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3D Multi-Disciplinary Inverse Design Based Optimization of a Centrifugal Compressor Impeller

[+] Author Affiliations
Mehrdad Zangeneh

University College London, London, UK

Fred Mendonça

CD-ADAPCO, London, UK

Youngwon Hahn, Jack Cofer

SIMULIA, Providence, RI

Paper No. GT2014-26961, pp. V02BT45A022; 8 pages
doi:10.1115/GT2014-26961
From:
  • ASME Turbo Expo 2014: Turbine Technical Conference and Exposition
  • Volume 2B: Turbomachinery
  • Düsseldorf, Germany, June 16–20, 2014
  • Conference Sponsors: International Gas Turbine Institute
  • ISBN: 978-0-7918-4561-5
  • Copyright © 2014 by ASME

abstract

Design of centrifugal compressors in different applications from industrial to turbochargers to aeroengine is subject to difficult multi-disciplinary ( aerodynamics and mechanical) and multipoint/multi-objective requirements. These multi-disciplinary and multi-point requirements have to be met by iterations between aerodynamics and mechanical design, leading to long development times and bottlenecks in the design process. In this paper, for the first time, a commercially available solution, compatible with industrial development times, is presented for 3D multi-disciplinary and multi-point design optimisation of turbomachinery blades. The methodology combines 3D inverse design method, automatic optimizers, 3D CFD and 3D FEA codes. The key aspect of the approach is to parameterise the 3D geometry through the blade loading distribution used in 3D inverse design code TURBOdesign1, which results in ability to access large part of design space with very few design parameters. The Design of Experiments method is used to generate a number of geometries which are then analysed by 3D CFD code STAR-CCM+ and 3D FEA code Abaqus. Different performance parameters related to aerodynamics (efficiency, stable operating range etc) and structural integrity (maximum principal stress, etc) are then evaluated. The data is then used to create a response surface. The validity and accuracy of the response surface is evaluated by CFD and FEA and then once confirmed a Multi-objective Genetic Algorithm is run on the response surface to explore the trade-offs between different design parameters, such as peak efficiency, stable operating range and mechanical stress. In this paper the methodology is applied to the redesign of the well-known Eckardt centrifugal compressor impeller.

Copyright © 2014 by ASME

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