Detailed Information

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

과도유동 해석을 위한 CNN에서의 이미지 변환방법Image Conversion Methods in CNN for Transient Flow Analysis

Other Titles
Image Conversion Methods in CNN for Transient Flow Analysis
Authors
박진현이태환
Issue Date
2020
Publisher
한국기계기술학회
Keywords
CNN; Thermal fluid problem; Image conversion; Pressure distribution; 볼루션 신경망; 열유체문제; 이미지 변환; 압력분포
Citation
한국기계기술학회지, v.22, no.4, pp 712 - 719
Pages
8
Indexed
KCI
Journal Title
한국기계기술학회지
Volume
22
Number
4
Start Page
712
End Page
719
URI
https://scholarworks.gnu.ac.kr/handle/sw.gnu/7198
DOI
10.17958/ksmt.22.4.202008.712
ISSN
1229-604X
2508-3805
Abstract
To apply CNN to a fluid problem, we need a method to effectively convert the physical quantities of fluid into an image. The performance of CNN was evaluated using the image transformation method using the minimum and maximum values of the pressure distribution data and the image transformation methods using the normal distribution of the pressure distribution data. Through the performance evaluation of the learned CNN, the image transformation methods of Method 4 and Method 5, which applied the normal distribution of representative pressure distribution data, were very effective. In particular, Method 5 includes the initial and final pressure distribution data to include overall pressure distribution data, thereby improving the resolution of the color map to improve classification performance.
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