean fronts play important roles in nutrient transport and in the shaping ecological *** zones in small bays are typically small in scale,have a complex structure,and they are spatially and temporally variable,but there are limited data on how biological communities respond to this *** Bay,a mediumsized estuary in China,is an ideal place in which to study the response of plankton to small-scale ocean fronts,because three water masses(Qiantang River Diluted Water,Changjiang River Diluted Water,and the East China Sea current) converge here and form dynamic salinity fronts throughout the *** investigate zooplankton communities,and temperature,salinity and chlorophyll a(Chl a) in Hangzhou Bay in June(wet perio d) and December(dry period) of 2022 and examine the dominant environmental factors that affect zooplankton community spatial *** then match the spatial distributions of zooplankton communities with those of salinity fronts.S alinity is the most important explanatory variable to affect zooplankton community spatial variability during both wet and dry periods,in that it contributes>60% of the variability in community ***,the spatial distributions of zooplankton match well with salinity *** December,with weaker Qiantang River Diluted Water and a stronger secondary Changjiang River Plume,zooplankton communities occur in moderate salinity(MS,salinity range 15.6±2.2) and high salinity(HS,22.4±1.7) regions,and their ecological boundaries closely match the Qiantang River Diluted Water *** June,different zooplankton communities occur in low salinity(LS,3.9±1.0),MS(11.7±3.6) and HS(21.3±1.9) *** the LS region occurs abnormally in the central bay rather than its apex because of the anomalous influence of rising and falling tides during the sampling perio d,the ecological boundaries still match salinity ***-salinity or brackish-water zooplankter taxa are relatively more abunda

关键词： zooplankton spatial distribution salinity fronts Hangzhou Bay

Enhancing Skin Cancer Diagnosis with Deep Learning:A Hybrid CNN-RNN Approach

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Computers, Materials & Continua 2024年第4期79卷 1497-1519页

作者： Syeda Shamaila Zareen Guangmin Sun Mahwish Kundi Syed Furqan Qadri Salman Qadri Faculty of Information Technology Beijing University of TechnologyBeijing100124China Computer Science International Engineering Collage Maynooth UniversityKildareW23 F2H6Irland Research center for Data Hub and security Zhejiang LabHangzhou311121China Computer Science Department MNS University of AgricultureMultan59220Pakistan

Skin cancer diagnosis is difficult due to lesion presentation variability. Conventionalmethods struggle to manuallyextract features and capture lesions spatial and temporal variations. This study introduces a deep learning-basedConvolutional and Recurrent Neural network (CNN-RNN) model with a ResNet-50 architecture which usedas the feature extractor to enhance skin cancer classification. Leveraging synergistic spatial feature extractionand temporal sequence learning, the model demonstrates robust performance on a dataset of 9000 skin lesionphotos from nine cancer types. Using pre-trained ResNet-50 for spatial data extraction and Long Short-TermMemory (LSTM) for temporal dependencies, the model achieves a high average recognition accuracy, surpassingprevious methods. The comprehensive evaluation, including accuracy, precision, recall, and F1-score, underscoresthe model’s competence in categorizing skin cancer types. This research contributes a sophisticated model andvaluable guidance for deep learning-based diagnostics, also this model excels in overcoming spatial and temporalcomplexities, offering a sophisticated solution for dermatological diagnostics research.

关键词： Skin cancer classification deep learning Convolutional Neural network(CNN) RNN ResNet-50

Detection and isolation of false data injection attack via adaptive Kalman filter bank

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Journal of Control and Decision 2024年第1期11卷 60-72页

作者： Xiaoyuan Luo Minggao Zhu Xinyu Wang Xinping Guan School of Electrical Engineering Yanshan UniversityQinhuangdaoPeople’s Republic of China Jiangsu Collaborative Innovation center for Smart Distribution network NanjingPeople’s Republic of China School of Electronic Information and Electrical EngineeringShanghai Jiao Tong UniversityShanghaiPeople’s Republic of China

Due to the integration of cyber–physical systems,smart grids have faced the new security risks caused by false data injection attacks(FDIAs).FDIAs can bypass the traditional bad data detection techniques by falsifying the process of state *** this reason,this paper studies the detection and isolation problem of FDIAs based on the adaptive Kalman filter bank(AKFB)in smart *** the covert characteristics of FDIAs into account,a novel detection method is proposed based on the designed ***,the adaptive threshold is proposed to solve the detection delay caused by a priori threshold in the current detection *** the case of multiple attacked sensor nodes,the AKFB-based isolation method is *** reduce the number of isolation iterations,a logical decision matrix scheme is ***,the effectiveness of the proposed detection and isolation method is demonstrated on an IEEE 22-bus smart grids.

关键词： Smart grids false data inject attack detection and isolation Kalman filter bank