Gas turbines are one of the most important energy conversion methods in the world today. This is because using gas turbines, large scale, high efficiency, low cost and low emission energy production is possible. For this type of engines, low pollutants emissions can be achieved by very lean premixed combustion systems. Numerical simulation is foreseen to provide a tremendous increase in gas turbine combustors design efficiency and quality over the next future. However, the numerical simulation of modern stationary gas-turbine combustion systems represents a very challenging task. Several numerical models have been developed in order to reduce the costs of flame simulations for engineering applications. In the present paper the Flamelet-Generated Manifold (FGM) chemistry reduction method is implemented and extended for the inclusion of all the features that are typically observed in stationary gas-turbine combustion. These consist of stratification effects, heat loss and turbulence. The latter is included by coupling FGM with the Reynolds Averaged Navier Stokes (RANS) model. 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 probability density function (PDF) approach, which is considered for progress variable and mixture fraction. This results in two extra control variables: progress variable variance and mixture fraction variance. The resulting manifold is therefore five-dimensional, in which the dimensions are progress variable, enthalpy, mixture fraction, progress variable variance and mixture fraction variance. A highly turbulent and swirling flame in a gas turbine model combustor is computed in order to test the 5-D FGM implementation. 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.

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