2.1 Combustion DNS

For the combustion DNS, we consider the free propagation of a planar $\text{H}_{2}$/air premixed flame along the streamwise $x$-direction in statistically stationary HIT. This inflow–outflow DNS configuration of turbulent flames (e.g. Tanahashi et al. Reference Tanahashi, Fujimura and Miyauchi2000; Aspden, Day & Bell Reference Aspden, Day and Bell2011; Savard, Bobbitt & Blanquart Reference Savard, Bobbitt and Blanquart2015; Nivarti & Cant Reference Nivarti and Cant2017; Minamoto, Yenerdag & Tanahashi Reference Minamoto, Yenerdag and Tanahashi2018) is presented in figure 1. The computational domain is a cuboid with sides $L_{x}\times L_{y}\times L_{z}=6L\times L\times L$ and $L=2~\text{mm}$. It has inflow and outflow conditions at the left and right boundaries, respectively, and periodic boundary conditions in the lateral $y$- and $z$-directions. This domain is discretized on uniform grid points $N_{x}\times N_{y}\times N_{z}=6N\times N\times N$ with the mesh spacing $\unicode[STIX]{x0394}x$.

Figure 1.

A schematic diagram of DNS configurations of the premixed flame propagation (top) and the non-reacting HIT (bottom), with light blue isosurfaces of $|\unicode[STIX]{x1D74E}|=3\times 10^{5}~\text{s}^{-1}$, the red flame front (top) and the red global propagating surface (bottom). The non-reacting HIT is utilized for the inflow condition in combustion DNS and for the tracking of propagating surfaces.

The unburnt gas is a lean $\text{H}_{2}$/air mixture with the equivalence ratio $\unicode[STIX]{x1D719}=0.6$ at the temperature $T_{u}=300~\text{K}$ and atmospheric pressure. It is ignited by a planar laminar flame initially located in the middle of the computational domain. The one-dimensional steady laminar premixed flame is computed using the PREMIX code (Kee et al. Reference Kee, Grcar, Smooke and Miller1985) with the nine-species detailed kinetic mechanism and mixture-averaged transport properties. The laminar flame speed is $S_{L}=0.723~\text{m}~\text{s}^{-1}$, the flame thermal thickness $\unicode[STIX]{x1D6FF}_{L}\equiv (T_{b}-T_{u})/|\unicode[STIX]{x1D735}T|_{max}=0.361~\text{mm}$ and the flame time scale $\unicode[STIX]{x1D70F}_{f}\equiv \unicode[STIX]{x1D6FF}_{L}/S_{L}=0.499~\text{ms}$, where $T_{u}$ and $T_{b}$ are temperatures in the unburnt and burnt mixtures, respectively, and $|\unicode[STIX]{x1D735}T|_{max}$ denotes the maximum temperature gradient in the laminar premixed flame.

We carried out five DNS cases with varied turbulent intensity $u^{\prime }$ listed in table 1. For the inflow condition, we first performed a separate DNS of non-reacting, statistically stationary HIT. These HIT data are then imposed on the bulk inflow velocity $U_{in}(t)$ by using Taylor’s hypothesis. Thus the inflow condition is $\boldsymbol{u}_{in}(y,z,t)=U_{in}(t)+\boldsymbol{u}^{\prime }(y,z,t)$ with the fluctuating velocity $\boldsymbol{u}^{\prime }(y,z,t)$ on the $y$–$z$ plane moving through the HIT field at $U_{in}(t)$. A feedback control algorithm (Bell et al. Reference Bell, Day, Grcar and Lijewski2006) is applied to dynamically adjust $U_{in}(t)$ to stabilize the turbulent flame in the middle of the computational domain. The convective condition (Desjardins et al. Reference Desjardins, Blanquart, Balarac and Pitsch2008) is used for the velocity and scalars at the outflow boundary in the streamwise direction. A stable, linear velocity forcing (Carroll & Blanquart Reference Carroll and Blanquart2013; Savard et al. Reference Savard, Bobbitt and Blanquart2015) is adopted to maintain the turbulent intensity from $x=0.5L$ to $5L$ along the streamwise direction in combustion DNS and in the entire domain in non-reacting DNS.

The integral length scale $l_{t}$, the eddy turnover time $T_{e}$, the Kolmogorov time scale $\unicode[STIX]{x1D70F}_{\unicode[STIX]{x1D702}}$ and length scale $\unicode[STIX]{x1D702}$ and the turbulent Reynolds number $Re\equiv u^{\prime }l_{t}/\unicode[STIX]{x1D708}$ of the HIT are summarized in table 1. The Karlovitz number $Ka\equiv (u^{\prime }/S_{L})^{3/2}(\unicode[STIX]{x1D6FF}_{L}/l_{t})^{1/2}$ and the Damköhler number $Da\equiv (S_{L}/u^{\prime })(l_{t}/\unicode[STIX]{x1D6FF}_{L})$ are computed in the unburnt side. In terms of the regime diagram (Peters Reference Peters2000) in figure 2, case A is very close to the regime of wrinkled flamelets and laminar flames, cases B, C and D are in the thin reaction zone and case E is close to the broken reaction zone. We remark that the boundaries dividing different regimes in the Borghi diagram in figure 2 are solely based on phenomenological arguments and dimensional analysis. Thus the applicability of the diagram is still under debate for accurately characterizing flame structures (e.g. Aspden et al. Reference Aspden, Day and Bell2011; Tamadonfar & Gülder Reference Tamadonfar and Gülder2015; Aspden et al. Reference Aspden, Bell, Day and Egolfopoulos2017; Wabel et al. Reference Wabel, Skiba and Driscoll2017; Skiba et al. Reference Skiba, Wabel, Carter, Hammack, Temme and Driscoll2018), and the diagram is only presented for roughly comparing flow and flame parameters in different DNS series.

The numerical resolution in all the cases is ensured to resolve the smallest turbulent scales by the criterion $\unicode[STIX]{x1D702}/\unicode[STIX]{x0394}x>0.5$ (see Pope Reference Pope2000) and to resolve the flame length scales using a minimum of 24 grid points within $\unicode[STIX]{x1D6FF}_{L}$. In addition, our grid convergence study (see supplementary material available at https://doi.org/10.1017/jfm.2019.1081) further validates that the present combustion DNS is sufficiently well resolved by comparing $S_{T}$ and flame structures from simulations on the present grid and a coarser one.

Table 1.

Parameters for DNS cases.

Figure 2.

Parameters of three DNS series in the regime diagram of turbulent premixed combustion. Circles: the present DNS; squares: DNS of Nivarti & Cant (Reference Nivarti and Cant2017); diamonds: DNS (group T) of Lee & Huh (Reference Lee and Huh2010).

The low-Mach-number, variable-density formulation of conservation equations of mass, momentum, species and energy are solved on staggered grid points using the NGA code (Desjardins et al. Reference Desjardins, Blanquart, Balarac and Pitsch2008). A second-order centred, kinetic-energy conservative finite difference scheme is used to discretize the spatial derivatives in the momentum equations. A third-order bounded QUICK scheme (Herrmann, Blanquart & Raman Reference Herrmann, Blanquart and Raman2006) with low numerical dissipation and preserved physical bounds of scalars is adopted to treat convection terms in the scalar transport equations of species mass fractions and temperature, and this scheme has been used in a series of DNS of turbulent premixed flames (e.g. Savard et al. Reference Savard, Bobbitt and Blanquart2015; Bobbitt, Lapointe & Blanquart Reference Bobbitt, Lapointe and Blanquart2016). The temporal integration of the conservation equations is advanced by an iterative semi-implicit Crank–Nicolson scheme (Pierce Reference Pierce2001). The detailed nine-species $\text{H}_{2}$/air kinetic mechanism is employed with reaction rates, thermodynamic properties are evaluated by the CHEMKIN (Kee et al. Reference Kee, Rupley, Meeks and Miller1996) library. The constant Lewis numbers listed in table 2 are used in DNS and they are determined from the fit in terms of mixture-averaged transport properties for the laminar premixed flame. The time integration of chemical source terms is performed using the stiff DVODE solver (Brown, Byrne & Hindmarsh Reference Brown, Byrne and Hindmarsh1989). Each DNS case is first run for at least $10T_{e}$ to reach a statistically stationary state, and then statistical properties of interest are calculated over a period of $20T_{e}$.

