NDLI: An Implicit Off-Design Deviation Angle Correlation of Axial Flow Compressor Blade Elements

Content Provider	The American Society of Mechanical Engineers (ASME) Digital Collection
Author	Dong-Run, Wu Jin-Fang, Teng Xiao-Qing, Qiang Jin-Zhang, Feng
Copyright Year	2017
Abstract	This paper applies a new analytical/empirical method to formulate the off-design deviation angle correlation of axial flow compressor blade elements. An implicit function of deviation angle is used to map off-design deviation curves into linear correlations (minimum linear correlation coefficient R = 0.959 in this paper). Solution of the coefficients in the correlation is given through the study of classical theories and statistical analysis of the experimental data. The off-design deviation angle can be calculated numerically. The approach requires only knowledge of the blade element geometry. The comparison among 2 classical correlations and the new correlation proposed in this paper shows the new correlation has minimum error over the entire range of incidence angle while classical correlations show high reliability only in a limited range. Experimental data in this paper is collected from NASA’s open technical reports. Rotors and stators are studied together. Considering there is significant deviation angle variation along spanwise direction, only data at 50% span is studied, if possible. The error among experimental data, statistical regressions of the experimental data, and numerical results based on the new correlation is discussed. It has to be noted that the influence of the flow condition other than incidence angle is only being discussed but with less break through.
Sponsorship	International Gas Turbine Institute
File Format	PDF
ISBN	9780791850794
DOI	10.1115/GT2017-63189
Volume Number	Volume 2B: Turbomachinery
Conference Proceedings	ASME Turbo Expo 2017: Turbomachinery Technical Conference and Exposition
Language	English
Publisher Date	2017-06-26
Publisher Place	Charlotte, North Carolina, USA
Access Restriction	Subscribed
Subject Keyword	Design Geometry Errors Statistical analysis Blades Rotors Stators Reliability Flow (dynamics) Axial flow
Content Type	Text
Resource Type	Article

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