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Framework for Multidisciplinary Optimization of Turbomachinery

[+] Author Affiliations
Mark G. Turner, Kevin Park, Kiran Siddappaji, Soumitr Dey, David P. Gutzwiller

University of Cincinnati, Cincinnati, OH

Ali Merchant

CADNexus, Burlington, MA

Dario Bruna

NASA Glenn Research Center, Cleveland, OH

Paper No. GT2010-22228, pp. 623-631; 9 pages
doi:10.1115/GT2010-22228
From:
  • ASME Turbo Expo 2010: Power for Land, Sea, and Air
  • Volume 7: Turbomachinery, Parts A, B, and C
  • Glasgow, UK, June 14–18, 2010
  • Conference Sponsors: International Gas Turbine Institute
  • ISBN: 978-0-7918-4402-1 | eISBN: 978-0-7918-3872-3
  • Copyright © 2010 by ASME

abstract

A multidisciplinary optimization framework is presented for turbomachinery that looks at weight and efficiency as multiple objective functions. Both the blades and disks are considered in a multi-level optimization approach. An axisymmetric solver with loss models is used for the flowpath and blade design, and optimized disks are created at each step of the process. Constraints include temperature dependent strength requirements for many common materials. The other constraint limits the work done by the component. A genetic algorithm is used to find the pareto front for the multi-objective functions. Optimization of the 10 stage GE EEE compressor is presented to demonstrate the framework. Detailed parameter based CAD models are also produced so these can be used as a starting point for higher fidelity optimization.

Copyright © 2010 by ASME

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