Table 2.

Constant species Lewis numbers.

We define a reaction progress variable

(2.1)$$\begin{eqnarray}c\equiv \frac{Y_{f}-Y_{f,u}}{Y_{f,b}-Y_{f,u}}\end{eqnarray}$$

to characterize the progress of reaction and flame propagation, where $Y_{f}$ is the fuel mass fraction, $Y_{f,u}$ and $Y_{f,b}$ are the fuel mass fractions in unburnt and burnt mixtures, respectively. The isosurface of $c={\hat{c}}$ propagates at a displacement speed $S_{d}$. The instantaneous flame front is chosen such that ${\hat{c}}=0.8$ corresponds to the location of the maximum heat release rate in the unstrained laminar flame.

Figure 3 depicts contours of the normalized local FSD $\unicode[STIX]{x1D6F4}^{\prime }\unicode[STIX]{x1D6FF}_{L}$ on a slice near the flame front at $t=20T_{e}$ in combustion DNS cases B, C, D and E, with three isolines of $c=0.05,0.8$ and $0.95$ to characterize the turbulent flame brush. Here, the large local FSD generally characterizes the flame front, and the detailed definition of the FSD is explained in appendix A. The laminar flamelet structure is retained in most of the flame brush in case B, and the flamelet structure in the preheat zone is disturbed and progressively broadened in cases C and D. The topology of the reaction layer, as the isoline of $c=0.8$, still retains sheet-like parallel surfaces in both cases in the thin reaction zone. With increasing $Ka$, some portions of the flame front are broken down in case E.

Figure 3.

Normalized local FSD $\unicode[STIX]{x1D6F4}^{\prime }\unicode[STIX]{x1D6FF}_{L}$ on a slice of size $2L\times L$ centred at $x=3L$ and at $t=20T_{e}$ from four combustion DNS cases.

2.2 Tracking of propagating surface elements

As sketched in figure 1, the non-reacting HIT field used in the inflow condition of combustion DNS is also utilized in the tracking of propagating surface elements. For each DNS case listed in table 1, an ensemble of infinitesimal propagating surface elements are initially arranged on a planar surface in non-reacting HIT to model the propagation of a turbulent premixed flame.

Each propagating surface element carries the information of its Lagrangian location $\boldsymbol{X}(t)$, local coordinate system $\boldsymbol{e}_{i}(\boldsymbol{X}(t),t)$, curvature tensor $h_{\unicode[STIX]{x1D6FC}\unicode[STIX]{x1D6FD}}$ and nominal surface area $\unicode[STIX]{x1D6FF}A$ (Pope Reference Pope1988). The evolution equation of $\boldsymbol{X}(t)$ is

(2.2)$$\begin{eqnarray}\frac{\text{d}\boldsymbol{X}(t)}{\text{d}t}=\boldsymbol{u}(\boldsymbol{X}(t),t)+S_{d}(\boldsymbol{X}(t),t)\boldsymbol{n}(\boldsymbol{X}(t),t).\end{eqnarray}$$

Each surface element moves with the local fluid velocity $\boldsymbol{u}$ and the displacement velocity $S_{d}\boldsymbol{n}$, where $\boldsymbol{n}$ denotes the unit normal of the surface element, and the displacement speed $S_{d}$ can be simply modelled by a constant $S_{L}$ or a variable accounting for the effect of weak flame stretch.

As sketched in figure 4, a local Cartesian coordinate system $\boldsymbol{e}_{i}(\boldsymbol{X}(t),t)$, $i=1,2,3$ is attached to each surface element in order to compute $\boldsymbol{n}$ and other geometric properties of the surface elements. Its origin, denoted by ‘O’, is at the position $\boldsymbol{X}(t)$ of the surface element. The unit normal vector $\boldsymbol{e}_{3}$ is equivalent to $\boldsymbol{n}$ in (2.2), and two orthogonal unit vectors $\boldsymbol{e}_{1}$ and $\boldsymbol{e}_{2}$ span the tangent plane.

Figure 4.

Sketch of the temporal evolution of the propagating surface elements.

The governing equations for this coordinate system are

(2.3)$$\begin{eqnarray}\displaystyle \left.\begin{array}{@{}c@{}}\displaystyle \frac{\text{d}\boldsymbol{e}_{3}}{\text{d}t}=-\boldsymbol{e}_{\unicode[STIX]{x1D6FC}}u_{3,\unicode[STIX]{x1D6FC}},\\ \displaystyle \frac{\text{d}\boldsymbol{e}_{\unicode[STIX]{x1D6FC}}}{\text{d}t}=\frac{1}{2}\boldsymbol{e}_{\unicode[STIX]{x1D6FD}}(u_{\unicode[STIX]{x1D6FD},\unicode[STIX]{x1D6FC}}-u_{\unicode[STIX]{x1D6FC},\unicode[STIX]{x1D6FD}})+\boldsymbol{e}_{3}u_{3,\unicode[STIX]{x1D6FC}},\quad \unicode[STIX]{x1D6FC},\unicode[STIX]{x1D6FD}=1,2,\end{array}\right\} & & \displaystyle\end{eqnarray}$$

where ‘$,\unicode[STIX]{x1D6FC}$’ denotes the partial derivative in the direction of $\boldsymbol{e}_{\unicode[STIX]{x1D6FC}}$. The governing equation of the curvature tensor $h_{\unicode[STIX]{x1D6FC}\unicode[STIX]{x1D6FD}}$ is

(2.4)$$\begin{eqnarray}\frac{\text{d}h_{\unicode[STIX]{x1D6FC}\unicode[STIX]{x1D6FD}}}{\text{d}t}=s_{33}h_{\unicode[STIX]{x1D6FC}\unicode[STIX]{x1D6FD}}-(s_{\unicode[STIX]{x1D6FE}\unicode[STIX]{x1D6FD}}h_{\unicode[STIX]{x1D6FC}\unicode[STIX]{x1D6FE}}+s_{\unicode[STIX]{x1D6FE}\unicode[STIX]{x1D6FC}}h_{\unicode[STIX]{x1D6FD}\unicode[STIX]{x1D6FE}})+u_{3,\unicode[STIX]{x1D6FC}\unicode[STIX]{x1D6FD}}+S_{d}h_{\unicode[STIX]{x1D6FC}\unicode[STIX]{x1D6FE}}h_{\unicode[STIX]{x1D6FE}\unicode[STIX]{x1D6FD}},\end{eqnarray}$$

where the partial derivatives of $S_{d}$ are neglected (Zheng et al. Reference Zheng, You and Yang2017) and

(2.5)$$\begin{eqnarray}s_{ij}\equiv \frac{1}{2}\left(\frac{\unicode[STIX]{x2202}u_{i}}{\unicode[STIX]{x2202}x_{j}}+\frac{\unicode[STIX]{x2202}u_{j}}{\unicode[STIX]{x2202}x_{i}}\right),\quad i,j=1,2,3\end{eqnarray}$$

denotes the local rate-of-strain tensor. Principal curvatures $\unicode[STIX]{x1D705}_{i},\;i=1,2$ of a surface element are defined as $\unicode[STIX]{x1D705}_{i}=-k_{i}$ with $\unicode[STIX]{x1D705}_{1}>\unicode[STIX]{x1D705}_{2}$, where $k_{i},\;i=1,2$ are eigenvalues of $h_{\unicode[STIX]{x1D6FC}\unicode[STIX]{x1D6FD}}$. A surface element convex (or concave) to the propagating direction $\boldsymbol{n}$ has a positive (or negative) curvature.

