Numerical modeling of turbulent premixed combustion using RANS based stochastic multiple mapping conditioning approach

Abstract

Stochastic multiple mapping conditioning (MMC) approach has been used to model a turbulent lean premixed jet flame of methane/air mixture within the Reynolds averaged Navier Stokes (RANS) framework. In MMC, the reaction progress variable is used as the reference variable. The mapping function approximates the cumulative probability distribution of reaction progress variable and the corresponding variance can be controlled by a standard implementation of the scalar mixing timescale. A separate equation is being solved for the evolution of the mapping function. Modified Curl's mixing model has been implemented to model the micro-mixing term. The stochastic MMC solver has been fully integrated with the RANS flow solver. Turbulence has been modeled using two equation k−ɛ model with a modified set of constants. A skeletal mechanism of 19 species and 15 reactions based on GRI 3.0 has been used in the present simulations. The Sydney piloted premixed jet burner (PPJB) operating in the distributed combustion regime has been considered for the model validation. Computed radial profiles of the mean axial velocity and species mass fractions are found to be in very good agreement with the available experimental data. In some instances, the RANS-MMC model produces a better match with the experimental data compared to the results obtained from other state-of-the-art turbulent combustion models.