检索结果-内蒙古大学图书馆

arXiv 2024年

作者： Liu, Qize Pan, Xiaofan Zheng, Xutao Gao, Huaizhong Li, Longhao Wang, Qidong Yang, Zirui Tang, Chenchong Wu, Wenxuan Cheng, Jianping Zeng, Zhi Zeng, Ming Feng, Hua Zhang, Binbin Wang, Zhonghai Zhou, Rong Liu, Yuanyuan Lin, Lin Zhong, Jiayong Jiang, Jianyong Han, Wentao Tian, Yang Xu, Benda Department of Engineering Physics Tsinghua University Beijing100084 China Department of Astronomy Beijing Normal University Beijing100875 China Beijing Normal University Beijing100875 China Institute of High Energy Physics CAS Beijing100049 China Department of Astronomy Tsinghua University Beijing100084 China School of Astronomy and Space Science Nanjing University Nanjing210093 China College of Physics Sichuan University Chengdu610064 China College of Nuclear Science and Technology Beijing Normal University Beijing100875 China Department of Computer Science and Technology Tsinghua University Beijing100084 China

The Gamma-Ray Integrated Detectors (GRID) are a space science mission that employs compact gamma-ray detectors mounted on NanoSats in low Earth orbit (LEO) to monitor the transient gamma-ray sky. Owing to the unpredictability of the time and location of gamma-ray bursts (GRBs), obtaining the photon responses of gamma-ray detectors at various incident angles is important for the scientific analysis of GRB data captured by GRID detectors. For this purpose, a dedicated Monte Carlo simulation framework has been developed for GRID detectors. By simulating each GRID detector and the NanoSat carrying it, the spectral energy response, detection efficiency, and other angular responses of each detector for photons with different incident angles and energies can be obtained within this framework. The accuracy of these simulations has been corroborated through on-ground calibration, and the derived angular responses have been successfully applied to the data analysis of recorded GRBs. Copyright © 2024, The Authors. All rights reserved.

关键词： Gamma rays

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Safety Analysis of Automatic Crane Trolley Running System Based on STAMP/STPA

Safety Analysis of Automatic Crane Trolley Running System Ba...

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International Conference on Informative and Cybernetics for Computational Social Systems (ICCSS)

作者： Wenbo Zhang Xiangkun Meng Jianyuan Wang Tieshan Li Qihe Shan Fei Teng College of Navigation Dalian Maritime University Dalian China Marine Electrical Engineering College Dalian Maritime University Dalian China College of Automation Engineering University of Electronic Science and Technology Chengdu China

ISBN: (纸本)9781665402460

Automatic crane is a complex system affected by the external environment and the internal components of the system, information fusion, software and hardware combination, and man-machine integration. The improvement of its automation and informatization proposes various challenges in the accident model construction and safety analysis. However, the safety analysis methods based on fault types consider that the occurrence of accidents is linear and ignore the correlation among components of the system. This paper adopts the system-theoretic accident model and process (STAMP) and system-theoretic process analysis (STPA) mode is to implement safety analysis of the automatic crane trolley running system (ACTRs). The paper starts from the identification of system-level losses and hazards, clarifies the function and internal logical control relationships of the system’s components, and then finds potential unsafe control actions (UCAs) and loss scenarios during the trolley running. The results show that the control requirements for the regular operation of the trolley running system can be analyzed in detail. Therefore, the STAMP/STPA can apply to the safety investigation of automatic cranes.

关键词： Analytical models Cranes Correlation automation Manuals Software Safety

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Research on Wind Turbine Gearbox Fault Diagnosis Based on CEEMDAN and CVFDT

Research on Wind Turbine Gearbox Fault Diagnosis Based on CE...

