Large Eddy Simulation of Combustion Systems at Gas Turbine Conditions

  • J. Janicka
  • J. Kuehne
  • G. Kuenne
  • A. KetelheunEmail author
Part of the Fluid Mechanics and Its Applications book series (FMIA, volume 1581)


Three different aspects of Large Eddy Simulation (LES) of combustion processes are covered in this chapter. All three are based on using tabulated chemistry models to cover the chemical reactions occurring in gas turbines. The chosen approaches are all based on flamelet models. One part of the work deals with the investigation of subgrid scale models using Transported Eulerian Monte Carlo Probability Density Function (PDF) methods. The chemistry is dealt with using non-premixed flamelets and premixed Flamelet Generated Manifolds (FGM). The second aspect covered is the extension of the FGM method towards premixed flames where unresolved subgrid flame structures need to be handled. Therefore, the FGM approach was coupled with the Artificially Thickened Flames (ATF) model. The third aspect of combustion LES discussed here deals with the inclusion of more detailed reaction kinetics in the FGM approach in order to better predict minor species like nitric oxides or carbon monoxide, which are important development goals in today’s gas turbine industry. As all three aspects discussed in this chapter are located on the smallest scales in a combustion system, either the flow or flame subgrid structures, they are closely related to each other.


Large Eddy Simulation Turbulent Combustion Premixed Flames Monte Carlo PDF Pollutant Prediction 



The authors acknowledge the financial support from the German Research Council (DFG) through the SFB568.


Project-Related Publications

  1. 1.
    Kuehne, J.: Analysis of combustion LES using an Eulerian Monte Carlo PDF method. PhD thesis, TU Darmstadt (2011)Google Scholar
  2. 2.
    Kuehne, J., Ketelheun, A., Janicka, J.: Analysis of sub-grid PDF of a progress variable approach using a hybrid LES/TPDF method. Proc. Combust. Inst. 33, 1411–1418 (2011)CrossRefGoogle Scholar
  3. 3.
    Kuenne, G., Ketelheun, A., Janicka, J.: LES modeling of premixed combustion using a thickened flame approach coupled with FGM tabulated chemistry. Combust. Flame 158, 1750–1767 (2011)CrossRefGoogle Scholar
  4. 4.
    Ketelheun, A., Olbricht, C., Hahn, F., Janicka, J.: NO prediction in turbulent flames using LES/FGM with additional transport equations. Proc. Combust. Inst. 33(2), 2975–2982 (2011)CrossRefGoogle Scholar
  5. 5.
    Ketelheun, A., Aschmoneit, K., Janicka, J.: CO prediction in LES of turbulent flames with additional modeling of the chemical source term. ASME Turbo Expo, Copenhagen, Denmark, accepted for publication, 11–15 June 2012 (2012)Google Scholar

Other Publications

  1. 6.
    Smith, G.P., Golden, D.M., Frenklach, M., Moriarty, N.W., Eiteneer, B., Goldenberg, M., Bowman, C.T., Hanson, R.K., Song, S., Gardiner Jr., W.C., Lissianski, V.V., Qin, Z.: GRI3.0: (2008). Accessed Apr 2008
  2. 7.
    Peters, N.: Laminar diffusion flamelet models in non-premixed turbulent combustion. Prog. Energy Combust. Sci. 10, 319–339 (1984)CrossRefGoogle Scholar
  3. 8.
    van Oijen, J.A., de Goey, L.P.H.: Modelling of premixed laminar flames using Flamelet-Generated Manifolds. Combust. Sci. Technol. 161, 113–137 (2000)CrossRefGoogle Scholar
  4. 9.
    Gicquel, O., Darabiha, N., Thévenin, D.: Laminar premixed hydrogen/air counterflow flame simulations using flame prolongation of ILDM with differential diffusion. Proc. Combust. Inst. 28, 1901–1908 (2000)CrossRefGoogle Scholar
  5. 10.
    Rhodes, R.P.: A probability distribution function for turbulent flows. In: Murthy, S.N.B. (ed.) Turbulent Mixing in Nonreactive and Reactive Flows, pp. 235–241. Plenum Press, New York (1975)CrossRefGoogle Scholar
  6. 11.
    Landenfeld, T., Sadiki, A.: A turbulence-chemistry interaction model based on a multivariate presumed beta-pdf method for turbulent flames. Flow Turbul. Combust. 68(2), 111–135 (2002)zbMATHCrossRefGoogle Scholar
  7. 12.
    Dally, B.B., Fletcher, D.F., Masri, A.R.: Flow and mixing fields of turbulent bluff-body jets and flames. Combust. Theory Model. 2, 193–219 (1998)zbMATHCrossRefGoogle Scholar
  8. 13.
    Dally, B.B., Masri, A.R., Barlow, R.S., Fiechtner, G.J.: Instantaneous and mean compositional structure of bluff-body stabilized nonpremixed flames. Combust. Flame 114, 119–148 (1998)CrossRefGoogle Scholar
  9. 14.
    Chem1D. A one-dimensional laminar flame code, developed at Eindhoven University of Technology, (2008). Accessed Apr 2008
  10. 15.
    Butler, T., O’Rourke, P.: A numerical method for two dimensional unsteady reacting flows. In: Proceedings of the 16th Symposium (International) on Combustion, pp. 1503–1515 (1977)Google Scholar
  11. 16.
    Colin, O., Ducros, F., Veynante, D., Poinsot, T.: A thickened flame model for large eddy simulations of turbulent premixed combustion. Phys. Fluids 12, 1843–1863 (2000)CrossRefGoogle Scholar
  12. 17.
    Schneider, C., Dreizler, A., Janicka, J.: Fluid dynamical analysis of atmospheric reacting and isothermal swirling flows. Flow Turbul. Combust. 74, 103–127 (2005)zbMATHCrossRefGoogle Scholar
  13. 18.
    Gregor, M., Seffrin, F., Fuest, F., Geyer, D., Dreizler, A.: Multi-scalar measurements in a premixed swirl burner using 1D Raman/Rayleigh scattering. Proc. Combust. Inst. 32, 1739–1746 (2009)CrossRefGoogle Scholar
  14. 19.
    Klein, M., Sadiki, A., Janicka, J.: A digital filter based generation of inflow data for spatially developing direct numerical or large eddy simulations. J. Comput. Phys. 186, 652–665 (2003)zbMATHCrossRefGoogle Scholar
  15. 20.
    Wegner, B., Gruschka, U., Krebs, W., Egorov, Y., Forkel, H., Ferreira, J., Aschmoneit, K.: CFD prediction of partload CO emissions using a two-timescale combustion model. J. Eng. Gas Turbines Power 133(7), 071502 (2011)CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2013

Authors and Affiliations

  • J. Janicka
    • 1
    • 2
  • J. Kuehne
    • 1
  • G. Kuenne
    • 1
  • A. Ketelheun
    • 1
    Email author
  1. 1.Department of Mechanical and Processing Engineering, Institute for Energy and Power Plant TechnologyTechnische Universität DarmstadtDarmstadtGermany
  2. 2.Center of Smart InterfacesTechnische Universität DarmstadtDarmstadtGermany

Personalised recommendations