Numerical simulation of turbulent propane–air combustion with nonhomogeneous reactants

Haworth, Daniel C.; Blint, Richard J.; Cuenot, Bénédicte; Poinsot, Thiérry

doi:10.1016/s0010-2180(99)00148-0

Cited by 147 publications

(70 citation statements)

References 15 publications

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“…Additionally, Figures 8 and 9 indicate that increasing ϕ 0 for stratified cases increases the variability of burning irrespective of the nature of initial mixture distribution. The reduction in burning rate due to mixture stratification in globally stoichiometric mixtures is consistent with several previous analyses (Haworth et al, 2000;Jiménez et al, 2002;Malkeson and Chakraborty, 2010;Patel and Chakraborty, 2014;Renou et al, 2004;Samson, 2002;Zhou et al, 1998). The bimodal distribution cases show higher probability of finding 1:0 ϕ 1:10 than in the Gaussian distribution cases for l ϕ =l f > 2:1 (see Figure 5).…”

Section: Gaussian Distribution Case Gt4yd Bimodal Distribution Case Bsupporting

confidence: 91%

“…A number of previous analyses concentrated on flame propagation in stratified mixtures based on experimental (Anselmo-Filho et al, 2009;Balusamy et al, 2014;Grune et al, 2013;Kang and Kyritsis, 2005;Mulla and Chakravarthy, 2014;Renou et al, 2004;Samson, 2002;Sweeney et al, 2013;Zhou et al, 1998Zhou et al, , 2013 and direct numerical simulations (DNS) (Cruz et al, 2000;Haworth et al, 2000;Hélie and Trouvé, 1998;Jiménez et al, 2002;Malkeson and Chakraborty, 2010;Patel and Chakraborty, 2014;Pera et al, 2013;Swaminathan et al, 2007) data. These studies demonstrated that the flame propagation statistics are strongly affected by the local gradient of equivalence ratio.…”

Section: Introductionmentioning

confidence: 99%

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Effects of Mixture Distribution on Localized Forced Ignition of Stratified Mixtures: A Direct Numerical Simulation Study

Patel

Chakraborty

2016

Combustion Science and Technology

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The influences of initial mixture distribution on localized forced ignition of globally stoichiometric stratified mixtures have been analyzed using three-dimensional compressible direct numerical simulations. The globally stoichiometric mixtures (i.e., hϕi ¼ 1:0) for different root-meansquare (rms) values of equivalence ratio (i.e., ϕ 0 = 0.2, 0.4, and 0.6) and the Taylor micro-scale lϕ of equivalence ratio ϕ variation (i.e., lϕ=l f ¼ 2.1, 5.5, and 8.3 with l f being the Zel'dovich flame thickness of stoichiometric mixture) have been analyzed for different initial rms values of turbulent velocity u 0 . The equivalence ratio variation is initialized following both Gaussian and bi-modal distributions for a given set of values of ϕ 0 and lϕ=l f in order to analyze the effects of mixture distribution. The localized forced ignition is accounted for by considering a source term in the energy conservation equation that deposits energy for a stipulated time interval. It has been demonstrated that the initial equivalence ratio distribution has significant effects on the extent of burning of stratified mixtures following successful localized forced ignition. It has been found that an increase in u 0 =S b ϕ¼1 ð Þ (ϕ 0 ) has adverse effects on the burned gas mass, whereas the effects of lϕ=l f on the extent of burning are nonmonotonic and dependent on ϕ 0 for initial bi-modal mixture distribution. The initial Gaussian mixture distribution exhibits an increase in burned gas mass with decreasing lϕ=l f , but these cases are more prone to flame extinction for high values of u 0 than the corresponding bi-modal distribution cases. Detailed physical explanations have been provided for the observed mixture distribution, ϕ 0 , u 0 , and lϕ=l f dependences on the extent of burning following localized forced ignition of stratified mixtures. ARTICLE HISTORY

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Section: Gaussian Distribution Case Gt4yd Bimodal Distribution Case Bsupporting

confidence: 91%

Section: Introductionmentioning

confidence: 99%

Effects of Mixture Distribution on Localized Forced Ignition of Stratified Mixtures: A Direct Numerical Simulation Study

