딥러닝을 이용한 회전된 정사각형 단면을 가진 장애물 주위의 과도유동 해석

Abstract

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.