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Settling behaviour of thin curved particles in quiescent fluid and turbulence

July 2021
Journal of Fluid Mechanics 922:30

DOI:10.1017/jfm.2021.520

Project: Multiphase flows

Authors:

Luis Blay

Bardehle Pagenberg

Sander Huisman

University of Twente

Show all 5 authorsHide

The motion of thin curved falling particles is ubiquitous in both nature and industry but is not yet widely examined. Here, we describe an experimental study on the dynamics of thin cylindrical shells resembling broken bottle fragments settling through quiescent fluid and homogeneous anisotropic turbulence. The particles have Archimedes numbers based on the mean descent velocity 0.75 × 10 4 Ar 2.75 × 10 4. Turbulence reaching a Reynolds number of Re λ ≈ 100 is generated in a water tank using random jet arrays mounted in a coplanar configuration. After the flow becomes statistically stationary, a particle is released and its three-dimensional motion is recorded using two orthogonally positioned high-speed cameras. We propose a simple pendulum model that accurately captures the velocity fluctuations of the particles in still fluid and find that differences in the falling style might be explained by a closer alignment between the particle's pitch angle and its velocity vector. By comparing the trajectories under background turbulence with the quiescent fluid cases, we measure a decrease in the mean descent velocity in turbulence for the conditions tested. We also study the secondary motion of the particles and identify descent events that are unique to turbulence such as 'long gliding' and 'rapid rotation' events. Lastly, we show an increase in the radial dispersion of the particles under background turbulence and correlate the time scale of descent events with the local settling velocity.

(a) Bottle-fragment-like particle considered in this study. The dash-dot line is the axis of revolution used to obtain the dimensionless moment of inertia I * , whereas α and β are the pitch and roll angles, respectively. (b) Front view and (c) top view of particle with β = 0. (d) Drawings (to scale) of the four tested particles whose dimensions are listed in table 1. (e) Tank and release mechanism employed. Pumps and wire meshes are installed on both sides for symmetry, though only those on the right are shown to reduce clutter. The distance between the pumps is 165 cm. The tank rests on a steel frame with a rectangular window at the bottom to allow optical access. The coordinate system is shown on the top left.

…

Reconstructed three-dimensional trajectories of particle no. 2 (θ = 73 • , D = 39 mm) in quiescent fluid.

…

Model pendulum trajectory (grey line) overlaid on the experimental data of particle no. 2.

…

Fitting parameter C as a function of Ar. In the context of underwater pendulums, C is related to the added-mass coefficient m * a . Inset shows m * a versus Ar.

…

The PIV measurements of the flow in the turbulence box. The time-averaged (a) r.m.s. flow velocity fluctuation field and (b) mean flow field at the middle of the tank. The subscripts (x, z) denote the corresponding velocity components.

…

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Content uploaded by Luis Blay

Content may be subject to copyright.

J. Fluid Mech. (2021), vol.922, A30, doi:10.1017/jfm.2021.520

Settling behaviour of thin curved particles in

quiescent ﬂuid and turbulence

Timothy T.K. Chan1,2, Luis Blay Esteban2, Sander G. Huisman1,

John S. Shrimpton2and Bharathram Ganapathisubramani2,†

1Physics of Fluids Group, Max Planck Center Twente for Complex Fluid Dynamics, Faculty of Science

and Technology, MESA+ Research Institute, and J. M. Burgers Centre for Fluid Dynamics, University of

Twente, P.O. Box 217, 7500 AE Enschede, The Netherlands

2Aerodynamics and Flight Mechanics Group, Faculty of Engineering and Physical Sciences, University of

Southampton, Southampton SO17 1BJ, UK

(Received 22 December 2020; revised 21 April 2021; accepted 3 June 2021)

The motion of thin curved falling particles is ubiquitous in both nature and industry but

is not yet widely examined. Here, we describe an experimental study on the dynamics

of thin cylindrical shells resembling broken bottle fragments settling through quiescent

ﬂuid and homogeneous anisotropic turbulence. The particles have Archimedes numbers

based on the mean descent velocity 0.75 ×104Ar 2.75 ×104. Turbulence reaching

a Reynolds number of Reλ≈100 is generated in a water tank using random jet arrays

mounted in a coplanar conﬁguration. After the ﬂow becomes statistically stationary, a

particle is released and its three-dimensional motion is recorded using two orthogonally

positioned high-speed cameras. We propose a simple pendulum model that accurately

captures the velocity ﬂuctuations of the particles in still ﬂuid and ﬁnd that differences

in the falling style might be explained by a closer alignment between the particle’s pitch

angle and its velocity vector. By comparing the trajectories under background turbulence

with the quiescent ﬂuid cases, we measure a decrease in the mean descent velocity in

turbulence for the conditions tested. We also study the secondary motion of the particles

and identify descent events that are unique to turbulence such as ‘long gliding’ and ‘rapid

rotation’ events. Lastly, we show an increase in the radial dispersion of the particles under

background turbulence and correlate the time scale of descent events with the local settling

velocity.