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IEEE International Conference on Power and Energy Systems (ICPES)

作者： Fangzhou Shi Jianghao Yu Min Gu Kai Lei Jian He Dongfang Electric Co. Ltd Chengdu China College of Automation Engineering University of Electronic Science and Technology of China Chengdu China Intelligent Terminal Key Laboratory of Sichuan Province University of Electronic Science and Technology of China Chengdu China

ISBN: (纸本)9781665413268

Gearbox fault diagnosis has always been a hot topic in the field of mechanical fault diagnosis and has great research value and significance. But at present, it is mainly based on offline data for fault diagnosis, which is not real-time and slow to find. In this paper, the real-time diagnosis of gearbox bearing fault is realized based on flow data. Aiming at the problems of nonstationary and weak fault characteristics of gearbox bearing vibration signals collected in real time, an energy entropy feature extraction method based on sliding window is proposed for adaptive noise complete set empirical mode decomposition (SWCEEMDAN), which not only effectively solves the problem of end-point effect of CEEMDAN, The feature vectors containing rich fault features can also be extracted; Then, the incremental training and adaptive update of the model are carried out by combining the incremental classification method CVFDT, and then the gearbox fault diagnosis can be realized in real time. Finally, the validity of the improved method was proved by the bearing data set of Case Western reserve university.

关键词： Fault diagnosis Vibrations Training Adaptation models Empirical mode decomposition Feature extraction Real-time systems

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Design of high-energy X-ray conversion target based on linear electron accelerator

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applied radiation and isotopes : including data, instrumentation and methods for use in agriculture, industry and medicine 2025年 224卷 111951页

作者： Hongchao Yang Xingfan Yang Yinghong Tang Heng Dai Pengcheng Li Guohua Liang Yadong Wu Xianguo Tuo Qibiao Wang College of Nuclear Technology and Automation Engineering Chengdu University of Technology East Third Road 1 Erxian Bridge 610059 Chengdu China Institute of Applied Electronics China Academy of Engineering Physics Mian Shan Road 64 621900 Mianyang China. College of Nuclear Technology and Automation Engineering Chengdu University of Technology East Third Road 1 Erxian Bridge 610059 Chengdu China. School of Computer Science and Engineering Sichuan University of Science and Engineering Huixing Road 519 Ziliujing District 643000 Zigong China. School of Physics and Electronic Engineering Sichuan University of Science and Engineering Huixing Road 519 Ziliujing District 643000 Zigong China. School of Physics and Electronic Engineering Sichuan University of Science and Engineering Huixing Road 519 Ziliujing District 643000 Zigong China. Electronic address: wangqibiao@***.

High-energy X-rays can be employed to inspect fuel elements, even weld seams, cracks, and internal structural deformations of the components due to their density-sensitive characteristics and strong penetration capabilities. The quality of these X-rays is determined by various factors such as the X-ray conversion target, the cooling system for the conversion target, and the filter type, thereby influencing the detection accuracy. This study was conducted using an electron linear accelerator with an energy of 10 MeV and an average current of 150 μA. Firstly, we designed the conversion target material and geometry structure by Monte Carlo method. The results indicate that the optimal target material is tungsten and the optimum shape of the conversion target is a cylinder with dimensions of Φ 40 × 2.2 mm. Second, finite element analysis was applied to design the conversion target cooling system. After 60 min of electron beam irradiation, the local maximum temperature of the conversion target is approximately 1330 °C. Lastly, theoretical analysis and Monte Carlo simulations were used to design the X-ray filters. The result demonstrates that a double-layer filter consisting of 8 mm bismuth and 4 mm iron can increase the proportion of high-energy X-rays by 13.89 ± 0.05 %. Finally, the results of using the attenuation method to measure the X-ray energy spectrum produced by an electron linear accelerator indicate that without a filter 78.81 % of the X-rays are above 1 MeV and with a filter this proportion increases to 80.55 %.

关键词： Attenuation curves COMSOL Conversion target Geant4 High energy X-ray nuclear fuel

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Temporal Correlation Meets Embedding: Towards a 2nd Generation of JDE-based Real-Time Multi-Object Tracking

arXiv

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arXiv 2024年

作者： Zhang, Yunfei Liang, Chao Gao, Jin Zhang, Zhipeng Hu, Weiming Maybank, Stephen Zhou, Xue Li, Liang School of Information Science and Technology Shanghaitech University Shanghai201210 China State Key Laboratory of Multimodal Artificial Intelligence System Institute of Automation Chinese Academy of Sciences Beijing100190 China School of Artificial Intelligence University of Chinese Academy of Sciences Beijing101408 China Shenzhen Institute for Advanced Study University of Electronic Science and Technology of China Shenzhen518110 China KargoBot China Department of Computer Science and Information Systems Birkbeck College LondonWC1E 7HX United Kingdom School of Automation Engineering University of Electronic Science and Technology of China Chengdu611731 China Beijing Institute of Basic Medical Sciences Beijing100850 China

