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An extended HAZOP analysis approach with dynamic fault tree
Affiliation:1. Office of Technical Inspection (UDT), Innovation and Development Department, 02-353 Warsaw, Szczesliwicka Street 34, Poland;2. Safety Engineering Department, Faculty of Process and Environmental Engineering, Technical University of Lodz, 90-942 Lodz, Ul. Wolczanska 213, Poland;3. Polskie LNG S.A., 72-600 Swinoujscie, Ul. Finska 7, Poland;1. Cryogenic Research Institute, Daesung Industrial Gases Co., Ltd, Ansan, Republic of Korea;2. National Fusion Research Institute, Daejeon, Republic of Korea;3. Department of Safety Engineering, Incheon National University, Incheon, Republic of Korea;1. College of Mechanical and Transportation Engineering, China University of Petroleum, Beijing 102249, China;2. CNOOC Zhong Jie Petrochemical Co., Ltd., Cang Zhou 061101, China
Abstract:An extended hazard and operability (HAZOP) analysis approach with dynamic fault tree is proposed to identify potential hazards in chemical plants. First, the conventional HAZOP analysis is used to identify the possible fault causes and consequences of abnormal conditions, which are called deviations. Based on HAZOP analysis results, hazard scenario models are built to explicitly represent the propagation pathway of faults. With the quantitative analysis requirements of HAZOP analysis and the time-dependent behavior of real failure events considered, the dynamic fault tree (DFT) analysis approach is then introduced to extend HAZOP analysis. To simplify the quantitative calculation, the DFT model is solved with modularization approach in which a binary decision diagram (BDD) and Markov chain approach are applied to solve static and dynamic subtrees, respectively. Subsequently, the occurrence probability of the top event and the probability importance of each basic event with respect to the top event are determined. Finally, a case study is performed to verify the effectiveness of the approach. Results indicate that compared with the conventional HAZOP approach, the proposed approach does not only identify effectively possible fault root causes but also quantitatively determines occurrence probability of the top event and the most likely fault causes. The approach can provide a reliable basis to improve process safety.
Keywords:HAZOP  Hazard scenario  DFT  BDD  Markov chain
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