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Development of radiation risk assessment simulator using system dynamics methodology

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dc.contributor.authorKang, Kyung Min-
dc.contributor.authorJae, Moosung-
dc.date.accessioned2022-12-21T02:48:25Z-
dc.date.available2022-12-21T02:48:25Z-
dc.date.created2022-08-26-
dc.date.issued2008-06-
dc.identifier.issn0022-3131-
dc.identifier.urihttps://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/178537-
dc.description.abstractThe potential magnitudes of radionuclide releases under severe accident loadings and offsite consequences as well as the overall risk (the product of accident frequencies and consequences) are analyzed and evaluated quantitatively in this study. The system dynamics methodology has been applied to predict the time-dependent behaviors such as feedback and dependency as well as to model uncertain behavior of complex physical system. It is used to construct the transfer mechanisms of time dependent radioactivity concentration and to evaluate them. Dynamic variations of radio activities are simulated by considering several effects such as deposition, weathering, washout, re-suspension, root uptake, translocation, leaching, senescence, intake, and excretion of soil. The time-dependent radio-ecological model applicable to Korean specific environment has been developed in order to assess the radiological consequences following the short-term deposition of radio-nuclides during severe accidents nuclear power plant. An ingestion food chain model can estimate time dependent radioactivity concentrations in foodstuffs. And it is also shown that the system dynamics approach is useful for analyzing the phenomenon of the complex system as well as the behavior of structure values with respect to time. The output of this model (Bq ingested per Bq m(-2) deposited) may be multiplied by the deposition and a dose conversion factor (Gy Bq(-1)) to yield organ-specific doses. The model may be run deterministically to yield a single estimate or stochastic distributions by "Monte-Carlo" calculation that reflects uncertainty of parameter and model uncertainties. The results of this study may contribute to identifying the relative importance of various parameters occurred in consequence analysis, as well as to assessing risk reduction effects in accident management.-
dc.language영어-
dc.language.isoen-
dc.publisherTAYLOR & FRANCIS LTD-
dc.titleDevelopment of radiation risk assessment simulator using system dynamics methodology-
dc.typeArticle-
dc.contributor.affiliatedAuthorJae, Moosung-
dc.identifier.doi10.1080/00223131.2008.10875958-
dc.identifier.scopusid2-s2.0-84911994600-
dc.identifier.wosid000267196000188-
dc.identifier.bibliographicCitationJOURNAL OF NUCLEAR SCIENCE AND TECHNOLOGY, pp.728 - 731-
dc.relation.isPartOfJOURNAL OF NUCLEAR SCIENCE AND TECHNOLOGY-
dc.citation.titleJOURNAL OF NUCLEAR SCIENCE AND TECHNOLOGY-
dc.citation.startPage728-
dc.citation.endPage731-
dc.type.rimsART-
dc.type.docTypeArticle; Proceedings Paper-
dc.description.journalClass1-
dc.description.isOpenAccessY-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.relation.journalResearchAreaNuclear Science & Technology-
dc.relation.journalWebOfScienceCategoryNuclear Science & Technology-
dc.subject.keywordPlusAccidents-
dc.subject.keywordPlusChains-
dc.subject.keywordPlusDeposition-
dc.subject.keywordPlusDynamics-
dc.subject.keywordPlusEcology-
dc.subject.keywordPlusNuclear power plants-
dc.subject.keywordPlusRadiation-
dc.subject.keywordPlusRadioactivity-
dc.subject.keywordPlusStochastic models-
dc.subject.keywordPlusStochastic systems-
dc.subject.keywordPlusSystem theory-
dc.subject.keywordPlusUncertainty analysis-
dc.subject.keywordAuthoringestion chain model-
dc.subject.keywordAuthordynamic-
dc.subject.keywordAuthorradioecology-
dc.subject.keywordAuthorsystem dynamics-
dc.identifier.urlhttps://www.tandfonline.com/doi/abs/10.1080/00223131.2008.10875958-
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