Available online at www.sciencedirect.com
Proceedings of the Combustion Institute 37 (2019) 5095–5103 www.elsevier.com/locate/proci
Head-on quenching of laminar premixed methane flames diluted with hot combustion products Bin Jiang∗, Robert L. Gordon, Mohsen Talei Department of Mechanical Engineering, The University of Melbourne, Parkville 3010, Australia Received 1 December 2017; accepted 30 July 2018 Available online 29 August 2018
Abstract Transient head-on quenching of laminar premixed methane flames diluted with hot combustion products is analyzed using full-chemistry 1D DNS. The impact of the dilution level, pressure and wall temperature on carbon monoxide (CO) emissions is investigated. Increasing dilution level and pressure reduce peak average near-wall CO concentrations, and reduce the near-wall CO reduction rate. However, the peak average nearwall CO and near-wall CO reduction rate increase with increasing wall temperature. Analysis of the species transport budget for CO near the wall before, during and after quenching indicates that there are conditions where diffusion is the dominant transport term. As a consequence, it may be possible to model the near-wall CO using only the integrated diffusion term within certain spatial regions. Dilution increases the size of these regions, whereas increasing pressure reduces this size. © 2018 The Combustion Institute. Published by Elsevier Inc. All rights reserved. Keywords: Flame–wall interaction; Head-on quenching; Direct numerical simulation; MILD and diluted flames; CO emissions
1. Introduction Environmental concerns and emissions regulation have motivated the development of novel combustion techniques for achieving ultra-low emissions. Combustion with dilution by hot combustion products is one such way to control emissions, and is often achieved by exhaust gas recirculation (EGR) or sequential combustion. These concepts have been investigated for gas turbine combustors, such as the inter-turbine burner (ITB) [1], the ∗
Corresponding author. E-mail address:
[email protected] (B. Jiang).
FLameless OXidation COMbustion (FLOXCOM) combustor [2], the LEan Azimuthal Flame (LEAF) combustor [3] and for the Colourless Distributed Combustion (CDC) burner [4]. High levels of dilution and preheat can change the combustion mode to one known as Moderate or Intense Low oxygen Dilution (MILD) combustion [5]. This mode has been shown to achieve ultra-low nitrogen oxides (NOx ) and carbon monoxide (CO), high thermal efficiency, fuel flexibility and low noise emission in the some of the above burners. The recent trend of using higher power densities for new industrial combustors has the potential to increase the impact of flame–wall interaction (FWI) on wall heat transfer and emissions characteristics [6]. Numerical and experimental studies
https://doi.org/10.1016/j.proci.2018.07.120 1540-7489 © 2018 The Combustion Institute. Published by Elsevier Inc. All rights reserved.
5096
B. Jiang et al. / Proceedings of the Combustion Institute 37 (2019) 5095–5103
have shown that a lowered reaction rate in the FWI zone can lead to incomplete combustion products to exist downstream of the flame [6]. FWI can also affect combustor durability, and hence understanding FWI is essential to minimise its impact on nextgeneration combustors. Head-on quenching (HOQ) and side-wall quenching (SWQ) are canonical configurations for investigating FWI. HOQ is well-suited to 1D numerical analysis of the transient combustion event. Key parameters are the quenching distance, the wall heat transfer, and the exhaust composition. There are few studies on preheated and diluted HOQ at constant volume. Yenerdag et al. [7] studied the 1D HOQ of methane/air diluted with hot combustion products. They reported that the EGR ratio can affect wall heat flux significantly. Quenching distance and thermal load are sensitive to the wall temperature. High pressure can decrease the quenching distance, while the FWI time remains constant. Pan et al. [8] reported a HOQ configuration with preheated H2 /air. They found that autoignition can occur at the foot of the preheated