At time $t$, $\unicode[STIX]{x1D6FF}A(t)$ denotes the nominal surface area, which can also be considered as the area ratio of infinitesimal surface elements. The governing equation of $\unicode[STIX]{x1D6FF}A(t)$ or the surface stretch rate $K$ of the propagating surface is

(2.6)$$\begin{eqnarray}K\equiv \frac{1}{\unicode[STIX]{x1D6FF}A(t)}\frac{\text{d}\unicode[STIX]{x1D6FF}A(t)}{\text{d}t}=K_{t}+2S_{d}\unicode[STIX]{x1D705},\end{eqnarray}$$

where the tangential strain rate $K_{t}\equiv u_{1,1}+u_{2,2}$ characterizes the stretching of the surface area due to the straining by the flow field, and $2S_{d}\unicode[STIX]{x1D705}$ with the mean curvature $\unicode[STIX]{x1D705}\equiv (\unicode[STIX]{x1D705}_{1}+\unicode[STIX]{x1D705}_{2})/2$ represents the factional rate of change of area due to propagation.

At the initial time, $N_{e}=256^{2}$ surface elements are uniformly arranged on an $x$–$y$ plane at $z=L/2$ to model a propagating planar flame in premixed combustion (see figures 1 and 4). Each surface element has $(\boldsymbol{e}_{1},\boldsymbol{e}_{2},\boldsymbol{e}_{3})=(0,0,1)$, $h_{\unicode[STIX]{x1D6FC}\unicode[STIX]{x1D6FD}}=0$ and $\unicode[STIX]{x1D6FF}A(0)=A_{0}/N_{e}$, where $A_{0}\equiv \sum _{N_{e}}\unicode[STIX]{x1D6FF}A(0)$ is the initial global surface area. A convergence test with increasing $N_{e}$ in figure 5 shows that the total surface area ratio, which is defined later in § 3.2, from $N_{e}=256^{2}$ surface elements is almost identical to that from $N_{e}=512^{2}$, so $N_{e}=256^{2}$ is used in the present study. Additionally, our grid convergence study (see supplementary material) validates that the present non-reacting DNS is sufficiently well resolved to calculate Lagrangian statistics of propagating surfaces.

Figure 5.

Convergence test of the number of propagating surface elements in non-reacting DNS case C.

The tracking of propagating surface elements begins when the non-reacting HIT has reached the statistically stationary state. A second-order, symmetry-preserved Runge–Kutta scheme (Zheng et al. Reference Zheng, You and Yang2017) is applied to advance (2.2), (2.3) and (2.6) explicitly and (2.4) implicitly. The time increment is sufficiently small to resolve the finest scales of the velocity field. The Fourier spectral method is used to evaluate the velocity derivatives involved in these equations. The interpolation is performed by a sixth-order Lagrangian interpolation scheme. In addition, the propagating surface elements can evolve into cusps after a finite time (Girimaji & Pope Reference Girimaji and Pope1992), and these cusps are removed in the tracking based on the positive definiteness of the curvature tensor. The detailed numerical implementation of the surface tracking and the criterion for detecting cusps are described in Zheng et al. (Reference Zheng, You and Yang2017), and numerical errors have been verified to be negligible. It is noted that the computational cost of the tracking of propagating surfaces in non-reacting DNS is very low, of $O(1)$ CPU hours on a single core. By contrast, the computational cost of each combustion DNS on a parallel machine is $O(10^{4})\sim O(10^{5})$ CPU hours.

The evolution of global propagating surfaces consisting of surface elements in stationary HIT is shown in figure 6 for cases B and D. From an initial plane, the propagating surface is gradually wrinkled and corrugated by turbulent straining motion to form the cellular geometry. Compared with the persistent stretch of a passive material surface with $S_{d}=0$, the evolution of a propagating surface with finite $S_{d}$ can generate cusps, and cusp locations are marked by red dots. Most of the cusps are generated around the crest of the surface with large negative curvatures. This ‘pocket structure’ is critical for predicting the flame stabilization and pollution formation in turbulent premixed combustion (Bell et al. Reference Bell, Day and Lijewski2013). At the same normalized time $t^{\ast }\equiv t/\unicode[STIX]{x1D70F}_{\unicode[STIX]{x1D702}}$, the surface is more wrinkled in case D with larger turbulence intensity than in case B.

Figure 6.

Temporal evolution of the global propagating surface in cases B and D at $t^{\ast }=1$, 2 and 3 (from top to bottom) in non-reacting HIT. The arrow denotes the propagation direction, and the red dots mark locations of cusp generation.

We remark that the ensemble of surface elements can only approximate the global propagating surface rather than exactly represent the real flame surface. The surface elements can be considered as sample points scattered on the global propagating surface. Moreover, the heat release in combustion can induce fluid thermal expansion and acceleration (Peters Reference Peters2000; Sabelnikov & Lipatnikov Reference Sabelnikov and Lipatnikov2017). The relevant density change and pressure effects can influence the turbulent flame morphology and dynamics, such as cusp formation and collision events (Fogla, Creta & Matalon Reference Fogla, Creta and Matalon2015), and they can be coupled with the Darrieus–Landau instability under weak turbulence (Creta & Matalon Reference Creta and Matalon2011; Troiani, Creta & Matalon Reference Troiani, Creta and Matalon2015). These variable-density effects are not considered in the present non-reacting HIT, and they can be incorporated via a modelled variable-density flow in future work.

3.1 Turbulent burning velocity

The turbulent burning velocity is defined using the global consumption speed of fuel

(3.1)$$\begin{eqnarray}S_{T}\equiv \frac{1}{\unicode[STIX]{x1D70C}_{u}Y_{f,u}L_{y}L_{z}}\int _{\unicode[STIX]{x1D6FA}}-\unicode[STIX]{x1D70C}\dot{\unicode[STIX]{x1D714}}_{f}(x,y,z,t)\,\text{d}\unicode[STIX]{x1D6FA},\end{eqnarray}$$

where $\unicode[STIX]{x1D70C}_{u}$ denotes the density of the unburnt mixture, $\dot{\unicode[STIX]{x1D714}}_{f}$ the net reaction rate of fuel and $\unicode[STIX]{x1D6FA}$ the entire computational domain. Although there is no consensus on the best definition of $S_{T}$ (Driscoll Reference Driscoll2008), i.e. $S_{T}$ can be defined by the local consumption speed or the local displacement speed, we use the global consumption speed (3.1) without the subjective selection of the isocontour threshold.

Damköhler (Reference Damköhler1940) conjectured that turbulence can enhance $S_{T}$ primarily through increasing the flame surface area under a low turbulence intensity, so the ratio of the flame surface area $A_{T}$ in turbulence and its projection in the propagating direction $A_{0}$ is generally equal to the ratio $S_{T}/S_{L}$. Thus the modelling of $A_{T}$ is essential to estimate $S_{T}$ under the assumption (see Driscoll Reference Driscoll2008)

(3.2)$$\begin{eqnarray}\frac{S_{T}}{S_{L}}=I_{0}\frac{A_{T}}{A_{0}}\approx \frac{A_{T}}{A_{0}},\end{eqnarray}$$

where the stretch factor $I_{0}$ depends on the effect of differential diffusion and is assumed to be unity from the present combustion DNS results (not shown). Some other DNS studies of turbulent premixed flames in HIT with moderate and high $u^{\prime }$ (see Bell, Day & Grcar Reference Bell, Day and Grcar2002; Hawkes & Chen Reference Hawkes and Chen2006; Nivarti & Cant Reference Nivarti and Cant2017; Wang, Magi & Abraham Reference Wang, Magi and Abraham2017) also observe that $S_{T}/S_{L}$ is proportional to $A_{T}/A_{0}$ with nearly unity $I_{0}$, which supports the validity of Damköhler’s hypothesis for the flame propagation in HIT. It is noted that, in some jet flames under very strong turbulence (e.g. Wabel et al. Reference Wabel, Skiba and Driscoll2017), Nivarti et al. (Reference Nivarti, Cant and Hochgreb2019) argued that small-scale turbulence can serve as an effective turbulent diffusivity to enhance $S_{T}$, and this additional factor should be incorporated into (3.2).

