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Metallic-Waveguide-Fed and Low-Sidelobe mmW End-Fire Antenna Based on SSPP

IEEE Antennas and Wireless Propagation Letters 2025年

作者： Chang, Le Liu, Dan Cui, Yaozhong Yang, Wenqian Yang, Fei Zhang, Anxue Xi'an Jiaotong University Shaanxi Key Laboratory of Deep Space Exploration Intelligent Information Technology School of Information and Communications Engineering Xi'an710049 China China Electronics Technology Group Corporation General Institute Beijing100041 China Xi'an Electronic Engineering Research Institute Xi'an710100 China

This letter addresses the antenna challenges faced in corridor-like environments in the IoT world. High-gain and large-bandwidth antenna with fixed beam is required and the spoof surface plasmon polariton (SSPP)-based mmW end-fire antenna fits the requirement perfectly. Few SSPP mmW antennas have been reported, and most of the existing SSPP antennas are fed by SMA and fabricated by PCB. Considering that metallic waveguide is the most important feeding interface and dielectric loss severely degrades antenna efficiency at mmW band, this letter proposes a metallic-waveguide-fed SSPP-based end-fire antenna at 60 GHz. A sword-shaped grooved copper rod is inserted into a metallic waveguide to form proposed antenna. The tapered handle penetrates into the trapezoidal matching air cavity for wideband matching. The grooves are tapered to achieve high end-fire gain and low sidelobes (SLLs). The CNC-machined prototype verified the design strategy. The measured results show that the -10 dB impedance bandwidth is basically 45.6∼>67 GHz and within 55∼65 GHz, the end-fire gains are 12.1∼15.6 dBi and the SLLs are better than -17.1 and -21.1 dB in E- and H-planes, respectively. This letter also proposes a new concept for designing mmW antennas by simply inserting a customized radiator into an open waveguide. © 2002-2011 IEEE.

关键词： Antenna feeders

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Object Detection Based on CNN and Vision-Transformer: A Survey

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IET Computer Vision 2025年第1期19卷

作者： Cao, Jinfeng Peng, Bo Gao, Mingzhong Hao, Haichun Li, Xinfang Mou, Hongwei School of Mechanical and Automotive Engineering Qingdao University of Technology Qingdao China Guangdong Provincial Key Laboratory of Deep Earth Sciences and Geothermal Energy Exploitation and Utilisation Institute of Deep Earth Sciences and Green Energy College of Civil and Transportation Engineering Shenzhen University Shenzhen China State Key Laboratory of Intelligent Construction and Healthy Operation and Maintenance of Deep Underground Engineering Shenzhen University Shenzhen China Shenzhen Key Laboratory of Deep Underground Engineering Sciences and Green Energy Shenzhen University Shenzhen China First Institute of Oceanography Ministry of Natural Resources Qingdao China

Object detection is the most crucial and challenging task of computer vision and has been used in various fields in recent years, such as autonomous driving and industrial inspection. Traditional object detection methods are mainly based on the sliding windows and the handcrafted features, which have problems such as insufficient understanding of image features and low accuracy of detection. With the rapid advancements in deep learning, convolutional neural networks (CNNs) and vision transformers have become fundamental components in object detection models. These components are capable of learning more advanced and deeper image properties, leading to a transformational breakthrough in the performance of object detection. In this review, we comprehensively review the representative object detection models from deep learning periods, tracing their architectural shifts and technological breakthroughs. Furthermore, we discuss key challenges and promising research directions in the object detection. This review aims to provide a comprehensive foundation for practitioners to enhance their understanding of object detection technologies. © 2025 The Author(s). IET Computer Vision published by John Wiley & Sons Ltd on behalf of The Institution of engineering and technology.

