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Conditional analysis on extreme wall shear stress and heat flux events in compressible turbulent boundary layers

Published online by Cambridge University Press:  03 November 2023

Peng-Jun-Yi Zhang
Affiliation:
Department of Modern Mechanics, University of Science and Technology of China, Hefei 230027, PR China
Zhen-Hua Wan*
Affiliation:
Department of Modern Mechanics, University of Science and Technology of China, Hefei 230027, PR China
Si-Wei Dong
Affiliation:
State Key Laboratory of Aerodynamics, China Aerodynamics Research and Development Center, Mianyang 621000, PR China
Nan-Sheng Liu
Affiliation:
Department of Modern Mechanics, University of Science and Technology of China, Hefei 230027, PR China
De-Jun Sun*
Affiliation:
Department of Modern Mechanics, University of Science and Technology of China, Hefei 230027, PR China
Xi-Yun Lu
Affiliation:
Department of Modern Mechanics, University of Science and Technology of China, Hefei 230027, PR China
*
†Email addresses for correspondence: wanzh@ustc.edu.cn, dsun@ustc.edu.cn
†Email addresses for correspondence: wanzh@ustc.edu.cn, dsun@ustc.edu.cn

Abstract

This study presents a comprehensive analysis on the extreme positive and negative events of wall shear stress and heat flux fluctuations in compressible turbulent boundary layers (TBLs) solved by direct numerical simulations. To examine the compressibility effects, we focus on the extreme events in two representative cases, i.e. a supersonic TBL of Mach number $M=2$ and a hypersonic TBL of $M=8$, by scrutinizing the coherent structures and their correlated dynamics based on conditional analysis. As characterized by the spatial distribution of wall shear stress and heat flux, the extreme events are indicated to be closely related to the structural organization of wall streaks, in addition to the occurrence of the alternating positive and negative structures (APNSs) in the hypersonic TBL. These two types of coherent structures are strikingly different, namely the nature of wall streaks and APNSs are shown to be related to the solenoidal and dilatational fluid motions, respectively. Quantitative analysis using a volumetric conditional average is performed to identify and extract the coherent structures that directly account for the extreme events. It is found that in the supersonic TBL, the essential ingredients of the conditional field are hairpin-like vortices, whose combinations can induce wall streaks, whereas in the hypersonic TBL, the essential ingredients become hairpin-like vortices as well as near-wall APNSs. To quantify the momentum and energy transport mechanisms underlying the extreme events, we proposed a novel decomposition method for extreme skin friction and heat flux, based on the integral identities of conditionally averaged governing equations. Taking advantage of this decomposition method, the dominant transport mechanisms of the hairpin-like vortices and APNSs are revealed. Specifically, the momentum and energy transports undertaken by the hairpin-like vortices are attributed to multiple comparable mechanisms, whereas those by the APNSs are convection dominated. In that, the dominant transport mechanisms in extreme events between the supersonic and hypersonic TBLs are indicated to be totally different.

Information

Type
JFM Papers
Copyright
© The Author(s), 2023. Published by Cambridge University Press
Figure 0

Table 1.The parameters of simulations: $N_x$, $N_y$ and $N_z$ are the numbers of grid points in three directions; $L_x$, $L_y$ and $L_z$ are the lengths of the physical computational domain based on the inlet boundary-layer thickness $\delta _i$; $\Delta x^+$ and $\Delta z^+$ represent streamwise and spanwise grid spacings in the wall unit, respectively; $\Delta y^+_w$ and $\Delta y^+_e$ represent the wall-normal grid spacings at the wall and the boundary edge, respectively; $N_f$ is the number of flow fields sampled for statistics and $t_su_\infty /\delta _i$ is the period for ensemble averaging.

Figure 1

Figure 1.Computational domain and vortical structures illustrated by isosurface of $Q$-criterion. The domains selected for analysis are colourfully flooded by the streamwise velocity.

Figure 2

Table 2.Parameters and statistical properties of the boundary layers at the centre location of the domain selected for analysis: $M=u_\infty /c_\infty$ and $T_\infty$ are the free stream Mach number and temperature, respectively; ${\textit {Re}}_\delta =\rho _{\infty }u_\infty \delta /\mu _\infty$ is the Reynolds number based on the boundary-layer thickness; ${\textit {Re}}_\tau =\bar {\rho }_w u_\tau \delta / \bar {\mu }_{w}$ is the friction Reynolds number. The Reynolds numbers based on the momentum thickness are ${{\textit {Re}}}_{\theta }=\rho _{\infty } u_{\infty } \theta / \mu _{\infty }$ and ${{\textit {Re}}}_{\delta _{2}}=\rho _{\infty } u_{\infty } \theta / \bar {\mu }_{w}$. Additionally, $\mathcal {H}=\delta ^{*} / \theta$ is the shape factor; $B_{q}=-(\mathrm {d} \bar {T} / \mathrm {d}y^+)_w / {\textit {Pr}} T_w$ indicates the non-dimensional wall heat flux; $T_w/T_r$ means the ratio of isothermal-wall temperature to recovery temperature and $\varTheta =(T_w-T_\infty )/(T_r-T_\infty )$ is the dimensionless temperature.

