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Comparison of Temperature Fields and Emissions Predictions Using Both an FGM Combustion Model, With Detailed Chemistry, and a Simple Eddy Dissipation Combustion Model With Simple Global Chemistry

[+] Author Affiliations
Pierre Q. Gauthier

Siemens Energy, Montreal, QC, Canada

Paper No. GT2017-65104, pp. V04BT04A068; 14 pages
  • ASME Turbo Expo 2017: Turbomachinery Technical Conference and Exposition
  • Volume 4B: Combustion, Fuels and Emissions
  • Charlotte, North Carolina, USA, June 26–30, 2017
  • Conference Sponsors: International Gas Turbine Institute
  • ISBN: 978-0-7918-5085-5
  • Copyright © 2017 by Siemens Canada Limited


The detailed modeling of the turbulence-chemistry interactions occurring in industrial flames has always been the leading challenge in combustion Computational Fluid Dynamics (CFD). The wide range of flame types found in Industrial Gas Turbine Combustion systems has exacerbated these difficulties greatly, since the combustion modeling approach must be able to predict the flames behavior from regions of fast chemistry, where turbulence has no significant impact on the reactions, to regions where turbulence effects play a significant role within the flame. One of these combustion models, that is being used more and more in industry today, is the Flamelet Generated Manifold (FGM) model, in which the flame properties are parametrized and tabulated based on mixture fraction and flame progress variables. This paper compares the results obtained using an FGM model, with a GRI-3.0 methane-air chemistry mechanism, against the more traditional Industrial work-horse, Finite-Rate Eddy Dissipation Model (FREDM), with a global 2-step Westbrook and Dryer methane-air mechanism. Both models were used to predict the temperature distributions, as well as emissions (NOx and CO) for a conventional, non-premixed, Industrial RB211 combustion system. The object of this work is to: (i) identify any significant differences in the predictive capabilities of each model and (ii) discuss the strengths and weakness of both approaches.

Copyright © 2017 by Siemens Canada Limited



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