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Okuno, Hiroshi; Yamamoto, Kazuya
JAEA-Review 2020-066, 32 Pages, 2021/02
JAEA-Review-2020-066.pdf:3.01MB
The International Atomic Energy Agency (abbreviated as IAEA) has been implementing the Asian Nuclear Safety Network (abbreviated as ANSN) activities since 2002. As part of this effort, Topical Group on Emergency Preparedness and Response (abbreviated as EPRTG) for nuclear or radiation disasters was established in 2006 under the umbrella of the ANSN. Based on the EPRTG proposal, the IAEA conducted 23 Asian regional workshops in the 12 years from 2006 to 2017. Typical topical fields of the regional workshops were nuclear emergency drills, emergency medical care, long-term response after nuclear/radiological emergency, international cooperation, national nuclear disaster prevention system. The Japan Atomic Energy Agency has produced coordinators for EPRTG since its establishment and has led its activities since then. This report summarizes the Asian regional workshops conducted by the IAEA based on the recommendations of the EPRTG.
Fukahori, Tokio
Kaku Deta Nyusu (Internet), (125), p.20 - 25, 2020/02
This report is review on one of the series presentations on "Work Reports on Nuclear Data of Sigma Special Advisory Committee in 2017-2018" at the Fall Meeting of Atomic Energy Society of Japan (AESJ). In this report, the work plan of this Committee in the next two-years period is introduced. The AESJ Investigation Advisory Committee on Nuclear Data researches world-wide nuclear data activities, reports from the view point of wide range collaborative fields, contributes to Japanese nuclear data investigation activities with contacting many of related organizations.
Yoshizawa, Atsufumi*; Oba, Kyoko; Kitamura, Masaharu*
Nihon Genshiryoku Gakkai Wabun Rombunshi, 18(2), p.55 - 68, 2019/06
This study aims to improve the potential of an emergency response by analyzing the workload management during the accident at the Emergency Response Center (ERC) of TEPCO's Fukushima Daiichi Nuclear Power Plant. Specifically, the research focused on the response of the ERC during the time between the discontinuation of Unit 3 core water injection and its recovery. It identified the different types of workload at the ERC had and how they had been managed based on the record of a TV conference. It also deduced the casual factors of the responses, supplementing the interview record of the director of ERC at the time by applying workload management analysis. On the basis of these findings, lessons to enhance the potential of the on-site emergency response have been obtained for ERC and outside organizations.
Ono, Tomio*; Subekti, M.*; Kudo, Kazuhiko*; Takamatsu, Kuniyoshi; Nakagawa, Shigeaki; Nabeshima, Kunihiko
Nihon Genshiryoku Gakkai Wabun Rombunshi, 4(2), p.115 - 126, 2005/06
Control-rod withdrawal tests simulating reactivity insertion are carried out in the HTTR to verify the inherent safety features of HTGRs. This paper describes pre-test analysis method using artificial neural networks to predict the changes of reactor power and reactivity. The network model applied in this study is based on recurrent neural networks. The inputs of the network are the changes of the central control rods position and other significant core parameters, and the outputs are the changes of reactor power and reactivity. Furthermore, Time Synchronizing Signal(TSS) is added to input to improve the modeling of time series data. The actual tests data, which were previously carried out in the HTTR, were used for learning the model of the plant dynamics. After the learning, the network can predict the changes of reactor power and reactivity in the following tests.
Minehara, Eisuke; Hajima, Ryoichi; Iijima, Hokuto; Kikuzawa, Nobuhiro; Nagai, Ryoji; Nishimori, Nobuyuki; Nishitani, Tomohiro; Sawamura, Masaru; Yamauchi, Toshihiko
Proceedings of 27th International Free Electron Laser Conference (FEL 2005) (CD-ROM), p.305 - 308, 2005/00
The JAERI high power ERL-FEL has been extended to the more powerful and efficient free-electron laser (FEL) than 10kW for nuclear energy industries, and other heavy industries like defense, shipbuilding, chemical industries, environmental sciences, space-debris, and power beaming and so on. In order to realize such a tunable, highly-efficient, high average power, high peak power and ultra-short pulse FEL, we need the efficient and powerful FEL driven by the JAERI compact, stand-alone and zero boil-off super-conducting RF linac with an energy-recovery geometry. Our discussions on the ERL-FEL will cover the current status of the 10kW upgrading and its applications of non-thermal peeling, cutting, and drilling to decommission the nuclear power plants, and to demonstrate successfully the proof of principle prevention of cold-worked stress-corrosion cracking failures in nuclear power reactors under routine operation using small cubic low-Carbon stainless steel samples.