3.2 Area growth of propagating surfaces

We model the ratio $A_{T}/A_{0}$ of flame surface areas by the ratio of global propagating surface areas in the DNS of non-reacting HIT. In the evolution of a global propagating surface initially consisting of $N_{e}$ surface elements, only $N_{s}(t)$ surface elements survive. As sketched in figure 7, the other $N_{d}(t)$ surface elements disappear, because they evolve into cusps at a finite time and their surface areas shrink to zero (Girimaji & Pope Reference Girimaji and Pope1992). Since these cusps cannot exist owing to smoothing effects of diffusion and curvature in real flames, these extreme samples are removed in the tracking of propagating elements (see Zheng et al. Reference Zheng, You and Yang2017). This removal of the cusps can be viewed as a mechanism of area reduction, and other flame destruction mechanisms, such as mutual annihilation and quenching, are implicitly involved in further modelling.

Figure 7.

A schematic diagram of the evolution of propagating surface elements (thin blue lines) and a flame front (thick red lines).

The surviving ratio $R_{s}\equiv N_{s}(t)/N_{e}$ of surface elements is shown in figure 8. We observe that the cusp generation occurs around $t^{\ast }=2$ and the cusps are generated more quickly at smaller turbulence intensity. At smaller $u^{\prime }/S_{L}$, the propagation term in (2.4) can dominate (see Zheng et al. Reference Zheng, You and Yang2017), so a surface element with a large negative curvature can more easily develop a singularity in a finite time.

It is noted that all the subsequent quantities with the superscript ‘*’ denote the ones normalized by Kolmogorov length scale $\unicode[STIX]{x1D702}$, time scale $\unicode[STIX]{x1D70F}_{\unicode[STIX]{x1D702}}$ or velocity scale $u_{\unicode[STIX]{x1D702}}$. Zheng et al. (Reference Zheng, You and Yang2017) demonstrated that the profiles of ensemble-averaged $\unicode[STIX]{x1D705}_{1}^{\ast }$ and $\unicode[STIX]{x1D705}_{2}^{\ast }$ of propagating surfaces in terms of $S_{d}^{\ast }$ at the statistically stationary state are almost independent of $Re$.

Figure 8.

Surviving ratios of propagating surface elements in non-reacting DNS cases.

After removing the cusps, the total surface area of the global propagating surface consisting of $N_{s}\leqslant N_{e}$ surviving surface elements is approximated as

(3.3)$$\begin{eqnarray}A(t)\equiv \mathop{\sum }_{N_{s}(t)}\unicode[STIX]{x1D6FF}A(t).\end{eqnarray}$$

Summing up the local quantities of $N_{s}(t)$ surviving surface elements in (2.6) yields the evolution equation of $A(t)$ (Zheng et al. Reference Zheng, You and Yang2017)

(3.4)$$\begin{eqnarray}\frac{\text{d}}{\text{d}t}\ln A(t)=\langle K_{t}(t)\rangle _{A}+2\langle S_{d}(t)\unicode[STIX]{x1D705}(t)\rangle _{A},\end{eqnarray}$$

where

(3.5)$$\begin{eqnarray}\langle f(t)\rangle _{A}\equiv \frac{\mathop{\sum }_{N_{s}(t)}f(t)\unicode[STIX]{x1D6FF}A(t)}{A(t)}\end{eqnarray}$$

denotes the area-weighted average of a quantity $f(t)$.

Integrating the normalized (3.4) from the initial tracking time $t^{\ast }=0$ to a given time $t^{\ast }$ yields the surface area of the global propagating surface

(3.6)$$\begin{eqnarray}\frac{A(t^{\ast })}{A_{0}}=\exp \left(\int _{0}^{t^{\ast }}\langle K_{t}^{\ast }(s)\rangle _{A}\,\text{d}s\right)\exp \left(2\int _{0}^{t^{\ast }}\langle S_{d}^{\ast }(s)\unicode[STIX]{x1D705}^{\ast }(s)\rangle _{A}\,\text{d}s\right).\end{eqnarray}$$

This implies that the growth of $A(t)$ of the propagating surfaces is due to the Lagrangian history of statistically positive tangential strain-rate and propagation-curvature terms in the wrinkling process of propagating surfaces in turbulence (Zheng et al. Reference Zheng, You and Yang2017). Subsequently, $S_{d}$ is assumed to be a constant laminar burning velocity $S_{L}$ as

(3.7)$$\begin{eqnarray}\frac{A(t^{\ast })}{A_{0}}=\exp \left(\int _{0}^{t^{\ast }}\langle K_{t}^{\ast }(s)\rangle _{A}+2S_{L}^{\ast }\langle \unicode[STIX]{x1D705}^{\ast }(s)\rangle _{A}\,\text{d}s\right).\end{eqnarray}$$

This assumption is justified and the effect of flame stretch on $S_{d}$ is discussed in appendix B.

Figure 9.

Surface area ratios of propagating surfaces in terms of (a) the physical time and (b) normalized time in non-reacting HIT.

As implied in (3.7), $A(t)/A_{0}$ grows with $t$ in figure 9(a), and its growth rate increases with $Re$ for the same $S_{L}$, because $K_{t}$ scales as $K_{t}\sim 1/\unicode[STIX]{x1D70F}_{\unicode[STIX]{x1D702}}\sim Re^{1/2}$. This result is consistent with the observation that $A_{T}$ of flames increases with $Re$ in the argument of FSD modelling in appendix A. On the other hand, if $t$ is normalized by corresponding $\unicode[STIX]{x1D70F}_{\unicode[STIX]{x1D702}}$ in each case, the profiles of $A(t^{\ast })/A_{0}$ for different $Re$ collapse in figure 9(b). Similarly, the surviving ratio for the same $S_{L}^{\ast }$ is almost independent of $Re$ (Zheng et al. Reference Zheng, You and Yang2017). These indicate that Kolmogorov scales are more appropriate than integral scales for the normalization in scale analyses, and further modelling based on the universal properties of $A(t^{\ast })$ naturally involves the effect of $Re$ on $S_{T}$ in terms of integral quantities.

Figure 10.

Growth rates of the surface area of propagating surfaces in non-reacting HIT.

The estimation of $A(t)/A_{0}$ of propagating surfaces is similar to that for material surfaces in non-reacting HIT. Batchelor (Reference Batchelor1952) proposed that $A(t)/A_{0}$ of material surfaces grows exponentially owing to the persistent stretching of turbulent motion, which was validated by DNS (e.g. Girimaji & Pope Reference Girimaji and Pope1990; Goto & Kida Reference Goto and Kida2007; Yang et al. Reference Yang, Pullin and Bermejo-Moreno2010). Considering the self-similar area growth of propagating surfaces at different $Re$, we re-express (3.7) in the form of

(3.8)$$\begin{eqnarray}\frac{A(t^{\ast })}{A_{0}}=\exp (\unicode[STIX]{x1D709}_{A}t^{\ast }),\end{eqnarray}$$

where $\unicode[STIX]{x1D709}_{A}(t^{\ast })\equiv \log (A(t^{\ast })/A_{0})/t^{\ast }$ is the area growth rate. A similar exponential growth of the flame surface was assumed by Kerstein (Reference Kerstein1988) and Yakhot (Reference Yakhot1988).