zone and upstream of the flame. These works did not study emissions behaviour. At elevated temperatures, wall surface chemistry can have an impact on FWI. While [9] notes that wall chemistry should be considered above 400 K, experiments conducted by Kim et al. [10] finding negligible wall-chemistry impact up to 623 K. Recent DNS FWI studies [11,12] have neglected surface chemistry at these temperatures. Few publications on FWI modelling can be found, especially for near-wall CO modelling. Westbrook et al. [13] studied the unburned hydrocarbon (UHC) emission and quenching behaviours on a 1D HOQ, and a correlation of quenching distance and pressure was fitted. Boust et al. [14] modelled the relation between the quenching distance and wall heat flux in a HOQ configuration. Suckart and Linse [15] developed a near-wall turbulent flame model based on the G-equation. However, these models do not include near-wall CO modelling. Ganter et al. [16] recently reported that for some premixed, atmospheric, undiluted flames the integral of the diffusion term can explain the observed near-wall CO for a SWQ configuration under some conditions. However, their integral analysis did not consider the effects of dilution, wall temperature or pressure. Further, combustion models for premixed flame propagation and autoignition have traditionally been developed for single combustion modes. At highly preheated conditions, premixed flame propagation and autoignition can coexist [17]. Detailed studies of flame behaviour and emissions near walls across combustion modes are required to aid the development of more generic modelling approaches. This paper focuses on numerical simulations of the nearwall CO in a diluted HOQ configuration. Analysis of the species transport budget for CO during
quenching is undertaken to determine what modelling simplifications may be possible to predict the emissions behaviour of this challenging regime. 2. Numerical method To study diluted FWI, a high-order direct numerical simulation code, NTMIX-CHEMKIN has been used [18]. It features an eighth-order finite difference scheme for spatial derivatives, in combination with a third-order Runge–Kutta time integrator. GRI 3.0 mechanism is used to describe CH4 /air combustion chemistry [19]. It consists of 53 species and 325 reactions. Soret (or thermal diffusion) and Dufour effects are accounted in the species and energy equations as per [9]. 2.1. Computational domain A 1D discretized domain is used. The domain outflow at one end uses a partially non-reflecting outflow imposed with the Navier–Stokes Characteristic Boundary Condition (NSCBC) method [20]. The flame generally propagates towards the other boundary, which is an inert isothermal wall. The wall is defined as x = 0, and is presented on the left-hand side in this work. The species boundary condition at the wall is set to satisfy a zero species flux for each species. The grid size is 4 μm in the whole domain to resolve the near-wall region and the flame region at 1 atm, and is 1 μm for cases at 15 atm pressure. Flame speed and peak CO concentrations of the present study and a Chemkin freely propagating model [21] were found to have less than a 5% difference for the premixed cases. 2.2. Domain initialization Dilution was achieved by mixing stoichiometric CH4 /air at 300 K and combustion products at equilibrium temperature. The degree of mixing is defined by the “dilution level”, ζ , which is the ratio of the mass flow rate of hot products to the total mass flow rate. The detailed dilution method can be found in [22]. The initial profile consists of three regions: a thermal boundary layer (TBL); the unburned premixed reactants; and a premixed flame: (1) The TBL is created with a non-reacting stagnation flow model with a 10 mm domain, and 10 m s−1 inlet velocity. In all cases, the flame is initialized sufficiently far from the wall that the TBL relaxes to a quasi-steady state prior to the FWI. (2) The flame profile is extracted from a Chemkin premixed flame model. For initialization of the cases at low dilution levels, a freely propagating flame is used. At high dilution levels, the freely propagating flame model does not converge, so the burner-stabilized premixed flame model is used. The flame profile is then superimposed in the