Joint Detection and Embedding (JDE) trackers have demonstrated excellent performance in Multi-Object Tracking (MOT) tasks by incorporating the extraction of appearance features as auxiliary tasks through embedding Re-Identification task (ReID) into the detector, achieving a balance between inference speed and tracking performance. However, solving the competition between the detector and the feature extractor has always been a challenge. Meanwhile, the issue of directly embedding the ReID task into MOT has remained unresolved. The lack of high discriminability in appearance features results in their limited utility. In this paper, a new learning approach using cross-correlation to capture temporal information of objects is proposed. The feature extraction network is no longer trained solely on appearance features from each frame but learns richer motion features by utilizing feature heatmaps from consecutive frames, which addresses the challenge of inter-class feature similarity. Furthermore, our learning approach is applied to a more lightweight feature extraction network, and treat the feature matching scores as strong cues rather than auxiliary cues, with an appropriate weight calculation to reflect the compatibility between our obtained features and the MOT task. Our tracker, named TCBTrack, achieves state-of-the-art performance on multiple public benchmarks, i.e., MOT17, MOT20, and DanceTrack datasets. Specifically, on the DanceTrack test set, we achieve 56.8 HOTA, 58.1 IDF1 and 92.5 MOTA, making it the best online tracker capable of achieving real-time performance. Comparative evaluations with other trackers prove that our tracker achieves the best balance between speed, robustness and accuracy. Code is available at https://***/yfzhang1214/TCBTrack. Copyright © 2024, The Authors. All rights reserved.

关键词： HTTP

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Research and Application of Query Optimization Based on HBase

Research and Application of Query Optimization Based on HBas...

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International Conference on Computer and Communications (ICCC)

作者： Kai Lei Xiaoyu Xiong Zengzhou Wang Fangzhou Shi Jian He Dongfang Electric Co. Ltd Chengdu China College of Automation Engineering University of Electronic Science and Technology of China Chengdu China University of Electronic Science and Technology of China Intelligent Terminal Key Laboratory of Sichuan Province Chengdu China

ISBN: (纸本)9781665409513

With the advent of the big data era, higher technical requirements have been put forward for the management and retrieval of massive data. As a distributed NoSQL database under the Hadoop framework, HBase has been chosen by many companies as the storage medium for big data due to its strong scalability, excellent storage capabilities, and good read and write capabilities. However, HBase uses the Map-Reduce framework to process aggregate queries, which requires Calculate in real time and cannot keep the calculated result. This paper is dedicated to the research of query optimization technology based on HBase. In order to improve the efficiency of HBase for time series data aggregation and query, an index structure based on time split tree is proposed. The query overhead of tree index stored on disk is high and the query time is high. For problems affected by the amount of data, the time division tree structure is improved, and the query algorithm is optimized at the same time to avoid the disk I/O overhead of traversing the index tree layer by layer. First, save the time summary information, that is, the fixed-length data aggregation information, by constructing a time split tree; then persist the time split tree index into HBase according to the set time, add the corresponding timing information, and construct the sequence number, timing number, The HBase primary key of time range information; using time sequence information, through optimized index query algorithms, it can effectively narrow the data table retrieval range and improve the efficiency of aggregated information query. The effectiveness of the improved method is proved by a large number of wind farm wind turbine operating data.

关键词： Technical requirements Query processing Scalability Time series analysis Data aggregation Big Data Wind farms

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Dynamic allocation method for airport gates based on capacity relaxation 7

Dynamic allocation method for airport gates based on capacit...