Figure 3

Figure 2.Statistical properties: (a) van Driest transformed mean velocity $u_{vd}^+$; (b) density-scaled turbulent intensity and Reynolds shear stress. $- {\cdot } - {\cdot } -$, wall law $u^+_{vd}=y^+$; $---$, log law $u^+_{vd}=\log {(y^+)}/k+C$ with $k=0.41$, $C=5.2$.

Figure 4

Figure 3.Velocity-temperature statistical properties: (a) the distribution of mean temperature $\bar {T}/T_\infty$ versus mean velocity $\bar {u}/u_\infty$; (b) the velocity-temperature correlation coefficient $-R_{uT}$; (c) the turbulent Prandtl number ${\textit {Pr}}_t$; (d) the modified SRA of Huang, Coleman & Bradshaw (1995).

Figure 5

Figure 4.Skin-friction coefficient $C_f$, heat-transfer coefficient $C_h$ and Reynolds analogy factor $s=2C_h/C_f$ versus Reynolds number $Re_\theta$ for the cases (a) M2T05, (b) M8T05. The dashed line indicates $s=1.14$, the symbols denote the incompressible relations of Kármán–Schoenherr (Roy & Blottner 2006) and Coles–Fernholz (Nagib, Chauhan & Monkewitz 2007) transformed by the van Driest II transformation. The lightly shaded regions (i) and (iii) mark the boundary layer developing region and the region influenced by buffer zone, respectively, and the shaded regions (ii) mark the domains selected for analysis.

Figure 6

Figure 5.P.d.f.s of $\tau _w^\prime /\tau _{w,rms}$ and $q_w^\prime /q_{w,rms}$: (a) the distributions of single point p.d.f.s; the distributions of joint p.d.f.s for (b) M2T05 and (c) M8T05. The diamond and circle symbols indicate the p.d.f.s of $\tau _w^\prime$ and $q_w^\prime$ in Tong et al. (2022) with $M=2.25$ and $T_w/T_r=0.75$, respectively. The shades mark the fluctuations belonging to extreme events. The values of joint p.d.f.s increase as the contour colours change from blue to red.

Figure 7

Table 3.Statistics of WSS and WHF fluctuations: root-mean-square value $\phi _{rms}=\sqrt {\phi ^{\prime 2}}$, skewness $S_\phi =\overline {\phi ^{\prime 3}} /(\overline {\phi ^{\prime 2}})^{3 / 2}$ and flatness $F_\phi =\overline {\phi ^{\prime 4}} /(\overline {\phi ^{\prime 2}})^2$.

Figure 8

Table 4.Thresholds of extreme events for WSS and WHF fluctuations.

Figure 9

Figure 6.Instantaneous fluctuating fields of (a,c) $\tau _w^\prime /\tau _{w,rms}$ and (b,d) $q_w^\prime /q_{w,rms}$, for (a,b) M2T05 and (c,d) M8T05. The purple and green colour scales indicate EP and EN events, respectively. Two types of flow structures associated with extreme events, namely the streak and APNS, are enlarged in the upper panels for a clearer observation.

Figure 10

Figure 7.Two-dimensional pre-multiplied wavenumber spectra $k_xk_z\varPhi ^+(\lambda _x^+,\lambda _z^+)$ with integrated one-dimensional pre-multiplied wavenumber spectra $k_x\phi ^+(\lambda _x^+)$ (top) and $k_z\phi ^+(\lambda _z^+)$ (right) of (a,c) $\tau _w^\prime$ and (b,d) $q_w^\prime$ for (a,b) M2T05 and (c,d) M8T05. The dashed lines correspond to the peak values in the one-dimensional spectra.

Figure 11

Table 5.Parameters and results of conditional average: $n_E$ is the sample number of extreme events; $C_f$ and $C_h$ are the skin-friction and heat-transfer coefficients, respectively; $\langle C_f\rangle$ and $\langle C_h\rangle$ indicate the conditionally averaged skin-friction and heat-transfer coefficients, respectively; $P$ is the percentage of the events which coexist both in extreme $\tau _w^\prime$ and $q_w^\prime$ events.

Figure 12

Figure 8.Conditionally averaged $\langle \tau _w^\prime \rangle$ and $\langle q_w^\prime \rangle$ fields around extreme events at $\Delta x^+=0$ and $\Delta z^+=0$ of (a–d) M2T05 and (e–h) M8T05. The left and right panels stand for EP and EN events, respectively. The white lines circle the regions belonging to extreme WSS and WHF fluctuations.

