Study on Nuclear Accident Precursors Using AHP and BBN
Most of the nuclear accident reports used to indicate the implicit precursors which are not easily quantified as underlying factors. The current Probabilistic Safety Assessment (PSA) is capable of quantifying the importance of accident causes in limited scope. It was, therefore, difficult to achieve...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2014-01-01
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| Series: | Science and Technology of Nuclear Installations |
| Online Access: | http://dx.doi.org/10.1155/2014/206258 |
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| author | Sujin Park Huichang Yang Gyunyoung Heo Muhammad Zubair Rahman Khalil Ur |
| author_facet | Sujin Park Huichang Yang Gyunyoung Heo Muhammad Zubair Rahman Khalil Ur |
| author_sort | Sujin Park |
| collection | DOAJ |
| description | Most of the nuclear accident reports used to indicate the implicit precursors which are not easily quantified as underlying factors. The current Probabilistic Safety Assessment (PSA) is capable of quantifying the importance of accident causes in limited scope. It was, therefore, difficult to achieve quantifiable decision-making for resource allocation. In this study, the methodology which facilitates quantifying these precursors and a case study were presented. First, four implicit precursors have been obtained by evaluating the causality and hierarchy structure of various accident factors. Eventually, it turned out that they represent the lack of knowledge. After four precursors are selected, subprecursors were investigated and their cause-consequence relationship was implemented by Bayesian Belief Network (BBN). To prioritize the precursors, the prior probability is initially estimated by expert judgment and updated upon observations. The pair-wise importance between precursors is calculated by Analytic Hierarchy Process (AHP) and the results are converted into node probability tables of the BBN model. Using this method, the sensitivity and the posterior probability of each precursor can be analyzed so that it enables making prioritization for the factors. We tried to prioritize the lessons learned from Fukushima accident to demonstrate the feasibility of the proposed methodology. |
| format | Article |
| id | doaj-art-84f3ddecae484ae5981049dc0d4782bc |
| institution | Kabale University |
| issn | 1687-6075 1687-6083 |
| language | English |
| publishDate | 2014-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Science and Technology of Nuclear Installations |
| spelling | doaj-art-84f3ddecae484ae5981049dc0d4782bc2025-08-20T03:37:12ZengWileyScience and Technology of Nuclear Installations1687-60751687-60832014-01-01201410.1155/2014/206258206258Study on Nuclear Accident Precursors Using AHP and BBNSujin Park0Huichang Yang1Gyunyoung Heo2Muhammad Zubair3Rahman Khalil Ur4Department of Nuclear Engineering, Kyung Hee University, Yongin Si, Gyeonggi Do 446-701, Republic of KoreaIndustrial Services TUV Rheinland Korea Ltd. 197-28 Guro-dong, Guro-gu, Seoul 152-719, Republic of KoreaDepartment of Nuclear Engineering, Kyung Hee University, Yongin Si, Gyeonggi Do 446-701, Republic of KoreaDepartment of Basic Sciences, University of Engineering and Technology, Taxila, PakistanDepartment of Nuclear Engineering, Kyung Hee University, Yongin Si, Gyeonggi Do 446-701, Republic of KoreaMost of the nuclear accident reports used to indicate the implicit precursors which are not easily quantified as underlying factors. The current Probabilistic Safety Assessment (PSA) is capable of quantifying the importance of accident causes in limited scope. It was, therefore, difficult to achieve quantifiable decision-making for resource allocation. In this study, the methodology which facilitates quantifying these precursors and a case study were presented. First, four implicit precursors have been obtained by evaluating the causality and hierarchy structure of various accident factors. Eventually, it turned out that they represent the lack of knowledge. After four precursors are selected, subprecursors were investigated and their cause-consequence relationship was implemented by Bayesian Belief Network (BBN). To prioritize the precursors, the prior probability is initially estimated by expert judgment and updated upon observations. The pair-wise importance between precursors is calculated by Analytic Hierarchy Process (AHP) and the results are converted into node probability tables of the BBN model. Using this method, the sensitivity and the posterior probability of each precursor can be analyzed so that it enables making prioritization for the factors. We tried to prioritize the lessons learned from Fukushima accident to demonstrate the feasibility of the proposed methodology.http://dx.doi.org/10.1155/2014/206258 |
| spellingShingle | Sujin Park Huichang Yang Gyunyoung Heo Muhammad Zubair Rahman Khalil Ur Study on Nuclear Accident Precursors Using AHP and BBN Science and Technology of Nuclear Installations |
| title | Study on Nuclear Accident Precursors Using AHP and BBN |
| title_full | Study on Nuclear Accident Precursors Using AHP and BBN |
| title_fullStr | Study on Nuclear Accident Precursors Using AHP and BBN |
| title_full_unstemmed | Study on Nuclear Accident Precursors Using AHP and BBN |
| title_short | Study on Nuclear Accident Precursors Using AHP and BBN |
| title_sort | study on nuclear accident precursors using ahp and bbn |
| url | http://dx.doi.org/10.1155/2014/206258 |
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