Investigation of an Atmospheric Gas Turbine Model Combustor with Large-Eddy Simulation Using Finite-Rate Chemistry

ABSTRACT

A large-eddy simulation (LES) of an atmospheric confined jet flame test case is presented, which represents a model gas turbine combustor and for which detailed experimental data is available. A genetic algorithm approach is used to develop a new, cost-effective reduced mechanism for lifted lean premixed methane-air flames at atmospheric conditions. For the mechanism development, auto-ignition-delay time of mixtures of reactants and cooled down combustion products has been introduced as an optimization criterion. The new mechanism consists of 11 species and 12 reactions. The developed mechanism is validated by comparing the results of zero-dimensional (0D) reactor and one-dimensional (1D) flame simulations against results from the well-known reaction mechanism, GRI-3.0 and Lu19. The three-dimensional (3D) LES are carried out using a finite-rate chemistry (FRC) approach combined with the dynamic thickened flame (DTF) model. In the simulations, the developed mechanism is compared against the Lu19 mechanism and experimental data. Simulations using Lu19 show that the flame is predicted accurately. The new mechanism predicts the flame liftoff and position well, while slightly underpredicting the flame length and showing deviation in quenching behavior but achieves a very significant speedup factor of approximately 2.9 for the entire 3D simulation. For the DTF model, two flame sensor functions are compared, the first based on the progress variable and the second on the local heat release rate. The heat release based formulation is found to be preferable, as it detects the reaction region well, as opposed to the progress variable based formulation which additionally senses zones where reaction products are mixed with reactants, i.e. zones where no classical premixed flame propagation is observed.

KEYWORDS:

• large-eddy simulation
• finite rate chemistry
• lifted jet flames

Acknowledgements

The authors gratefully acknowledge the financial support of the Bundesministerium für Wirtschaft und Energie for the project “RoBoFlex AP 4.5 - Untersuchung/Vorhersage von hochfrequenten Verbrennungsinstabilitäten mit LES” (FKZ.: 03EE5013D) and the computing time granted by the Center for Computational Sciences and Simulation (CCSS) of the University of Duisburg-Essen provided on the supercomputer magnitUDE (DFG grants INST 20876/209-1 FUGG, INST 20876/243-1 FUGG) at the Zentrum für Informations- und Mediendienste.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This work was supported by the Bundesministerium für Witschaft und Energie under Grant 03EE5013D; and Deutsche Forschungsgemeinschaft under Grants INST 20876/209-1 FUGG and INST 20876/243-1 FUGG