The work presented in this thesis explores the feasibility of the Multiple Mapping Conditioning (MMC) approach and its closures for real (laboratory) flames. Three different
configurations with relatively high Reynolds numbers but without considerable degree of
extinction and re-ignition are investigated, and results are compared against experimental
measurements of mixing and reactive scalar fields and other commonly used models.
MMC combines the probability density function (PDF) approach and the conditioning
methods via the application of a generalised mapping function to a prescribed reference
space. Stochastic and deterministic formulations of MMC exist. Both formulations have
been explored here for the case of one dimensional Gaussian reference space that is associated with the evolution of mixture fraction. The chemically reactive species are implicitly
conditioned on mixture fraction, and their fluctuations around the conditional means are
neglected for the deterministic approach and modelled for the stochastic approach. Regarding the velocity field evolution, the Reynolds Averaged Navier-Stokes equations are
solved with a k-[epsilon]turbulence model.
In the deterministic context, this work evaluates the ability of MMC to provide accurate and consistent closures for the mixture fraction PDF and the conditional scalar
dissipation which do not rely on presumed shape functions for the PDF such as the commonly used [Beta]-PDF. Computed probability distributions agree well with measurements,
and a detailed comparison of the modelled conditional and mean scalar dissipation with
experimental data and conventional closures demonstrate MMC’s potential. Predictions of
reactive species and temperature are in good agreement with experimental data and similar in quality to singly-conditioned, first-order CMC predictions. MMC therefore provides
an attractive -since consistent- alternative approach for the modelling of scalar mixing in
turbulent reacting flows.
In the stochastic context the evolution of the reference space is described by a Markov
process that is coupled with a full PDF method for joint scalar evolution. A modified
IECM model is applied for the modelling of the mixing operator where the particles mix
with their means conditioned on the reference space. The formulation of the closure leads
to localness of mixing in the mixture fraction space and consequently localness is expected
to be improved in the composition space. Focus is given on the accurate prediction of
scattering around the conditional means. Results demonstrate the potential of the method,
however some discrepancies are noted in the predictions that can probably be associated
with the chemical mechanism and the uncertainties associated with the choice of the minor
dissipation time.