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Analysis of Transient Flow Around the Obstacle with Rotated Square Cross Sections using Deep Learning

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한국기계기술학회지 (Journal of the Korean Society of Mechanical Technology)
한국기계기술학회 (Korean Society of Mechanical Technology)
초록

The numerical analysis of two-dimensional transient flow around the obstacle with rotated square cross sections was carried out. The obtained velocity distributions for each time step and each rotation angle were imaged to provide data for CNN(convolutional neural network). Both classification and regression neural networks were used for prediction of rotation angle. As results The classification method incorrectly predicted the rotation angle in only 2 of the 470 images. The regression method predicted the rotation angle errors within except 2 out of 470 images. From these facts, it could be concluded that both methods can be sufficiently applicable to the flow analysis.

저자
  • 이태환(경남과학기술대학교) | LEE TAE HWAN
  • 박진현(경남과학기술대학교) | Park Jin-Hyun 교신