关键词： Convolutional neural networks

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Dynamic Splitting Performance and Energy Dissipation of Steel Fiber Reinforced Concrete

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KSCE Journal of Civil engineering 2025年

作者： Yuheng Wang Guojun Liu Jianhui Wang Quanping Zheng Xiaofeng Wang Yingying Zhang Army Engineering University of PLA Xuzhou 221116 China Institute of Defense Engineering AMS PLA Luoyang 471023 Henan China Jiangsu Key Laboratory of Disaster Impact and Intelligent Prevention in Civil Engineering State Key Laboratory of intelligent Construction and Healthy Operation and Maintenance of Deep Underground Engineering China University of Mining and Technology Xuzhou Jiangsu 221116 China

Through quasi-static and dynamic splitting tensile tests, the mechanical response characteristics of Steel Fiber Reinforced Concrete (SFRC) under varying strain rates, matrix strengths, and fiber contents were investigated. The analysis focused on the typical failure modes, splitting tensile strength, and energy dissipation behavior of specimens under different parameters. The results indicate that both loading strain rate and steel fiber content significantly influence the macroscopic failure morphology of SFRC. The dynamic splitting tensile strength exceeds its static counterpart, with their ratio (defined as the Dynamic Splitting Tensile Strength Increase Factor, DIF) exhibiting a bilinear relationship with the logarithm of strain rate. The enhancement effect of steel fibers on the splitting tensile strength is primarily manifested under static loading, while the influence of concrete matrix strength on splitting tensile strength is not significant. In terms of energy dissipation in dynamic splitting tests, the partial replacement of cement with silica fume not only effectively improves the tensile resistance of steel fibers but also maximizes their tensile properties.

关键词： Steel fiber reinforced concrete (SFRC) Split Hopkinson pressure bar (SHPB) Splitting tensile strength Failure mode Energy dissipation

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Software Defect Prediction via deep Belief Network

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Chinese Journal of Electronics 2019年第5期28卷 925-932页

作者： WEI Hua SHAN Chun HU Changzhen ZHANG Yu YU Xiao School of Computer Science and Technology Beijing Institute of Technology China Information Technology Security Evaluation Center Beijing Key Laboratory of Software Security Engineering Technology Beijing Institute of Technology School of Electrical and Information Engineering and Beijing Key Laboratory of Intelligent Processing for Building Big Data Beijing University of Civil Engineering and Architecture State Key Laboratory in China for Geomechanics and Deep Underground Engineering (Beijing) China University of Mining and Technology School of Computer Science and Technology Shandong University of Technology

Defect distribution prediction is a meaningful topic because software defects are the fundamental cause of many attacks and data loss. Building accurate prediction models can help developers find bugs and prioritize their testing efforts. Previous researches focus on exploring different machine learning algorithms based on the features that encode the characteristics of *** problem of data redundancy exists in software defect data set, which has great influence on prediction *** propose a defect distribution prediction model(deep belief network prediction model, DBNPM), a system for detecting whether a program module contains defects. The key insight of DBNPM is deep belief network(DBN)technology, which is an effective deep learning technique in image processing and natural language processing,whose features are similar to defects in source *** results show that DBNPM can efficiently extract and process the data characteristics of source program and the performance is better than Support vector machine(SVM), Locally linear embedding SVM(LLE-SVM), and Neighborhood preserving embedding SVM(NPE-SVM).

关键词： Defect prediction Software security deep belief network(DBN)

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Detection and Analysis of disturbance signal of Cable Tunnel based on Optical Fiber Vibration Sensors 19

Detection and Analysis of disturbance signal of Cable Tunnel...

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19th International Conference on Optical Communications and Networks, ICOCN 2021

作者： Zhu, Feng Huang, Bingxiang Liu, Tongyu Hu, Binxin Song, Guangdong Zhang, Hua Mao, Wodong Gao, Huabin Li, Yang Su, Huairui Jinan250014 China State Key Laboratory of Coal Resources and Safe Mining China University of Mining and Technology Xuzhou221116 China Engineering Laboratory of Deep Mine Rockburst Disaster Assessment Shandong Province Jinan250102 China Jining Anran Intelligent Technology Co. Ltd Jining272000 China Shandong Province Research Institute of Coal Geology Planning and Exploration Jinan250102 China Geophysical Detection Team Shandong Bureau of Coal Geology Jinan250102 China

ISBN: (纸本)9781665424462

Cable tunnel is easily affected by external force, such as excavating equipment, which leads to abnormal cable and affects normal transmission. In order to detect the abnormal phenomenon of cable tunnel in time, the optical fiber sensing technology is used to monitor the cable tunnel in real time. Four fiber vibration sensors are installed on the roof of cable tunnel and connected to the self-developed optical fiber microseismic monitor. Different vibration signals are simulated directly above the cable tunnel, the time domain and frequency domain information generated by the vibration signal are analyzed, and the source type of the disturbed cable tunnel is identified in order to protect the cable tunnel in time. The results show that there are obvious differences in the main frequency produced by different source types, and the source information can be classified according to different main frequency signals, especially the information of external force damage, so as to protect cables in time and ensure the safety of electricity consumption. © 2021 IEEE.

