Initialising ...
Initialising ...
Initialising ...
Initialising ...
Initialising ...
Initialising ...
Initialising ...
Futagami, Satoshi; Yamano, Hidemasa; Kurisaka, Kenichi; Ujita, Hiroshi*
Proceedings of proceedings of PSAM 2023 Topical Conference AI & Risk Analysis for Probabilistic Safety/Security Assessment & Management, 8 Pages, 2023/10
To create an innovation for efficient and effective social implementation of nuclear power plant PRA, automatic construction tool for fault tree architecture and automatic failure judgment tool to construct reliability database are developed by using AI and digitization technology. This paper describes overall development plan of PRA methodology using the AI technology and the progress of automatic FT creation tools development.
Takahara, Shogo; Iijima, Masashi*; Yoneda, Minoru*; Shimada, Yoko*
Risk Analysis, 39(1), p.212 - 224, 2019/01
Times Cited Count：5 Percentile：48.71(Public, Environmental & Occupational Health)A dose assessment model was developed based on measurements and surveys of individual doses and relevant contributors in Fukushima City for four population groups: Fukushima City Office staff, Senior Citizens' Club, Contractors' Association, and AgriculturalCooperative. In addition, probabilistic assessments were performed for these population groups by considering the spatial variability of contamination and interpopulation differencesresulting from behavior patterns. As a result of comparison with the actual measurements, the assessment results for participants from the Fukushima City Office, Senior Citizens' Club and the Agricultural Cooperative agreed with the measured values. By contrast, the measurements obtained for the participants from the Contractors' Association were not reproduced well in the present study. To assess the doses to this group, further investigations of association members' work activities and the related dose reduction effects are needed.
Takahara, Shogo; Ikegami, Maiko*; Yoneda, Minoru*; Kondo, Hitoshi*; Ishizaki, Azusa; Iijima, Masashi; Shimada, Yoko*; Matsui, Yasuto*
Risk Analysis, 37(7), p.1256 - 1267, 2017/07
Times Cited Count：6 Percentile：52.04(Public, Environmental & Occupational Health)Suzuki, Atsuyuki
Risk Analysis, 34(7), p.1240 - 1256, 2014/07
Times Cited Count：14 Percentile：71.17(Public, Environmental & Occupational Health)The Fukushima Daiichi accident raises a fundamental question: Can science and technology prevent the inevitability of serious accidents, especially those with low probabilities and high consequences? This question reminds us of a longstanding challenge with the trans-sciences, originally addressed by Alvin Weinberg well before the Three Mile Island and Chernobyl accidents. This paper, revisiting Weinberg's issue, aims at gaining insights from the accident with a special emphasis on the socio-technical or human behavioral aspects lying behind the accident's causes. In particular, an innovative method for managing the challenge is explored referring to behavioral science approaches for a decision-making process on risk management; such as managing human behavioral risks with information asymmetry, seeking a rational consensus with communicative action, and pursuing procedural rationality through interactions with the outer environment. In short, this paper describes the emerging needs for Japan to transform its national safety management institutions so that these might be based on interactive communication with parties inside and outside Japan.
Shu, Y.; Nakajima, Norihiro
Proceedings of 1st International Workshop on Risk Management System with Intelligent Data Analysis (RMDA 2005) in Conjunction with 19th Annual Conference of the Japanese Society for Artificial Intelligence (JSAI 2005), p.35 - 44, 2005/06
This paper presents an intelligent information inference system based on a hybrid data mining approach, which integrates human cognitive model in a data mining loop. In the proposed system, the mining control agent emulated human analysts interacts directly with the data miner, analyzing and verifying the output of the data miner and controlling the data mining process. In additional, the neural network method, which is adopted as a core component of the proposed hybrid data mining method, is evolved by adding the retraining facility and explaining function for handling complicated quake-proof data of nuclear power plant. To demonstrate how the method can be used as a powerful tool for extracting information relevant to plant safety and reliability, plant quake-proof testing data have been applied to the inference system.
