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Turbulent kinetic energy budget in compressible turbulent mixing layers: effects of large-scale structures

Published online by Cambridge University Press:  16 January 2025

Xiaoning Wang
Affiliation:
Department of Mechanics and Aerospace Engineering, Southern University of Science and Technology, Shenzhen 518055, PR ChinaGuangdong Provincial Key Laboratory of Turbulence Research and Applications, Southern University of Science and Technology, Shenzhen 518055, PR ChinaGuangdong-Hong Kong-Macao Joint Laboratory for Data-Driven Fluid Mechanics and Engineering Applications, Southern University of Science and Technology, Shenzhen 518055, PR China
Jing Guo
Affiliation:
Department of Mechanics and Aerospace Engineering, Southern University of Science and Technology, Shenzhen 518055, PR China
Jianchun Wang*
Affiliation:
Department of Mechanics and Aerospace Engineering, Southern University of Science and Technology, Shenzhen 518055, PR ChinaGuangdong Provincial Key Laboratory of Turbulence Research and Applications, Southern University of Science and Technology, Shenzhen 518055, PR ChinaGuangdong-Hong Kong-Macao Joint Laboratory for Data-Driven Fluid Mechanics and Engineering Applications, Southern University of Science and Technology, Shenzhen 518055, PR China
Shiyi Chen
Affiliation:
Department of Mechanics and Aerospace Engineering, Southern University of Science and Technology, Shenzhen 518055, PR ChinaGuangdong Provincial Key Laboratory of Turbulence Research and Applications, Southern University of Science and Technology, Shenzhen 518055, PR ChinaGuangdong-Hong Kong-Macao Joint Laboratory for Data-Driven Fluid Mechanics and Engineering Applications, Southern University of Science and Technology, Shenzhen 518055, PR ChinaEastern Institute for Advanced Study, Eastern Institute of Technology, Ningbo 315200, PR China
*
†Email address for correspondence: wangjc@sustech.edu.cn

Abstract

Direct numerical simulations of temporally developing compressible mixing layers have been performed to investigate the effects of large-scale structures (LSSs) on turbulent kinetic energy (TKE) budgets at convective Mach numbers ranging from $M_c=0.2$ to $1.8$ and at Taylor Reynolds numbers up to 290. In the core region of mixing layers, the volume fraction of low-speed LSSs decreases linearly with respect to the vertical distance at a Mach-number-independent rate. The contributions of low-speed LSSs to TKE, and its budget, including production, dissipation, pressure-strain and spatial diffusion terms, are primarily concentrated in the upper region of mixing layer. The streamwise and vertical mass flux coupling terms mainly transport TKE downwards in low-speed LSSs, and their magnitudes are comparable to the other dominant terms. Near the edges of LSSs, the sources and losses of all three components of TKE are completely different to each other, and dominated by turbulent diffusion, pressure diffusion, pressure-strain and dissipation terms. The TKE, their total variation and dissipation are significantly amplified at edges of low-speed LSSs, especially at the upper edge. This observation supports the existence of amplitude modulation exerted by the LSSs onto the near-edge small-scale structures in mixing layers. The level of amplitude modulation is strongest for the vertical velocity, followed by the streamwise velocity, and weakest for the spanwise velocity. Additionally, the amplitude modulation effect decreases significantly with increasing convective Mach number. The results on the amplitude modulation effect is helpful for developing predictive models of budget terms of TKE in mixing layers.

Information

Type
JFM Papers
Copyright
© The Author(s), 2025. Published by Cambridge University Press
Figure 0

Table 1.Simulation parameters at the beginning ($\tau =\tau _0$) and end ($\tau =\tau _f$) of the self-similar period. The values of $M_t$, $Re_{\lambda }$, $K$, $\omega$, $\varTheta _{rms}$, $\eta$, $l_x$ and $l_z$ are obtained at $y = 0$.