关键词： Optical fibers

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Density-driven reactive transport in fracture-porous media: the characteristics of gravitational instability and CO 2 transport area

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Journal of Cleaner Production 2025年 518卷

作者： Mengzi Ren Liping Qiao Xia-Ting Feng Zhechao Wang Kaixuan Sun Fei Liang Key Laboratory of Liaoning Province on Deep Engineering and Intelligent Technology Northeastern University Shenyang 110819 China Liaoning Provincial Research Center on Underground Storage Engineering Northeastern University Shenyang 110819 China Exploration and Development Research Institute of Liaohe Oilfield of CNPC Panjin 124010 China

CO 2 sequestration in saline aquifers is an important method to reduce CO 2 emissions. Saline aquifer reservoirs are fracture-porous media. CO 2 dissolves in brine water, forming a density difference and reacting with the surrounding rock mineral. Density-driven reactive solute transport in fracture-porous media can change the porosity, fracture aperture and permeability of the reservoir rock, thus affecting the characteristics of reactive solute transport, directly determining the efficiency of CO 2 dissolution and trapping, and finally affecting the CO 2 sequestration potential in saline aquifers. A coupled calculation method of density-driven reactive solute transport is proposed. The method comprehensively considers the variation of porosity in rock matrix, aperture in fracture, and the corresponding evolution of permeability under chemical reactions. In addition, a method for quantitatively characterizing gravitational instability and CO 2 transport area is proposed, and based on this, the impact of different Damköhler ( Da ) number and fracture morphology parameters on density-driven reactive transport is analyzed. The results show that gravitational instability and CO 2 transport area are negatively correlated with the Da number. As the Da number increases, the gravitational instability decreases by up to 0.008 ( Da = 0 to 10), 0.040 ( Da = 10 to 100), and 0.075 ( Da = 100 to 1000), the CO 2 transport area decreases by up to 0.02 ( Da = 0 to 10), 0.23 ( Da = 10 to 100), and 0.24 ( Da = 100 to 1000). The gravitational instability and CO 2 transport area are positively correlated with the length of single fracture and permeability ratio between the single fracture and the porous rock matrix. As the fracture length ( l f ) increases, the gravitational instability increases by up to 0.008 ( l f = 0.2 to 0.4), 0.009 ( l f = 0.4 to 0.6), and 0.012 ( l f = 0.6 to 0.8), the CO 2 transport area increases by up to 0.03 ( l f = 0.2 to 0.4), 0.03 ( l f = 0.4 t

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Experimental Study of Heat Transfer Characteristics for Subcooled Flow Boiling in Compound Heat Transfer Tubes

SSRN

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SSRN 2022年

作者： Liu, Ping Liu, Ping He, M.Y. Qin, G.J. Song, Y.T. Peng, X.B. Tang, M.Y. Guo, Y.S. Wang, W.H. Huang, S.F. Ji, J.D. Chen, Q.H. Mao, X. State Key Laboratory of Mining Response and Disaster Prevention and Control in Deep Coal Mines Anhui University of Science and Technology Huainan232001 China School of Mechanical Engineering Anhui University of Science and Technology Huainan232001 China Institute of physical and Information Technology Anhui University Hefei230061 China Institute of Plasma Physics Chinese Academy of Sciences Hefei230031 China School of Mining and Safety Engineering Anhui University of Science and Technology Huainan232001 China Nanjing University of Aeronautics and Astronautics Jiangsu Key Laboratory of Precision and Micro-Manufacturing Technology Nanjing210016 China Anhui Key Laboratory of Mine Intelligent Equipment and Technology Anhui University of Science and Technology Huainan232001 China

