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Lee, Deokjung
Computational Reactor physics & Experiment Lab.
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dc.citation.endPage 731 -
dc.citation.number 3 -
dc.citation.startPage 715 -
dc.citation.title NUCLEAR ENGINEERING AND TECHNOLOGY -
dc.citation.volume 53 -
dc.contributor.author Ebiwonjumi, Bamidele -
dc.contributor.author Kong, Chidong -
dc.contributor.author Zhang, Peng -
dc.contributor.author Cherezov, Alexey -
dc.contributor.author Lee, Deokjung -
dc.date.accessioned 2023-12-21T16:09:24Z -
dc.date.available 2023-12-21T16:09:24Z -
dc.date.created 2021-05-04 -
dc.date.issued 2021-03 -
dc.description.abstract Uncertainties are calculated for pressurized water reactor (PWR) spent nuclear fuel (SNF) characteristics. The deterministic code STREAM is currently being used as an SNF analysis tool to obtain isotopic in-ventory, radioactivity, decay heat, neutron and gamma source strengths. The SNF analysis capability of STREAM was recently validated. However, the uncertainty analysis is yet to be conducted. To estimate the uncertainty due to nuclear data, STREAM is used to perturb nuclear cross section (XS) and resonance integral (RI) libraries produced by NJOY99. The perturbation of XS and RI involves the stochastic sam-pling of ENDF/B-VII.1 covariance data. To estimate the uncertainty due to modeling parameters (fuel design and irradiation history), surrogate models are built based on polynomial chaos expansion (PCE) and variance-based sensitivity indices (i.e., Sobol & rsquo; indices) are employed to perform global sensitivity analysis (GSA). The calculation results indicate that uncertainty of SNF due to modeling parameters are also very important and as a result can contribute significantly to the difference of uncertainties due to nuclear data and modeling parameters. In addition, the surrogate model offers a computationally effi-cient approach with significantly reduced computation time, to accurately evaluate uncertainties of SNF integral characteristics. (c) 2020 Korean Nuclear Society, Published by Elsevier Korea LLC. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). -
dc.identifier.bibliographicCitation NUCLEAR ENGINEERING AND TECHNOLOGY, v.53, no.3, pp.715 - 731 -
dc.identifier.doi 10.1016/j.net.2020.07.012 -
dc.identifier.issn 1738-5733 -
dc.identifier.scopusid 2-s2.0-85089300101 -
dc.identifier.uri https://scholarworks.unist.ac.kr/handle/201301/52816 -
dc.identifier.url https://www.sciencedirect.com/science/article/pii/S1738573320303521?via%3Dihub -
dc.identifier.wosid 000631704600002 -
dc.language 영어 -
dc.publisher KOREAN NUCLEAR SOC -
dc.title Uncertainty quanti fi cation of PWR spent fuel due to nuclear data and modeling parameters -
dc.type Article -
dc.description.isOpenAccess TRUE -
dc.relation.journalWebOfScienceCategory Nuclear Science & Technology -
dc.identifier.kciid ART002690782 -
dc.relation.journalResearchArea Nuclear Science & Technology -
dc.type.docType Article -
dc.description.journalRegisteredClass scie -
dc.description.journalRegisteredClass scopus -
dc.description.journalRegisteredClass kci -
dc.subject.keywordAuthor STREAM -
dc.subject.keywordAuthor Spent nuclear fuel -
dc.subject.keywordAuthor PWR -
dc.subject.keywordAuthor quantification -
dc.subject.keywordAuthor Stochastic sampling -
dc.subject.keywordAuthor Surrogate models -
dc.subject.keywordPlus GLOBAL SENSITIVITY-ANALYSIS -
dc.subject.keywordPlus VALIDATION -
dc.subject.keywordPlus QUANTIFICATION -
dc.subject.keywordPlus VERIFICATION -
dc.subject.keywordPlus SCALE -

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