Suzuki, Mitsuhiro
JAERI-Review 2004-013, 123 Pages, 2004/05
JAERI-Review-2004-013.pdf:6.62MB
no abstracts in English
Nabeshima, Kunihiko; Ayaz, E.*; Seker, S.*; Barutcu, B.*; T
rkcan, E.*
Proceedings of International Conference on Artificial Neural Networks and the International Conference on Neural Information Processing (ICANN/ICONIP 2003), p.406 - 409, 2003/06
On-line plant monitoring system with neural networks and an expert system has been developed for Borssele Nuclear Power Plant (NPP) in the Netherlands. The feedforward and the recurrent neural networks are utilized for plant modeling and anomaly detection. The rule-based expert system is applied for plant diagnosis with the outputs of the neural networks. The off-line results showed that the neural network could model the plant dynamics precisely. The on-line results indicated that the monitoring system could sufficiently diagnose the plant status in real time.
Nabeshima, Kunihiko; Suzudo, Tomoaki; Ono, Tomio*; Kudo, Kazuhiko*
Mathematics and Computers in Simulation, 60(3-5), p.233 - 244, 2002/09
Times Cited Count：15 Percentile：69.77(Computer Science, Interdisciplinary Applications)This study presents a hybrid monitoring system for nuclear reactor utilizing neural networks and a rule-based real-time expert system. The whole monitoring system including a data acquisition system and the advisory displays has been tested by an on-line simulator of pressurized water reactor. From the testing results, it was shown that the neural network in the monitoring system successfully modeled the plant dynamics and detected the symptoms of anomalies earlier than the conventional alarm system. The real-time expert system also worked satisfactorily in diagnosing and displaying the system status by using the outputs of neural networks and a priori knowledge base.
Nabeshima, Kunihiko; Suzudo, Tomoaki; Ono, Tomio*; Kudo, Kazuhiko*
Knowledge-Based Intelligent Information Engineering Systems & Allied Technologies, p.1506 - 1510, 2001/09
no abstracts in English
Nabeshima, Kunihiko; Tuerkcan, E.*; Suzudo, Tomoaki; Nakagawa, Shigeaki; Inoue, K.*; Oono, Tomio*; *; Suzuki, Katsuo
Proc. of Human-Computer Interaction International'99, 2, p.1187 - 1191, 1999/00
no abstracts in English
Nabeshima, Kunihiko; Suzudo, Tomoaki; Suzuki, Katsuo; Tuerkcan, E.*
Journal of Nuclear Science and Technology, 35(2), p.93 - 100, 1998/02
Times Cited Count：36 Percentile：91.61(Nuclear Science & Technology)no abstracts in English
Nabeshima, Kunihiko; Suzuki, Katsuo; Nose, Shoichi*; *
Monitoring and Diagnosis Systems to Improve Nuclear Power Plant Reliability and Safety, 0, p.17 - 26, 1996/00
no abstracts in English
Nabeshima, Kunihiko; Suzuki, Katsuo; E.Tuerkcan*
Proc. of 9th Power Plant Dynamics, Control & Testing Symp., Vol. 1, 0, p.51.01 - 51.09, 1995/00
no abstracts in English
Nabeshima, Kunihiko; Suzuki, Katsuo; E.Tuekcan*
SMORN-VII,Symp. on Nuclear Reactor Surveillance and Diagnostics,Vol. 1, 0, P. 4_1, 1995/00
no abstracts in English
Yanagihara, Satoshi;
JAERI-M 94-005, 61 Pages, 1994/02
no abstracts in English
Yanagihara, Satoshi; ; ; Fujiki, Kazuo
1st JSME/ASME Joint Int. Conf. on Nuclear Engineering, p.65 - 70, 1991/00
no abstracts in English
Fukahori, Tokio
no journal, ,
This report is one of the series presentations on "Work Reports on Nuclear Data of Sigma Special Advisory Committee in 2017-2018". The Investigation Advisory Committee on Nuclear Data researches world-wide nuclear data activities, reports from the view point of wide range collaborative fields, contributes to Japanese nuclear data investigation activities with contacting many of related organizations. In this presentation, the work plan of the Committee in the next two-years period is introduced.