Figure 1

Figure 1.An example of high-speed LSSs (red contours of $u^{\prime \prime } > 0$) and low-speed LSSs (blue contours of $u^{\prime \prime } < 0$) in fluctuating streamwise velocity field is shown in the $y\unicode{x2013}z$ plane. The black solid lines present the TNTI. The green dashed line show a specific horizontal plane.

Figure 2

Figure 2.Volume fraction of ($a$) low-speed LSS and ($b$) high-speed LSS at $M_c=0.2$, $0.8$ and $1.8$.

Figure 3

Figure 3.(a–c) Contributions of the low-speed LSSs to turbulent kinetic energy $\bar {K}_{i,{n}}/(\rho _\infty \Delta U^2)$ and (d–f) conditionally averaged turbulent kinetic energy $\hat {K}_{i,{n}}/(\rho _\infty \Delta U^2)$ at $M_c=0.2$, $0.8$ and $1.8$. (a,d) Streamwise, (b,e) vertical and (c,f) spanwise components.

Figure 4

Figure 4.($a$) Contributions of the low-speed LSSs to production $\bar {P}_{n}/\bar {\epsilon }_{c}$ and ($b$) conditionally averaged production $\hat {P}_{n}/\bar {\epsilon }_{c}$ based on low-speed events with $u^{\prime \prime }<0$ at $M_c=0.2$, $0.8$ and $1.8$.

Figure 5

Figure 5.Two-dimensional conditionally averaged production $\breve {P}_{n}/\bar {\epsilon }_{c}$ (contours), streamwise velocity $\breve {u}_{n}/\Delta U$ (solid lines) and vertical velocity $\breve {v}_{n}/\Delta U$ (dashed lines), and based on low-speed events with $u^{\prime \prime }<-0.15\Delta U$ at ($a$) $M_c=0.2$, ($b$) $M_c=1.8$. Conditionally averaged negative component of production $\breve {P}^-_{n}/\bar {\epsilon }_{c}$ at ($c$) $M_c=0.2$, ($d$) $M_c=1.8$.

Figure 6

Figure 6.($a$) Contributions of the low-speed LSSs to dissipation $\bar {\epsilon }_{n}/\bar {\epsilon }_{c}$ and ($b$) conditionally averaged dissipation $\hat {\epsilon }_{n}/\bar {\epsilon }_{c}$ based on low-speed events with $u^{\prime \prime }<0$ at $M_c=0.2$, $0.8$ and $1.8$. ($c$) $\bar {\epsilon }_{n}$ is normalized by $\rho _\infty \Delta U^3/\delta _\omega$ with the error bar representing discrepancy among the maximum and minimum dissipation components.

Figure 7

Figure 7.Two-dimensional conditionally averaged components of dissipation $\breve {\epsilon }_{i,{n}}/\bar {\epsilon }_{c}$ (contours) and streamwise velocity $\breve {u}_{n}/\Delta U$ (solid lines) based on low-speed events with $u^{\prime \prime }<-0.15\Delta U$ at ($a$–$c$) $M_c=0.2$ and ($d$–$f$) $1.8$. (a,d) Streamwise, (b,e) vertical and (c,f) spanwise components.

Figure 8

Figure 8.($a$) Contributions of the low-speed LSSs to pressure-dilatation $\bar {\varPhi }_{n}/\bar {\epsilon }_{c}$ and ($b$) conditionally averaged pressure-dilatation $\hat {\varPhi }_{n}/\bar {\epsilon }_{c}$ based on low-speed events with $u^{\prime \prime }<0$ at $M_c=0.2$, $0.8$ and $1.8$.

Figure 9

Figure 9.($a$–$c$) Contributions of the low-speed LSSs to pressure-strain $\bar {\varPhi }_{i,{n}}/\bar {\epsilon }_{c}$ and ($d$–$f$) conditionally averaged pressure-strain $\hat {\varPhi }_{i,{n}}/\bar {\epsilon }_{c}$ based on low-speed events with $u^{\prime \prime }<0$ at $M_c=0.2$, $0.8$ and $1.8$. (a,d) Streamwise, (b,e) vertical and (c,f) spanwise components.

