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Overview of KAGRA : Data transfer and management

Progress of Theoretical and Experimental Physics 2023年第10期2023卷

作者： Akutsu, T Ando, M Arai, K Arai, Y Araki, S Araya, A Aritomi, N Asada, H Aso, Y Bae, S Bae, Y Baiotti, L Bajpai, R Barton, M A Cannon, K Cao, Z Capocasa, E Chan, M Chen, C Chen, K Chen, Y Chiang, C-Y Chu, H Chu, Y-K Eguchi, S Enomoto, Y Flaminio, R Fujii, Y Fujikawa, Y Fukunaga, M Fukushima, M Gao, D Ge, G Ha, S Hagiwara, A Haino, S Han, W-B Hasegawa, K Hattori, K Hayakawa, H Hayama, K Himemoto, Y Hiranuma, Y Hirata, N Hirose, E Hong, Z Hsieh, B Huang, G-Z Huang, H-Y Huang, P Huang, Y-C Huang, Y Hui, D C Y Ide, S Ikenoue, B Imam, S Inayoshi, K Inoue, Y Ioka, K Ito, K Itoh, Y Izumi, K Jeon, C Jin, H-B Jung, K Jung, P Kaihotsu, K Kajita, T Kakizaki, M Kamiizumi, M Kanda, N Kang, G Kawaguchi, K Kawai, N Kawasaki, T Kim, C Kim, J Kim, J C Kim, W S Kim, Y-M Kimura, N Kita, N Kitazawa, H Kobayashi, Y Kojima, Y Kokeyama, K Komori, K Kong, A K H Kotake, K Kozakai, C Kozu, R Kumar, R Kume, J Kuo, C Kuo, H-S Kuromiya, Y Kuroyanagi, S Kusayanagi, K Kwak, K Lee, H K Lee, H W Lee, R Leonardi, M Li, K L Lin, L C-C Lin, C-Y Lin, F-K Lin, F-L Lin, H L Liu, G C Luo, L-W Majorana, E Marchio, M Michimura, Y Mio, N Miyakawa, O Miyamoto, A Miyazaki, Y Miyo, K Miyoki, S Mori, Y Morisaki, S Moriwaki, Y Nagano, K Nagano, S Nakamura, K Nakano, H Nakano, M Nakashima, R Nakayama, Y Narikawa, T Naticchioni, L Negishi, R Quynh, L Nguyen Ni, W-T Nishizawa, A Nozaki, S Obuchi, Y Ogaki, W Oh, J J Oh, K Oh, S H Ohashi, M Ohashi, T Ohishi, N Ohkawa, M Ohta, H Okutani, Y Okutomi, K Oohara, K Ooi, C Oshino, S Otabe, S Pan, K Pang, H Parisi, A Park, J Arellano, F E Peña Pinto, I Sago, N Saito, S Saito, Y Sakai, K Sakai, Y Sakuno, Y Sasaki, Y Sato, S Sato, T Sawada, T Sekiguchi, T Sekiguchi, Y Shao, L Shibagaki, S Shimizu, R Shimoda, T Shimode, K Shinkai, H Shishido, T Shoda, A Somiya, K Son, E J Sotani, H Sugimoto, R Suresh, J Suzuki, T Tagoshi, H Takahashi, H Takahashi, R Takamori, A Takano, S Takeda, H Takeda, M Tanaka, H Tanaka, K Tanaka, T Tanioka, S Martin, E N Tapia San Telada, S Tomaru, T Tomigami, Y Tomura, T Travasso, F Trozzo, L Tsang, T Ts Gravitational Wave Science Project National Astronomical Observatory of Japan (NAOJ) 2-21-1 Osawa Mitaka City Tokyo 181-8588 Japan Advanced Technology Center National Astronomical Observatory of Japan (NAOJ) 2-21-1 Osawa Mitaka City Tokyo 181-8588 Japan Department of Physics The University of Tokyo 7-3-1 Hongo Bunkyo-ku Tokyo 113-0033 Japan Research Center for the Early Universe (RESCEU) The University of Tokyo 7-3-1 Hongo Bunkyo-ku Tokyo 113-0033 Japan Institute for Cosmic Ray Research (ICRR) KAGRA Observatory The University of Tokyo 5-1-5 Kashiwa-no-Ha Kashiwa City Chiba 277-8582 Japan Accelerator Laboratory High Energy Accelerator Research Organization (KEK) 1-1 Oho Tsukuba City Ibaraki 305-0801 Japan Earthquake Research Institute The University of Tokyo 1-1-1 Yayoi Bunkyo-ku Tokyo 113-0032 Japan Department of Mathematics and Physics Hirosaki University 3 Bunkyo-cho Hirosaki City Aomori 036-8561 Japan Kamioka Branch National Astronomical Observatory of Japan (NAOJ) 238 Higashi-Mozumi Kamioka-cho Hida City Gifu 506-1205 Japan The Graduate University for Advanced Studies (SOKENDAI) 2-21-1 Osawa Mitaka City Tokyo 181-8588 Japan Korea Institute of Science and Technology Information (KISTI) 245 Daehak-ro Yuseong-gu Daejeon 34141 Korea National Institute for Mathematical Sciences 70 Yuseong-daero 1689 Beon-gil Yuseong-gu Daejeon 34047 Korea International College Osaka University 1-1 Machikaneyama-cho Toyonaka City Osaka 560-0043 Japan School of High Energy Accelerator Science The Graduate University for Advanced Studies (SOKENDAI) 1-1 Oho Tsukuba City Ibaraki 305-0801 Japan Department of Astronomy Beijing Normal University No. 19 Xinjiekou Street Beijing 100875 China Department of Applied Physics Fukuoka University 8-19-1 Nanakuma Jonan Fukuoka City Fukuoka 814-0180 Japan Department of Physics Tamkang University No. 151 Yingzhuan Rd. Danshui Dist. New Taipei City 25137 Taiwan Department of Physics and Institute of Astronomy Nation

