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김남훈

Kim, Namhun
UNIST Computer-Integrated Manufacturing Lab.
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dc.citation.number 1 -
dc.citation.startPage e2411024 -
dc.citation.title VIRTUAL AND PHYSICAL PROTOTYPING -
dc.citation.volume 19 -
dc.contributor.author Kim, Hayeol -
dc.contributor.author Seo, Junyoung -
dc.contributor.author Baek, Adrian Matias Chung -
dc.contributor.author Shin, Woo Yeong -
dc.contributor.author Jeon, Hongryung -
dc.contributor.author Moon, Seung Ki -
dc.contributor.author Kim, Hyungmo -
dc.contributor.author Kim, Namhun -
dc.contributor.author Jung, Im Doo -
dc.date.accessioned 2024-10-30T09:35:08Z -
dc.date.available 2024-10-30T09:35:08Z -
dc.date.created 2024-10-28 -
dc.date.issued 2024-12 -
dc.description.abstract Nuclear microreactors (MRs) have attracted significant attention for their versatility in installation locations, especially with the growing demand for sustainable green energy in large data processing facilities. However, ensuring their safe operation necessitates frequent inspections, which can be challenging for practical efficient management. This study proposes a novel approach using direct energy deposition to incorporate an optical fiber sensor into MR components, enabling real-time monitoring with artificial intelligence. The embedded optical fiber generates real-time data that allows for AI-driven in-vivo thermal deformation analysis. Our smart MR component can detect structural anomalies, identify abnormal operations, and assess operational conditions through augmented reality interfaces and AI technology. -
dc.identifier.bibliographicCitation VIRTUAL AND PHYSICAL PROTOTYPING, v.19, no.1, pp.e2411024 -
dc.identifier.doi 10.1080/17452759.2024.2411024 -
dc.identifier.issn 1745-2759 -
dc.identifier.scopusid 2-s2.0-85206366941 -
dc.identifier.uri https://scholarworks.unist.ac.kr/handle/201301/84324 -
dc.identifier.wosid 001330052000001 -
dc.language 영어 -
dc.publisher TAYLOR & FRANCIS LTD -
dc.title Direct energy deposition for smart micro reactor -
dc.type Article -
dc.description.isOpenAccess TRUE -
dc.relation.journalWebOfScienceCategory Engineering, Manufacturing; Materials Science, Multidisciplinary -
dc.relation.journalResearchArea Engineering; Materials Science -
dc.type.docType Article -
dc.description.journalRegisteredClass scie -
dc.description.journalRegisteredClass scopus -
dc.subject.keywordAuthor 3-Dimensional printing -
dc.subject.keywordAuthor direct metal deposition -
dc.subject.keywordAuthor machine learning -
dc.subject.keywordAuthor design for additive manufacturing -
dc.subject.keywordAuthor virtual prototyping -
dc.subject.keywordPlus NUCLEAR -
dc.subject.keywordPlus PERFORMANCE -
dc.subject.keywordPlus SENSORS -
dc.subject.keywordPlus STRESS -
dc.subject.keywordPlus FIBERS -

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