Multi-point and multi-objective optimization of a centrifugal compressor impeller based on genetic algorithm

Li, Xiaojian, Liu, Zhengxian and Lin, Yujing (2017) Multi-point and multi-objective optimization of a centrifugal compressor impeller based on genetic algorithm. Mathematical Problems in Engineering, 2017(6263274), ISSN (print) 1024-123X

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Abstract

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.

Item Type: Article
Research Area: Mechanical, aeronautical and manufacturing engineering
Faculty, School or Research Centre: Faculty of Science, Engineering and Computing (until 2017) > School of Aerospace and Aircraft Engineering
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Depositing User: Susan Miles
Date Deposited: 27 Nov 2017 15:03
Last Modified: 06 Aug 2018 14:52
DOI: https://doi.org/10.1155/2017/6263274
URI: http://eprints.kingston.ac.uk/id/eprint/39661

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