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A machine learning informed prediction of severe accident progressions in nuclear power plantsGo to Linkopen access

Song, JinHo; Kim, SungJoong

ArticleIssue Date2024CitationNuclear Engineering and Technology, v.56, no.6, pp 2266 - 2273Publisher한국원자력학회
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Experimental analysis of helium bubble-driven flow for enhanced natural circulation in passive molten salt fast reactorGo to Link

Choi, Won Jun; Hyeon, Seung Gyu; Park, Jae Hyung; Song, JinHo; Kim, Sung Joong

ArticleIssue Date2026CitationNuclear Engineering and Design, v.446, pp 1 - 15PublisherElsevier BV
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Experimental validation of predominant radiative heat loss through a metal containment vessel of small modular reactors under normal operationGo to Link

Byeon, Geunyoung; Jeong, Beomjin; Kim, Namgook; Song, JinHo; Kim, Sung Joong

ArticleIssue Date2026CitationProgress in Nuclear Energy, v.196, pp 1 - 20PublisherElsevier Ltd
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Prediction of Severe Accident Progression Using Machine Learning With Data-Driven Surrogate Modeling as Operator Support ToolGo to Linkopen access

Bae, Joon Young; Song, Chang Hyun; Song, JinHo; Lee, Jeong Ik; Seo, Miro; Kim, Sung Joong

ArticleIssue Date2026CitationINTERNATIONAL JOURNAL OF ENERGY RESEARCH, v.2026, no.1, pp 1 - 27PublisherWILEY
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