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딥러닝 기법을 사용한 이차원 과도유동 해석
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | 이태환 | - |
| dc.contributor.author | 박진현 | - |
| dc.date.accessioned | 2022-12-26T13:17:30Z | - |
| dc.date.available | 2022-12-26T13:17:30Z | - |
| dc.date.issued | 2020 | - |
| dc.identifier.issn | 1229-604X | - |
| dc.identifier.issn | 2508-3805 | - |
| dc.identifier.uri | https://scholarworks.gnu.ac.kr/handle/sw.gnu/7267 | - |
| dc.description.abstract | The 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.extent | 7 | - |
| dc.language | 한국어 | - |
| dc.language.iso | KOR | - |
| dc.publisher | 한국기계기술학회 | - |
| dc.title | 딥러닝 기법을 사용한 이차원 과도유동 해석 | - |
| dc.title.alternative | Analysis of Two Dimensional Transient Flow Using Deep Learning Technique | - |
| dc.type | Article | - |
| dc.publisher.location | 대한민국 | - |
| dc.identifier.doi | 10.17958/ksmt.22.1.202002.12 | - |
| dc.identifier.bibliographicCitation | 한국기계기술학회지, v.22, no.1, pp 12 - 18 | - |
| dc.citation.title | 한국기계기술학회지 | - |
| dc.citation.volume | 22 | - |
| dc.citation.number | 1 | - |
| dc.citation.startPage | 12 | - |
| dc.citation.endPage | 18 | - |
| dc.identifier.kciid | ART002560573 | - |
| dc.description.isOpenAccess | Y | - |
| dc.description.journalRegisteredClass | kci | - |
| dc.subject.keywordAuthor | 딥러닝 | - |
| dc.subject.keywordAuthor | 컨볼루션 신경망 | - |
| dc.subject.keywordAuthor | 과도유동 | - |
| dc.subject.keywordAuthor | 속도분포 | - |
| dc.subject.keywordAuthor | Deep learning | - |
| dc.subject.keywordAuthor | Convolutional neural network | - |
| dc.subject.keywordAuthor | Transient flow | - |
| dc.subject.keywordAuthor | Velocity distribution | - |
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