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7th International Conference on Information Science and Control engineering, ICISCE 2020

作者： Xing, Zhiwei Wang, Sibo Qiao, DI Luo, Qian Cheng, Hua Wen, Tao Civil Aviation University of China College of Electronic Information and Automation Tianjin China The Second Research Institute of CAAC Engineering Technology Research Center Chengdu China

ISBN: (纸本)9781728164069

Due to the weather, air control and other reasons, the original pre-allocation scheme can not be implemented, and the original allocation scheme needs to be readjusted. In this paper, starting from the two perspectives of reducing airport operating costs and staff workload, taking the number of flight adjustments and increasing the number of slack gates as the optimization goals, a dynamic adjustment model of gates is established, and a stochastic gradient descent algorithm is used to solve the model. In order to verify the validity of the model, a simulation is carried out based on the actual operating data of a domestic hub airport. The research results show that the optimized scheme produced by the proposed method not only reduces the number of adjustments and the number of slack gates significantly, but also makes the gate occupancy ratio more evenly distributed compared with the original gate allocation plan. The theory of gate allocation is improved to provide reliable management basis for airport operation managers. © 2020 IEEE.

关键词： Operating costs

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Analyzing and Modeling of Co Purging for High-Temperature Proton Exchange Membrane Fuel Cells

SSRN

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SSRN 2023年

作者： Lei, Gang Zheng, Hualin Zhang, Caizhi Chen, Huicui Chin, Cheng Siong Xu, Xinhai School of Mechatronic Engineering Southwest Petroleum University Chengdu610500 China College of Mechanical and Vehicle Engineering The State Key Laboratory of Mechanical Transmissions Chongqing Automotive Collaborative Innovation Centre Chongqing University Chongqing400044 China School of Automotive Studies Tongji University Shanghai201804 China Faculty of Science Agriculture and Engineering Newcastle University Singapore599493 Singapore School of Mechanical Engineering and Automation Harbin Institute of Technology Guangdong Shenzhen China

Purge is a simple, economical method to remove inert gases accumulated in high-temperature proton exchange membrane fuel cells (HT-PEMFC) in dead-end anode (DEA) mode. However, early works mainly focused on inert gases. Since HT-PEMFC has strong adsorption of CO, the application of inert gas methods for CO purification becomes challenging. In this paper, a CO purging model was established and verified experimentally. By using this model, the key parameter of the CO concentration within the anode was analyzed, and the theoretical extreme values were deduced. Finally, purging strategies under different operating conditions were proposed. The results show the minimum concentration of CO inside the HT-PEMFC is affected by the current, feed gas flow rate and feed gas CO concentration, while the maximum concentration of CO is also affected by the off-duration of the purge valve in addition to the above. Under the operating condition of 200 °C, the CO concentration threshold purge strategy should be adopted, while under the operating condition of 175 °C, voltage drop and CO concentration threshold purge strategies should be adopted respectively above and below the cutoff line according to the current. The research helps to solve the problem of CO accumulation in DEA mode. © 2023, The Authors. All rights reserved.

关键词： Anodes

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Variations of secondary particle arrival time detected by LHAASO-KM2A during thunderstorms 38

Variations of secondary particle arrival time detected by LH...

