Detailed Information

Cited 0 time in webofscience Cited 0 time in scopus
Metadata Downloads

딥러닝 기법을 사용한 이차원 과도유동 해석

Full metadata record
DC Field Value Language
dc.contributor.author이태환-
dc.contributor.author박진현-
dc.date.accessioned2022-12-26T13:17:30Z-
dc.date.available2022-12-26T13:17:30Z-
dc.date.issued2020-
dc.identifier.issn1229-604X-
dc.identifier.issn2508-3805-
dc.identifier.urihttps://scholarworks.gnu.ac.kr/handle/sw.gnu/7267-
dc.description.abstractThe flow analysis of two dimensional transient flow over the obstacles with rectangular cross sections was performed. And 190 velocity distributions for each aspect ratio were imaged to provide input data for convolutional neural network learning. The classification and regression methods were used in estimating the aspect ratio from given velocity distributions. As a result the classification method was more exact than the regression method. But both the classification and regression methods gave relatively accurate prediction of the defined aspect ratio judging from the imaged velocity distributions. This confirms that the deep learning technique is applicable to the flow analysis.-
dc.format.extent7-
dc.language한국어-
dc.language.isoKOR-
dc.publisher한국기계기술학회-
dc.title딥러닝 기법을 사용한 이차원 과도유동 해석-
dc.title.alternativeAnalysis of Two Dimensional Transient Flow Using Deep Learning Technique-
dc.typeArticle-
dc.publisher.location대한민국-
dc.identifier.doi10.17958/ksmt.22.1.202002.12-
dc.identifier.bibliographicCitation한국기계기술학회지, v.22, no.1, pp 12 - 18-
dc.citation.title한국기계기술학회지-
dc.citation.volume22-
dc.citation.number1-
dc.citation.startPage12-
dc.citation.endPage18-
dc.identifier.kciidART002560573-
dc.description.isOpenAccessY-
dc.description.journalRegisteredClasskci-
dc.subject.keywordAuthor딥러닝-
dc.subject.keywordAuthor컨볼루션 신경망-
dc.subject.keywordAuthor과도유동-
dc.subject.keywordAuthor속도분포-
dc.subject.keywordAuthorDeep learning-
dc.subject.keywordAuthorConvolutional neural network-
dc.subject.keywordAuthorTransient flow-
dc.subject.keywordAuthorVelocity distribution-
Files in This Item
There are no files associated with this item.
Appears in
Collections
융합기술공과대학 > Division of Mechatronics Engineering > Journal Articles

qrcode

Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.

Related Researcher

Researcher Park, Jin Hyun photo

Park, Jin Hyun
IT공과대학 (메카트로닉스공학부)
Read more

Altmetrics

Total Views & Downloads

BROWSE