In figure 10, the area growth rates also nearly collapse, consistent with the observation in figure 9(b). For material surfaces in HIT, $\unicode[STIX]{x1D709}_{A}$ approaches a statistically stationary state as $\unicode[STIX]{x1D709}_{A}=0.33\pm 0.04$ after a rapid, monotonic growth in $2\sim 3\unicode[STIX]{x1D70F}_{\unicode[STIX]{x1D702}}$ (see Yang et al. Reference Yang, Pullin and Bermejo-Moreno2010). For propagating surfaces, by contrast, $\unicode[STIX]{x1D709}_{A}$ does not reach the statistically stationary state, so an additional approximation is introduced to model

(3.9)$$\begin{eqnarray}\unicode[STIX]{x1D709}_{A}(t^{\ast })=\unicode[STIX]{x1D709}\end{eqnarray}$$

by a constant $\unicode[STIX]{x1D709}$, which is addressed in § 3.5 in detail.

3.3 Introduction of the truncation time

A global propagating surface in turbulence should have $A(t)\rightarrow \infty$ as $t\rightarrow \infty$ in (3.8) owing to the persistent stretching and the lack of surface shortening mechanisms. On the other hand, the shortening mechanism in real turbulent flames may occur when adjacent flamelets consume the intervening reactant, thereby annihilating both surface elements. Thus the flame area $A_{T}$ should be finite, which can be considered as a stationary random variable with competing flame stretching and shortening mechanisms (Marble & Broadwell Reference Marble and Broadwell1977).

To resolve this contradiction, we postulate that the surface area of turbulent flames can be estimated by

(3.10)$$\begin{eqnarray}A_{T}=A(T_{s}^{\ast })\end{eqnarray}$$

at a truncation time $T_{s}^{\ast }$ when the statistical geometry of the propagating surfaces just reaches a statistically stationary state (Zheng et al. Reference Zheng, You and Yang2017). As sketched in figure 7, this state resembles the statistical equilibrium state in combustion between the flame area growth due to turbulent straining and the area consumption due to flame self-propagation. After this state, the nominal area of independent propagating surfaces with infinitesimal thickness can still grow (see figure 9), but the area of real flames statistically converges to a finite value. In § 3.6, we will demonstrate that the ansatz of (3.10), together with modelled $T_{s}^{\ast }$, serves as the basic analytical structure leading to a physically reasonable functional form of $S_{T}$ with finite $A_{T}$, so the flame shortening mechanisms can be implicitly incorporated into the truncation time. Applying (3.8) and (3.9) to (3.10), we have the model of $A_{T}$ in terms of $T_{s}^{\ast }$ as

(3.11)$$\begin{eqnarray}\frac{A_{T}}{A_{0}}=\exp \left(\unicode[STIX]{x1D709}T_{s}^{\ast }\right).\end{eqnarray}$$

Before modelling $T_{s}^{\ast }$, we first use the characteristic curvature

(3.12)$$\begin{eqnarray}C^{\ast }\equiv \sqrt{{\unicode[STIX]{x1D705}_{1}^{\ast }}^{2}+{\unicode[STIX]{x1D705}_{2}^{\ast }}^{2}}\end{eqnarray}$$

to characterize the statistical stationary state of propagating surfaces. We find that the temporal evolution of the ensemble-averaged $C^{\ast }$ is statistically more robust than those of $K_{t}^{\ast }$ and $\unicode[STIX]{x1D705}^{\ast }$ in (3.6). The latter two are found to be very sensitive to specific realizations in DNS.

The DNS of propagating surfaces demonstrates that $\langle C^{\ast }\rangle$ can reach a statistically stationary state after a short time in figure 11(a), where $\langle \cdot \rangle$ denotes the ensemble average over all the surviving surface elements, and this result is supported by the theoretical analysis in appendix C. The temporal growth rate $\text{d}\langle C^{\ast }\rangle /\text{d}t^{\ast }$ of $\langle C^{\ast }\rangle$ is also computed and shown in figure 11(b). After a rapid growth at very small times, the growth rate decays and finally approaches a statistical stationary state. We observe that the growth rates almost collapse in cases C, D and E at moderate $Re$, which implies that the time $T_{s}^{\ast }$ to reach the statistically stationary state of $\langle C^{\ast }\rangle$ approaches a finite value as $u^{\prime }/S_{L}\rightarrow \infty$. Furthermore, the temporal evolution of probability density functions (PDFs) of $C^{\ast }$ in figure 12 indicates that the PDFs at different times almost collapse after reaching the statistically stationary state around $t^{\ast }>4$.

Figure 11.

The temporal evolution of (a) the ensemble-averaged characteristic curvature and (b) its temporal growth rate of propagating surface elements in non-reacting HIT.

Figure 12.

The temporal evolution of PDFs of the normalized characteristic curvature of propagating surfaces in non-reacting DNS: (a) case B and (b) case D.

We denote the truncation time

(3.13)$$\begin{eqnarray}T_{\infty }^{\ast }=\lim _{u^{\prime }/S_{L}\rightarrow \infty }T_{s}^{\ast }\end{eqnarray}$$

for $u^{\prime }/S_{L}\rightarrow \infty$ or material surfaces, which is useful in the modelling of $T_{s}^{\ast }$ in § 3.4. We approximate

(3.14)$$\begin{eqnarray}T_{\infty }^{\ast }=\underset{t^{\ast }}{\arg \min }\left\{\left|\frac{\text{d}\langle C^{\ast }\rangle (t^{\ast })}{\text{d}t^{\ast }}\right|<\unicode[STIX]{x1D700}_{T}\right\},\end{eqnarray}$$

by $T_{s}^{\ast }$ from the DNS of propagating surfaces in case E with large $u^{\prime }/S_{L}$, where $\unicode[STIX]{x1D700}_{T}=0.1\,\%$ is a small threshold. We determine $T_{\infty }^{\ast }=5.5$ using (3.14) and it appears to be a universal constant, because the normalized time $t^{\ast }$ when $\langle C^{\ast }\rangle$ of the material surfaces reaches the stationary state (Girimaji & Pope Reference Girimaji and Pope1990; Girimaji Reference Girimaji1991) can be almost independent of large $Re$ owing to the self-similar statistical geometry.

3.4 Modelling of the truncation time

The determination of the truncation time scale $T_{s}^{\ast }$ in (3.11) is crucial for the modelling of $A_{T}/A_{0}$ using Lagrangian statistics of propagating surfaces, which is similar to the critical role of characteristic time scales in statistical turbulence models (see He, Jin & Yang Reference He, Jin and Yang2017). Based on discussions in § 3.3, $T_{s}^{\ast }$ is determined when averaged geometric quantities of propagating surfaces reach the statistically stationary state. This state is an analogy to the statistically stationary $A_{T}/A_{0}$ of turbulent premixed flames in combustion DNS.

We observe that $T_{s}^{\ast }$ varies with $u^{\prime }/S_{L}$ from the temporal evolution of $\langle C^{\ast }\rangle$ in figure 11, so we assume

(3.15)$$\begin{eqnarray}T_{s}^{\ast }=F\left(\frac{1}{S_{L}^{\ast }}\right)=F\left(Re^{-1/4}\frac{u^{\prime }}{S_{L}}\right).\end{eqnarray}$$

Next, it is essential to determine the form of function $F$. Inspired by the modelling approach for the width of a thermal wake in turbulent dispersion (Taylor Reference Taylor1921) and the pressure–rate-of-strain tensor in Reynolds stress models (Launder, Reece & Rodi Reference Launder, Reece and Rodi1975; Pope Reference Pope2000), we first determine $F$ at some limiting values of $u^{\prime }/S_{L}$ at finite $Re$.

