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Self-turbulization in cellularly unstable laminar flames

Published online by Cambridge University Press:  30 April 2021

Zirui Liu
Affiliation:
Department of Mechanical and Aerospace Engineering, Princeton University, Princeton, NJ 08544, USA
Vishnu R. Unni
Affiliation:
Department of Mechanical and Aerospace Engineering, University of California San Diego, La Jolla, CA 92093, USA
Swetaprovo Chaudhuri
Affiliation:
Institute of Aerospace Studies, University of Toronto, Toronto, ON M3H 5T6, Canada
Ran Sui
Affiliation:
Department of Mechanical and Aerospace Engineering, Princeton University, Princeton, NJ 08544, USA
Chung K. Law
Affiliation:
Department of Mechanical and Aerospace Engineering, Princeton University, Princeton, NJ 08544, USA
Abhishek Saha*
Affiliation:
Department of Mechanical and Aerospace Engineering, University of California San Diego, La Jolla, CA 92093, USA
*
†Email address for correspondence: asaha@eng.ucsd.edu

Abstract

It has been suggested that a cellularly unstable laminar flame, which is freely propagating in unbounded space, can accelerate and evolve into a turbulent flame with the neighbouring flow exhibiting the basic characteristics of turbulence. Famously known as self-turbulization, this conceptual transition in the flow regime, which arises from local interactions between the propagating wrinkled flamefront and the flow, is critical in extreme events such as the deflagration-to-detonation transition (DDT) leading to supernova explosions. Recognizing that such a transition in the flow regime has not been conclusively demonstrated through experiments, in this work, we present experimental measurements of flow characteristics of flame-generated ‘turbulence’ for expanding cellular laminar flames. The energy spectra of such ‘turbulence’ at different stages of cellular instability are analysed. A subsequent scaling analysis points out that the observed energy spectra are driven by the fractal topology of the cellularly unstable flamefront.

Information

Type
JFM Papers
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.
Copyright
© The Author(s), 2021. Published by Cambridge University Press.
Figure 0

Figure 1. Experimental setup: Dual chamber vessel with high-speed camera, optics and laser used for high-speed particle image velocimetry.

Figure 1

Figure 2. (a) Schlieren image. The inset bar indicates 10 mm. (b) Three-stage behaviour of flame propagation. Here, $Pe$, Péclet number; $\widetilde {S_{L,b}}$, flame propagation speed normalized by laminar unstretched flame speed (burned side). Replotted from data presented in Yang et al. (2018). (c) Mie scattering image with edge detection. (d) Vector field from particle image velocimetry. Colour represents magnitude of local velocity.

Figure 2

Table 1. Experimental conditions with corresponding flame parameters. The parameters are $\phi$, equivalence ratio; $Y_i$, mole fraction of species $i$ in unburned mixture; Le, Lewis number; P, pressure; $S_{L,0}$, flame speed of laminar planar flame; $\delta _{L,0}$, thickness of laminar planar flame.

Figure 3

Figure 3. (a) Averaged normalized radial velocity, $\langle \overline {U_r} \rangle _{\theta }$, versus distance away from flamefront, ${\rm \Delta} R$, at different $Pe$. Inset: Averaged normalized radial velocity, $\langle \overline {U_r} \rangle _{\theta }$, on the flamefront (${\rm \Delta} R = 0$) versus $Pe$. (b) Averaged normalized azimuthal velocity, $\langle \overline {U_{\theta }} \rangle _{\theta }$, versus distance away from flamefront, ${\rm \Delta} R$, at different $Pe$. (c) Root-mean-square (RMS) of normalized radial and azimuthal velocity fluctuation $\overline {u_r}$,$\overline {u_{\theta }}$ versus distance away from flamefront, ${\rm \Delta} R$, in the saturated stage. The uncertainties (shown in c) for radial and azimuthal velocities are within ${\pm }6\,\%$.

Figure 4

Figure 4. (a) Energy spectra of normal velocity fluctuation $u_n$ on the flamefront at different $Pe$. (b) Energy spectra of tangential velocity fluctuation $u_t$ on the flamefront at different $Pe$. Here, $Pe=587$, smooth expansion stage; $Pe=1235$, transition stage; the rest, saturated stage. The uncertainty of the power spectral density is approximately ${\pm }12\,\%$.

Figure 5

Figure 5. (a) Flamefront fluctuation $g$ versus $\theta$ in the smooth expansion stage and the saturated stage. In the smooth expansion stage, only large cracks are present on the flamefront, while in the saturated stage, small cellular structures are generated on the flamefront. (b) Power spectra density of $\textrm {d} g/{\textrm {d}x}$ of the flamefront. Here wavenumber $k$ is based on the distance along the flamefront. The smallest resolved scale is controlled by the resolution of the Mie scattering images. The uncertainty for edge detection is approximately ${\pm }1\,\%$, and for $PSD$ is ${\pm }2\,\%$.

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