引用

38th International Cosmic Ray Conference, ICRC 2023

作者： Chen, Xuejian Zhou, Xunxiu Yang, Ci Huang, Daihui Cao, Zhen Aharonian, F. An, Q. Axikegu Bai, Y.X. Bao, Y.W. Bastieri, D. Bi, X.J. Bi, Y.J. Cai, J.T. Cao, Q. Cao, W.Y. Cao, Zhe Chang, J. Chang, J.F. Chen, A.M. Chen, E.S. Chen, Liang Chen, Lin Chen, Long Chen, M.J. Chen, M.L. Chen, Q.H. Chen, S.H. Chen, S.Z. Chen, T.L. Chen, Y. Cheng, N. Cheng, Y.D. Cui, M.Y. Cui, S.W. Cui, X.H. Cui, Y.D. Dai, B.Z. Dai, H.L. Dai, Z.G. Danzengluobu della Volpe, D. Dong, X.Q. Duan, K.K. Fan, J.H. Fan, Y.Z. Fang, J. Fang, K. Feng, C.F. Feng, L. Feng, S.H. Feng, X.T. Feng, Y.L. Gabici, S. Gao, B. Gao, C.D. Gao, L.Q. Gao, Q. Gao, W. Gao, W.K. Ge, M.M. Geng, L.S. Giacinti, G. Gong, G.H. Gou, Q.B. Gu, M.H. Guo, F.L. Guo, X.L. Guo, Y.Q. Guo, Y.Y. Han, Y.A. He, H.H. He, H.N. He, J.Y. He, X.B. He, Y. Heller, M. Hor, Y.K. Hou, B.W. Hou, C. Hou, X. Hu, H.B. Hu, Q. Hu, S.C. Huang, D.H. Huang, T.Q. Huang, W.J. Huang, X.T. Huang, X.Y. Huang, Y. Huang, Z.C. Ji, X.L. Jia, H.Y. Jia, K. Jiang, K. Jiang, X.W. Jiang, Z.J. Jin, M. Kang, M.M. Ke, T. Kuleshov, D. Kurinov, K. Li, B.B. Li, Cheng Li, Cong Li, D. Li, F. Li, H.B. Li, H.C. Li, H.Y. Li, J. Li, Jian Li, Jie Li, K. Li, W.L. Li, W.L. Li, X.R. Li, Xin Li, Y.Z. Li, Zhe Li, Zhuo Liang, E.W. Liang, Y.F. Lin, S.J. Liu, B. Liu, C. Liu, D. Liu, H. Liu, H.D. Liu, J. Liu, J.L. Liu, J.Y. Liu, M.Y. Liu, R.Y. Liu, S.M. Liu, W. Liu, Y. Liu, Y.N. Lu, R. Luo, Q. Lv, H.K. Ma, B.Q. Ma, L.L. Ma, X.H. Mao, J.R. Min, Z. Mitthumsiri, W. Mu, H.J. Nan, Y.C. Neronov, A. Ou, Z.W. Pang, B.Y. Pattarakijwanich, P. Pei, Z.Y. Qi, M.Y. Qi, Y.Q. Qiao, B.Q. Qin, J.J. Ruffolo, D. Sáiz, A. Semikoz, D. Shao, C.Y. Shao, L. Shchegolev, O. Sheng, X.D. Shu, F.W. Song, H.C. Stenkin, Yu.V. Stepanov, V. Su, Y. Sun, Q.N. Sun, X.N. School of Physical Science and Technology Southwest Jiaotong University Chengdu610031 China Key Laboratory of Particle Astrophyics Experimental Physics Division Computing Center Institute of High Energy Physics Chinese Academy of Sciences Beijing100049 China University of Chinese Academy of Sciences Beijing100049 China TIANFU Cosmic Ray Research Center Sichuan Chengdu China Dublin Institute for Advanced Studies 31 Fitzwilliam Place Dublin 2 Ireland Max-Planck-Institut for Nuclear Physics P.O. Box 103980 Heidelberg69029 Germany State Key Laboratory of Particle Detection and Electronics China University of Science and Technology of China Anhui Hefei230026 China School of Physical Science and Technology School of Information Science and Technology Southwest Jiaotong University Sichuan Chengdu610031 China School of Astronomy and Space Science Nanjing University Jiangsu Nanjing210023 China Center for Astrophysics Guangzhou University Guangdong Guangzhou510006 China Hebei Normal University Hebei Shijiazhuang050024 China Key Laboratory of Dark Matter and Space Astronomy Key Laboratory of Radio Astronomy Purple Mountain Observatory Chinese Academy of Sciences Jiangsu Nanjing210023 China Tsung-Dao Lee Institute School of Physics and Astronomy Shanghai Jiao Tong University Shanghai200240 China Key Laboratory for Research in Galaxies and Cosmology Shanghai Astronomical Observatory Chinese Academy of Sciences Shanghai200030 China Key Laboratory of Cosmic Rays Tibet University Ministry of Education Tibet Lhasa850000 China National Astronomical Observatories Chinese Academy of Sciences Beijing100101 China School of Physics and Astronomy Sun Yat-sen University Zhuhai519000 China School of Physics Sun Yat-sen University Guangdong Guangzhou510275 China Sino-French Institute of Nuclear Engineering and Technology Sun Yat-sen University Zhuhai519000 China School of Physics and Astronomy Yunnan University Yunnan Kunming650091 China Départeme

