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Mathematical Problems in Engineering
Volume 2017, Article ID 6263274, 18 pages
Research Article

Multipoint and Multiobjective Optimization of a Centrifugal Compressor Impeller Based on Genetic Algorithm

1Department of Mechanics, Tianjin University, Tianjin 300072, China
2School of Mechanical and Aerospace Engineering, Kingston University London, London SW15 3DW, UK

Correspondence should be addressed to Zhengxian Liu; nc.ude.ujt@uilxz

Received 25 July 2017; Accepted 6 September 2017; Published 15 October 2017

Academic Editor: Filippo Ubertini

Copyright © 2017 Xiaojian Li et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


The design of high efficiency, high pressure ratio, and wide flow range centrifugal impellers is a challenging task. The paper describes the application of a multiobjective, multipoint optimization methodology to the redesign of a transonic compressor impeller for this purpose. The aerodynamic optimization method integrates an improved nondominated sorting genetic algorithm II (NSGA-II), blade geometry parameterization based on NURBS, a 3D RANS solver, a self-organization map (SOM) based data mining technique, and a time series based surge detection method. The optimization results indicate a considerable improvement to the total pressure ratio and isentropic efficiency of the compressor over the whole design speed line and by 5.3% and 1.9% at design point, respectively. Meanwhile, surge margin and choke mass flow increase by 6.8% and 1.4%, respectively. The mechanism behind the performance improvement is further extracted by combining the geometry changes with detailed flow analysis.