B. Jiang et al. / Proceedings of the Combustion Institute 37 (2019) 5095–5103
5097
Table 1 Initial conditions and properties of reactants at P = 1 atm. ζ
Tini (K)
XCH4
XO2
XH2O
XCO2
XCO
SL (cm s−1 )
τ AI (ms)
0 0.4 0.6
300 1132 1504
0.095 0.058 0.039
0.190 0.117 0.080
– 0.073 0.110
– 0.033 0.050
– 0.0034 0.0051
36.64 260.31 –
– 107.8 0.697
initial DNS domain. It is set sufficiently far from the wall such that the flame propagates at a constant speed for some time to achieve a quasi-steady state [13]. Numerical independence has been confirmed based on quenching distance and average near-wall CO. (3) Unburned premixed reactants are initialized between the TBL and the flame profile. Cases were simulated for ζ of 0, 0.4 and 0.6, wall temperatures Twall of 300 K and 600 K, and pressure, P, of 1 atm and 15 atm. The initial flame–wall distance (δ FW ) at ζ = 0 are 2 mm and 0.15 mm at 1 atm and 15 atm, 5 mm at ζ = 0.4 for 1 atm and 15 atm, and 15 mm at ζ = 0.6 for 1 atm and 15 atm. Initial velocity and mass flow rate are set to zero in the domain. Table 1 shows mixture initial temperature (Tini ), mole fractions of CH4 , O2 , H2 O, CO2 , CO, laminar flame speed (SL ), ignition delay (τ AI ). All combustion products and minor species are retained in the mixture, however neither concentrations of other species nor the thickness of the initial TBL are shown for brevity.
3. Results The results for temperature and CO concentration are presented on distance-time (x–t) contour plots (Figs. 1–3). CO concentration is normalized to a dry, 15% O2 basis. The figures are composites of the 1D domain plotted at each point in time, proceeding from bottom to top and with the wall at x = 0 mm. The quenching distance δ Q , and quenching time, tQ , are determined by the closest flame position to the wall. The flame position is defined at the maximum CH4 consumption rate. A vertical dashed line is overlaid at the quenching position (x = δ Q ). Various definitions of the flame position have been used in the literature, most of which give similar results for the premixed flame case (ζ = 0.0). The CH4 consumption rate is a consistent marker for the hot diluted cases. Other markers such as the peak heat release rate have been found to misreport the flame location for hot, diluted flames due to non-flame chemistry or radical recombination near the wall after quenching [23]. The quenching time is set as a reference between cases such that tQ = 0 s. From the temperature contours, the flame propagation and the reaction zone’s retreat after quenching can be observed. The gradient of the
isothermal contour at 1500 K represents the flame speed. The near-wall temperature gradient is proportional to the wall heat flux. The gradients of the CO x–t contours represent the rate of change of CO. 3.1. Effects of dilution level, ζ Figure 1 shows the x–t plots for changes in the dilution level at 1 atm and Twall = 300 K. The ζ = 0.0, 0.6 cases are presented as representatives for premixed combustion and MILD combustion, respectively. The quenching distance increases at higher dilution levels. The near-wall CO lasts longer at a higher ζ , although the peak near-wall CO is lower. Autoignition happens between the wall and the initial premixed flame at t = −1.1 ms, which is 0.7 ms after the start of the calculation and corresponds to the τ AI in Table 1. Due to the sudden expansion from the autoignion, the premixed flame is pushed away from the wall, which can be seen in the temperature contour plot, marked as “AI–PF interaction”. Around the quenching event (t = 0 or the vertical dashed line), the flame after autoignition at ζ = 0.6 propagates slower towards the wall, while the flame at ζ = 0 propagates faster towards the wall. This reduction in propagation speed appears to be due to the TBL at ζ = 0.6 cooling down the unburned gas. The near-wall temperature gradient is less steep for ζ = 0.6, which reduces heat transfer to the wall.