As $u^{\prime }/S_{L}\rightarrow \infty$, propagating surfaces can be considered as material surfaces. According to the discussion in § 3.3, there exists a universal truncation time $T_{\infty }^{\ast }$ (3.13) when $\langle C^{\ast }\rangle$ reaches the statistically stationary state. If $F$ is a smooth function, (3.13) implies that

(3.16)$$\begin{eqnarray}\lim _{u^{\prime }/S_{L}\rightarrow \infty }\frac{\text{d}T_{s}^{\ast }}{\text{d}(1/S_{L}^{\ast })}=0.\end{eqnarray}$$

As $u^{\prime }/S_{L}\rightarrow 0$, we consider a laminar premixed flame with $u^{\prime }=0$ and finite $S_{L}$. Since the initial planar propagating surface cannot deform, the truncation time is

(3.17)$$\begin{eqnarray}\lim _{u^{\prime }/S_{L}\rightarrow 0}T_{s}^{\ast }=0.\end{eqnarray}$$

In weak turbulence with very small $u^{\prime }/S_{L}$, the dependence of $S_{T}$ on $u^{\prime }$ can be described by a general power law (e.g. Peters Reference Peters1999; Creta & Matalon Reference Creta and Matalon2011; Lipatnikov Reference Lipatnikov2012)

(3.18)$$\begin{eqnarray}\frac{S_{T}}{S_{L}}=1+{\mathcal{C}}\left(\frac{u^{\prime }}{S_{L}}\right)^{\unicode[STIX]{x1D701}},\end{eqnarray}$$

where ${\mathcal{C}}$ is independent of $u^{\prime }$ but may depend on the unburnt mixture composition (Lipatnikov & Chomiak Reference Lipatnikov and Chomiak2002), and $\unicode[STIX]{x1D701}$ is an empirical constant.

The first-order Taylor expansion of the modelled area ratio (3.11) with (3.2) for very small $T_{s}^{\ast }$ and $u^{\prime }/S_{L}$ is

(3.19)$$\begin{eqnarray}\frac{S_{T}}{S_{L}}=1+\unicode[STIX]{x1D709}T_{s}^{\ast }.\end{eqnarray}$$

This should be consistent with (3.18) at a laminar state with $Re=1$, so we have

(3.20)$$\begin{eqnarray}\lim _{u^{\prime }/S_{L}\rightarrow 0}\frac{\text{d}^{n}T_{s}^{\ast }}{\text{d}(1/S_{L}^{\ast })^{n}}=\frac{{\mathcal{C}}}{\unicode[STIX]{x1D709}}\mathop{\prod }_{m=0}^{n-1}(\unicode[STIX]{x1D701}-m)\left(\frac{u^{\prime }}{S_{L}}\right)^{\unicode[STIX]{x1D701}-n}\end{eqnarray}$$

with an integer $1\leqslant n\leqslant \unicode[STIX]{x1D701}$. Here, we specify $\unicode[STIX]{x1D701}=1$ as the simplest linear model

(3.21)$$\begin{eqnarray}S_{T}=S_{L}+{\mathcal{C}}u^{\prime }\end{eqnarray}$$

in weak turbulence, which is generally applicable to various fuels. Then (3.20) is simplified as

(3.22)$$\begin{eqnarray}\lim _{u^{\prime }/S_{L}\rightarrow 0}\frac{\text{d}T_{s}^{\ast }}{\text{d}(1/S_{L}^{\ast })}=\frac{{\mathcal{C}}}{\unicode[STIX]{x1D709}}.\end{eqnarray}$$

In order to determine ${\mathcal{C}}$, we only need a very few sample data points

(3.23)$$\begin{eqnarray}G=\{(x_{i},y_{i})=(u^{\prime }/S_{L},S_{T}/S_{L})\mid i\in \{0,1,\ldots ,N_{G}\}\}\end{eqnarray}$$

from existing DNS or experimental measurement of propagating flames in weak turbulence with $u^{\prime }/S_{L}<\unicode[STIX]{x1D716}_{C}$, where the small threshold value is set to $\unicode[STIX]{x1D716}_{C}=2$ and the data point of $(x_{0},y_{0})=(0,1)$ at laminar conditions is specified. Then, a least-squared fit is utilized to estimate ${\mathcal{C}}$ from $G$ as

(3.24)$$\begin{eqnarray}{\mathcal{C}}=\frac{\unicode[STIX]{x1D6F4}x_{i}y_{i}-\unicode[STIX]{x1D6F4}x_{i}\unicode[STIX]{x1D6F4}y_{i}/N_{G}}{\unicode[STIX]{x1D6F4}x_{i}^{2}-(\unicode[STIX]{x1D6F4}x_{i})^{2}/N_{G}}.\end{eqnarray}$$

This simple linear fit appears to be more robust than the high-order fit with $\unicode[STIX]{x1D701}>1$ in (3.18) from very sparse sample data points with finite uncertainties.

Considering the function $F$ at all the limiting values above (also sketched in figure 13), we propose a model for the truncation time as

(3.25)$$\begin{eqnarray}T_{s}^{\ast }=T_{\infty }^{\ast }\left[1-\exp \left(-\frac{{\mathcal{C}}}{\unicode[STIX]{x1D709}T_{\infty }^{\ast }S_{L}^{\ast }}\right)\right],\end{eqnarray}$$

which satisfies (3.13), (3.16), (3.17) and (3.22), and is a monotonically increasing function in terms of $1/S_{L}^{\ast }$. It is noted that substituting the first-order Taylor expansion of (3.25) in terms of very small $1/S_{L}^{\ast }$ into (3.19) with $Re=1$ recovers the linear model (3.21).

Figure 13.

A schematic diagram for the functional form of $F$ for $T_{s}^{\ast }$. Circles: values of $F$ at limiting conditions (3.13) and (3.17); dashed lines: slopes of $F$ at asymptotic conditions (3.16) and (3.22).

3.5 Modelling of the area growth rate

In the modelling of $A_{T}/A_{0}$ in (3.11), the constant $\unicode[STIX]{x1D709}$ needs to be determined by a function of given turbulence or flame parameters. Although $\unicode[STIX]{x1D709}_{A}$ grows with time in figure 10, we approximate $\unicode[STIX]{x1D709}_{A}$ as a constant effective growth rate

(3.26)$$\begin{eqnarray}\unicode[STIX]{x1D709}=\unicode[STIX]{x1D709}_{A}(t^{\ast }=T_{\infty }^{\ast })\end{eqnarray}$$

at the universal truncation time $T_{\infty }^{\ast }$.

Since the growth of $A(t^{\ast })/A_{0}$ is independent of $Re$, as demonstrated in figure 9(b), $\unicode[STIX]{x1D709}$ at large $Re$ should be the same for a given mixture composition. For example, we estimate $\unicode[STIX]{x1D709}=0.35$ by (3.26) from case E of the DNS of propagating surfaces. In figure 9(b), the comparison of $A(t^{\ast })/A_{0}$ from DNS and the model (3.8) with $\unicode[STIX]{x1D709}=0.35$ indicates that (3.8) with (3.26) can provide a good approximation for the growth of $A(t^{\ast })/A_{0}$.

Furthermore, $\unicode[STIX]{x1D709}$ may vary with $S_{L}^{\ast }$ for the same $Re$, so it is necessary to model this possible dependence of $\unicode[STIX]{x1D709}$ on different mixture compositions or fuels. By comparing (3.11) and (3.6), we obtain

(3.27)$$\begin{eqnarray}\unicode[STIX]{x1D709}T_{s}^{\ast }=\int _{0}^{T_{s}^{\ast }}\langle K_{t}^{\ast }\rangle _{A}+2S_{L}^{\ast }\langle \unicode[STIX]{x1D705}^{\ast }\rangle _{A}\,\text{d}s.\end{eqnarray}$$

Applying the mean value theorem for integrals to (3.27) yields

(3.28)$$\begin{eqnarray}\unicode[STIX]{x1D709}={\textstyle \frac{1}{2}}\langle K_{t}^{\ast }(t^{\prime })\rangle _{A}+S_{L}^{\ast }\langle \unicode[STIX]{x1D705}^{\ast }(t^{\prime })\rangle _{A},\quad t^{\prime }\in (0,T_{s}^{\ast }),\end{eqnarray}$$

which indicates an explicit dependence of $\unicode[STIX]{x1D709}$ on the laminar flame speed.

