{"title":"基于动态概率风险评估的日本核电站事故序列前兆分析","authors":"K. Kubo","doi":"10.1155/2023/7402217","DOIUrl":null,"url":null,"abstract":"Probabilistic risk assessment (PRA) is an effective methodology that could be used to improve the safety of nuclear power plants in a reasonable manner. Dynamic PRA, as an advanced PRA, allows for more realistic and detailed analyses by handling time-dependent information. However, the applications of this method to practical problems are limited because it remains in the research and development stage. This study aimed to investigate the possibility of utilizing dynamic PRA in risk-informeddecision-making. Specifically, the author performed an accident sequence precursor (ASP) analysis on the failure of emergency diesel generators that occurred at Unit 1 of the Tomari Nuclear Power Plant in Japan using dynamic PRA. The results were evaluated by comparison with the results of simplified classical PRA. The findings indicated that dynamic PRA may estimate lower risks compared with those obtained from classical PRA by reasonable modeling of alternating current power recovery. The author also showed that dynamic PRA can provide detailed information that cannot be obtained with classical PRA, such as uncertainty distribution of core damage timing and importance measure considering the system failure timing.","PeriodicalId":21629,"journal":{"name":"Science and Technology of Nuclear Installations","volume":" ","pages":""},"PeriodicalIF":1.0000,"publicationDate":"2023-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Accident Sequence Precursor Analysis of an Incident in a Japanese Nuclear Power Plant Based on Dynamic Probabilistic Risk Assessment\",\"authors\":\"K. Kubo\",\"doi\":\"10.1155/2023/7402217\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Probabilistic risk assessment (PRA) is an effective methodology that could be used to improve the safety of nuclear power plants in a reasonable manner. Dynamic PRA, as an advanced PRA, allows for more realistic and detailed analyses by handling time-dependent information. However, the applications of this method to practical problems are limited because it remains in the research and development stage. This study aimed to investigate the possibility of utilizing dynamic PRA in risk-informeddecision-making. Specifically, the author performed an accident sequence precursor (ASP) analysis on the failure of emergency diesel generators that occurred at Unit 1 of the Tomari Nuclear Power Plant in Japan using dynamic PRA. The results were evaluated by comparison with the results of simplified classical PRA. The findings indicated that dynamic PRA may estimate lower risks compared with those obtained from classical PRA by reasonable modeling of alternating current power recovery. The author also showed that dynamic PRA can provide detailed information that cannot be obtained with classical PRA, such as uncertainty distribution of core damage timing and importance measure considering the system failure timing.\",\"PeriodicalId\":21629,\"journal\":{\"name\":\"Science and Technology of Nuclear Installations\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":1.0000,\"publicationDate\":\"2023-06-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Science and Technology of Nuclear Installations\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://doi.org/10.1155/2023/7402217\",\"RegionNum\":4,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"NUCLEAR SCIENCE & TECHNOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Science and Technology of Nuclear Installations","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1155/2023/7402217","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"NUCLEAR SCIENCE & TECHNOLOGY","Score":null,"Total":0}
Accident Sequence Precursor Analysis of an Incident in a Japanese Nuclear Power Plant Based on Dynamic Probabilistic Risk Assessment
Probabilistic risk assessment (PRA) is an effective methodology that could be used to improve the safety of nuclear power plants in a reasonable manner. Dynamic PRA, as an advanced PRA, allows for more realistic and detailed analyses by handling time-dependent information. However, the applications of this method to practical problems are limited because it remains in the research and development stage. This study aimed to investigate the possibility of utilizing dynamic PRA in risk-informeddecision-making. Specifically, the author performed an accident sequence precursor (ASP) analysis on the failure of emergency diesel generators that occurred at Unit 1 of the Tomari Nuclear Power Plant in Japan using dynamic PRA. The results were evaluated by comparison with the results of simplified classical PRA. The findings indicated that dynamic PRA may estimate lower risks compared with those obtained from classical PRA by reasonable modeling of alternating current power recovery. The author also showed that dynamic PRA can provide detailed information that cannot be obtained with classical PRA, such as uncertainty distribution of core damage timing and importance measure considering the system failure timing.
期刊介绍:
Science and Technology of Nuclear Installations is an international scientific journal that aims to make available knowledge on issues related to the nuclear industry and to promote development in the area of nuclear sciences and technologies. The endeavor associated with the establishment and the growth of the journal is expected to lend support to the renaissance of nuclear technology in the world and especially in those countries where nuclear programs have not yet been developed.