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A Study on an Accident Diagnosis Methodology Using Influence Diagrams

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dc.contributor.authorKang, Kyung-Min-
dc.contributor.authorJae, Moosung-
dc.date.accessioned2022-12-21T02:48:39Z-
dc.date.available2022-12-21T02:48:39Z-
dc.date.issued2008-06-
dc.identifier.issn0022-3131-
dc.identifier.issn1881-1248-
dc.identifier.urihttps://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/178540-
dc.description.abstractIn nuclear power plants, operators are allowed to follow EOPs (Emergency Operating Procedures) when reactor tripped because of accidents. But, it's very difficult to diagnose accidents and find out appropriate procedures to mitigate current accidents in a given short time. Even if they diagnose accidents quickly, it also has possibility to misdiagnose. Methodology using Influence Diagrams has been developed and applied for representing the dependency behaviors and uncertain behaviors of complex systems. An example to diagnose the accidents such as SLOCA and SGTR with similar symptoms has been introduced. From the constructed model, operators could diagnose accidents at any states of accidents. Also, The integrated design of Thermal Hydraulics Online Monitoring Advisory System(THOMAS) is introduced in this paper. THOMAS, for improved Korea Standard Nuclear Power Plant, is an advisory monitoring system that uses the digital engineering technology such as virtual reality, and database. It is believed that the new design will improve the operability and maintainability and simplify design process of the monitoring and diagnosis system of the nuclear power plant. And this model can offer the information about accidents with given symptoms. This model might help operators to diagnose correctly and rapidly. It might be very useful to support operators for reducing human error.-
dc.format.extent4-
dc.language영어-
dc.language.isoENG-
dc.publisherAtomic Energy Society of Japan/Nihon Genshiroku Gakkai-
dc.titleA Study on an Accident Diagnosis Methodology Using Influence Diagrams-
dc.typeArticle-
dc.publisher.location영국-
dc.identifier.doi10.1080/00223131.2008.10875953-
dc.identifier.scopusid2-s2.0-84912031253-
dc.identifier.wosid000267196000183-
dc.identifier.bibliographicCitationJournal of Nuclear Science and Technology, pp 706 - 709-
dc.citation.titleJournal of Nuclear Science and Technology-
dc.citation.startPage706-
dc.citation.endPage709-
dc.type.docTypeArticle; Proceedings Paper-
dc.description.isOpenAccessN-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.relation.journalResearchAreaNuclear Science & Technology-
dc.relation.journalWebOfScienceCategoryNuclear Science & Technology-
dc.subject.keywordPlusDesign-
dc.subject.keywordPlusMonitoring-
dc.subject.keywordPlusNuclear energy-
dc.subject.keywordPlusNuclear power plants-
dc.subject.keywordPlusVirtual reality-
dc.subject.keywordAuthoraccident diagnosis-
dc.subject.keywordAuthoremergency operating procedures-
dc.subject.keywordAuthorinfluence diagrams-
dc.subject.keywordAuthorbayesian theorem-
dc.identifier.urlhttps://www.tandfonline.com/doi/abs/10.1080/00223131.2008.10875953-
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