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딥러닝 기법을 사용한 이차원 과도유동 해석open accessAnalysis of Two Dimensional Transient Flow Using Deep Learning Technique

Other Titles
Analysis of Two Dimensional Transient Flow Using Deep Learning Technique
Authors
이태환박진현
Issue Date
2020
Publisher
한국기계기술학회
Keywords
딥러닝; 컨볼루션 신경망; 과도유동; 속도분포; Deep learning; Convolutional neural network; Transient flow; Velocity distribution
Citation
한국기계기술학회지, v.22, no.1, pp 12 - 18
Pages
7
Indexed
KCI
Journal Title
한국기계기술학회지
Volume
22
Number
1
Start Page
12
End Page
18
URI
https://scholarworks.gnu.ac.kr/handle/sw.gnu/7267
DOI
10.17958/ksmt.22.1.202002.12
ISSN
1229-604X
2508-3805
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.
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융합기술공과대학 > Division of Mechatronics Engineering > Journal Articles

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Park, Jin Hyun
IT공과대학 (메카트로닉스공학부)
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