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Computational Design of Turbomachine Blades

Authors: Wen-Quan Wu; Rong-Guo Zhu; Cui-E Liu;

Computational Design of Turbomachine Blades

Abstract

Based upon Wu's general three-dimensional turbomachine flow theory, a set of computer programs was established to measure flow along the relative stream surfaces S1 and S2, employing nonorthogonal curvilinear coordinates and nonorthogonal velocity components. The streamline extension technique, matrix direct solution, and line relaxation method are used in these programs. With the employment of fictitious grid points, the internal storage capacity required in the matrix direct solution is reduced by nearly two-thirds. The matrix direct solution and the line relaxation method are found to converge nearly 10 times faster than the streamline extension technique. These programs constitute a design system of axial flow turbomachine blades based upon three-dimensional flow. Experience shows that iterative solutions considering three-dimensional flow obtained by the successive calculation of the Sj and S2 surface flows are rapid and practical. The major results of a number of typical applications are included in the paper.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
2
Average
Top 10%
Average
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