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이승준

Lee, Seung Jun
Nuclear Safety Assessment and Plant HMI Evolution Lab.
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dc.citation.conferencePlace US -
dc.citation.conferencePlace Las Vegas -
dc.citation.endPage 339 -
dc.citation.startPage 333 -
dc.citation.title HCI International 2018 (20th International Conference on Human-Computer Interaction) -
dc.contributor.author Ahn, Jeeya -
dc.contributor.author Kim, Jaemin -
dc.contributor.author Lee, Seung Jun -
dc.date.accessioned 2024-02-01T01:38:29Z -
dc.date.available 2024-02-01T01:38:29Z -
dc.date.created 2018-08-01 -
dc.date.issued 2018-07-18 -
dc.description.abstract Nowadays, automation has been generalized with artificial intelligences in many areas. In nuclear power plants, some features which have simple logics in nuclear power plants such as reactor trip and engineered safety features (ESFs) actuation have been automated, whereas, other components have not been automated yet, so human operators are still necessary to control the reactor in emergency or abnormal situations. However, there exists a risk of human errors since human operators are involved in nuclear power operations. That is because, human error may contribute to the risk of severe accidents. To reduce those human errors, moreover, to draw to extend the portion of automation in nuclear power plants, a framework which automatically detects Unsafe Acts (UAs) which are occurred in advanced main control rooms of nuclear power plants has been introduced. Human operators are supposed to operate nuclear power plants by following operating procedures. However, in real operational situation, they violate operating procedures sometimes to achieve the goal (to keep the plant integrity) based on their own experiences and their know-hows. Critical safety functions (CSFs) can disentangle whether an operator’s action will adversely affect plant integrity. Thus, the UA autodetection system considers both procedure violation and CSFs violation to find out errors made by human operator. © Springer International Publishing AG, part of Springer Nature 2018. -
dc.identifier.bibliographicCitation HCI International 2018 (20th International Conference on Human-Computer Interaction), pp.333 - 339 -
dc.identifier.doi 10.1007/978-3-319-92270-6_48 -
dc.identifier.scopusid 2-s2.0-85061546570 -
dc.identifier.uri https://scholarworks.unist.ac.kr/handle/201301/81143 -
dc.identifier.url https://link.springer.com/chapter/10.1007%2F978-3-319-92270-6_48 -
dc.language 영어 -
dc.publisher HCI International -
dc.title An Unsafe Act Autodetection Methodology in Nuclear Power Plant Operations -
dc.type Conference Paper -
dc.date.conferenceDate 2018-07-15 -

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