A new compound heat transfer tube (CHTT) was proposed to investigate the heat removal technique for the divertor in the International Thermonuclear Experimental Reactor (ITER). Twisted tape (TT) with twist ratios of 2, 5 and 8 was inserted into the internally ribbed tube (IRT) with pitches of 1.5 and 2 mm to form the CHTT. Heat transfer experiments on subcooled flow boiling were conducted in the plain tube (PT), tube with twisted tape inserts (TWTT), internally ribbed tube (IRT) and CHTT. The hydraulic parameters covered mass fluxes range of 992 to 4960 kg/m 2 s, pressure range of 0.4 to 2 MPa, the inlet subcoolings of 87.01 to 119.21 ℃ and the heat flux of 1 to 17.2 MW/m 2 for vacuum adiabatic conditions. The results revealed that, firstly, the coupling structure of TT inserts and internal rib could enhance the heat transfer characteristics in the subcooled flow boiling state than the individual technique. Meanwhile, it was observed that the CHTT with a twist ratio of 2 and a pitch of 2 mm showed the best heat transfer performance and achieved the highest performance evaluation criterion (PEC). Secondly, the effects of twist ratios, pitches, mass fluxes and pressures on heat transfer characteristics were analyzed in CHTT. The heat transfer coefficient was directly proportional to the pitches and mass fluxes but inversely proportional to the twist ratios and pressures. The influences of mass flux and pressure on Onset of Nucleate Boiling (ONB) point were also discussed in detail. Lastly, a new correlation for Nusselt number ( Nu ) was developed to predict the heat transfer characteristics of CHTT based on the present experimental data, and the predicted errors were within ± 10%. The mean absolute error (MAE) and the root mean square error (RMSE) of the new correlation were 4.03% and 5.04%, respectively. © 2022, The Authors. All rights reserved.

关键词： Tubes (components)

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Probabilistic network topology prediction for active planning: An adaptive algorithm and application

arXiv

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arXiv 2022年

作者： Zhang, Liang Zhang, Zexu Siegwart, Roland Chung, Jen Jen The School of Engineering and Automation Anhui University Hefei230601 China The Deep Space Exploration and Research Center School of Astronautics Harbin Institute of Technology Harbin150001 China Autonomous System Lab ETH Zürich 8092 Switzerland The Shaanxi Key Laboratory of Integrated and Intelligent Navigation China The Autonomous Systems Lab ETH Zürich Zürich8092 Switzerland

This paper tackles the problem of active planning to achieve cooperative localization for multi-robot systems (MRS) under measurement uncertainty in GNSS-limited scenarios. Specifically, we address the issue of accurately predicting the probability of a future connection between two robots equipped with range-based measurement devices. Due to the limited range of the equipped sensors, edges in the network connection topology will be created or destroyed as the robots move with respect to one another. Accurately predicting the future existence of an edge, given imperfect state estimation and noisy actuation, is therefore a challenging task. An adaptive power series expansion (or APSE) algorithm is developed based on current estimates and control candidates. Such an algorithm applies the power series expansion formula of the quadratic positive form in a normal distribution. Finite-term approximation is made to realize the computational tractability. Further analyses are presented to show that the truncation error in the finite-term approximation can be theoretically reduced to a desired threshold by adaptively choosing the summation degree of the power series. Several sufficient conditions are rigorously derived as the selection principles. Finally, extensive simulation results and comparisons, with respect to both single and multi-robot cases, validate that a formally computed and therefore more accurate probability of future topology can help improve the performance of active planning under uncertainty. Copyright © 2022, The Authors. All rights reserved.