Patel

Chakraborty

2016

Combustion Science and Technology

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“…Consequently, a large proportion of numerical studies of hydrocarbon flames is confined either to simple and/or two-dimensional flows with full chemical kinetic schemes (see [12] and references therein) or to complex and/or three-dimensional flows with simple/reduced schemes (see [13] and references therein). However, it is worth noting that significant advances have been made in recent years towards simulating systems burning practically relevant fuels together with detailed and accurate models for both the chemical and transport phenomena [14][15][16]. Thanks to the rapid growth of computational capabilities, adequate numerical predictions of the turbulent burning velocity have been provided [17,18] up to laboratory scale configurations [19,20] using high fidelity DNS.…”

Section: Introductionmentioning

confidence: 99%

Impact of Turbulence Intensity and Equivalence Ratio on the Burning Rate of Premixed Methane–Air Flames

Fru¹,

Thévenin²,

Janiga³

2011

Energies

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Direct Numerical Simulations (DNS) have been conducted to study the response of initially laminar spherical premixed methane-air flame kernels to successively higher turbulence intensities at five different equivalence ratios. The numerical experiments include a 16-species/25-step skeletal mechanism for methane oxidation and a multicomponent molecular transport model. Highly turbulent conditions (with integral Reynolds numbers up to 4 513) have been accessed. The effect of turbulence on the physical properties of the flame, in particular its consumption speed S c , which is an interesting measure of the turbulent flame speed S T has been investigated. Local quenching events are increasingly observed for highly turbulent conditions, particularly for lean mixtures. The obtained results qualitatively confirm the expected trend regarding correlations between u ′ /S L and the consumption speed: S c first increases, roughly linearly, with u ′ /S L (low turbulence zone), then levels off (bending zone) before decreasing again (quenching limit) for too intense turbulence. For a fixed value of u ′ /S L , S c /S L varies with the mixture equivalence ratio, showing that additional parameters should probably enter phenomenological expressions relating these two quantities.

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“…Two-dimensional examples germane to this configuration include Baum et al [2] who studied turbulent flame interactions for detailed hydrogen chemistry and more recent studies by Chen and Im [3] and Im and Chen [4]. Haworth et al [5] examined the effect of inhomogeneous reactants for propane/air flames using detailed propane chemistry at conditions typical of an IC engine. Analogous studies in 3D have been performed by Rutland and Trouvé [6], Trouvé and Poinsot [7], Zhang and Rutland [8], and Chakraborty and Cant [9].…”

Section: Introductionmentioning

confidence: 99%

Numerical simulation of Lewis number effects on lean premixed turbulent flames

Bell

Cheng

Day

et al. 2007

Proceedings of the Combustion Institute

120

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A dominant factor in determining the burning rate of a premixed turbulent flame is the degree to which the flame front is wrinkled by turbulence. Higher turbulent intensities lead to greater wrinkling of the flame front and an increase in the turbulent burning rate. This picture of turbulent flame dynamics must be modified, however, to accommodate the affects of variations in the local propagation speed of the flame front. Classical flame analysis characterizes these local variations in propagation speed by the Markstein number which represents the response of the flame front to curvature and strain. In this paper, we consider lean premixed flames for three different fuels having widely varying fuel Lewis numbers corresponding to widely varying Markstein numbers. In particular, we present numerical simulations of premixed turbulent flames for lean hydrogen, propane and methane mixtures in two dimensions. Each simulation is performed at turbulence conditions similar to those found in laboratory-scale experiments and is performed using detailed chemical kinetics and transport properties. We discuss the effect of Lewis number on the overall flame morphology and explore the dependence of local flame propagation speed on flame curvature. We also explore the relationship between local flame speed and experimentally accessible variables such as OH concentration. Finally, we focus on the low Lewis number case, hydrogen, in which the flame front is broken indicating local extinction.

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Numerical simulation of turbulent propane–air combustion with nonhomogeneous reactants

Cited by 147 publications

References 15 publications

Effects of Mixture Distribution on Localized Forced Ignition of Stratified Mixtures: A Direct Numerical Simulation Study

Effects of Mixture Distribution on Localized Forced Ignition of Stratified Mixtures: A Direct Numerical Simulation Study

Impact of Turbulence Intensity and Equivalence Ratio on the Burning Rate of Premixed Methane–Air Flames

Numerical simulation of Lewis number effects on lean premixed turbulent flames

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