3.2. Effects of wall temperature The isothermal, inert wall was changed to 600 K to study the effect of wall temperature. Figure 2 shows that the quenching distance decreases for both cases with increasing wall temperature. Compared with the 300 K wall temperature case, the near-wall CO decreases faster at a higher wall temperature than the 300 K wall temperature case. The radical recombination CO + O + M = CO2 + M promotes this CO reduction [9]. Using the approach presented in Section 2.2 to generate the initial TBL, the ζ = 0.0 case now has a TBL (negative gradient) of 0.45 mm, and the initial TBL at ζ = 0.6 has decreased from 1.0 mm to 0.9 mm. The decrease of quenching distance and TBL increase the near-wall temperature gradient.
5098
B. Jiang et al. / Proceedings of the Combustion Institute 37 (2019) 5095–5103
Fig. 1. x–t plots of temperature (K) and CO concentration (ppmvd, 15% O2 ) for ζ = 0.0 (top) and 0.6 (middle, bottom). P = 1 atm, Twall = 300 K. The bottom row is zoomed into the closest 1 mm to wall for ζ = 0.6 case. The vertical dashed line indicates quenching distance, δ Q .
3.3. Effects of pressure The effect of pressure is investigated through comparing cases at 15 atm, 300 K wall temperature (Fig. 3). The ζ = 0.6 case displays an autoignition at 15 atm, but the small timescale of the event makes comparison with the ζ = 0 case challenging. ζ = 0.4 at 15 atm also displays autoignition, so is used to demonstrate the pressure effects. At a higher pressure, the quenching distance decreases, consistent with the literature [13]. The peak CO decreases, likely due to the inhibition of CO2 dissociation, expected due to the impact of pressure on the
kinetics. For the ζ = 0.4 case at a higher pressure, the decrease of initial TBL from 0.8 mm to 0.2 mm and quenching distance from 0.4 mm to 0.19 mm increase the near-wall temperature gradient.
4. Discussion At higher dilution levels, the peak near-wall CO is lower, and near-wall CO reduces more slowly. However, the near-wall CO reduction rate is higher at a higher wall temperature, while the near-wall CO reduction rate is lower at a higher pressure. The
B. Jiang et al. / Proceedings of the Combustion Institute 37 (2019) 5095–5103
5099
Fig. 2. x–t plots of temperature (K) and CO concentration (ppmvd, 15% O2 ) for ζ = 0.0 (top) and 0.6 (middle, bottom), P = 1 atm, Twall = 600 K. The bottom row is zoomed into the closest 1 mm to wall for ζ = 0.6 case. The vertical dashed line indicates quenching distance, δ Q .
near-wall CO behaviour is now further characterized to determine under what conditions the results can be modelled simply.
4.1. Average CO mass fraction The average CO mass fraction within the quenching distance was calculated from the beginning of the simulation for each case. The average CO, Y˜ co , is determined within one quenching
distance, and is defined as, Y˜ co =
∫ ρYco dx ∫ ρdx
(1)
Figure 4 plots Y˜ co from 2 ms prior to quenching to 2 ms after quenching for ζ = 0, 0.4 and 0.6 for different Twall and P. Figure 4(a) shows that at a higher dilution level, the average CO has a lower peak but lasts longer, indicated by the average CO at 2 ms. Comparison of Fig. 4(a) and (b) shows that the peak average CO increases at higher wall temperature. Comparison of Fig. 4(a)
5100
B. Jiang et al. / Proceedings of the Combustion Institute 37 (2019) 5095–5103
Fig. 3. x–t plots of temperature (K) and CO concentration (ppmvd, 15% O2 ) for ζ = 0.0 (top) and 0.4 (middle, bottom), P = 15 atm, Twall = 300 K. The bottom row is zoomed into the closest 1 mm to wall for ζ = 0.4 case. The vertical dashed line indicates quenching distance, δ Q .
Fig. 4. Average near-wall CO over time within the quenching distance. t = 0 is the quenching time.