Key words: particle/ﬂuid ﬂow

†Email address for correspondence: g.bharath@soton.ac.uk

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 in any medium,

provided the original work is properly cited. 922 A30-1

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T.T.K. Chan and others

1. Introduction

Solid particles settling through ﬂuids are all around us. Some of these processes occur in

natural environments, such as falling leaves, while others happen in engineering processes

or due to human activities. In fact, the latter often have detrimental effects on nature such as

water and air pollution. Differences in the inertial characteristics of solid materials are also

used in engineering applications to separate residues and reduce the ‘human footprint’ on

the environment. Standard and uniﬂow cyclones are extensively used to remove particulate

matter (up to 10 µm) from the carrier ﬂuid; e.g. remove sand and black powder in the

natural gas industry (Bahadori 2014), to improve clinker burning processes (Wasilewski

& Singh Brar 2017) and in solid–solid separation in the mineral processing industry

(Tripathy et al. 2015). Hydrodynamic separators based on similar physical principles are

also employed in the recycling industry (Esteban et al. 2016), where they classify materials

based on the inertial properties of the materials through interaction with turbulence. In

this type of device, comingled waste is introduced into a container where background

turbulence prevents plastics from sinking. In contrast, glass particles which struggle to

follow vortical structures drop to the bottom of the tank, where a strong mean ﬂow carries

them to the next stage for further treatment. In these facilities, different turbulent regimes

are found at various depths of the separator. Plastic-glass separation predominantly occurs

in the middle region of the tank, where particle concentration is low and the turbulence is

not modiﬁed by the solids. However, to improve the separation efﬁciency of these devices,

a thorough understanding of settling characteristics of irregular particles in turbulence is

required.

Much research has been conducted on axisymmetric solids settling in quiescent ﬂuid

(see Ern et al. (2012) for a detailed review), and it is much accepted that particle dynamics

are determined by three dimensionless numbers. These are: (1) the Reynolds number Re =

VzD/ν,whereVzstands for the particle mean descent velocity, Dfor its characteristic

length scale and νfor the ﬂuid kinematic viscosity; (2) the dimensionless rotational inertia

I∗, deﬁned as the ratio of the moment of inertia of the particle over that of its solid of

revolution with the same density as the ﬂuid; and (3) the particle aspect ratio D/h,where

hdenotes the object’s thickness.

The most widely studied non-spherical particles are planar disks and rectangular plates

(Stringham, Simons & Guy 1969;Smith1971; Field et al. 1997; Mahadevan, Ryu &

Samuel 1999; Zhong, Chen & Lee 2011;Ernet al. 2012; Auguste, Magnaudet & Fabre

2013; Chrust, Bouchet & Dušek 2013;Leeet al. 2013; Zhong et al. 2013; Heisinger,

Newton & Kanso 2014), whose falling styles share the same dominant features. Still,

speciﬁc dynamics occur when the particle perimeter contains sharp edges (Esteban,

Shrimpton & Ganapathisubramani 2018,2019b,c). The four dominant regimes in both

disks and rectangular plates are ‘steady fall’, ‘zigzag motion’, ‘chaotic motion’ and

‘tumbling motion’ – these are shown in the Re–I∗phase space in ﬁgure 1.When

Re is sufﬁciently small, a particle descends following a ‘steady fall’ independent of

its dimensionless moment of inertia. Under this mode, the solid falls vertically with

oscillation amplitudes much smaller than its characteristic length scale. As Re increases,

the swaying motion grows and the particle transits into a ‘zigzag motion’ caused by vortex

shedding. Various types of zigzag motions have been identiﬁed, ranging from ‘planar

zigzag’ to more three-dimensional ones such as ‘spiralling’ and ‘hula-hoop’ motion

(Zhong et al. 2011; Auguste et al. 2013). From this point, as I∗rises, the pitching motion

of the particle overcomes the ﬂuid torque damping it and the descent enters a ‘chaotic

regime’ where the particle ﬂips over intermittently while exhibiting a zigzag motion. As

I∗increases further, tumbling becomes more persistent and eventually continuous in the

922 A30-2

Settling behaviour of thin curved particles

10–2

10–4

104105

Plates

Disks

Zigzag (disks)

Chaotic (disks)

Tumbling (disks)

Tumbling

(plates)

Zigzag

(plates)

Steady

falling

101102103

102

100

Figure 1. The Re–I∗phase space explored in the current study. The regime boundaries are taken from Field

et al. (1997)andSmith(1971). Markers denote the particles considered, whose properties are listed in table 1.

‘tumbling motion’ regime. Markers in ﬁgure 1 locate the solids investigated in this study

in the Re–I∗phase space originally determined for disks and plates (Willmarth, Hawk &

Harvey 1964; Stringham et al. 1969;Smith1971; Field et al. 1997). Details on deﬁning the

dimensionless numbers of these particles are included in § 2.

