Robust design optimization method for centrifugal impellers under surface roughness uncertainties due to blade fouling

Blade fouling has been proved to be a great threat to compressor performance in operating stage. The current researches on fouling-induced performance degradations of centrifugal compressors are based mainly on simplified roughness models without taking into account the realistic factors such as spatial non-uniformity and randomness of the fouling-induced surface roughness. Moreover, little attention has been paid to the robust design optimization of centrifugal compressor impellers with considerations of blade fouling. In this paper, a multi-objective robust design optimization method is developed for centrifugal impellers under surface roughness uncertainties due to blade fouling. A three-dimensional surface roughness map is proposed to describe the nonuniformity and randomness of realistic fouling accumulations on blades. To lower computational cost in robust design optimization, the support vector regression (SVR) metamodel is combined with the Monte Carlo simulation (MCS) method to conduct the uncertainty analysis of fouled impeller performance. The analyzed results show that the critical fouled region associated with impeller performance degradations lies at the leading edge of blade tip. The SVR metamodel has been proved to be an efficient and accurate means in the detection of impeller performance variations caused by roughness uncertainties. After design optimization, the robust optimal design is found to be more efficient and less sensitive to fouling uncertainties while maintaining good impeller performance in the clean condition. This research proposes a systematic design optimization method for centrifugal compressors with considerations of blade fouling, providing a practical guidance to the design of advanced centrifugal compressors.

[1]  Qiang Zhang,et al.  Aerodynamic Losses of a Cambered Turbine Vane: Influences of Surface Roughness and Freestream Turbulence Intensity , 2006 .

[2]  Ryusuke Numakura,et al.  Prediction of Surface Roughness Effects on Centrifugal Compressor Performance , 2008 .

[3]  Tiziano Ghisu,et al.  Robust design optimization of gas turbine compression systems , 2011 .

[4]  Lei Yu,et al.  Test and Simulation of the Effects of Surface Roughness on a Shrouded Centrifugal Impeller , 2014 .

[5]  Yaping Ju,et al.  Optimization of Centrifugal Impellers for Uniform Discharge Flow and Wide Operating Range , 2012 .

[6]  O. L. Maître,et al.  Spectral Methods for Uncertainty Quantification: With Applications to Computational Fluid Dynamics , 2010 .

[7]  Kai-Tai Fang,et al.  Uniform design and its industrial applications , 2007 .

[8]  Andy J. Keane,et al.  Robust design using Bayesian Monte Carlo , 2008 .

[9]  J. Bons.  A Review of Surface Roughness Effects in Gas Turbines , 2010 .

[10]  Omar M. Knio,et al.  Spectral Methods for Uncertainty Quantification , 2010 .

[11]  Friedrich-K. Benra,et al.  Sensitivity Study on the Impact of Surface Roughness Due to Milling on the Efficiency of Shrouded Centrifugal Compressor Impellers , 2006 .

[12]  Y P Ju,et al.  Multi-point robust design optimization of wind turbine airfoil under geometric uncertainty , 2012 .

[13]  Tom Hynes,et al.  Influence of Surface Roughness on Three-Dimensional Separation in Axial Compressors , 2004 .

[14]  Jeffrey P. Bons,et al.  Effects of a Realistically Rough Surface on Vane Heat Transfer Including the Influence of Turbulence Condition and Reynolds Number , 2010 .

[15]  G. Gary Wang,et al.  Review of Metamodeling Techniques in Support of Engineering Design Optimization , 2007 .

[16]  Michael Casey,et al.  A unified correction method for Reynolds number, size, and roughness effects on the performance of compressors , 2011 .

[17]  Bernhard Schölkopf,et al.  A tutorial on support vector regression , 2004, Stat. Comput..

[18]  H. Krain,et al.  Verification of an Impeller Design by Laser Measurements and 3D-Viscous Flow Calculations , 1989 .

[19]  F. Menter.  Two-equation eddy-viscosity turbulence models for engineering applications , 1994 .

[20]  Y P Ju,et al.  Multi-point and multi-objective optimization design method for industrial axial compressor cascades , 2011 .

[21]  Matteo Giovannini,et al.  A Path Toward the Aerodynamic Robust Design of Low Pressure Turbines , 2013 .

[22]  Lars E. Bakken,et al.  The Impact of Surface Roughness on Axial Compressor Performance Deterioration , 2006 .

[23]  H. Simon,et al.  On the Evaluation of Reynolds Number and Relative Surface Roughness Effects on Centrifugal Compressor Performance Based on Systematic Experimental Investigations , 1984 .

[24]  Michele Pinelli,et al.  Numerical Analysis of the Effects of Nonuniform Surface Roughness on Compressor Stage Performance , 2011 .

[25]  Andy J. Keane,et al.  Cokriging for Robust Design Optimization , 2012 .

[26]  Sriram Shankaran,et al.  Robust Optimization for Aerodynamic Problems Using Polynomial Chaos and Adjoints , 2012 .

[27]  I. N. Egorov,et al.  HOW TO EXECUTE ROBUST DESIGN OPTIMIZATION , 2002 .

[28]  W. B. Roberts,et al.  The effect of adding roughness and thickness to a transonic axial compressor rotor , 1994 .

[29]  M. Zangeneh,et al.  Investigation of an Inversely Designed Centrifugal Compressor Stage-Part I: Design and Numerical Verification (2003-GT-38531) , 2004 .

[30]  Min Xie,et al.  A systematic comparison of metamodeling techniques for simulation optimization in Decision Support Systems , 2010, Appl. Soft Comput..

[31]  T. Simpson,et al.  Analysis of support vector regression for approximation of complex engineering analyses , 2005, DAC 2003.

[32]  Ihor S. Diakunchak.  Performance Deterioration in Industrial Gas Turbines , 1992 .