KAGRA is a newly built gravitational wave observatory, a laser interferometer with a 3 km arm length, located in Kamioka, Gifu prefecture, Japan. In this article, we describe the KAGRA data management system, i.e., recording of data, transfer from the KAGRA experiment site to computing resources, as well as data distribution to tier sites, including international sites in Taiwan and Korea. The amount of KAGRA data exceeded 1.0 PiB and increased by about 1.5 TB per day during operation in 2020. Our system has succeeded in data management, and has achieved performance that can withstand observations after 2023, that is, a transfer rate of 20 MB s-1or more and file storage of sufficient capacity for petabyte class. We also discuss the sharing of data between the global gravitational-wave detector network with other experiments, namely LIGO and Virgo. The latency, which consists of calculation of calibrated strain data and transfer time within the global network, is very important from the view of multi-messenger astronomy using gravitational waves. Real-time calbrated data delivered from the KAGRA detector site and other detectors to our computing system arrive with about 4–15 seconds of latency. These latencies are sufficiently short compared to the time taken for gravitational wave event search computations. We also established a high-latency exchange of offline calibrated data that was aggregated with a better accuracy compared with real-time data.

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Short-term prediction model of module temperature for photovoltaic power forcasting based on support vector machine

Short-term prediction model of module temperature for photov...

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International Conference on Renewable Power Generation, RPG 2015

作者： Sun, Yujing Wang, Fei Mi, Zengaiang Sun, Hongbin Liu, Chun Wang, Bo Lu, Jing Zhen, Zhao Li, Kangping State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources North China Electric Power University Baoding Hebei Province071003 China State Key Laboratory of Control and Simulation of Power Systems and Generation Equipment Department of Electrical Engineering Tsinghua University Haidian District Beijing100084 China China Electric Power Research Institute Haidian District Beijing100192 China

ISBN: (纸本)9781785610400

To improve the prediction accuracy of photovoltaic (PV) power generation, the temperature of PV modules and its prediction is very important. A short-term step-wise temperature prediction model for PV module based on Support Vector Machine (SVM) is proposed in this paper. Firstly, the primary impact factors of PV module temperature are determined in terms of the PV module physical characteristics and the correlation coefficient between each factor and module temperature. Secondly, two kinds of prediction models, direct and step-wise models, are built to predict module temperature respectively. For direct model, the prediction model is based on SVM using the historical data. For step-wise one, the prediction models of the primary impact factors are built at the first step and then the mapping models between module temperature and the impact factors are established. In the end, the deviations of two different kinds of prediction models are analyzed and discussed based on actual operation data. The results indicate that the stepwise prediction model has better accuracy than the direct prediction model if other things are equal.

