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Uncertainty analysis of measured geometric variations in turbine blades and impact on aerodynamic performance

Chinese Journal of Aeronautics 2023年第6期36卷 140-160页

作者： Xiaojing WANG Pengcheng DU Lichao YAO Zhengping ZOU Fei ZENG School of Energy and Power Engineering Beihang UniversityBejing 100191China National Key Laboratory of Science and Technology on Aero-Engine Aero-Thermodynamics Beihang UniversityBejing 100191China Research Institute of Aero-Engine Beihang UniversityBeijing 100191China AECC Hunan Aviation Powerplant Research Institute Zhuzhou 412002China

Inevitable geometric variations significantly affect the performance of turbines or even that of entire engines;thus,it is necessary to determine their actual characteristics and accurately estimate their impact on *** this study,based on 1781 measured profiles of a typical turbine blade,the statistical characteristics of the geometric variations and the uncertainty impact are analyzed,and some commonly used uncertainty modelling methods based on Principal-Component Analysis(PCA)are *** geometric variations are found to be evident,asymmetric,and non-uniform,and the non-normality of the random distributions is *** performance is notably affected,which is manifested as an overall offset,a notable scattering,and significant deterioration in several extreme ***,it is demonstrated that the PCA reconstruction model is effective in characterizing major uncertainty characteristics of the geometric variations and their impact on the performance with almost the first 10 PCA *** on a reasonable profile error and mean geometric deviation,the Gaussian assumption and stochasticprocess-based model are also found to be effective in predicting the mean values and standard deviations of the performance ***,they fail to predict the probability of some extreme cases with high ***,a Chi-square-based correction model is proposed to compensate for this *** present work can provide a useful reference for uncertainty analysis of the impact of geometric variations,and the corresponding uncertainty design of turbine blades.

关键词： Aerodynamic performance measured geometric variations Principal-component analysis Turbine blade Uncertainty analysis

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