B. Jiang et al. / Proceedings of the Combustion Institute 37 (2019) 5095–5103
5101
Fig. 5. Species transport budgets and CO mass fraction for ζ = 0.0 (top) and 0.6 (bottom) 0.5 ms before, during, and 0.5 ms after quenching. P = 1 atm, Twall = 300 K. The vertical black dashed line indicates quenching distance, δ Q .
and (c) shows that the CO peak decreases at a higher pressure. Analysis of the derivatives of the curves shows that the reduction rate of average CO is lower at higher pressure and higher at higher Twall (not shown here). These results are consistent with those presented in Figs. 1–3. 4.2. CO species transport budgets The species transport budget can be used to analyze the CO transport near the wall, which gives the contribution of each term to the CO concentration, e.g. [24]. The unsteady species transport equation is: ∂ρYk ∂ρuYk ∂ρVkYk =− − + MWk ω˙ k (2) ∂t ∂x ∂x The first term on the right-hand side (RHS) of Eq. (2) represents the mass convection (C). The second term represents the molecular diffusion (D), and the last is the reaction source term (R). Here, ρ is the mixture density, u is the axial velocity, Yk is the mass fraction of species k, MWk is the molecular weight of species k, ω˙ k is the net reaction rate of species k, and Vk is the diffusion velocity. 4.2.1. Dilution level effects on the CO species transport budget Figure 5 shows the species transport budget for CO at ζ = 0 and 0.6 at 300 K wall temperature and 1 atm for 0.5 ms before quenching, the moment of quenching, and 0.5 ms after quenching (t = −0.5, 0, 0.5 ms). The near-wall CO transport is mainly
dominated by diffusion and reaction, while the convection term is relatively small, especially at ζ = 0.6 case. The contribution of these species budget terms on CO is indicated by the sign of these terms in the corresponding region. For ζ = 0, the region with positive R is identified as the premixed flame reaction zone. Before quenching (t = −0.5 ms), R > 0 and D < 0 in the reaction zone, which indicates that CO generated in the flame is diffused out of the reaction zone. The effect is enhanced as the flame gets closer to the wall, and at the quenching time all the contributions increase the near-wall CO. After quenching (t = 0.5 ms), the diffusion and reaction terms decrease the near-wall CO, and diffusion again has the dominant role. For the ζ = 0.6 case, all three terms feature lower values compared to the ζ = 0 case, while the reaction and convection terms are almost zero near the wall. CO transport is then mainly driven by diffusion. At all these three times, the diffusion term always makes positive contributions to increase near-wall CO.
4.2.2. Effects of wall temperature and pressure on CO species transport budgets Increasing the wall temperature results in increased diffusion and reaction terms before and after quenching points. At the quenching point, the diffusion and reaction terms all tend to decrease the near-wall CO, which is opposite to the low wall temperature cases. Except for these differences, the
5102
B. Jiang et al. / Proceedings of the Combustion Institute 37 (2019) 5095–5103