关键词： Forecasting

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Cloud identification model for sky images based on Otsu

Cloud identification model for sky images based on Otsu

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International Conference on Renewable Power Generation, RPG 2015

作者： Li, Hongping Wang, Fei Ren, Hui Sun, Hongbin Liu, Chun Wang, Bo Lu, Jing Zhen, Zhao State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources North China Electric Power University Baoding Hebei Province071003 China State Key Laboratory of Control and Simulation of Power Systems and Generation Equipment Department of Electrical Engineering Tsinghua University Haidian District Beijing100084 China China Electric Power Research Institute Haidian District Beijing100192 China

ISBN: (纸本)9781785610400

Irradiance changes caused by clouds movement are the mam factors, which lead to mutation of photovoltaic power. In order to increase the accuracy of the ultra-short-term photovoltaic power prediction, based on of clouds images, the cloud identification for sky images is one of the primary aspects for improving photovoltaic power accuracy. A cloud identification model for sky images is established based on Otsu. Firstly, a series of sky images are collected by Total Sky Imager (TSI) with the regions of clouds and sky are distinguished. Secondly, the color features (based on RGB values) of pixels in sample images and the spectral and texture features of the whole image are extracted;Finally, we established a cloud identification model for sky images based on Otsu according to the clouds' and sky areas' division and the general characteristics featured by pixels and images. The simulated results show that the model in this paper can identify the clouds in a sky images effectively.

关键词： Pixels

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Photovoltaic plant Operating Statuses Identification model based on support vector machine using loss quantity of electricity feature parameters

Photovoltaic plant Operating Statuses Identification model b...

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International Conference on Renewable Power Generation, RPG 2015

作者： Li, Kangping Wang, Fei Zhen, Zhao Sun, Yujing Mi, Zengqiang Sun, Hongbin Liu, Chun Wang, Bo Lu, Jing State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources North China Electric Power University Baoding Hebei Province071003 China State Key Laboratory of Control and Simulation of Power Systems and Generation Equipment Department of Electrical Engineering Tsinghua University Haidian District Beijing100084 China China Electric Power Research Institute Haidian District Beijing100192 China

ISBN: (纸本)9781785610400

Operating Statuses Identification (OSI) can help operators to find fault timely and minimize the loss. So it is of great significance for optimal operation of photovoltaic (PV) plants. The loss quantity of electricity (LQOE) is defined as that should have been generated but actually not, which is caused by inverter fault, PV modules fault, dust stratification or combinations of them. Firstly, mathematical models of PV cells are proposed to figure out the LQOE of each PV module. Secondly, after analysing the relation between LQOE and operating statuses, an index set of LQOE describing the distinction of different operating statuses are defined including four statistical feature parameters and a user-defined index. Thirdly, Support Vector Classification models for OSI (OSI-SVC) are built with input features extracted from the index set. Lastly, simulations are carried out to verify the effectiveness and evaluate the performance of the OSI-SVC models. The results indicated that the operating statuses can be effectively recognized by the proposed model.

关键词： Support vector machines

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Electro-peroxone degradation of diethyl phthalate: Cathode selection, operational parameters, and degradation mechanisms

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Journal of hazardous materials 2016年 319卷 61-8页

作者： Meifang Hou Yaofei Chu Xiang Li Huijiao Wang Weikun Yao Gang Yu Seiichi Murayama Yujue Wang School of Ecological Technology and Engineering Shanghai Institute of Technology Shanghai 201418 China. School of Ecological Technology and Engineering Shanghai Institute of Technology Shanghai 201418 China School of Environment Beijing Key Laboratory for Emerging Organic Contaminants Control State Key Joint Laboratory of Environmental Simulation and Pollution Control Tsinghua University Beijing 100084 China. School of Environment Beijing Key Laboratory for Emerging Organic Contaminants Control State Key Joint Laboratory of Environmental Simulation and Pollution Control Tsinghua University Beijing 100084 China. Power and Industrial Systems R&D Center Toshiba Corporation Fuchu-shi Tokyo Japan. School of Environment Beijing Key Laboratory for Emerging Organic Contaminants Control State Key Joint Laboratory of Environmental Simulation and Pollution Control Tsinghua University Beijing 100084 China. Electronic address: wangyujue@***.

This study compares the degradation of diethyl phthalate (DEP) by the electro-peroxone (E-peroxone) process with three different carbon-based cathodes, namely, carbon-polytetrafluorethylene (carbon-PTFE), carbon felt, and reticulated vitreous carbon (RVC). Results show that the three cathodes had different electrocatalytic activity for converting sparged O2 to H2O2, which increased in order of carbon felt, RVC, and carbon-PTFE. The in-situ generated H2O2 then reacts with sparged O3 to yield OH, which can in turn oxidize ozone-refractory DEP toward complete mineralization. In general, satisfactory total organic carbon removal yields (76.4-91.8%) could be obtained after 60min of the E-peroxone treatment with the three carbon-based cathodes, and the highest yield was obtained with the carbon-PTFE cathode due to its highest activity for H2O2 generation. In addition, the carbon-PTFE and carbon felt cathodes exhibited excellent stability over six cycles of the E-peroxone treatment of DEP solutions. Based on the intermediates (e.g., monoethyl phthalate, phthalic acid, phenolics, and carboxylic acids) identified by HPLC-UV, plausible reaction pathways were proposed for DEP mineralization by the E-peroxone process. The results of this study indicate that carbon-based cathodes generally have good electrocatalytic activity and stability for application in extended E-peroxone operations to effectively remove phthalates from water.

