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Multiscale circulation in wall-parallel planes of turbulent channel flows

Published online by Cambridge University Press:  07 May 2025

Peng-Yu Duan
Affiliation:
Key Laboratory of Fluid Mechanics of Ministry of Education, Beihang University (Beijing University of Aeronautics and Astronautics), Beijing 100191, PR China
Xi Chen*
Affiliation:
Key Laboratory of Fluid Mechanics of Ministry of Education, Beihang University (Beijing University of Aeronautics and Astronautics), Beijing 100191, PR China
Katepalli R. Sreenivasan
Affiliation:
Tandon School of Engineering, Courant Institute of Mathematical Sciences, and Department of Physics, New York University, New York 10012, USA
*
Corresponding author: Xi Chen, chenxi97@outlook.com

Abstract

Wall turbulence consists of various sizes of vortical structures that induce flow circulation around a wide range of closed Eulerian loops. Here we investigate the multiscale properties of circulation around such loops in statistically homogeneous planes parallel to the wall. Using a high-resolution direct numerical simulation database of turbulent channels at Reynolds numbers of $Re_\tau =180$, 550, 1000 and 5200, circulation statistics are obtained in planes at different wall-normal heights. Intermittency of circulation in the planes of the outer flow ($y^+ \gtrsim 0.1Re_\tau$) takes the form of universal bifractality as in homogeneous and isotropic turbulence. The bifractal character simplifies to space-filling character close to the wall, with scaling exponents that are linear in the moment order, and lower than those given by the Kolmogorov paradigm. The probability density functions of circulation are long-tailed in the outer bifractal region, with evidence showing their invariance with respect to the loop aspect ratio, while those in the inner region are closely Gaussian. The unifractality near the wall implies that the circulation there is not intermittent in character.

Information

Type
JFM Rapids
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 (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited.
Copyright
© The Author(s), 2025. Published by Cambridge University Press
Figure 0

Table 1. Discretisation of DNS of Navier–Stokes equation. Cases of $Re_\tau =180$ and 550 are our current simulations, and $Re_\tau =1000$ and 5200 are simulations by Lee & Moser (2015) from Johns Hopkins Turbulence Database. Here, $N_x$, $N_y$ and $N_z$ are the number of grids in the corresponding directions. Note that $\Delta x$ and $\Delta z$ are uniform grids, while $\Delta y$ stretches in the wall-normal direction in terms of $\eta$, which is the local Kolmogorov length scale.

Figure 1

Figure 1. (a) Sketch of the computational domain for channel where $L_x$ and $L_z$ are the streamwise and spanwise sizes, respectively. (b) An illustration of the circulation around a rectangular loop with side lengths $r_x$ and $r_z$ in a wall-parallel plane, top-left for $y^+=Re_\tau$ and bottom-right for $y^+=5$ (superscript ‘+’ denotes normalisation in wall units). The panels show contours of the normalised wall-normal vorticity $\omega _y\boldsymbol {e_y}$ in the domain of 2000$\eta$ in length and 1000$\eta$ in width using the DNS data at $Re_\tau =5200$. Here, $\rm \omega_{\textit{rms}}$ is the root mean square of $\omega_y$. Spot-like structures appear in the centre plane while streak-like structures are visible near the wall.

Figure 2

Figure 2. (a) Mean velocity profile and (b) mean shear distribution for $Re_\tau =5200$, with dots highlighting the selected heights. The discrete points marked on the profiles correspond to planes on which circulation statistics are presented. Their colours carry over to figure 3. (c–f) Second-order circulation moments (or the variance of circulation) as a function of the loop area $A/\eta ^2$, with line colours corresponding to the selected heights in (a) and (b). Inset shows the corresponding local exponents, with dash-dotted line indicating the scaling in the IR for each case.

Figure 3

Figure 3. Determination of power-law scaling exponents by fitting circulation moments within the IR at (a$y^+=Re_\tau$ and (b) $y^+=5$. Symbols are simulation data at $Re_\tau =5200$, and solid lines (colours corresponding to the positions depicted in figures 2a, b) are the fitting results.

Figure 4

Figure 4. The IR scaling exponents $\zeta _p$ as a function of moment order $p$ at different heights for $Re_\tau =5200$. The long-dashed line is the K41 prediction, $\zeta _p=4p/3$. The solid line indicates the unifractal model for results above the log layer, while the short-dashed lines passing through the origin indicate unifractality below the log layer. Symbols are consistent with figures 2(a,b).

Figure 5

Figure 5. Normalised probability density function $\mathcal {P}$ of $\Gamma _A/(u^\prime _{rms}\delta )$ in (a) inner region (with dashed lines representing the Gaussian distribution) and (b) outer region, both with a loop size of $A/\delta ^2=0.0036$ in the IRs. (c) Circulation flatness $F(A)$ at different heights as a function of loop size for $Re_\tau =5200$; dashed line indicates the Gaussian flatness of 3. The grey shading highlights the iR $A/\delta ^2\sim 10^{-3}$ to $10^{-1}$. Symbols and line colours are consistent with figures 2(a)–2(b).

Figure 6

Figure 6. (a) Normalised probability density function of normalised circulation around closed loops with a fixed area but varying aspect ratios. Both (a) and (b) are sampling at the channel centre plane for $Re_\tau =5200$. Solid lines correspond to loops with both sides contained within the IR; they collapse on each other. Dashed lines indicate loops with one side outside the IR, and thus depart from the collapsed curves. (b) Normalised second-order moments of circulation as a function of area. Data for loop ratio $2:1$ are represented by symbols, and for $1:1$ by a solid line. The dash-dotted line indicates the K41’s scaling $\langle \Gamma _A^2 \rangle \sim A^{4/3}$. Inset shows the relative difference for data for the two loop ratios; it is close to unity shown by the dashed line.

Figure 7

Figure 7. (a) The ESS plot of $\langle |\Gamma _A|^p\rangle ^{1/p}$ versus $\langle |\Gamma _A|^2\rangle$ at the channel centre for $Re_\tau =550$. Symbols are data, and lines are the power-law fits. The top-left inset shows the relative difference between the fits and data; the bottom-right inset shows the centre-plane circulation variance for $Re_\tau =180$, 550, 1000 and 5200 (from top to bottom), with the dash-dotted lines representing the K41’s scaling. (b) Circulation flatness at the channel centre for all $Re_\tau$ cases (symbols) compared with the Gaussian value $3$ (dashed line). (c) The ESS scaling exponents $\zeta _p/\zeta _2$ at the channel centre for all $Re_\tau$. The dashed line is K41, and the solid lines are the monofractal fits. Data of three-dimensional HIT (Iyer et al.2019), quantum turbulence (Müller et al.2021) and quasi-two-dimensional turbulence (Zhu et al.2023) are also included for comparison.