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http://dx.doi.org/10.6110/KJACR.2013.25.2.070

Qualitative RBI Analysis in Considered with Uncertain Variables by Probabilistic Distribution  

Heo, Ho-Jin (Department of Mechanical Engineering, Sungkyunkwan University)
Jeong, Jae-Uk (Department of Mechanical Engineering, Sungkyunkwan University)
Kim, Joo-Dong (Department of Mechanical Engineering, Sungkyunkwan University)
Choi, Jae-Boong (Department of Mechanical Engineering, Sungkyunkwan University)
Choi, Song-Chun (Institute of Gas Safety of Korea Gas Safety Corporation)
Hwang, In-Ju (Korea Institute of Construction Technology)
Publication Information
Korean Journal of Air-Conditioning and Refrigeration Engineering / v.25, no.2, 2013 , pp. 70-78 More about this Journal
Abstract
Plants which are having conditions of high temperature and pressure always are exposed to danger. In order to prevent unexpected accidents, safety management that can effectively and appropriately examine facilities is required in plant operation. RBI(Risk-Based Inspection) technology in API 581 is one of standard management technique for evaluating risk on petroleum plants. There are qualitative and quantitative assessments in RBI methodology. Quantitative evaluation step is complex and required much information, so high-risk facilities in plant are selected firstly by qualitative method. Qualitative RBI is performed by choosing the answer in prepared questionnaire. However, it is difficult to believe thoroughly results from survey including ambiguous information. In this study, the procedure of qualitative RBI analysis with considering probability distribution concept were proposed by using Monte Carlo simulation method in order to increase reliability in spite of uncertain factors. In addition, qualitative risk of cooling system for LNG plant was evaluated using proposed procedure. Although 20 items of total 39 assessment items are applied to uncertain factors, risk section of high probability(89%) were verified. The detailed results were described in manuscript.
Keywords
Beta distribution; Monte Calro simulation; Probability distribution; Qualitative inspection; Risk-based Inspection;
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