A sub-array of the Large High Altitude Air Shower Observatory (LHAASO), KM2A contains 5216 electromagnetic particle detectors (EDs) and 1188 muon detectors (MDs). For each shower event that meets the trigger conditions (at least 20 fired EDs within a time window of 400 ns) in KM2A array, there are many signals from ED and MD detectors. The information on the arrival time and location of each signal are recorded, and the ED hits are used for shower reconstruction. Due to the acceleration and deflection by the atmospheric electric field (AEF) during a thunderstorm, the arrival time and position of the ground-level particles are modified, resulting in the changes in the inferred shower detection. To understand the shower event variation during thunderstorms, the particle arrival time is studied by analyzing the KM2A data. We can measure the distribution of changes of arrival time in the thunderstorm electric field. The variation amplitude is not only dependent on the AEF, but also highly correlated with the direction of the shower event. With the increase of the AEF strength and the zenith angle, the variation in amplitude of the arrival time becomes larger. Our results are useful in understanding the variation of shower rate detected by LHAASO-KM2A, and will also provide important information for shower reconstruction during thunderstorms. © Copyright owned by the author(s) under the terms of the Creative Commons.

关键词： Thunderstorms

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Simulation study on cosmic ray shower rate variations with LHAASO-KM2A during thunderstorms 38

Simulation study on cosmic ray shower rate variations with L...

