An SMLD joint PDF model for turbulent non-premixed combustion using the flamelet progress-variable approach
Alessandro Coclite, Giuseppe Pascazio, Pietro De Palma, Luigi Cutrone,, Matthias Ihme

TL;DR
This paper introduces an improved flamelet/progress variable model for turbulent combustion that uses the statistically most likely distribution approach for joint PDFs, relaxing common assumptions and validating against experimental Sandia flames.
Contribution
It develops a more general joint PDF model for turbulent combustion, relaxing independence and shape assumptions, enhancing the accuracy of FPV simulations.
Findings
The new model better matches experimental data.
Relaxing assumptions improves simulation accuracy.
Comparison shows advantages over standard FPV models.
Abstract
This paper provides an improved flamelet/progress variable (FPV) model for the simulation of turbulent combustion, employing the statistically most likely distribution (SMLD) approach for the joint probability density function (PDF) of the mixture fraction, Z, and of the progress parameter, {\Lambda} . Steady-state FPV models are built presuming the func- tional shape of the joint PDF of Z and {\Lambda} in order to evaluate Favre-averages of thermody- namic quantities. The mixture fraction is widely assumed to behave as a passive scalar with a mono-modal behaviour modelled by a \b{eta} -distribution. Moreover, under the hypothesis that Z and {\Lambda} are statistically independent, the joint PDF coincides with the product of the two marginal PDFs. In this work we discuss these two constitutive hypotheses. The proposed model evaluates the most probable joint distribution of Z and…
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