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Direct numerical simulation of drag reduction in rotating pipe flow up to $\boldsymbol{Re_\tau \approx 3000}$

Published online by Cambridge University Press:  02 October 2024

Maochao Xiao
Affiliation:
Dipartimento di Ingegneria Meccanica e Aerospaziale, Sapienza Università di Roma, Via Eudossiana 18, 00184 Roma, Italy
Alessandro Ceci
Affiliation:
Dipartimento di Ingegneria Meccanica e Aerospaziale, Sapienza Università di Roma, Via Eudossiana 18, 00184 Roma, Italy
Paolo Orlandi
Affiliation:
Dipartimento di Ingegneria Meccanica e Aerospaziale, Sapienza Università di Roma, Via Eudossiana 18, 00184 Roma, Italy
Sergio Pirozzoli*
Affiliation:
Dipartimento di Ingegneria Meccanica e Aerospaziale, Sapienza Università di Roma, Via Eudossiana 18, 00184 Roma, Italy
*
†Email address for correspondence: sergio.pirozzoli@uniroma1.it

Abstract

Direct numerical simulation (DNS) of rotating pipe flows up to $Re_\tau \approx 3000$ is carried out to investigate drag reduction effects associated with axial rotation, extending previous studies carried out at a modest Reynolds number (Orlandi & Fatica, J. Fluid Mech., vol. 343, 1997, pp. 43–72; Orlandi & Ebstein, Intl J. Heat Fluid Flow, vol. 21, 2000, pp. 499–505). The results show that the drag reduction, which we theoretically show to be equivalent to net power saving assuming no mechanical losses, monotonically increases as either the Reynolds number or the rotation number increases, proportionally to the inner-scaled rotational speed. Net drag reduction up to approximately $70\,\%$ is observed, while being far from flow relaminarisation. Scaling laws for the mean axial and azimuthal velocity are proposed, from which a predictive formula for the friction factor is derived. The formula can correctly represent the dependency of the friction factor on the Reynolds and rotation numbers, maintaining good accuracy for low-to-moderate rotation numbers. Examination of the turbulent structures highlights the role of rotation in widening and elongating the small-scale streaks, with subsequent suppression of sweeps and ejections. In the core part of the flow, clear weakening of large-scale turbulent motions is observed at high Reynolds numbers, with subsequent suppression of the outer-layer peak in the pre-multiplied spectra. The Fukagata–Iwamoto–Kasagi decomposition indicates that, consistent with a theoretically derived formula, the outer layer yields the largest contribution to drag reduction at increasingly high Reynolds numbers. In contrast, both the inner and the outer layers contribute to drag reduction as the rotation number increases.

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JFM Papers
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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, provided the original article is properly cited.
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© The Author(s), 2024. Published by Cambridge University Press.
Figure 0

Table 1. Flow parameters for DNS. $Re_b = 2 R u_b / \nu$ is the bulk Reynolds number; $Re_{\tau } = u_\tau R/\nu$ is the friction Reynolds number; $Re_{\tau,0}$ is the friction Reynolds number for the non-rotating case; $N = \varOmega R / u_b$ is the rotation number; $N_\theta$, $N_r$ and $N_z$ are the number of grid points along the azimuthal, radial and axial directions, respectively; $N^+=\varOmega R/u_{\tau,0}$ is the inner-scaled rotational speed; $\lambda$ is the friction factor; $DR$ is the percentage of drag reduction; and #ETT is the time-averaging interval, expressed in terms of the eddy turnover time, $R/u_\tau$. The symbol $*$ denotes DNS with pipe length $L = 30R$ and $**$ denotes DNS with doubled resolution in the radial direction. The standard uncertainty of the friction factor is estimated using a modified batch means method (Russo & Luchini 2017) and the uncertainty of drag reduction is evaluated by propagating the standard uncertainties of the friction factors.

Figure 1

Figure 1. Global flow properties: (a) friction factor as a function of $N$; (b) friction factor as a function of $Re_b$; (c) drag reduction coefficient as a function of $N$; (d) drag reduction coefficient as a function of $N^+$. In panels (a,c,d), we show data for $Re_{\tau,0}= 180$ (black), $495$ (red), $1137$ (green), $1979$ (blue) and $3020$ (pink); in panel (b), we show $N=0$ (black), $0.25$ (red), $0.5$ (green), $1.0$ (cyan), $2.0$ (blue) and $4.0$ (pink). In panel (b), the brown dashed line denotes Prandtl's friction law (Pirozzoli et al.2021) and the orange dashed line denotes the laminar friction law $\lambda = 64/Re_b$. In panels (c,d), the horizontal dashed lines denote the laminar limits of drag reduction for various Reynolds numbers. The triangle symbols denote DNS data at $Re_{\tau,0} \approx 180$ and $540$ (Davis et al.2019), and the circles denote experiments at $Re_{\tau,0} \approx 240$ and $570$ (Kikuyama et al.1983).

Figure 2

Figure 2. (a) Inner-scaled mean axial velocity profiles and (b) corresponding logarithmic diagnostic functions. The colour codes correspond to the same values of the rotation number: $N=0$ (black); $N=0.25$ (red); $N=0.5$ (green); $N=1$ (cyan); $N=2$ (blue) and $N=4$ (pink). The line patterns correspond to the same values of the nominal Reynolds number: $Re_{\tau,0}=495$ (dash-dotted); $Re_{\tau,0}=1137$ (dotted); $Re_{\tau,0}=1979$ (dashed) and $Re_{\tau,0}=3020$ (solid). The dashed black lines in panel (a) denote the expected logarithmic distribution given in (3.3), and in panel (b), the inverse of the Kármán constant ($1/\kappa$).