Figure 10

Figure 10.Two-dimensional conditionally averaged components of pressure-strain $\breve {\varPhi }_{i,{n}}/\bar {\epsilon }_{c}$ (contours) and streamwise velocity $\breve {u}_{n}/\Delta U$ (solid lines) based on low-speed events with $u^{\prime \prime }<-0.15\Delta U$ at ($a$–$c$) $M_c=0.2$ and ($d$–$f$) $1.8$. (a,d) Streamwise, (b,e) vertical and (c,f) spanwise components.

Figure 11

Figure 11.Two-dimensional conditionally averaged ($a$–$c$) positive part of pressure-strain $\breve {\varPhi }^+_{i,{n}}/\bar {\epsilon }_{c}$, ($d$–$f$) negative part of pressure-strain $\breve {\varPhi }^-_{i,{n}}/\bar {\epsilon }_{c}$ (contours) and streamwise velocity $\breve {u}_{n}/\Delta U$ (solid lines) based on low-speed events with $u^{\prime \prime }<-0.15\Delta U$ at $M_c=0.2$. (a,d) Streamwise, (b,e) vertical and (c,f) spanwise components.

Figure 12

Figure 12.Two-dimensional conditionally averaged ($a$–$c$) positive part of pressure-strain $\breve {\varPhi }^+_{i,{n}}/\bar {\epsilon }_{c}$, ($d$–$f$) negative part of pressure-strain $\breve {\varPhi }^-_{i,{n}}/\bar {\epsilon }_{c}$ (contours) and streamwise velocity $\breve {u}_{n}/\Delta U$ (solid lines) based on low-speed events with $u^{\prime \prime }<-0.15\Delta U$ at $M_c=1.8$. (a,d) Streamwise, (b,e) vertical and (c,f) spanwise components.

Figure 13

Figure 13.($a$–$c$) Contributions of the low-speed LSSs to turbulent diffusion $\bar {T}_{t,i,{n}}/\bar {\epsilon }_{c}$ and ($d$–$f$) conditionally averaged turbulent diffusion $\hat {T}_{t,i,{n}}/\bar {\epsilon }_{c}$ based on low-speed events with $u^{\prime \prime }<0$ at $M_c=0.2$, $0.8$ and $1.8$. (a,d) Streamwise, (b,e) vertical and (c,f) spanwise components.

Figure 14

Figure 14.Two-dimensional conditionally averaged components of turbulent diffusion $\breve {T}_{t,i,{n}}/\bar {\epsilon }_{c}$ (contours) and streamwise velocity $\breve {u}_{n}/\Delta U$ (solid lines) based on low-speed events with $u^{\prime \prime }<-0.15\Delta U$ at ($a$–$c$) $M_c=0.2$ and ($d$–$f$) $1.8$. (a,d) Streamwise, (b,e) vertical and (c,f) spanwise components.

Figure 15

Figure 15.($a$–$c$) Contributions of the low-speed LSSs to pressure diffusion $\bar {T}_{p,i,{n}}/\bar {\epsilon }_{c}$ and ($d$–$f$) conditionally averaged pressure diffusion $\hat {T}_{p,i,{n}}/\bar {\epsilon }_{c}$ based on low-speed events with $u^{\prime \prime }<0$ at $M_c=0.2$, $0.8$ and $1.8$. (a,d) Streamwise, (b,e) vertical and (c,f) spanwise components.

Figure 16

Figure 16.Two-dimensional conditionally averaged components of pressure diffusion $\breve {T}_{p,i,{n}}/\bar {\epsilon }_{c}$ (contours) and streamwise velocity $\breve {u}_{n}/\Delta U$ (solid lines) based on low-speed events with $u^{\prime \prime }<-0.15\Delta U$ at ($a$–$c$) $M_c=0.2$ and ($d$–$f$) $1.8$. (a,d) Streamwise, (b,e) vertical and (c,f) spanwise components.