results are similar to the low Twall cases, so these results have not been plotted for brevity. Increasing the pressure increases both the diffusion and reaction terms before and after quenching. A higher pressure increases the diffusion term, due to the decreased flame thickness, which increases the mass fraction gradient. The reaction term also increases at higher pressure, because of the increased reactant density. Like the ζ = 0.6, P = 1 atm case, at P = 15 atm, the nearwall diffusion term after quenching is still positive, so the near-wall CO increases after quenching, as shown in the average CO profile in Fig. 4. 4.3. Approximations for near-wall CO modelling Near-wall CO and flame quenching are challenging and costly to model explicitly. It has been indicated in a recent work [16] that for some premixed, atmospheric, undiluted flames the integral of the diffusion term can largely predict the observed near-wall CO for a SWQ configuration. A similar approach may be sufficient to predict near-wall CO within certain distances and times of quenching for the head-on quenching configuration, and the influence of dilution, pressure and wall temperature on this approach should be tested. As shown in Fig. 5, the reaction term decreases within the quenching distance δ Q , especially closer to the wall or during the reaction zone’s retreat after quenching. To evaluate the relative importance of the diffusion to the other two terms, the spatial mean of the absolute of the terms are calculated as, 1 |transport term|i n i=1 n
(3)
where n is the total number of grid points in a sample region; i denotes the ith grid point from the wall. The sample regions used in this analysis are 0.5δ Q , 0.75δ Q and 1δ Q . Figure 6 shows the average CO mass fraction from Eq. (1), and average CO calculated from the integral of D at ζ = 0.0 and 0.4. This is calculated as: δQ δQ Y˜ CO,D = Dd td x/ ρd x (4) 0
0
Y˜ CO,D enables the evaluation of to what extent YCO can be determined from the diffusion term alone. These are compared to profiles of the mean absolute diffusion, |D|mean , and the mean of the absolute convection and reaction terms, |C + R|mean . The modelled Y˜ CO,D for the ζ = 0 case is only qualitatively captured when the integral is started from t = −2 ms, whereas the modelled Y˜ CO,D for the ζ = 0.4 case matches Y˜ CO with less than 5% error. The ratio of peak |C + R|mean to |D|mean is tested to determine whether the relative contributions of the transport terms can provide an indicator for the
Fig. 6. Solid lines: mean absolute of D (thick red) and (C + R) (thin black) for CO (× 100). Dashed lines: average CO mass fraction from DNS data (thin black) and from the integral of the CO diffusion species transport term (thick red) for ζ = 0 (top) and ζ = 0.4 (bottom). P = 1 atm, Twall = 300 K. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)
Table 2 Ratio of peak |C + R|mean to |D|mean at different ζ , P (atm), Twall (K) within different distances from the wall. Sample region/
ζ /P/Twall
δQ
0.75 δ Q
0.5 δ Q
0/1/300 0.4/1/300 0.6/1/300 0/1/600 0.4/1/600 0.6/1/600 0/15/300 0.4/15/300 0.6/15/300
0.57 0.43 0.38 0.42 0.30 0.26 0.82 0.83 0.64
0.50 0.42 0.24 0.32 0.23 0.18 0.61 0.57 0.29
0.40 0.35 0.24 0.28 0.18 0.14 0.48 0.56 0.30
success of this approach. For ζ = 0 and 0.4 these ratios are 0.57 and 0.43, respectively. For Y˜ CO,D to effectively model near-wall Y˜ CO , the diffusion term must be dominant in a certain spatial region. The previous analysis suggests a value of 50% or less for the ratio of peak |C + R|mean to |D|mean could be an indicator of such conditions. Table 2 presents this ratio evaluated for all cases for 0.5δ Q , 0.75δ Q and 1δ Q . For cases where autoignition occurs, this ratio is only evaluated from after the autoignition event. Generally, the ratio decreases for narrower spatial regions. The diluted cases that are not autoigniting meet the 50% criterion over wider spatial regions than the undiluted cases. A higher pressure reduces the spatial regions where the ratio is less than 0.5.