关键词： Electrocatalytic ozonation Electrode Hydrogen peroxide Ozone Phthalates

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Method of coordination among strongly coupled power plants for automatic voltage control

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Dianli Xitong Zidonghua/Automation of Electric Power systems 2015年第12期39卷 165-171页

作者： Wang, Bin Guo, Qinglai Sun, Hongbin Tang, Lei Zhang, Boming Tian, Junjie Department of Electrical Engineering Tsinghua University Beijing100084 China State Key Laboratory of Control and Simulation of Power Systems and Generation Equipments Tsinghua University Beijing100084 China Dispatching and Communication Center of State Grid Shanxi Electric Power Corporation Taiyuan030001 China

To solve the problem of reactive power non-coordination among strongly coupled plants, a coordinating method for strongly coupled plants for automatic voltage control (AVC) is proposed. The coupling coefficient among plants is introduced, and the plant coordinating group is generated as the coordinating unit. The reactive power unbalanced index among strongly coupled plants is defined. And the current operation state of power grid is determined. In the event the pilot bus voltage is not controlled in place, the control strategy of voltage regulation and reactive power tracking control is adopted so that the pilot bus voltage will be enabled to guarantee that the reactive power unbalanced index between strongly coupled plants will meet the control requirement while tracking optimal settings. If the pilot bus voltage is already in place, reactive correction control based on the objective of plant-to-plant coordination will be carried out to reduce the deviation in reactive load while ensuring that the pilot bus voltage is maintained within the range of control dead zone. Reactive regulating commands will be added to the traditional voltage regulating commands to suppress possible irrational reactive power distribution or reactive fluctuation between strongly coupled plants. Application of the proposed method in a number of regional and provincial grids in China shows that the proposed method is able to reduce irrational reactive power distribution between strongly coupled plants. © 2015 State Grid Electric Power Research Institute Press.

关键词： Reactive power

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Smart substation advanced application software adapted for two-level distributed smart dispatch and control

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Dianli Xitong Zidonghua/Automation of Electric Power systems 2015年第1期39卷 233-240页

作者： Sun, Hongbin Mu, Jianan Sheng, Tongtian Li, Qingxin Wang, Jing Wang, Bin Wang, Xuran Ji, Guoqiang Wu, Wenchuan Guo, Qinglai Li, Yalou Wang, Dexing Department of Electrical Engineering Tsinghua University Beijing100084 China State Key Laboratory of Control and Simulation of Power Systems and Generation Equipments Tsinghua University Beijing100084 China China Electric Power Research Institute Beijing100192 China East China Electric Power Dispatching and Control Sub-Center of State Grid Shanghai200120 China

The development of smart grid has posed a challenge to the traditional centralized dispatch mode. The basic contradiction between distributed autonomy and centralized coordination is reexamined, and an architecture of smart substation advanced application software system is proposed, including such advanced applications as modeling, state estimation, intelligent alarming, voltage stability assessment and control, automatic voltage control, risk assessment modeling, etc. This facilitates a change from centralized dispatch and control mode to a more reliable, agile substation-control center two-level distributed smart dispatch and control mode. The features, functions and realization of the proposed advanced application software are described, some field engineering application cases demonstrated, and certain practical aspects of implementation discussed. Finally, the prospect for future development of the smart substation advanced application software is displayed.

关键词： State estimation

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A Travel Time Prediction Method for Urban Road Traffic Sensors Data

A Travel Time Prediction Method for Urban Road Traffic Senso...

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International Conference on Identification, Information and Knowledge in the Internet of Things (IIKI)

作者： Guangyu Zhu Kang Song Peng Zhang Ministry of Education Key Laboratory of System Control and Information Processing Shanghai China MOE Key Laboratory for Transportation Complex Systems- Theory and Technology Beijing Jiaotong University Beijing China Beijing Municipality Key Laboratory of Urban Traffic Operation Simulation and Decision Support Beijing China

Travel time parameters obtained from road traffic sensors data play an important role in traffic management practice. In this paper, a travel time analysis and prediction model was established for urban road traffic sensors data based on the change point analysis algorithm and ARIMA model. Firstly, time series of travel time parameters were clustered by using change point mining algorithm after traffic sensors data preprocessing. Then, a travel time prediction model was established based on ARIMA model. Finally, the model was verified with high accuracy through simulation by using multiple sets of data and analysis of its practicability was done.