Figure 17

Figure 17.(a,b) Contributions of the low-speed LSSs to mass flux coupling $\bar {\varSigma }_{i,{n}}/\bar {\epsilon }_{c}$ and (c,d) conditionally averaged mass flux coupling $\hat {\varSigma }_{i,{n}}/\bar {\epsilon }_{c}$ based on low-speed events with $u^{\prime \prime }<0$ at $M_c=0.2$, $0.8$ and $1.8$. (a,c) Streamwise and (b,d) vertical components.

Figure 18

Figure 18.Two-dimensional conditionally averaged mass flux coupling $\breve {\varSigma }_{i,{n}}/\bar {\epsilon }_{c}$ (contours) and streamwise velocity $\breve {u}_{n}/\Delta U$ (solid lines) based on low-speed events with $u^{\prime \prime }<-0.15\Delta U$ at (a,b) $M_c=0.2$ and (c,d) $1.8$. (a,c) Streamwise and (b,d) vertical components.

Figure 19

Figure 19.($a$–$c$) Contributions of the low-speed LSSs to the total variation of turbulent kinetic energy $\bar {V}_{i,{n}}/\bar {\epsilon }_{c}$ and ($d$–$f$) conditionally averaged total variation $\hat {V}_{i,{n}}/\bar {\epsilon }_{c}$ based on low-speed events with $u^{\prime \prime }<0$ at $M_c=0.2$, $0.8$ and $1.8$. (a,d) Streamwise, (b,e) vertical and (c,f) spanwise components.

Figure 20

Figure 20.($a$–$c$) Streamwise and ($d$–$f$) spanwise two-point correlations of (a,d) streamwise, (b,e) vertical and (c,f) spanwise velocities at the centreline at several time instants from $\tau =125$ to $\tau =750$ for the case with $M_c=0.2$.

Figure 21

Figure 21.($a$–$c$) Streamwise and ($d$–$f$) spanwise two-point correlations of (a,d) streamwise, (b,e) vertical and (c,f) spanwise velocities at the centreline at several time instants from $\tau =250$ to $\tau =2250$ for the case with $M_c=1.8$.

Figure 22

Figure 22.Comparison of one-point statistics with different $\tau _f$ for $M_c=1.8$. ($a$–$c$) Conditionally averaged turbulent kinetic energy $\hat {K}_{i,{n}}/(\rho _\infty \Delta U^2)$. ($d$–$f$) Conditionally averaged production $\hat {P}_{n}/\bar {\epsilon }_{c}$, dissipation $\hat {\epsilon }_{n}/\bar {\epsilon }_{c}$ and pressure-dilatation $\hat {\varPhi }_{n}/\bar {\epsilon }_{c}$.

Figure 23

Figure 23.Comparison of two-dimensional conditionally averaged ($a$) streamwise velocity $\breve {u}_{n}/\Delta U$, ($b$) production $\breve {P}_{n}/\bar {\epsilon }_{c}$ and dissipation $\breve {\epsilon }_{1,{n}}/\bar {\epsilon }_{c}$ with different $\tau _f$ for $M_c=1.8$.

Figure 24

Table 2.The beginning ($\tau =\tau _0$) and end ($\tau =\tau _f$) times of the self-similar period, domain lengths ($L_x$, $L_y$ and $L_z$) and integral lengths ($l_x$ and $l_z$) in the most relevant publications of DNS of temporally developing compressible mixing layer at higher convective Mach number. Only the integral lengths at the end time ($\tau =\tau _f$) of the self-similar period are presented by Pantano & Sarkar (2002), Vaghefi (2014), Arun et al. (2019) and Yu & Lu (2020).