引用

38th International Cosmic Ray Conference, ICRC 2023

作者： Yang, Ci Zhou, Xunxiu Chen, Xuejian Huang, Daihui Cao, Zhen Aharonian, F. An, Q. Axikegu Bai, Y.X. Bao, Y.W. Bastieri, D. Bi, X.J. Bi, Y.J. Cai, J.T. Cao, Q. Cao, W.Y. Cao, Zhe Chang, J. Chang, J.F. Chen, A.M. Chen, E.S. Chen, Liang Chen, Lin Chen, Long Chen, M.J. Chen, M.L. Chen, Q.H. Chen, S.H. Chen, S.Z. Chen, T.L. Chen, Y. Cheng, N. Cheng, Y.D. Cui, M.Y. Cui, S.W. Cui, X.H. Cui, Y.D. Dai, B.Z. Dai, H.L. Dai, Z.G. Danzengluobu della Volpe, D. Dong, X.Q. Duan, K.K. Fan, J.H. Fan, Y.Z. Fang, J. Fang, K. Feng, C.F. Feng, L. Feng, S.H. Feng, X.T. Feng, Y.L. Gabici, S. Gao, B. Gao, C.D. Gao, L.Q. Gao, Q. Gao, W. Gao, W.K. Ge, M.M. Geng, L.S. Giacinti, G. Gong, G.H. Gou, Q.B. Gu, M.H. Guo, F.L. Guo, X.L. Guo, Y.Q. Guo, Y.Y. Han, Y.A. He, H.H. He, H.N. He, J.Y. He, X.B. He, Y. Heller, M. Hor, Y.K. Hou, B.W. Hou, C. Hou, X. Hu, H.B. Hu, Q. Hu, S.C. Huang, D.H. Huang, T.Q. Huang, W.J. Huang, X.T. Huang, X.Y. Huang, Y. Huang, Z.C. Ji, X.L. Jia, H.Y. Jia, K. Jiang, K. Jiang, X.W. Jiang, Z.J. Jin, M. Kang, M.M. Ke, T. Kuleshov, D. Kurinov, K. Li, B.B. Li, Cheng Li, Cong Li, D. Li, F. Li, H.B. Li, H.C. Li, H.Y. Li, J. Li, Jian Li, Jie Li, K. Li, W.L. Li, W.L. Li, X.R. Li, Xin Li, Y.Z. Li, Zhe Li, Zhuo Liang, E.W. Liang, Y.F. Lin, S.J. Liu, B. Liu, C. Liu, D. Liu, H. Liu, H.D. Liu, J. Liu, J.L. Liu, J.Y. Liu, M.Y. Liu, R.Y. Liu, S.M. Liu, W. Liu, Y. Liu, Y.N. Lu, R. Luo, Q. Lv, H.K. Ma, B.Q. Ma, L.L. Ma, X.H. Mao, J.R. Min, Z. Mitthumsiri, W. Mu, H.J. Nan, Y.C. Neronov, A. Ou, Z.W. Pang, B.Y. Pattarakijwanich, P. Pei, Z.Y. Qi, M.Y. Qi, Y.Q. Qiao, B.Q. Qin, J.J. Ruffolo, D. Sáiz, A. Semikoz, D. Shao, C.Y. Shao, L. Shchegolev, O. Sheng, X.D. Shu, F.W. Song, H.C. Stenkin, Yu.V. Stepanov, V. Su, Y. Sun, Q.N. Sun, X.N. School of Physical Science and Technology Southwest Jiaotong University Chengdu610031 China Key Laboratory of Particle Astrophyics Experimental Physics Division Computing Center Institute of High Energy Physics Chinese Academy of Sciences Beijing100049 China University of Chinese Academy of Sciences Beijing100049 China TIANFU Cosmic Ray Research Center Sichuan Chengdu China Dublin Institute for Advanced Studies 31 Fitzwilliam Place Dublin 2 Ireland Max-Planck-Institut for Nuclear Physics P.O. Box 103980 Heidelberg69029 Germany State Key Laboratory of Particle Detection and Electronics China University of Science and Technology of China Anhui Hefei230026 China School of Physical Science and Technology School of Information Science and Technology Southwest Jiaotong University Sichuan Chengdu610031 China School of Astronomy and Space Science Nanjing University Jiangsu Nanjing210023 China Center for Astrophysics Guangzhou University Guangdong Guangzhou510006 China Hebei Normal University Hebei Shijiazhuang050024 China Key Laboratory of Dark Matter and Space Astronomy Key Laboratory of Radio Astronomy Purple Mountain Observatory Chinese Academy of Sciences Jiangsu Nanjing210023 China Tsung-Dao Lee Institute School of Physics and Astronomy Shanghai Jiao Tong University Shanghai200240 China Key Laboratory for Research in Galaxies and Cosmology Shanghai Astronomical Observatory Chinese Academy of Sciences Shanghai200030 China Key Laboratory of Cosmic Rays Tibet University Ministry of Education Tibet Lhasa850000 China National Astronomical Observatories Chinese Academy of Sciences Beijing100101 China School of Physics and Astronomy Sun Yat-sen University Zhuhai519000 China School of Physics Sun Yat-sen University Guangdong Guangzhou510275 China Sino-French Institute of Nuclear Engineering and Technology Sun Yat-sen University Zhuhai519000 China School of Physics and Astronomy Yunnan University Yunnan Kunming650091 China Départeme

The Large High Altitude Air Shower Observatory (LHAASO) has three sub-arrays, KM2A, WCDA, and WFCTA. As the major array of LHAASO, KM2A has been operating stably in shower mode. To study the near-earth atmospheric electric field (AEF) effect on the trigger event rate during thunderstorms, Monte Carlo simulations are performed with CORSIKA and G4KM2A. According to the simulations, the shower rate variations are found to be strongly dependent on the strength and polarity of the AEF. The shower rates increase with the field intensity. In positive AEF (defined as the direction pointing towards the ground), the increased amplitude is less than that in negative AEF. With the same field strength 1000 V/cm, the value exceeds 12% in a negative field, and merely is up to 6% in the positive one. The dependence of the trigger rate variation on the thickness of the AEF layer is also simulated. The shower event rate increases dramatically at small thickness, and then the trend of variation slows down with the AEF layer thickness. This indicates that the AEF with larger layer thickness has more deflection effects on the development of an extensive air shower. The shower rate variations are also found to be dependent on the primary zenith angle. Our simulation results could be useful in understanding the variation of trigger rate detected by LHAASO-KM2A during thunderstorms. © Copyright owned by the author(s) under the terms of the Creative Commons.

关键词： Cosmology

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