关键词： Network topology

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Study on the mechanism of microcrack propagation in bentonite under confining pressure conditions

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Quarterly Journal of engineering Geology and Hydrogeology 2025年

作者： Guo, Jingna Liu, Jiangfeng Liu, Daoping Zhao, Yu Lei, Min Shi, Hao School of Applied Mathematics Chengdu University of Information Technology Sichuan Chengdu610225 China State Key Laboratory of Intelligent Construction and Healthy Operation and Maintenance of Deep Underground Engineering China University of Mining and Technology Jiangsu Xuzhou221116 China Science and Technology on Reactor System Design Technology Laboratory Nuclear Power Institute of China Chendu610213 China School of Civil Engineering and Architecture Anhui University of Science and Technology Huainan232001 China

For underground nuclear disposal repositories, sealing performance is crucial to ensuring long-term operational safety. Bentonite, widely employed as a sealing material, effectively reduces leakage risks owing to its self-healing capacity. However, a comprehensive investigation of gas migration mechanisms in bentonite is imperative to elucidate the underlying leakage dynamics. This study not only offers theoretical insights for the safety assessment and design optimization of disposal repositories but also holds substantial practical significance in ensuring their secure performance. To accurately model gas migration in saturated bentonite, this study systematically investigates the effects of pore pressure on soil deformation and experimentally evaluates the impact of damage evolution on permeability and elastic modulus. Building on these experimental insights, we propose a coupled fluid-solid constitutive model. This model elucidates the progressive development of microcracks within bentonite under increasing gas pressure, providing a mechanistic understanding of fracture propagation in sealing systems. By integrating experimental data from bentonite hydration and gas breakthrough tests, the study verifies that gas migration under flexible boundary conditions is primarily governed by the dilatancy effect of bentonite. Furthermore, the model's validity and applicability are demonstrated. Subsequently, the model is employed to systematically investigate the influence of confining pressure on (1) the evolution of microcracks in bentonite, (2) permeability variations, and (3) gas breakthrough pressure thresholds. Based on these analyses, theoretical mitigation strategies to prevent gas breakthrough are established for specific confining pressure ranges. © 2025 The Author(s). Published by The Geological Society of London. All rights, including for text and data mining (TDM), artificial intelligence (AI) training, and similar technologies, are reserved. For permissions:

关键词： Microcracks

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Seismic fragility analysis of near-fault mountainous wind turbines considering source-path-site effects

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Renewable Energy 2025年

作者： Wenze Wang Jianze Wang Kaoshan Dai Zhenning Ba Mengtao Wu Baofeng Zhou Reza Sharbati Ashraf El Damatty Department of Civil Engineering and State Key Laboratory of Intelligent Construction and Healthy Operation and Maintenance of Deep Underground Engineering Sichuan University Chengdu China Department of Civil Engineering Tianjin University Tianjin China Institute of Engineering Mechanics China Earthquake Administration Harbin China Department of Civil and Environmental Engineering Amirkabir University of Technology Tehran Iran Department of Civil and Environmental Engineering University of Western Ontario London Canada

With the increasing demand for renewable energy, the deployment of wind turbines (WTs) in mountainous areas has surged, raising concerns about the associated seismic risk. The seismic fragility of these turbines is governed by a combination of factors, including the characteristics of the seismic source, the propagation paths, and the site-specific conditions. However, there is limited understanding of how these coupled source-path-site effects impact WT fragility, creating a critical knowledge gap that impedes the development of reliable seismic design guidelines for wind farms in mountainous areas. To address this issue, a physics-based method for fragility assessment is proposed, combining scenario-specific ground motion simulations with a hybrid semi-analytical-numerical modeling approach. This methodology integrates three computational components: (1) the frequency-wavenumber (FK) technique to compute the semi-analytical Green's function for a semi-infinite crustal space, (2) the spectral element method (SEM) for efficient wavefield simulations in heterogeneous terrains, and (3) the finite element method (FEM) for detailed nonlinear modeling of WT structural responses. The FK-SEM-FEM framework enables end-to-end simulation of seismic wave propagation from fault rupture to the nonlinear structural response of the WTs. The study analyzes the effects of key parameters on the seismic performance of WTs in mountainous regions, and introduces, for the first time, a fragility model for WTs considering diverse mountain geometries. The results indicate that the seismic response of WTs on mountaintops can be amplified by 1.16 to 3.02 times compared to those at the base. The combined effect of fault rupture mode and local site effects leads to spatially variable damage patterns, making WTs on mountaintops more susceptible to failure. The findings reveal that current seismic design codes for WTs in mountainous areas are inadequate, highlighting the need for immediate updat

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