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DC Field | Value | Language |
---|---|---|
dc.citation.endPage | 1058 | - |
dc.citation.number | 8 | - |
dc.citation.startPage | 1050 | - |
dc.citation.title | IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS | - |
dc.citation.volume | E107D | - |
dc.contributor.author | Choi, Hyebong | - |
dc.contributor.author | Shin, Joel | - |
dc.contributor.author | Kim, Jeongho | - |
dc.contributor.author | Yoon, Samuel | - |
dc.contributor.author | Park, Hyeonmin | - |
dc.contributor.author | Cho, Hyejin | - |
dc.contributor.author | Jung, Jiyoung | - |
dc.date.accessioned | 2024-08-22T11:35:06Z | - |
dc.date.available | 2024-08-22T11:35:06Z | - |
dc.date.created | 2024-08-22 | - |
dc.date.issued | 2024-08 | - |
dc.description.abstract | The design of automobile lamps requires accurate estimation of heat distribution to prevent overheating and deformation of the product. Traditional heat resistant analysis using Computational Fluid Dynamics (CFD) is time-consuming and requires expertise in thermofluid mechanics, making real-time temperature analysis less accessible to lamp designers. We propose a machine learning-based temperature prediction system for automobile lamp design. We trained our machine learning models using CFD results of various lamp designs, providing lamp designers real-time Heat- Resistant Analysis. Comprehensive tests on real lamp products demonstrate that our prediction model accurately estimates heat distribution comparable to CFD analysis within a minute. Our system visualizes the estimated heat distribution of car lamp design supporting quick decision-making by lamp designer. It is expected to shorten the product design process, improving the market competitiveness. | - |
dc.identifier.bibliographicCitation | IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS, v.E107D, no.8, pp.1050 - 1058 | - |
dc.identifier.doi | 10.1587/transinf.2023EDP7137 | - |
dc.identifier.issn | 0916-8532 | - |
dc.identifier.scopusid | 2-s2.0-85200466309 | - |
dc.identifier.uri | https://scholarworks.unist.ac.kr/handle/201301/83545 | - |
dc.identifier.wosid | 001282279400016 | - |
dc.language | 영어 | - |
dc.publisher | IEICE-INST ELECTRONICS INFORMATION COMMUNICATION ENGINEERS | - |
dc.title | Machine Learning-Based System for Heat-Resistant Analysis of Car Lamp Design | - |
dc.type | Article | - |
dc.description.isOpenAccess | FALSE | - |
dc.relation.journalWebOfScienceCategory | Computer Science, Information Systems; Computer Science, Software Engineering | - |
dc.relation.journalResearchArea | Computer Science | - |
dc.type.docType | Article | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.subject.keywordAuthor | heat-resistant analysis | - |
dc.subject.keywordAuthor | temperature predic- tion | - |
dc.subject.keywordAuthor | machine learning | - |
dc.subject.keywordAuthor | automobile lamp | - |
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