Probabilistic Safety Assessment of Gas Plant Using Fault Tree-based Bayesian Network

Se-Hyeok Lee; Changuk Mun; Sangki Park; Jeong-Rae Cho; Junho Song

doi:10.7734/COSEIK.2023.36.4.273

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2023 Vol.36, Issue 4 Preview Page

Research Paper

Probabilistic Safety Assessment of Gas Plant Using Fault Tree-based Bayesian Network 고장수목 기반 베이지안 네트워크를 이용한 가스 플랜트 시스템의 확률론적 안전성 평가

31 August 2023. pp. 273-282

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Abstract

Probabilistic safety assessment (PSA) has been widely used to evaluate the seismic risk of nuclear power plants (NPPs). However, studies on seismic PSA for process plants, such as gas plants, oil refineries, and chemical plants, have been scarce. This is because the major disasters to which these process plants are vulnerable include explosions, fires, and release (or dispersion) of toxic chemicals. However, seismic PSA is essential for the plants located in regions with significant earthquake risks. Seismic PSA entails probabilistic seismic hazard analysis (PSHA), event tree analysis (ETA), fault tree analysis (FTA), and fragility analysis for the structures and essential equipment items. Among those analyses, ETA can depict the accident sequence for core damage, which is the worst disaster and top event concerning NPPs. However, there is no general top event with regard to process plants. Therefore, PSA cannot be directly applied to process plants. Moreover, there is a paucity of studies on developing fragility curves for various equipment. This paper introduces PSA for gas plants based on FTA, which is then transformed into Bayesian network, that is, a probabilistic graph model that can aid risk-informed decision-making. Finally, the proposed method is applied to a gas plant, and several decision-making cases are demonstrated.

Keywords

fault tree

bayesian network

probabilistic safety assessment

decision-making

gas plant

원자력발전소 지진 확률론적 안전성 평가인 PSA(Probabilistic Safety Assessment)는 오랜 기간에 걸쳐 확고히 구축되어 왔다. 반면에 다양한 공정 기반의 산업시설물의 경우 화재, 폭발, 확산(유출) 재난에 대해 주로 연구되어 왔으며, 지진에 대해서는 상대적으로 연구가 미미하였다. 하지만, 플랜트 설계 당시와 달리 해당 부지가 지진 영향권에 들어갈 경우 지진 PSA 수행은 필수적이다. 지진 PSA를 수행하기 위해서는 확률론적 지진 재해도 해석(Probabilistic Seismic Hazard Analysis), 사건수목 해석(Event Tree Analysis), 고장수목 해석(Fault Tree Analysis), 취약도 곡선 등을 필요로 한다. 원자력 발전소의 경우 노심 손상 방지라는 최우선 목표에 따라 많은 사고시나리오 분석을 통해 사건수목이 구축되었지만, 산업시설물의 경우 공정의 다양성과 최우선 손상 방지 핵심설비의 부재로 인해 일반적인 사건수목 구축이 어렵다. 따라서, 본 연구에서는 산업시설물 지진 PSA를 수행하기 위해 고장수목을 바탕으로 확률론적 시각도구인 베이지안 네트워크(Bayesian Network, BN)로 변환하여 리스크를 평가하는 방법을 제안한다. 제안된 방법을 이용하여 임의로 생성된 가스플랜트 Plot Plan에 대해 최종 BN을 구축하고, 다양한 사건 경우에 대한 효용성있는 의사결정과정을 보임으로써 그 우수성을 확인하였다.

키워드

고장 수목

베이지안 네트워크

확률론적 안전성 평가

의사결정

가스 플랜트

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Information

Publisher :Computational Structural Engineering Institute of Korea
Publisher(Ko) :한국전산구조공학회
Journal Title :Journal of the Computational Structural Engineering Institute of Korea
Journal Title(Ko) :한국전산구조공학회 논문집
Volume : 36
No :4
Pages :273-282
Received Date : 2023-08-01
Revised Date : 2023-08-09
Accepted Date : 2023-08-09
DOI :https://doi.org/10.7734/COSEIK.2023.36.4.273

Journal of the Computational Structural Engineering Institute of Korea ISSN:1229-3059(Print) 2287-2302(Online) 한국전산구조공학회 논문집

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