Reduced-Order Modeling of Cavity Flow Oscillations across Multi-Mach Numbers Using Deep Learning
The reduced-order model can accurately and efficiently predict unsteady problems in many aerospace engineering applications. The traditional reduced-order model based on proper orthogonal decomposition (POD) and Galerkin projection has poor robustness and large error in predicting complex problems....
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Main Authors: | Zhe Liu, Fangli Ning, Hui Ding, Qingbo Zhai, Juan Wei |
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Format: | Article |
Language: | English |
Published: |
Wiley
2021-01-01
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Series: | Shock and Vibration |
Online Access: | http://dx.doi.org/10.1155/2021/5575722 |
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