Considering the independence of $\unicode[STIX]{x1D709}$ for large $Re$, we use DNS case E of propagating surfaces with varying $S_{L}$ to fit (3.28). We find that $\unicode[STIX]{x1D709}=0.33\pm 0.02$ has a weak dependence on $S_{L}$ for a range of moderate $S_{L}$ in figure 14, where the selection of $S_{L}=0\sim 0.8~\text{m}~\text{s}^{-1}$ covers all the $S_{L}$ in the combustion DNS series discussed in § 4.1. Since the dependence appears to be linear, we propose an empirical model

(3.29)$$\begin{eqnarray}\unicode[STIX]{x1D709}={\mathcal{A}}+{\mathcal{B}}S_{L0}.\end{eqnarray}$$

Here, model coefficients ${\mathcal{A}}=0.317$ and ${\mathcal{B}}=0.033$ are determined by the least-squared fit, and they represent the tangential strain-rate and propagation-curvature effects in (3.28), respectively; $S_{L0}=S_{L}/S_{L,ref}$ is a dimensionless laminar flame speed and is normalized by a reference value $S_{L,ref}=1~\text{m}~\text{s}^{-1}$.

Figure 14.

Modelled area growth rates of propagating surfaces with $S_{L}=0\sim 0.8~\text{m}~\text{s}^{-1}$ in non-reacting HIT. Circles: results obtained by (3.26) from the tracking of propagating surfaces in case E; solid line: the linear fit (3.29) with ${\mathcal{A}}=0.317$ and ${\mathcal{B}}=0.033$.

We remark that the model (3.29) can be valid for various fuels with moderate $S_{L}$, but it may break down for very large $S_{L}$. In principle, $\unicode[STIX]{x1D709}$ of initial planar propagating surfaces is vanishing as $S_{L}/u^{\prime }\rightarrow \infty$, so we speculate that $\unicode[STIX]{x1D709}$ may decrease at very large $S_{L}$.

3.6 Predictive model of the turbulent burning velocity

Substituting models (3.25) for $T_{s}^{\ast }$ and (3.29) for $\unicode[STIX]{x1D709}$ into (3.11) and using (3.2), we obtain

(3.30)$$\begin{eqnarray}\frac{S_{T}}{S_{L}}=\exp \left\{T_{\infty }^{\ast }\left({\mathcal{A}}+{\mathcal{B}}S_{L0}\right)\left[1-\exp \left(-\frac{{\mathcal{C}}Re^{-1/4}}{\left({\mathcal{A}}+{\mathcal{B}}S_{L0}\right)T_{\infty }^{\ast }}\frac{u^{\prime }}{S_{L}}\right)\right]\!\right\}.\end{eqnarray}$$

The physical meaning and determination method of the model parameters in (3.30) are summarized in table 3. They are either given turbulence/flame parameters or universal constants pre-determined by Lagrangian statistics of propagating surfaces, except for ${\mathcal{C}}$ determined by (3.24) from one or a few available data points of $S_{T}$ of premixed flames in weak turbulence.

Table 3.

Summary of the model parameters in the proposed model (3.30), where m.s. and p.s. denote material and propagating surfaces in non-reacting HIT, respectively.

The model (3.30) can predict most of the basic trends of $S_{T}$ summarized in Lipatnikov & Chomiak (Reference Lipatnikov and Chomiak2002). As $u^{\prime }/S_{L}\rightarrow 0$ with $Re=1$, (3.30) is reduced to the linear model (3.21), so the modelled $S_{T}$ increases with $u^{\prime }$ and ${\mathcal{C}}$ for small $u^{\prime }/S_{L}$. The form of (3.30) implies the ‘bending’ of $S_{T}/S_{L}$ at moderate $u^{\prime }/S_{L}$. As $u^{\prime }/S_{L}\rightarrow \infty$ with finite $Re$, this model converges to a finite value

(3.31)$$\begin{eqnarray}\frac{S_{T}}{S_{L}}=\exp \left[T_{\infty }^{\ast }\left({\mathcal{A}}+{\mathcal{B}}S_{L0}\right)\right].\end{eqnarray}$$

This implies that the modelled $S_{T}$ depends weakly on $u^{\prime }$ and increases with the laminar flame speed at large $u^{\prime }/S_{L}$, but it cannot predict the global quenching of flames characterized by a sharp drop of $S_{T}/S_{L}$ at very large $u^{\prime }/S_{L}$ (e.g. Karpov & Severin Reference Karpov and Severin1978, Reference Karpov and Severin1980; Driscoll Reference Driscoll2008; Lipatnikov Reference Lipatnikov2012). In particular, (3.31) suggests that the assumption in (3.10) with modelled $T_{s}^{\ast }$ in (3.25) recovers the finite flame area in high-$Re$ turbulence by implicitly accounting for surface annihilation of real flames.

Substituting all the model constants ${\mathcal{A}}=0.317,{\mathcal{B}}=0.033$ and $T_{\infty }^{\ast }=5.5$ calculated from Lagrangian statistics of propagating or material surfaces in non-reacting HIT, we finally obtain a predictive model for the turbulent burning velocity in terms of $u^{\prime }/S_{L}$ as

(3.32)$$\begin{eqnarray}\frac{S_{T}}{S_{L}}=\exp \left\{\left(1.742+0.182S_{L0}\right)\left[1-\exp \left(-\frac{{\mathcal{C}}Re^{-1/4}}{1.742+0.182S_{L0}}\frac{u^{\prime }}{S_{L}}\right)\right]\right\}.\end{eqnarray}$$

This model is validated in § 4.1 by three DNS data sets of various fuels.

Compared with existing models of $S_{T}$, the features of the present one are summarized as follows. (i) The Lagrangian history of flame wrinkling is represented by the Lagrangian statistics of propagating surfaces in non-reacting HIT, and is utilized to construct the model. In other words, the model (3.30) not only depends on local values of $u^{\prime }$, flow integral property $Re$ and flame properties $S_{L}$ and ${\mathcal{C}}$, but also on the Lagrangian-based parameters $T_{\infty }^{\ast }$, ${\mathcal{A}}$ and ${\mathcal{B}}$. (ii) The $Re$-independent profile of $A(t^{\ast })$ in terms of the quantities normalized by Kolmogorov scales is used in the modelling procedure, which introduces the universal statistics of propagating surfaces in small-scale turbulence and naturally involves the effect of $Re$ on $S_{T}$ in terms of integral scales. (iii) All the model parameters are derived via scale analysis and asymptotic analysis, and their values are determined by DNS of propagating surfaces in non-reacting HIT and existing data of $S_{T}$ in weak turbulence.

4.1 A posteriori test

We assess the model (3.32) of $S_{T}$ by comparing the model prediction and the results from the present combustion DNS and another two DNS series in the literature (see Lee & Huh Reference Lee and Huh2012; Nivarti & Cant Reference Nivarti and Cant2017) with the same flame configuration in figure 1 but with different fuels and $S_{L}$.

The three DNS series of turbulent premixed flames are briefly reviewed below. (i) The present DNS: $\text{H}_{2}$/air flame with detailed chemistry. (ii) DNS of Nivarti & Cant (Reference Nivarti and Cant2017): CH$_{4}$/air flame with the chemistry described using a single-step Arrhenius expression. (iii) DNS (Group T) of Lee & Huh (Reference Lee and Huh2010): the premixed mixture is modelled by a reaction progress variable, and the chemistry is computed by the single-step Arrhenius expression. As shown in figure 2, these three DNS series cover a range of $Re$, $Ka$ and premixed combustion regimes. All the model parameters in (3.32) are summarized in table 4, where ${\mathcal{C}}$ for each case is calculated from one or two corresponding DNS data points of $S_{T}$ at $u^{\prime }/S_{L}<2$ by (3.24).

