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Pairwise interaction of spherical particles aligned in high-frequency oscillatory flow

Published online by Cambridge University Press:  08 April 2024

F. Kleischmann*
Affiliation:
Leichtweiß-Institute for Hydraulic Engineering and Water Resources, Technische Universität Braunschweig, 38106 Braunschweig, Germany Institute of Urban and Industrial Water Management, Technische Universität Dresden, 01062 Dresden, Germany Department of Mechanical Engineering, UC Santa Barbara, Santa Barbara, CA 93106, USA
P. Luzzatto-Fegiz
Affiliation:
Department of Mechanical Engineering, UC Santa Barbara, Santa Barbara, CA 93106, USA
E. Meiburg
Affiliation:
Department of Mechanical Engineering, UC Santa Barbara, Santa Barbara, CA 93106, USA
B. Vowinckel
Affiliation:
Leichtweiß-Institute for Hydraulic Engineering and Water Resources, Technische Universität Braunschweig, 38106 Braunschweig, Germany Institute of Urban and Industrial Water Management, Technische Universität Dresden, 01062 Dresden, Germany
*
Email address for correspondence: fabian.kleischmann@tu-dresden.de

Abstract

We present a systematic simulation campaign to investigate the pairwise interaction of two mobile, monodisperse particles submerged in a viscous fluid and subjected to monochromatic oscillating flows. To this end, we employ the immersed boundary method to geometrically resolve the flow around the two particles in a non-inertial reference frame. We neglect gravity to focus on fluid–particle interactions associated with particle inertia and consider particles of three different density ratios aligned along the axis of oscillation. We systematically vary the initial particle distance and the frequency based on which the particles show either attractive or repulsive behaviour by approaching or moving away from each other, respectively. This behaviour is consistently confirmed for the three density ratios investigated, although particle inertia dictates the overall magnitude of the particle dynamics. Based on this, threshold conditions for the transition from attraction to repulsion are introduced that obey the same power law for all density ratios investigated. We furthermore analyse the flow patterns by suitable averaging and decomposition of the flow fields and find competing effects of the vorticity induced by the fluid–particle interactions. Based on these flow patterns, we derive a circulation-based criterion that provides a quantitative measure to categorize the different cases. It is shown that such a criterion provides a consistent measure to distinguish the attractive and repulsive arrangements.

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

Figure 1. Two-dimensional sketch of the cubic numerical domain with size $L_{x,y,z} = L = 10D_p$. Two mobile spherical particles with identical diameters $D_p$ are initially placed so that the centre of the initial particle distance $\zeta _i$ coincides with the centre of the domain. The arrangement is aligned with an initial angle $\theta _i$ with respect to the direction of oscillation. The domain oscillates with velocity $u_f$ in the $x$ direction, as indicated by the arrows.

Figure 1

Figure 2. Flow characteristics illustrated by streamlines and vorticity contours for steady streaming of two stationary and axially arranged particles in oscillatory flow. (a) The numerical results of the set-up with ${S = 0.89}$, $ Re = 0.32$ and $ Re _s = 0.0032$. (b) A simplified sketch to highlight the quadrupole structures surrounding each particle as well as the direction of the imposed oscillation by the black arrows. The vorticity colouring ranges from $-0.01$ (blue) for clockwise rotations to $0.01$ (red) for counterclockwise rotations.

Figure 2

Figure 3. Location of the midpoint between the particles relative to its initial location over time for (a) the instantaneous location $\Delta x_c$ and (b) the moving average $\langle \Delta x_c\rangle$ with an averaging window equal to the oscillation period $T$.

Figure 3

Figure 4. Evolution of instantaneous $\zeta$ over $100$ oscillation periods for $\rho _s = 4.68$, $\zeta _i = 0.25$ and a variety of $S$.

Figure 4

Figure 5. Plots of $\zeta _{100}$ as a function of $S$ with $\rho _s=4.68$ for (a) $\zeta _i = 0.25$ and (b) $\zeta _i = 3.00$. The sketches in the insets illustrate the initial configuration and the direction of oscillation (black arrows). Note the difference in scale by one order of magnitude for the $y$ axes of the two panels. Condition $\zeta _{100} < 0$ represents attraction and $\zeta _{100} > 0$ repulsion.

Figure 5

Figure 6. Plot of $\zeta _{100}$ as a function of $\zeta _i$ with $\rho _s=4.68$ and for $S = 2.09$.

Figure 6

Figure 7. Amplitude ratio $\sigma = A_{2p}(S,\zeta _i) / A_{1p}(S)$ between the amplitudes of the two-particle set-ups $A_{2p}(S,\zeta _i)$ and the respective individual-particle set-ups $A_{1p}(S)$ for $\rho _s = 4.68$ and as a function of $S$ and $\zeta _i$.

Figure 7

Figure 8. Evolution of (a) $\theta$ and (b) $\zeta$ over $100$ oscillation periods for $\rho _s = 4.68$, $\zeta _i = 0.25$ and $S = 0.35$.

Figure 8

Figure 9. Evolution of (a) $\theta$ and (b) $\zeta$ over $100$ oscillation periods for $\rho _s = 4.68$, $\zeta _i = 0.25$ and $S = 2.09$. Note the difference in scale for the $y$ axis in (b) compared with figure 8.

