Two effective methods for flow-field performance forecast

WANG Bao-guo; WU Jun-hong; LIU Shu-yan; QIAN Geng; LIU Yan-ming

Volume 25 Issue 8

Aug. 2010

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WANG Bao-guo, WU Jun-hong, LIU Shu-yan, QIAN Geng, LIU Yan-ming. Two effective methods for flow-field performance forecast[J]. Journal of Aerospace Power, 2010, 25(8): 1763-1767.

Citation:

WANG Bao-guo, WU Jun-hong, LIU Shu-yan, QIAN Geng, LIU Yan-ming. Two effective methods for flow-field performance forecast[J]. Journal of Aerospace Power, 2010, 25(8): 1763-1767.

WANG Bao-guo, WU Jun-hong, LIU Shu-yan, QIAN Geng, LIU Yan-ming. Two effective methods for flow-field performance forecast[J]. Journal of Aerospace Power, 2010, 25(8): 1763-1767.

Citation:

WANG Bao-guo, WU Jun-hong, LIU Shu-yan, QIAN Geng, LIU Yan-ming. Two effective methods for flow-field performance forecast[J]. Journal of Aerospace Power, 2010, 25(8): 1763-1767.

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Two effective methods for flow-field performance forecast

School of Aerospace Engineering, Beijing Institute of Technology, Beijing 100081, China

Received Date: 2009-06-29
Rev Recd Date: 2009-09-15
Publish Date: 2010-08-28

Abstract

Abstract

Based on database established by multi-factor and multi-level design methods,two effective methods of flow-field performance forecast were proposed.One is response surface method,and the other is wavelet neural networks method.The typical examples indicate that two methods can forecast flow-field performance effectively.The results also show that wavelet neural networks method is superior to response surface method in terms of efficiency and precision.
- wavelet neural networks,
- response surface method,
- uniform experimental design,
- flow-field forecast,
- flow-field performance