Figure 3

Figure 3. Mean axial velocity defect profiles ($U_{CL}$ is the pipe centreline velocity), normalised (a) by the friction velocity, $u_{\tau }$, and (b) by the pipe rotational velocity, $\varOmega R$. The colour codes correspond to the same values of rotation number: $N=0$ (black); $N=0.25$ (red); $N=0.5$ (green); $N=1$ (cyan); $N=2$ (green) and $N=4$ (pink). The line patterns correspond to the same values of the nominal Reynolds number: $Re_{\tau,0}=495$ (dash-dotted); $Re_{\tau,0}=1137$ (dotted); $Re_{\tau,0}=1979$ (dashed) and $Re_{\tau,0}=3020$ (solid). The solid black lines in panel (b) indicate the power-law fitting function (3.4), with coefficients given in (3.5a,b).

Figure 4

Figure 4. (a,b) Inner-scaled bulk velocity and (c,d) friction factor, as a function of the (a,c) friction Reynolds number and (b,d) bulk Reynolds number. The colour codes correspond to the same values of rotation number: $N=0$ (black); $N=0.25$ (red); $N=0.5$ (green); $N=1$ (cyan); $N=2$ (blue) and $N=4$ (pink). Symbols denote the DNS data, and lines the corresponding predictions of (3.9). The solid black line denotes the predictions of Prandtl's friction law for a non-rotating pipe (Pirozzoli et al.2021).

Figure 5

Figure 5. Radial profiles of mean azimuthal velocity in (a) linear and (b) logarithmic scale. The colour codes correspond to the same values of rotation number: $N=0.25$ (red); $1.0$ (cyan); $2.0$ (blue) and $4.0$ (pink). The line patterns correspond to the same values of the nominal Reynolds number: $Re_{\tau,0}=495$ (dash-dotted); $Re_{\tau,0}=1137$ (dotted); $Re_{\tau,0}=1979$ (dashed) and $Re_{\tau,0}=3020$ (solid). The solid black lines denote (3.12), with the coefficient given in (3.13). The black dashed lines correspond to the case of solid body rotation.

Figure 6

Figure 6. Instantaneous fields of axial velocity on a near-wall cylindrical shell and cross-stream plane. The cylindrical shell is located at a wall distance $y^+ \approx 15$. The colour scale is from blue (low speed) to red (high speed). Rotation numbers $N = 0, 0.5$ and $2.0$ are reported in panels (a,d), (b,e) and (c,f), respectively, for (a–c) $Re_{\tau,0} = 495$ and (d–f) $Re_{\tau,0} = 3020$. The arrows indicate the direction of rotation.

Figure 7

Figure 7. Distributions of: (a) turbulence kinetic energy for $Re_{\tau,0}=495$; (b) turbulence kinetic energy for $Re_{\tau,0}=3020$; (c) individual velocity variances for $Re_{\tau,0}=3020$. In panel (c), lines correspond to: $\langle u_\theta ^2 \rangle$ (solid); $\langle u_r^2 \rangle$ (dashed) and $\langle u_z^2\rangle$ (dash-dot). Colour codes: $N = 0$ (black); $0.25$ (red); $0.5$ (green); $1.0$ (cyan) and $2.0$ (blue).

Figure 8

Figure 8. Pre-multiplied azimuthal energy spectra of axial velocity $( \kappa _\theta E_{uu})^+$ for (a,d) $N=0$, (b,e) $N=0.5$, (c,f) $N=2.0$, at (a–c) $Re_{\tau,0} = 495$, (d–f) $Re_{\tau,0} = 3020$. The solid lines denote the trend $y = 0.14 \lambda _\theta$, and the dashed lines denote the trend $\lambda _\theta /R = 2.35(y/R)^{0.52}$ in panel (c), and $\lambda _\theta /R = 2.20(y/R)^{0.72}$ in panel (f). The crosses denote spectral peaks.

Figure 9

Figure 9. (a) Turbulent shear stress for $N=0$ (dashed lines) and $N=2$ (solid lines); (b) local contributions to turbulent friction (as from (3.15)) for $N=0$ (dashed lines) and $N=2$ (solid lines); (c) turbulent contribution to friction as a function of $Re_\tau$; (d) fraction of drag reduction due to turbulence as a function of $Re_b$. In panels (a,b), $Re_{\tau,0} = 180$ (black), $495$ (red), $1137$ (green), $1979$ (blue) and $3020$ (pink). In panels (c,d), $N=0$ (black), $0.25$ (red), $0.5$ (green), $1.0$ (cyan), $2.0$ (blue) and $4.0$ (pink). In panel (c), the dash-dotted line indicates the prediction of (3.17).

Figure 10

Figure 10. Radial profiles for $Re_{\tau,0} = 1137$ and $N=4.0$: (a) axial velocity and (b) azimuthal velocity. Pink, $L = 15R$ and $N_r=164$; blue, $L = 30R$ and $N_r=164$; green, $L=15R$ and $N_r=328$.

Figure 11

Figure 11. Time history of axial pressure gradient for $Re_{\tau,0} = 495$. Black, $N = 0$ and pink, $N = 4.0$.

Supplementary material: File

Xiao et al. supplementary movie

Animations of axial velocity on a near-wall cylindrical shell and cross-stream plane at various rotation numbers and Reynolds numbers. The color scale is from blue (low speed) to red (high speed).
Download Xiao et al. supplementary movie(File)
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