Statistical Analysis of the Reaction Progress Variable and Mixture Fraction Gradients in Flames Propagating into Droplet Mist: A Direct Numerical Simulation Analysis

The modelling of scalar dissipation rate in conditional methods for large-eddy simulations is investigated based on a priori direct numerical simulation analysis using a dataset representing an igniting non-premixed planar jet flame. The main objective is to provide a comprehensive assessment of models typically used for large-eddy simulations of non-premixed turbulent flames with the Conditional Moment Closure combustion model. The linear relaxation model gives a good estimate of the Favre-filtered scalar dissipation rate throughout the ignition with a value of the related constant close to the one deduced from theoretical arguments. Such value of the constant is one order of magnitude higher than typical values used in Reynolds-averaged approaches. The amplitude mapping closure model provides a satisfactory estimate of the conditionally filtered scalar dissipation rate even in flows characterised by shear driven turbulence and strong density variation.

Section: Dns Datasetmentioning

confidence: 63%

A-Priori Validation of Scalar Dissipation Rate Models for Turbulent Non-Premixed Flames

Sitte

Turquand

Giusti

et al. 2020

“…Furthermore, the validity of existing closures of e ε Y and the unclosed terms of its transport equation, which were originally proposed for purely gaseous phase combustion, is yet to be assessed for turbulent spray flames. These gaps in the existing literature have been addressed here by analysing the statistical behaviours of e ε Y and the terms of its transport equation using a three-dimensional compressible Direct Numerical Simulations (DNS) database [9][10][11][12] of statistically planar turbulent flames propagating into droplet-laden mixtures where the fuel is supplied in the form of mono-disperse droplets ahead of the flame. The current study considers selected cases from a large database [9][10][11][12] such that the effects of droplet diameter a d and droplet equivalence ratio ϕ d (i.e.…”

Section: Introductionmentioning

confidence: 99%

“…These gaps in the existing literature have been addressed here by analysing the statistical behaviours of e ε Y and the terms of its transport equation using a three-dimensional compressible Direct Numerical Simulations (DNS) database [9][10][11][12] of statistically planar turbulent flames propagating into droplet-laden mixtures where the fuel is supplied in the form of mono-disperse droplets ahead of the flame. The current study considers selected cases from a large database [9][10][11][12] such that the effects of droplet diameter a d and droplet equivalence ratio ϕ d (i.e. fuel in liquid droplets to air ratio by mass, normalised by fuel to air ratio by mass under stoichiometric condition) on the statistical behaviours of e ε Y and its transport can be analysed in detail.…”

Section: Introductionmentioning

confidence: 99%

Statistical Behaviour and Modelling of Fuel Mass Fraction Dissipation Rate Transport in Turbulent Flame-Droplet Interaction: A Direct Numerical Simulation study

Malkeson

Wacks

Chakraborty

2020

Self Cite

Three-dimensional Direct Numerical Simulation (DNS) data of statistically planar turbulent spray flames propagating into mono-disperse droplets for different values of droplet diameter ad and droplet equivalence ratio ϕd has been used to analyse the statistical behaviour of the fuel mass fraction dissipation rate $$ \overset{\sim }{\upvarepsilon_Y} $$εY~ and its transport in the context of Reynolds Averaged Navier-Stokes (RANS) simulations. Closures previously derived for high Damköhler number turbulent stratified mixture combustion have been shown not to capture the statistical behaviour of $$ \overset{\sim }{\upvarepsilon_Y} $$εY~ for turbulent spray flames, because the underlying assumptions behind the original modelling are invalid for the cases considered in this analysis. The modelling of the unclosed terms of the fuel mass fraction dissipation rate $$ \overset{\sim }{\upvarepsilon_Y} $$εY~ transport equation (i.e. the turbulent transport term T1, the density variation term T2, the scalar turbulence interaction term T3, the reaction rate term T4, the evaporation contribution terms T5 and T6, and the dissipation rate term −D2) has been analysed in the context of RANS simulations. The models previously proposed in the context of turbulent gaseous stratified flames have been considered here to assess their suitability for turbulent spray flames. Based on a-priori DNS analysis, suitable model expressions have been identified for T1, T2, T31, T32, T33, [T4 − D2 + f(D)] and [T5 + T6], which have been shown to perform generally satisfactorily for all cases considered here.

“…In a numerical study of flame propagation in quiescent sprays, Neophytou and Mastorakos [ 5 ] showed that the effective equivalence ratio, as compared to the overall equivalence ratio, was an important parameter with respect to the burning velocity. Direct numerical simulations (DNS) showed that the flame propagation consisted of the successive ignition of flames engulfing individual droplets [ 6 ] and that premixed and non-premixed combustion modes co-exist in spray flames [ 7 – 9 ].…”

Section: Introductionmentioning

confidence: 99%

Modelling of Spray Flames with Doubly Conditional Moment Closure

Sitte

Mastorakos

2017

Simulations of a pilot-stabilised flame in a uniformly dispersed ethanol spray are performed using a Doubly Conditional Moment Closure (DCMC) model. The DCMC equation for spray combustion is derived, using the mixture fraction and the reaction progress variable as conditioning variables, including droplet evaporation and differential diffusion terms. A set of closure sub-models is suggested to allow for a first, preliminary application of the DCMC model to the test case presented here. In particular, the DCMC model is used to provide complete closure for the Favre-averaged spray terms in the mean and variance equations of the conditioning variables and the present test case is used to assess the importance of each term. Comparison with experimental data shows a promising overall agreement, whilst differences are related to modelling choices.