Numerical investigation of auto-igniting turbulent lifted CH4/air jet diffusion flames in a vitiated co-flow using a RANS based stochastic multiple mapping conditioning approach

Abstract

Numerical simulations of auto-igniting turbulent lifted jet diffusion flames of CH4/air fuel issued into a vitiated coflow of lean combustion products of H2/air are performed using Reynolds-averaged Navier-Stokes (RANS) based stochastic multiple mapping conditioning (MMC) approach. A two-dimensional axisymmetric formulation is used to model the fluid flow, where the gas-phase turbulence terms are closed using the standard two-equation k-ε turbulence model with a modified set of constants. A reduced chemical mechanism ARM2 is used which consists of 19 species and 15 reactions derived from the GRI 3.0 mechanism. In MMC, the concept of mapping function is used, which approximates the cumulative probability distribution of the major scalar, namely mixture fraction for nonpremixed combustion. The corresponding variance of the major scalar is modelled by choosing a standard implementation of the major mixing time scale τϕ modelled in terms of the turbulent time scale as τϕ=τt/Cϕ. For all simulations reported herein, the same major mixing time constant Cϕ=3.0 is used. Additionally, in MMC, a minor mixing time scale τmin is introduced which controls fluctuations of scalars relative to the major fluctuations via the minor mixing time constant, Cmin. Three different values of Cmin=(τmin/τϕ)=0.25,0.35and0.50 are used and the corresponding ratios of minor to turbulent time scales are τmin/τt=0.083,0.116 and 0.166, respectively. The conditional and unconditional reactive scalar fields are found to be highly dependent on the choice of Cmin and hence the ratio of the minor and major mixing time scales. The numerical results are thoroughly validated against the experimental measurements. The variation in lift-off height is found to be in good agreement with the experimental data for the entire range of coflow temperature for Cmin=0.25. Also, the predicted conditional and unconditional scalar fields from the present RANS-MMC model shows an excellent agreement with the experimental measurements.