Turbulence, scalar transport, and reaction rates in flame-wall interaction

Al-Shaalan, Tareq M.; Rutland, Christopher J.

doi:10.1016/s0082-0784(98)80474-8

Cited by 80 publications

(75 citation statements)

References 19 publications

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“…In the last few decades, DNS has contributed significantly to the fundamental understanding of turbulent non-reacting and reacting flows, but relatively limited attention has been devoted to the analysis of FWI [2][3][4][5][6][7][8][9]. Poinsot et al [2] pioneered DNS based analysis of FWI by carrying out two-dimensional simple chemistry simulations of head-on quenching of premixed turbulent flames.…”

Section: Introductionmentioning

confidence: 99%

“…Alshalaan and Rutland [5,6] analysed oblique flame quenching by carrying out three-dimensional simple chemistry DNS for the interaction of a V-flame with an isothermal wall, and utilised the resulting data for the analysis of the wall heat flux statistics, and the near-wall behaviours of FSD, and turbulent scalar flux. All the aforementioned DNS analyses [2][3][4][5][6] indicated that the maximum wall heat flux in turbulent flows can assume values greater than the corresponding laminar value due to turbulent convection of flame elements towards the wall. Moreover, stream-wise vortices in a turbulent channel flow push the flame elements towards the wall leading to an increase in the wall heat flux magnitude, whereas convection away from the wall tends to reduce the wall heat flux magnitude [3,4].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Direct Numerical Simulation of Head-On Quenching of Statistically Planar Turbulent Premixed Methane-Air Flames Using a Detailed Chemical Mechanism

Lai

Klein

Chakraborty

2018

Flow Turbulence Combust

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A three-dimensional compressible Direct Numerical Simulation (DNS) analysis has been carried out for head-on quenching of a statistically planar stoichiometric methaneair flame by an isothermal inert wall. A multi-step chemical mechanism for methane-air combustion is used for the purpose of detailed chemistry DNS. For head-on quenching of stoichiometric methane-air flames, the mass fractions of major reactant species such as methane and oxygen tend to vanish at the wall during flame quenching. The absence of OH at the wall gives rise to accumulation of carbon monoxide during flame quenching because CO cannot be oxidised anymore. Furthermore, it has been found that low-temperature reactions give rise to accumulation of HO 2 and H 2 O 2 at the wall during flame quenching. Moreover, these low temperature reactions are responsible for non-zero heat release rate at the wall during flame-wall interaction. In order to perform an in-depth comparison between simple and detailed chemistry DNS results, a corresponding simulation has been carried out for the same turbulence parameters for a representative single-step Arrhenius type irreversible chemical mechanism. In the corresponding simple chemistry simulation, heat release rate vanishes once the flame reaches a threshold distance from the wall. The distributions of reaction progress variable c and non-dimensional temperature T are found to be identical to each other away from the wall for the simple chemistry simulation but this equality does not hold during head-on quenching. The inequality between c (defined based on CH 4 mass fraction) and T holds both away from and close to the wall for the detailed chemistry simulation but it becomes particularly prominent in the near-wall region. The temporal evolutions of wall heat flux and wall Peclet number (i.e. normalised wall-normal distance of T = 0.9 isosurface) for both simple and detailed chemistry laminar and turbulent cases have been found to be qualitatively similar. However, small differences have been observed in the numerical values of the maximum normalised wall heat flux magnitude ( max ) L and the minimum Peclet number (P e min ) L obtained from simple and detailed chemistry based laminar head-on quenching calculations. Detailed explanations have been provided for the observed differences in behaviours of ( max ) L and (P e min ) L . The usual Flame Surface Density (FSD) and scalar dissipation rate (SDR) based reaction rate closures do not adequately predict the mean reaction rate of reaction progress variable in the near-wall region for both simple and detailed chemistry simulations. It has been found that recently proposed FSD and SDR based reaction rate closures based on a-priori DNS analysis of simple chemistry data perform satisfactorily also for the detailed chemistry case both away from and close to the wall without any adjustment to the model parameters.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Direct Numerical Simulation of Head-On Quenching of Statistically Planar Turbulent Premixed Methane-Air Flames Using a Detailed Chemical Mechanism

Lai

Klein

Chakraborty

2018

Flow Turbulence Combust

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“…Smith and Gouldin, 1978;Veynante et al, 1994;Gouldin, 1996;Shepherd, 1996;Sattler et al, 2002) and numerical (e.g. Alshaalan and Rutland, 1998;Domingo et al, 2005;Bell et al, 2005) studies on this type of flame have been carried out previously. Recently, Dunstan et al (2011) reported 3D fully compressible DNS of premixed turbulent V-flames to evaluate the turbulent flame speed.…”

Section: V-flame Dns Datamentioning

confidence: 99%

On the Space-Time Correlation of Heat Release Rate in Turbulent Premixed Flames

Liu

2015

Combustion Science and Technology

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The spectral characteristics of combustion noise is dictated by the temporal correlation of the heat release rate fluctuation. This paper investigates the two-point space-time correlation of heat release rate fluctuations by analysing recent direct numerical simulation (DNS) data of turbulent premixed flames. The results show that this correlation decays rapidly in both space and time due to the abrupt fluctuation of the heat release rate. The two-point space-time correlation can be modelled by Gaussian-type functions including the streamwise direction with strong convection. A flat low-frequency dependence is observed for the spectrum of the correlation function, which will allow the modelling of the spectral peak and the low-frequency spectral slope of combustion noise when multiplying the term ω 2 (ω is the angular frequency). This exploratory work shows the potential of this correlation function for capturing the spectral shape of combustion noise.

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“…Swaminathan 30 et al [5,6] have attempted to analyse and model this two-point correlation 31 using DNS [16][17][18] and laser diagnostics [19] data of turbulent premixed 32 flames. They found that the two-point correlations of heat release rate, 33 Ω, and the rate of change of fluctuating heat release rate, Ω 1 , can be 34 well represented by Gaussian-type functions commonly used in classical 35 turbulence, and that the length scale of the correlation volume, v cor , is 36 0.5δ L . This model was then shown to give a good agreement with recent 37 experimental measurements [20] of the far-field overall sound pressure level The construction of Ω 1 requires the rate of change of fluctuating heat 40 release rate, which was calculated in Refs.…”

mentioning

confidence: 99%

“…where the original double integral is split into two single integrals work [29][30][31][32][33] and numerical simulations [34][35][36]. Recently, DNS for features of these V-flames will be discussed in more detail in Section 4.1.…”

mentioning

confidence: 99%