关键词： Predictive models Data models Roads Time series analysis Detectors Analytical models

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Flight testing a real-time hazard detection system for safe lunar landing on the rocket-powered morpheus vehicle

Flight testing a real-time hazard detection system for safe ...

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AIAA Guidance, Navigation, and control Conference 2015, MGNC 2015 - Held at the AIAA SciTech Forum 2015

作者： Trawny, Nikolas Huertas, Andres Luna, Michael E. Villalpando, Carlos Y. Martin, Keith E. Carson, John M. Johnson, Andrew E. Restrepo, Carolina Roback, Vincent E. GN&C Hardware and Testbed Development Group Jet Propulsion Laboratory California Institute of Technology PasadenaCA91109 United States Maritime & Aerial Perception Systems Group Jet Propulsion Laboratory California Institute of Technology PasadenaCA91109 United States Guidance & Control Operations Group Jet Propulsion Laboratory California Institute of Technology PasadenaCA91109 United States Advanced Computer Systems & Technologies Group Jet Propulsion Laboratory California Institute of Technology PasadenaCA91109 United States Simulation & Support Equipment Group Jet Propulsion Laboratory California Institute of Technology PasadenaCA91109 United States Jet Propulsion Laboratory California Institute of Technology PasadenaCA91109 United States Integrated GN&C Analysis Branch NASA Johnson Space Center HoustonTX77058 United States Remote Sensing Flight Systems Branch NASA Langley Research Center HamptonVA23681 United States

ISBN: (纸本)9781510801097

The Hazard Detection System (HDS) is a component of the ALHAT (Autonomous Landing and Hazard Avoidance Technology) sensor suite, which together provide a lander Guidance, Navigation and control (GN&C) system with the relevant measurements necessary to enable safe precision landing under any lighting conditions. The HDS consists of a stand-alone compute element (CE), an Inertial Measurement Unit (IMU), and a gimbaled ash LIDAR sensor that are used, in real-time, to generate a Digital Elevation Map (DEM) of the landing terrain, detect candidate safe landing sites for the vehicle through Hazard Detection (HD), and generate hazard-relative navigation (HRN) measurements used for safe precision landing. Following an extensive ground and helicopter test campaign, ALHAT was integrated onto the Morpheus rocket-powered terrestrial test vehicle in March 2014. Morpheus and ALHAT then performed five successful free flights at the simulated lunar hazard field constructed at the Shuttle Landing Facility (SLF) at Kennedy Space Center, for the first time testing the full system on a lunar-like approach geometry in a relevant dynamic environment. During these flights, the HDS successfully generated DEMs, correctly identified safe landing sites and provided HRN measurements to the vehicle, marking the first autonomous landing of a NASA rocket-powered vehicle in hazardous terrain. This paper provides a brief overview of the HDS architecture and describes its in-flight performance. © 2015, E-flow American Institute of Aeronautics and Astronautics (AIAA). All rights reserved.

关键词： Hazards

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An Improved OPA Model in Power System Considering Planning 33

An Improved OPA Model in Power System Considering Planning

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第三十三届中国控制会议

作者： GONG Yuan MEI Shengwei PENG Dong LONG Wangcheng GUO Mingxing Power Systems and Power Generation Equipment Control and Simulation National Key Laboratory Department of Electrical Engineering Tsinghua University State Power Economic Research Institute

ISBN: (纸本)9781479947249

The power system now is a typical complex system, which has inherent characteristics of SOC. Studying on cascading failures are necessary and meaningful to insure the grid's safety, national security and economic development. This paper firstly establishes the indices of power system development diagnosis, which are closely relevant to the trigger of power system evolution. Then a cascading failure model is proposed, considering planning and evolution of the power system. This model is based on OPA model, including both fast dynamics and slow dynamics. The slow dynamic process simulates the evolution of power system, which represents the functions of the planning department, while the fast dynamic process simulates power flow and cascading failures, which takes the effects of dispatch, relay protection and automation into consideration. Moreover, simulations are tested on the case of Kaifeng-Shangqiu power system in Henan Province of China, and evolution results are presented.

关键词： Power system evolution,cascading failure,power system diagnosis,power grid complexity,OPA model

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