1. Improvement of a Tip Clearance Loss Prediction Model Based on Geometric Variation
- Author
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Xingmin Gui, Donghai Jin, Jiancheng Zhang, and Zefeng Li
- Subjects
Tip clearance ,Variation (linguistics) ,Materials science ,Mechanics - Abstract
Tip leakage flow is an important factor affecting the efficiency and stability of compressors. It is important to study the tip leakage flow model in the design and performance prediction process of turbomachinery. This work analyzes the existing tip clearance loss prediction model and refines it to predict the tip clearance loss considering more blade geometric parameters. After analyzing the Yaras tip leakage loss model derivation process, it is found that the discharge coefficient (taken as constants by Yaras) will change with the gap geometry, namely, it is related to the maximum thickness and the gap size of the blade. In this paper the discharge coefficient of tip gap is revised to better predict the effect of gap loss with regard to the maximum thickness of the blade. In this paper, the research objects are linear cascades with NACA65 profile and numerical experiments were carried out by a CFD package Numeca under the condition of Mach number equal to 0.45, where the variables are the gap sizes (1%, 2%, 3%, 4%, 6% of the axial chord length) and the maximum thickness of blades (3%, 5%, 7%, 9%, 11% of the axial chord length). Combined with the numerical calculation results, according to Yaras loss prediction formula and using the similar characteristics to the discharge coefficient of the variation trend and the Planck blackbody radiation formula, the relationship between the discharge coefficient and the maximum thickness of the blade and the tip clearance is summarized, which is integrated with the Yaras loss prediction formula to obtain the final formula. This prediction formula fits the NACA65 blade calculation fairly. The average error of 24 calculation points is 2.59%. Then the improved model was compared with several existing models. Besides the CDA062, C4 and polynomial thickness distribution blade tip clearance loss is predicted using the refined prediction formula and the biggest prediction error is 5.46%. Therefore, the improved formula still has a good prediction effect when the blade type change. It is considered that within a certain range of maximum thickness of the blade type and tip gap sizes, the improved formula can give good predictions even though the blade type is different.
- Published
- 2021
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