Impact of Geometric Variability on Axial Compressor Performance

Author:

Garzon Victor E.1,Darmofal David L.1

Affiliation:

1. Department of Aeronautics and Astronautics, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, MA 02139

Abstract

A probabilistic methodology to quantify the impact of geometric variability on compressor aerodynamic performance is presented. High-fidelity probabilistic models of geometric variability are derived using a principal-component analysis of blade surface measurements. This probabilistic blade geometry model is then combined with a compressible, viscous blade-passage analysis to estimate the impact on the passage loss and turning using a Monte Carlo simulation. Finally, a mean-line multistage compressor model, with probabilistic loss and turning models from the blade-passage analysis, is developed to quantify the impact of the blade variability on overall compressor efficiency and pressure ratio. The methodology is applied to a flank-milled integrally bladed rotor. Results demonstrate that overall compressor efficiency can be reduced by approximately 1% due to blade-passage effects arising from representative manufacturing variability.

Publisher

ASME International

Subject

Mechanical Engineering

Reference19 articles.

1. Lykins, C., Thompson, D., and Pomfret, C., 1994, “The Air Force’s Application of Probabilistics to Gas Turbine Engines,” AIAA paper 94-1440-CP.

2. Preisendorfer, R. W., 1988, Principal Component Analysis in Meteorology and Oceanography, Elsevier, Amsterdam.

3. Jolliffe, I. T., 1986, Principal Component Analysis, Springer Verlag, New York.

4. Trefethen, L. N., and Bau, D., 1997, Numerical Linear Algebra, Society for Industrial and Applied Mathematics, Philadelphia, PA.

5. Drela, M., and Youngren, H., 2001, XFOIL 6.9 User Guide, Dept. of Aeronautics and Astronautics, Massachusetts Institute of Technology, 77 Massachusetts Ave, Cambridge MA 02139.

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