B. Jiang et al. / Proceedings of the Combustion Institute 37 (2019) 5095–5103
It must be noted that these simulations are laminar, 1D flames. The purpose of this study is to begin the exploration of near-wall modelling simplifications through the identification of trends. It is acknowledged that multi-dimensional effects, turbulence and other quenching modes (e.g. SWQ) may have different properties. 5. Conclusion 1D DNS with detailed chemistry and transport properties was used to simulate a constant pressure, laminar head-on quenching configuration with CH4 /air mixture diluted with hot combustion products. The effects of dilution levels, wall temperature and pressure on near-wall CO and species transport budgets were studied. The results show that increasing dilution level and pressure can create an autoignition between the propagating flame and the wall. At higher dilution levels and for higher pressure, the peak average near-wall CO decreases, and the rate of near-wall CO reduction also decreases. However, increasing wall temperature increases the peak average near-wall CO and the near-wall CO reduction rate. The near-wall CO may be modelled using only the integrated diffusion term within certain spatial regions where the diffusion is dominant. Dilution increases the spatial region where diffusion is dominant for atmospheric conditions, whereas increasing pressure reduces this region. Acknowledgements Robert Gordon is supported by the Royal Academy of Engineering, through the Newton International Fellowship Alumni Programme. The authors acknowledge the generous support of the European Centre for Research and Advanced Training in Scientific Computation (CERFACS, http://www.cerfacs.fr), in providing the authors with the source code for NTMIX-CHEMKIN. The authors thank Benedicte Cuenot and Davy Brouzet for their help with NTMIX-CHEMKIN. The research was supported by computational resources on the Australian NCI Facility through the National Computational Merit Allocation Scheme and the Pawsey Supercomputing Centre. Bin Jiang
5103
acknowledges the financial support of the China Scholarship Council. References [1] A.A.V Perpignan, M.G. Talboom, Y. Levy, A.G. Rao, Energy Fuels 32 (1) (2017) 822–838. [2] Y. Levy, V. Sherbaum, P. Arfi, Appl. Therm. Eng. 24 (11–12) (2004) 1593–1605. [3] I. El Helou, J. Foale, A. Giusti, J.A.M. Sidey, and E. Mastorakos, Energy Proc., 120 (2017) 214–221. [4] A.E.E. Khalil, A.K. Gupta, Fuel 195 (2017) 113–122. [5] A Cavaliere, M. de Joannon, Prog. Energy Combust. Sci. 30 (4) (2004) 329–366. [6] A. Dreizler, B. Bohm, Proc. Combust. Inst. 35 (2015) 37–64. [7] B. Yenerdag, Y. Minamoto, K. Aoki, M. Shimura, Y. Nada, M. Tanahashi, Fuel 189 (2016) 8–14. [8] J. Pan, G. Shu, P. Zhao, H. Wei, Z. Chen, Combust. Flame 164 (2016) 319–328. [9] P. Popp, M. Baum, Combust. Flame 108 (3) (1997) 327–348. [10] K.T. Kim, D.H. Lee, S. Kwon, Combust. Flame 146 (1–2) (2006) 19–28. [11] A. Gruber, R. Sankaran, E.R. Hawkes, J.H. Chen, J. Fluid Mech. 658 (2010) 5–32. [12] R. Owston, V. Magi, J. Abraham, Combust. Flame 148 (3) (2007) 127–147. [13] C.K. Westbrook, A.A. Adamczyk, G.A. Lavoie, Combust. Flame 40 (1981) 81–99. [14] B. Boust, J. Sotton, S.A. Labuda, M. Bellenoue, Combust. Flame 149 (3) (2007) 286–294. [15] D. Suckart, D. Linse, Combust. Flame 190 (2018) 50–64. [16] S. Ganter, A. Heinrich, T. Meier, et al., Combust. Flame 186 (2017) 299–310. [17] O. Schulz, T. Jaravel, T.J. Poinsot, B. Cuenot, N. Noiray, Proc. Combust. Inst 36 (2) (2017) 1637–1644. [18] T.J. Poinsot, D.C. Haworth, G. Bruneaux, Combust. Flame 95 (1–2) (1993) 118–132. [19] G P. Smith, D M. Golden, M. Frenklach, et al. Nd GRI 3.0. http://wwwmeberkeleyedu/gri_mech/. [20] T.J. Poinsot, S.K. Lele, J. Comput. Phys. 101 (1992) 104–129. [21] CHEMKIN-PRO 15131. Reaction Design: San Diego, 2013. [22] J. Sidey, E. Mastorakos, R.L. Gordon, Combust. Sci. Technol. 186 (4–5) (2014) 453–465. [23] F. Dabireau, B. Cuenot, O. Vermorel, T. Poinsot, Combust. Flame 135 (2003) 123–133. [24] R.L. Gordon, A.R. Masri, S.B. Pope, G.M. Goldin, Combust. Flame 151 (3) (2007) 495–511.