A neural network approach for centrifugal impeller inverse design

被引：4

作者：

Fan, HY ^{[1
]}

机构：

[1] Xian Jiao Tong Univ, Sch Energy & Power Engn, SER Turbomachinery Res Ctr, Xian 710049, Peoples R China

来源：

PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART A-JOURNAL OF POWER AND ENERGY | 2000年 / 214卷 / A2期

关键词：

neural network; centrifugal impeller; blade; inverse design;

D O I：

10.1243/0957650001538272

中图分类号：

O414.1 [热力学];

学科分类号：

摘要：

In this paper a neural network approach is proposed to solve an inverse design problem of a centrifugal impeller when the basic structure parameter and the hub-shroud contours are known, and the expected blade surface velocity distribution is given. The proposed neural networks have a four-layered feedforward architecture and are trained with finite samples by means of a back-propagation algorithm. The simulations show that the trained networks can yield a blade shape that generates the expected velocity distribution on its surface.

引用

页码：183 / 186

页数：4

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