Table 4.

Summary of the model parameters in three DNS series with various fuels.

The model (3.32) is validated by combustion DNS of various fuels in figure 15. In general, the model predictions (solid lines) from (3.32) agree well with the DNS results (symbols) and capture the bending of the profile of $S_{T}/S_{L}$ in terms of $u^{\prime }/S_{L}$. The overall good agreement ranges over $0<u^{\prime }/S_{L}\leqslant 20$ and various fuels, indicating the generality of our proposed model. In appendix D, the present model is also compared with other models of $S_{T}$ in the three DNS series, and the present one gives the overall best performance. The discrepancies at very large $u^{\prime }/S_{L}$ for DNS series of Nivarti & Cant (Reference Nivarti and Cant2017) and Lee & Huh (Reference Lee and Huh2010) are perhaps due to the breakdown of flame fronts close to the broken reaction zone. Moreover, uncertainties of the model constants in (3.30) can result in the discrepancies, which are elaborated below.

Figure 15.

Comparison of $S_{T}$ calculated from the combustion DNS (symbols) and the proposed model (3.32) (solid lines).

First, the value of ${\mathcal{C}}$ is fuel dependent and relies on available data points of $S_{T}$ under weak turbulence. In principle, the linear scaling (3.21) is recovered at $u^{\prime }/S_{L}=0$ with $Re\sim O(1)$. On the other hand, if only the data points of $S_{T}/S_{L}$ with finite $u^{\prime }/S_{L}$ and $Re>O(1)$ are available, ${\mathcal{C}}$ fitted from (3.24) can cause the discrepancy from (3.21) near $u^{\prime }/S_{L}=0$ in figure 15.

Furthermore, if there are no available data of $S_{T}/S_{L}$ for fitting ${\mathcal{C}}$, we suggest that the value of ${\mathcal{C}}$ can be simply set to ${\mathcal{C}}_{0}=2.0$ for hydrogen fuels and ${\mathcal{C}}_{0}=1.0$ for other fuels based on the chemical activity of the fuels. We observe the good agreement between the DNS result and the model prediction of (3.32) with the empirical constant ${\mathcal{C}}={\mathcal{C}}_{0}$ instead of fitting ${\mathcal{C}}$ from data, and illustrate the sensitivity of the model prediction to ${\mathcal{C}}$ by varying ${\mathcal{C}}={\mathcal{C}}_{0}\pm 0.5$ in figure 16. In general, $S_{T}/S_{L}$ predicted from (3.32) increases with ${\mathcal{C}}$.

Figure 16.

Model predictions of $S_{T}$ with the model constant ${\mathcal{C}}={\mathcal{C}}_{0}$ or ${\mathcal{C}}={\mathcal{C}}_{0}\pm 0.5$.

Second, the model constants ${\mathcal{A}}$, ${\mathcal{B}}$ and $T_{\infty }^{\ast }$ appear to be universal, but the determination of their values may involve some uncertainties owing to numerical schemes, forcing methods and finite-$Re$ effects in the DNS of non-reacting HIT and fitting methods to determine the constants, which can slightly affect the model prediction of $S_{T}$.

Although the present $S_{T}$ model still has some uncertainties and discrepancies owing to the physical assumptions in model development and the lack of rigorous methods for determining ${\mathcal{C}}$, generally controlled by combustion chemistry, it is able to predict the relatively accurate bending effect for flames in HIT at large $u^{\prime }/S_{L}$ in figures 15 and 16, which is superior to existing $S_{T}$ models (see detailed comparisons in appendix D). In particular, the propagating surface used in the model was introduced only for the flamelet regime (see Girimaji & Pope Reference Girimaji and Pope1992), but the present modelling approach appears to extend the concept of propagating surfaces to the thin-reaction-zone regime. The truncation of the area growth by $T_{s}^{\ast }$ and the cusp removal of propagating surfaces result in a finite $A(T_{s}^{\ast })$, which can model the statistically stationary $A_{T}$ under competing mechanisms between the flame area growth and consumption.

4.2 A priori test

In order to further validate the key modelling assumption in (3.10), we assess the contributions to the growth of $A_{T}$ on the right-hand side of (3.6) by comparing $\langle K_{t}^{\ast }(T_{s}^{\ast })\rangle _{A}$ and $\langle \unicode[STIX]{x1D705}^{\ast }(T_{s}^{\ast })\rangle _{A}$ of propagating surfaces at the modelled truncation time (3.25) in non-reacting HIT with $\langle K_{t}^{\ast }\rangle _{A}$ and $\langle \unicode[STIX]{x1D705}^{\ast }\rangle _{A}$ of the isosurface $c={\hat{c}}$ at the statistically stationary state in the present combustion DNS. The PDFs of $(K_{t}^{\ast })_{A}$ and $(\unicode[STIX]{x1D705}^{\ast })_{A}$ from propagating surfaces and flames in two typical cases B and D are plotted in figure 17. Here, based on (3.5) and the FSD described in appendix A, $(f)_{A}=f\unicode[STIX]{x1D6FF}A/(A/N_{s})$ and $(f)_{A}=f\unicode[STIX]{x1D6F4}^{\prime }/\unicode[STIX]{x1D6F4}$ denote area-weighted quantities for propagating surfaces and flames, respectively, and $\langle f\rangle _{A}$ is equal to the integration of the product of $(f)_{A}$ and its PDF in the sample space. Moreover, $K_{t}$ and $\unicode[STIX]{x1D705}$ in combustion DNS are calculated by (A 2) and (A 3).

Figure 17.

PDFs of (a) the normalized area-weighted tangential strain rate and (b) the mean curvature from flames and propagating surfaces in DNS cases B and D. Circles: flame in case B; diamonds: flame in case D; solid lines: propagating surface in case B; dashed lines: propagating surface in case D.

Figure 17(a) indicates that all the cases exhibit positive $\langle K_{t}^{\ast }\rangle _{A}$, which is consistent with the positive contribution of turbulent straining to the area growth of material surfaces (Girimaji & Pope Reference Girimaji and Pope1990). Similar PDFs of $(K_{t}^{\ast })_{A}$ in propagating surfaces and flames imply that the straining process experienced by propagating surfaces in non-reacting HIT resembles that of flames in turbulent combustion.

Figure 17(b) shows that the PDF of $(\unicode[STIX]{x1D705}^{\ast })_{A}$ of the propagating surfaces is qualitatively similar to that of flames, but the former distribution is generally broader than the latter one. This observation implies that nearly singular propagating surfaces with very large curvatures can be smoothed in real flames owing to diffusion and curvature effects. Furthermore, $\langle \unicode[STIX]{x1D705}^{\ast }\rangle _{A}$ of flames is close to zero, which agrees with the former finding (e.g. Trouvé & Poinsot Reference Trouvé and Poinsot1994; Chakraborty & Cant Reference Chakraborty and Cant2005; Nivarti & Cant Reference Nivarti and Cant2017) that the curvature effect can consume the flame area. On the other hand, $\langle \unicode[STIX]{x1D705}^{\ast }\rangle _{A}$ of the propagating surfaces is slightly positive and of the order of $O(0.01)$. The cellular structures of propagating surfaces in figure 6 with positive $\langle \unicode[STIX]{x1D705}^{\ast }\rangle _{A}$ (Zheng et al. Reference Zheng, You and Yang2017) are only observed in turbulent premixed flames at low $Ka$ in figure 3 (see Matalon Reference Matalon2009), whereas they break down at high $Ka$. This structural difference causes the discrepancy between PDFs of $(\unicode[STIX]{x1D705}^{\ast })_{A}$ for propagating surfaces and flames in case D.