Figure 13

Figure 9.Conditional analysis on extreme events of $\tau _w^\prime$ for M2T05: (a,b) conditionally averaged fluctuation fields, the isosurfaces of high-/low-speed streaks are flooded by $v$, the vortices displayed by the isosurfaces of $Q$-criterion are flooded by $\omega _x$. An $x$–$y$ plane at $\Delta z^+=0$ and a $y$–$z$ plane at $\Delta x^+=0$ are shifted aside for clearer observation. Components of conditionally averaged skin-friction coefficients normalized by $C_f$: (c,e) $C_f^i$; (d,f) $C_f^i(y_b)$ as a function of the upper bound of integrals. Panels (a,c,d) and (b,e,f) are for the EP and EN events, respectively.

Figure 14

Figure 10.Conditional analysis on extreme events of $\tau _w^\prime$ for M8T05: (a,b) conditionally averaged fluctuation fields, the isosurfaces of dilatation $\theta ^+$ are flooded by itself, the isosurfaces of high-/low-speed streaks are flooded by $v$, the vortices displayed by the isosurfaces $Q$-criterion are flooded by $\omega _x$. An $x$–$y$ plane at $\Delta z^+=0$ and a $y$–$z$ plane at $\Delta x^+=0$ are shifted aside for clearer observation. Components of conditionally averaged skin-friction coefficients normalized by $C_f$: (c,e) $C_f^i$; (d,f) $C_f^i(y_b)$ as a function of upper bound of integrals. Panels (a,c,d) and (b,e,f) are for the EP and EN events, respectively.

Figure 15

Figure 11.Contours of the conditionally averaged fluctuation field of extreme $\tau _w^\prime$ events for M8T05 at $\Delta z^+=0$ plane: (a,b) the streamwise velocity $u$; (c,d) the solenoidal component $u_s$ and (d,f) the dilatational component $u_d$. Panels (a,c,e) and (b,d,f) are for EP and EN events, respectively.

Figure 16

Figure 12.Contours of the conditionally averaged field based on extreme $\tau _w^\prime$ events for M8T05 at the $y^+=15$ plane: (a,b) the wall-normal velocity $v$; (c,d) the solenoidal component $v_s$; (e,f) the dilatational component $v_d$. Panels (a,c,e) and (b,d,f) are for EP and EN events, respectively.

Figure 17

Figure 13.Conditional analysis on extreme events of $q_w^\prime$ for M2T05: (a,b) conditionally averaged fluctuation fields, the isosurfaces of high-/low-temperature streaks are flooded by $v$, the vortices displayed by the isosurfaces of $Q$-criterion are flooded by $\omega _x$. An $x$–$y$ plane at $\Delta z^+=0$ and a $y$–$z$ plane at $\Delta x^+=0$ are shifted aside for clearer observation. Components of conditionally averaged heat-transfer coefficients normalized by $C_h$: (c,e) $C_h^i$; (d,f) $C_h^i(y_b)$ as a function of the upper bound of integrals. Panels (a,c,d) and (b,e,f) are for the EP and EN events, respectively.

Figure 18

Figure 14.Conditional analysis on extreme events of $q_w^\prime$ for M8T05: (a,b) conditionally averaged fluctuation fields, the isosurfaces of dilatation $\theta ^+$ and temperature $T^+$ are flooded by themselves, the vortices displayed by the $Q$-criterion are flooded by $\omega _z$. An $x$–$y$ plane at $\Delta z^+=0$ and a $y$–$z$ plane at $\Delta x^+=0$ are shifted aside for clearer observation. Components of conditionally averaged heat-transfer coefficients normalized by $C_h$: (c,e) $C_h^i$; (d,f) $C_h^i(y_b)$ as a function of the upper bound of integrals. Panels (a,c,d) and (b,e,f) are for the EP and EN events, respectively.

Figure 19

Figure 15.Recombined components of conditionally averaged heat-transfer coefficients for M8T05 normalized by $C_h$: (a,c) $C_h^i$; (b,d) $C_h^i(y_b)$ as a function of the upper bound of integrals. Panels (a,b) and (c,d) are for the EP and EN events, respectively.

Figure 20

Figure 16.Budgets of conditionally averaged equations based on EP events of M2T05: (a) the momentum equation of (4.1) and (b) the energy equation of (4.8). Conditional decompositions: (c) components of conditionally averaged skin-friction coefficients $C_f^i$ normalized by $\langle C_f\rangle _{EP}$; (d) components of conditionally averaged heat-transfer coefficients $C_h^i$ normalized by $\langle C_h\rangle _{EP}$.

Figure 21

Figure 17.Dependence of the decompositions on sample numbers of extreme events $n$ for (a–d) M2T05 and (e–h) M8T05: (a,b,e,f) components of conditionally averaged skin-friction coefficient $C_f^i(y_b)$; (c,d,g,h) components of conditionally averaged heat-transfer coefficient $C_h^i(y_b)$. Panels (a,c,e,g) and (b,d,f,h) are for EP events and EN events, respectively. The solid lines, circles and diamonds indicate sample numbers $n=n_E$, $n_E/2$ and $n_E/10$, respectively.