A 5-D Implementation of FGM for the Large Eddy Simulation of a Stratified Swirled Flame with Heat Loss in a Gas Turbine Combustor

Numerical simulations are foreseen to provide a tremendous increase in gas-turbine burners efficiency in the near future. Modern developments in numerical schemes, turbulence models and the consistent increase of computing power allow Large Eddy Simulation (LES) to be applied to real cold flow industrial applications. However, the detailed simulation of the gas-turbine combustion process remains still prohibited because of its enormous computational cost. Several numerical models have been developed in order to reduce the costs of flame simulations for engineering applications. In this paper, the Flamelet-Generated Manifold (FGM) chemistry reduction technique is implemented and progressively extended for the inclusion of all the combustion features that are typically observed in stationary gas-turbine combustion. These consist of stratification effects, heat loss and turbulence. Three control variables are included for the chemistry representation: the reaction evolution is described by the reaction progress variable, the heat loss is described by the enthalpy and the stratification effect is expressed by the mixture fraction. The interaction between chemistry and turbulence is considered through a presumed beta-shaped probability density function (PDF) approach, which is considered for progress variable and mixture fraction, finally attaining a 5-D manifold. The application of FGM in combination with heat loss, fuel stratification and turbulence has never been studied in literature. To this aim, a highly turbulent and swirling flame in a gas turbine combustor is computed by means of the present 5-D FGM implementation coupled to an LES turbulence model, and the results are compared with experimental data. In general, the model gives a rather good agreement with experimental data. It is shown that the inclusion of heat loss strongly enhances the temperature predictions in the whole burner and leads to greatly improved NO predictions. The use of FGM as a combustion model shows that combustion features at gas turbine conditions can be satisfactorily reproduced with a reasonable computational effort. The implemented combustion model retains most of the physical accuracy of a detailed simulation while drastically reducing its computational time, paving the way for new developments of alternative fuel usage in a cleaner and more efficient combustion.