A large-eddy simulation scheme for turbulent reacting flows

Abstract. In the present study a Large Eddy Simulation and Filtered Density Function model is applied to three premixed piloted turbulent methane flames at different Reynolds Numbers using the Eulerian stochastic fields approach. The model is able to reproduce the flame structure and flow characteristics with a low number of fields (between 4 and 16 fields). The results show a good agreement with experimental data with the same closures employed in non-premixed combustion without any adjustment for combustion regime. The effect of heat release on the flow field is captured correctly. A wide range of sensitivity studies is carried out, including the number of fields, the chemical mechanism, differential diffusion effects and micro-mixing closures. The present work shows that premixed combustion (at least in the conditions under study) can be modelled using LES-PDF methods.. Finally, the ability of the model to predict flame quenching is studied. The model can accurate capture the conditions at which combustion is not sustainable and large pockets of extinction appear.

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“…(1), a density-weighted sub-grid (or filtered) PDF for the N S +1 scalar quantities can be defined as follows [34]:…”

Section: Filtered Probability Density Functionmentioning

confidence: 99%

Large Eddy Simulation of Premixed Turbulent Flames Using the Probability Density Function Approach

Dodoulas

Navarro‐Martinez

2013

Flow Turbulence Combust

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“…He showed that the use of this methodology offers for reacting flow simulations the same advantage as the use of PDF methods: chemical reactions appear in a closed form. Gao and O'Brien [5] developed a transport equation for the scalar FDF and offered suggestions for modeling of the unclosed terms in this equation.…”

Section: Introductionmentioning

confidence: 99%

On Fokker–Planck Equations for Turbulent Reacting Flows. Part 1. Probability Density Function for Reynolds-Averaged Navier–Stokes Equations

Stefan

2003

Flow, Turbulence and Combustion

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Abstract. The application of large eddy simulation (LES) to turbulent reacting flow calculations is faced with several closure problems. Suitable parametrizations for filtered reaction rates for instance are hardly available in general. A way to overcome these problems is investigated here. This is done by extending LES equations for filtered velocities and scalars (mass fractions of species and temperature) to equations that involve subgrid scale (SGS) fluctuations. Such equations are called filter density function (FDF) methods because they determine the FDF, which is essentially the probability density function of SGS variables. The FDF model considered involves only three parameters: C 0 that controls the generation of velocity fluctuations and two parameters which determine the relaxation of velocity and scalar fluctuations. The consideration of this model may be seen as the analysis of a limiting case: the implications of the most simple equations for the dynamics of SGS fluctuations are investigated in this way. These equations were proved recently by various simulations. Here, the FDF model is used analytically to improve simpler methods. Existing models for the SGS stress tensor in velocity LES equations and the diffusion coefficient in scalar FDF equations are generalized in this way. The advantages of these models compared to existing ones are pointed out. These investigations provide further evidence for the suitability of the FDF model considered and they provide its parameters. A theoretical value C 0 = 19/12 is derived, which agrees very well with the results of direct numerical simulation. This estimate implies the same value for the universal Kolmogorov constant of the energy spectrum, which is consistent with the results of many measurements. The other two model parameters can be obtained then by dynamic procedures. Therefore, the closure problems of LES equations are overcome in this way such that adjustable parameters are not involved.

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“…19 This is the most elementary form of the model, [20][21][22][23][24] and has experienced widespread applications for LES of a variety of reactive flows. Some examples are in Refs; see Ref.…”

Section: Scalar-fdf (S-fdf and S-fmdf)mentioning

confidence: 99%