Figure 9

Figure 10. Regime maps of the fluid–particle interactions as a function of $S$ and $\zeta _i$ in log–log plots for different particle density ratios: (a) $\rho _s = 4.68$, (b) $1.78$ and (c) $0.47$. Right-pointing triangles ($\vartriangleright$) indicate $\zeta _{100} < 0$ and left-pointing triangles ($\vartriangleleft$) $\zeta _{100} > 0$. The colouring of the symbols is according to the classification stated in (3.1), where $\blacktriangleright$ (red) represents attraction, $\blacktriangleleft$ (blue) repulsion and open symbols ($\vartriangleleft \vartriangleright$) transition. The dashed line has been determined by best fit of a power law and marks the threshold condition for which the particle interaction transitions from attractive to repulsive.

Figure 10

Figure 11. Streamlines and vorticity contours of the steady streaming in (a,c) $xy$ plane and (b,d) $zy$ plane. (a,b) An attractive case with $S = 0.35$ and (c,d) a repulsive behaviour with $S = 1.05$. Both are arrangements with $\zeta _i = 0.75$ and $\rho _s = 4.68$. The black circles in the middle of the $zy$ planes indicate the particle positions, which are arranged in line along the $x$ axis. The outer circle in (b) is a stagnation line of the flow field and results from the averaging process of computing the steady streaming. Colour scheme as in figure 2.

Figure 11

Figure 12. Streamlines and vorticity contours of the symmetric (a,c) and antisymmetric (b,d) components for $\zeta _i = 0.75$ and $\rho _s = 4.68$. (a,b) Parameter $S = 0.35$ resulting in attraction and (c,d) $S = 1.05$ leading to repulsion. The total steady streaming used for decomposition is given in figure 11(a,c). Colour scheme as in figure 2.

Figure 12

Figure 13. Streamlines and vorticity contours of the total steady streaming (a,b), and its symmetric (c,d) and antisymmetric (ef) components for a set-up with $\zeta _i = 0.75$ and $S = 0.35$. Here, $\rho _s = 1.78$ (a,c,e) and ${\rho _s = 0.47}$ (b,df). Colour scheme as in figure 2.

Figure 13

Figure 14. Streamlines and vorticity contours of the antisymmetric part of the flow field for a constant $\zeta _i = 0.50$ and varying $S$: (a) $S = 0.35$ with attractive behaviour, (b) $S = 0.70$ (transition) and (c) $S = 1.05$ (repulsion). Colour scheme as in figure 2.

Figure 14

Figure 15. Streamlines and vorticity contours of the antisymmetric part of the fluid field for constant $S = 0.94$ and varying $\zeta _i$: (a) $\zeta _i = 0.10$ resulting in attraction, (b) $\zeta _i = 0.25$ leading to transition and (c) $\zeta _i = 0.50$ causing repulsion. Colour scheme as in figure 2. The dashed lines in (c) indicate the symmetry lines used for the division into four quadrants to compute $\omega _{z,\alpha }$ (4.3).

Figure 15

Figure 16. Circulation ratio $\phi _\varGamma = \varGamma _{attr} / \varGamma _{rep}$ in dependence of $\zeta _i$ and $S$. The colour scheme represents the initial particle distances: $\vartriangleleft \vartriangleright$ red, $\zeta _i = 0.10$; $\vartriangleleft \vartriangleright$ green, $\zeta _i = 0.25$; $\vartriangleleft \vartriangleright$ dark blue, $\zeta _i = 0.50$; $\vartriangleleft \vartriangleright$ light blue, $\zeta _i = 0.75$; $\vartriangleleft \vartriangleright$ pink, $\zeta _i = 1.00$; $\vartriangleleft \vartriangleright$ brown, $\zeta _i = 1.50$; $\vartriangleleft \vartriangleright$ violet, $\zeta _i = 2.00$; $\vartriangleleft \vartriangleright$ sky blue, $\zeta _i = 3.00$. Right-pointing triangles ($\vartriangleright$) indicate $\zeta _{100} < 0$ and left-pointing triangles ($\vartriangleleft$) $\zeta _{100} > 0$. According to the classification stated in (3.1), filled symbols represent either attraction or repulsion depending on the orientation of the symbol, and open symbols indicate transition. Density $\rho _s = 4.68$ (a), $1.78$ (b) and $0.47$ (c).

Figure 16

Figure 17. Comparison of the numerical simulation results of the amplitude ratio $\eta$ for various dimensionless frequencies $S$ with the analytical predictions and experimental results of L'Espérance et al. (2005) for a constant amplitude $A_f = 0.1$ and three different density ratios $\rho _s = 0.47$, $1.78$ and $4.68$.

Figure 17

Figure 18. Flow characteristics illustrated by streamlines of the steady streaming of a single particle oscillating horizontally (black arrows) in a fluid at rest. (a) The numerical results of the set-up with $S = 9.33$, ${Re = 16.79}$ and $ Re _s = 0.84$. (b) A simplified sketch of a close-up to highlight the flow characteristics as well as the stagnation point indicated by the cross.

Figure 18

Figure 19. Logarithmic plot of the comparison of $\delta _{SP}$ for various $S$ between the numerical simulations and experimental and numerical data of Kotas et al. (2007) and Klotsa (2009), respectively. The solid and dashed lines represent the respective best fits.