Probabilistic typhoon hazard and sensitivity analysis for nuclear power plant sites in Korea using logic tree

被引:0
作者
Kim, Gungyu [1 ]
Kwag, Shinyoung [2 ]
Choun, Youngsun [3 ]
Eem, Seunghyun [1 ]
机构
[1] Kyungpook Natl Univ, Dept Convergence & Fus Syst Engn, Daegu, South Korea
[2] Hanbat Natl Univ, Dept Civil & Environm Engn, Daejeon, South Korea
[3] CENITS Corp Inc, Inst Technol, Uiryeong, South Korea
基金
新加坡国家研究基金会;
关键词
Logic tree; Monte Carlo simulation; Probabilistic typhoon wind hazard assessment; Wind hazard curve; Sensitivity analysis; HURRICANE WIND SPEEDS;
D O I
10.1016/j.pnucene.2024.105347
中图分类号
TL [原子能技术]; O571 [原子核物理学];
学科分类号
0827 ; 082701 ;
摘要
There has been an increase in typhoon intensity, and high-intensity typhoons can affect the safety of nuclear power plants (NPPs). Typhoons can damage the structures, systems, and components (SSCs) of NPPs, causing core damage and the release of radioactive materials into the environment. Therefore, design criteria for the effects of natural phenomena are demanded to ensure the safety-critical SSC functions of NPPs. Also, there is a need for safety assessments of typhoons in operational NPPs, which require typhoon hazard analysis. In this study, we derived typhoon hazards for NPPs in Korea using Logic Tree and Monte Carlo simulations. We performed sensitivity analysis on the typhoon hazards based on the distances (up to 100 km) from the NPP sites. Among other NPP sites, the typhoon hazard of the Kori site showed the highest wind speed, and the Hanul site showed the lowest wind speed. The uncertainty of the wind speed increased as the recurrence interval of the typhoon hazard increased. We compared the typhoon hazard in the areas of interest to that within 100 km. The range of the distance deviation for the Hanbit site's typhoon hazard was within mu +/-sigma up to 75 km, while for the other sites, it was within mu +/-sigma up to 100 km.
引用
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页数:18
相关论文
共 30 条
[1]  
[Anonymous], 2007, Design-Basis Tornado and Tornado Missiles for Nuclear Power Plants
[2]  
[Anonymous], TROPICAL CYCLONES
[3]  
BATTS ME, 1980, J STRUCT DIV-ASCE, V106, P2001
[4]  
Cho KH, 2009, P WIND ENG I KOR SEO, P39
[5]   Logic tree approach for probabilistic typhoon wind hazard assessment [J].
Choun, Young-Sun ;
Kim, Min-Kyu .
NUCLEAR ENGINEERING AND TECHNOLOGY, 2019, 51 (02) :607-617
[6]  
Electric Power Research Institute (EPRI), 2015, TR-3002003107
[7]  
Fujii T, 1998, MON WEATHER REV, V126, P1091, DOI 10.1175/1520-0493(1998)126<1091:SAOTCO>2.0.CO
[8]  
2
[9]  
Golnaraghi M., 2014, Climate and Water Extremes (1970-2012)
[10]  
Harper B A., 2010, Guidelines for converting between various wind averaging periods in tropical cyclone conditions