Full Content is available to subscribers

Subscribe/Learn More  >

Global Three-Dimensional Surrogate Modeling of Gas Turbine Aerodynamic Performance

[+] Author Affiliations
Zafer Leylek

Defence Science Technology Group, Fishermens Bend, Australia

A. J. Neely

University of New South Wales, Australian Defence Force Academy, Australia

Paper No. GT2017-63920, pp. V02BT41A025; 12 pages
  • ASME Turbo Expo 2017: Turbomachinery Technical Conference and Exposition
  • Volume 2B: Turbomachinery
  • Charlotte, North Carolina, USA, June 26–30, 2017
  • Conference Sponsors: International Gas Turbine Institute
  • ISBN: 978-0-7918-5079-4
  • Copyright © 2017 by ASME


Turbine blade aerodynamic performance can be accurately predicted using one-dimensional mean-line and two-dimensional through-flow solvers. These predictions have been achieved by coupling one and two-dimensional ideal flow equations with blade aerodynamic loss and flow deviation angle models. These loss and deviation models are largely generated using classical cascade testing which have limitations and constraints. These limitations are associated with testing in general and include scope, time, resources, geometric and operating parameter space, data scatter and uncertainty. The models largely ignore interaction effects and can be subjective. The loss and deviation models also do not incorporate blade features associated with modern turbine blades. The objective of this paper is to study the feasibility of conducting these experiments numerically using three-dimensional turbine blade and constructing global blade performance and loss models.

The study looks at a number of competing surrogate modeling techniques and evaluates their performance for optimum blade loss and deviation prediction. The effect of Reynolds number, performance parameter definition, operating condition specification along with the use of extended parameters are investigated to further enhance the surrogate models. The performance map generated using the optimized surrogate models is then validated using a 1.5 stage axial turbine. The results show that numerically generated surrogate models can be used to accurately predict the CFD based axial turbine performance.

Copyright © 2017 by ASME



Interactive Graphics


Country-Specific Mortality and Growth Failure in Infancy and Yound Children and Association With Material Stature

Use interactive graphics and maps to view and sort country-specific infant and early dhildhood mortality and growth failure data and their association with maternal

Citing articles are presented as examples only. In non-demo SCM6 implementation, integration with CrossRef’s "Cited By" API will populate this tab (http://www.crossref.org/citedby.html).

Some tools below are only available to our subscribers or users with an online account.

Related Content

Customize your page view by dragging and repositioning the boxes below.

Related eBook Content
Topic Collections

Sorry! You do not have access to this content. For assistance or to subscribe, please contact us:

  • TELEPHONE: 1-800-843-2763 (Toll-free in the USA)
  • EMAIL: asmedigitalcollection@asme.org
Sign In