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
- 박진현; 이태환
- 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.
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Collections - 융합기술공과대학 > Division of Mechatronics Engineering > Journal Articles
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