• 제목/요약/키워드: Graph operation

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베이지안 네트워크를 이용한 지진 유발 화재・폭발 복합재해 확률론적 안전성 평가 (Bayesian Network-based Probabilistic Safety Assessment for Multi-Hazard of Earthquake-Induced Fire and Explosion)

  • 이세혁;석의찬;송준호
    • 한국전산구조공학회논문집
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    • 제37권3호
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    • pp.205-216
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    • 2024
  • 최근 원자력 지진 PSA(Probabilistic Safety Assessment)를 토대로 산업시설물의 지진 PSA를 수행하는 연구가 진행되었다. 해당 연구는 원자력 발전소와 산업시설물의 차이를 파악하고, 최종적으로 운영정지를 목표로 하는 고장수목(Fault Tree)를 구축한 후 시각적 확률도구인 베이지안 네트워크(Bayesian Network, BN)으로 변환하였다. 본 연구는 선행연구를 기반으로 지진으로 유발된 구조손상으로 인해 발생 가능한 화재・폭발에 대해 PSA를 수행하고자 하였다. 이를 위해 화재・폭발을 사건수목(Event Tree)으로 표현하고, BN으로 변환하였다. 변환된 BN은 화재・폭발 모듈로서 선행연구에서 제시된 고장수목 기반 BN과 연계되어 최종적으로 지진 유발 화재・폭발 PSA를 수행할 수 있는 BN 기반 방법론이 개발되었다. 개발된 BN을 검증하기위해 수치예제로서 가상의 가스플랜트 Plot Plan을 생성하였고, 가스플랜트의 설비 종류가 구체적으로 반영된 대규모 BN을 구축하였다. 해당 BN을 이용하여 지진 규모에 따른 전체시스템의 운영정지 확률 및 하위시스템들의 고장확률 산정과 더불어 역으로 전체시스템이 운영 정지되었을 때 하위시스템들의 영향도 분석과 화재・폭발 가능성을 산정하여 다양한 의사결정을 수행할 수 있음을 제시함으로써 그 우수성을 확인하였다.

A Study of Wind Characteristics around Nuclear Power Plants Based on the Joint Distribution of the Wind Direction and Wind Speed

  • Yunjong Lee
    • 방사선산업학회지
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    • 제17권3호
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    • pp.299-307
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    • 2023
  • Given that toxic substances are diffused by the various movements of the atmosphere, it is very important to evaluate the risks associated with this phenomenon. When analyzing the behavioral characteristics of these atmospheric diffusion models, the main input data are the wind speed and wind direction among the meteorological data. In particular, it is known that a certain wind direction occurs in summer and winter in Korea under the influence of westerlies and monsoons. In this study, synoptic meteorological observation data provided by the Korea Meteorological Administration were analyzed from January 1, 2012 to the end of August of 2022 to understand the regional wind characteristics of nuclear power plants and surrounding areas. The selected target areas consisted of 16 weather stations around the Hanbit, Kori, Wolsong, Hanul, and Saeul nuclear power plants that are currently in operation. The analysis was based on the temperature, wind direction, and wind speed data at those locations. Average, maximum, minimum, median, and mode values were analyzed using long-term annual temperature, wind speed, and wind direction data. Correlation coefficient values were also analyzed to determine the linear relationships among the temperature, wind direction, and wind speed. Among the 16 districts, Uljin had the highest wind speed. The median wind speed values for each region were lower than the average wind speed values. For regions where the average wind speed exceeds the median wind speed, Yeongju, Gochang, Gyeongju, Yeonggwang, and Gimhae were calculated as 0.69 m s-1, 0.54m s-1, 0.45m s-1, 0.4m s-1, and 0.36m s-1, respectively. The average temperature in the 16 regions was 13.52 degrees Celsius; the median temperature was 14.31 degrees and the mode temperature was 20.69 degrees. The average regional temperature standard deviation was calculated and found to be 9.83 degrees. The maximum summer temperatures were 39.7, 39.5, and 39.3 in Yeongdeok, Pohang, and Yeongcheon, respectively. The wind directions and speeds in the 16 regions were plotted as a wind rose graph, and the characteristics of the wind direction and speed of each region were investigated. It was found that there is a dominant wind direction correlated with the topographical characteristics in each region. However, the linear relationship between the wind speed and direction by region varied from 0.53 to 0.07. Through this study, by evaluating meteorological observation data on a long-term synoptic scale of ten years, regional characteristics were found.