Regarding three-dimensional particles with curvature, spheroids, spheres and cylinders

are the canonical geometries that have been investigated in more detail. Oblate spheroids

have the same principal falling styles as disks. However, as they become more spherical,

zigzag and chaotic descents vanish. Yet, when they are close to spheres, chaotic motion

returns (Zhou, Chrust & Dušek 2017). The dynamics of spheres is also very complex,

with steady fall, oblique descent, horizontal oscillations due to vortex shedding,as well as

helical and chaotic motions all being observed (Jenny, Dušek & Bouchet 2004; Veldhuis

& Biesheuvel 2007; Horowitz & Williamson 2010a; Zhou & Dušek 2015; Ardekani

et al. 2016). Fibre-like shapes such as prolate spheroids fall helically with no visible

zigzag motion (Ardekani et al. 2016). Still, as the aspect ratio increases and the particles

become long cylinders, they settle rectilinearly or with oscillations along its axial direction

(Horowitz & Williamson 2006,2010b; Toupoint, Ern & Roig 2019). We refer the reader

to the comprehensive review by Voth & Soldati (2017) for the orientation of ﬁbre-like

particles under different ﬂow conditions.

Despite these studies, there has been little research on the kinematics of thin curved

particles settling in quiescent ﬂuid or under background turbulence. Nonetheless, this

represents an interesting area of research not only for its fundamental signiﬁcance but

also for its industrial relevance.

The literature concerning solids settling or rising in turbulence is far sparser due to the

relative complexity of turbulence generation in a controlled environment. Studies generally

focused on two issues: (1) the settling styles of individual particles and (2) how turbulence

modiﬁes the mean descent velocities. Note that research on the alignment or rotation of

nearly buoyant solids with the carrier ﬂow are not included.

Experiments generally focused on large particles so that their characteristic length

scale lies within the range of turbulent inertial scales where solid–turbulence interactions

are richer. Rising spheres in turbulence with a downward mean ﬂow perform zigzag

922 A30-3

T.T.K. Chan and others

motion or tumbling motion with the transition triggered by changes in I∗(Mathai et al.

2018). Disks which undergo planar zigzag motion in quiescent ﬂuid settle differently

in statistically stationary homogeneous anisotropic turbulence (Esteban, Shrimpton &

Ganapathisubramani 2020). The dominant features of the planar zigzag mode in quiescent

ﬂuid are still observed. However, these are sometimes replaced by fast descents, tumbling

events, long gliding sections and hovering motions, among others. The variety of descent

scenarios demonstrate the complexity of the particle–turbulence interactions that occur

during settling.

Despite the consensus that turbulence with zero mean ﬂow changes the average settling

velocity of spherical and non-spherical particles, a full understanding of this phenomenon

has yet to be established. Four mechanisms that modify settling have been proposed

to date: the ‘preferential sweeping effect’ (Maxey & Corrsin 1986; Maxey 1987;Tom

&Bragg2019), nonlinear drag due to ﬂuid acceleration (Ho 1964), ‘loitering effect’

(Nielsen 1993)and vortex entrainment (Nielsen 1984,1992). Preferential sweeping effect

refers to the situation where particles are accelerated by the descending side of vortices

as they spiral outwards from the core, whereas loitering effect simply means they stay

relatively longer in upward ﬂows. These four processes affect the local descend velocity

Vzdifferently, with the ﬁrst increasing it and the others reducing it. In this framework,

the settling rate modiﬁcation depends on the relative importance of the competing

mechanisms.

The situation is further complicated as these effects may not be easily delineated, and

opposite results regarding the descent speed have been reported. For droplets in isotropic

turbulence, settling is enhanced when the ratio of the particle’s characteristic gravitational

velocity to the root mean square (r.m.s.) ﬂow velocity ﬂuctuations is smaller than unity

and hindered otherwise (Good et al. 2014). Nonlinear drag has been proven to be vital for

attenuating the descent in that case. On the other hand, simulations of ﬁnite rigid spheres

in Fornari, Picano & Brandt (2016a) found slower settling velocities in turbulence for all

the tested ratios of the mean descent velocity in quiescent ﬂuid to the r.m.s. ﬂow velocity

ﬂuctuations (Vq/u

rms). However, the reduction in the mean descent velocity is greater

when Vq/u

rms <1(Fornariet al. 2016b). There, the authors attributed hindered settling

to unsteady wake forces in addition to severe nonlinear drag due to horizontal oscillations.

Recently, Tom & Bragg (2019) argued in the context of preferential sweeping that the

parameter demarcating enhanced and hindered settling should account for the multiscale

nature of particle–turbulence interactions. It is possible that the apparent contradictions

can be reconciled with scale-dependent quantities, which have been employed to model

pair statistics in turbulence (Bec et al. 2008).

The above results are restricted to spheres in turbulence. Non-spherical solids with ﬁnite

size and particle inertia add more complexity to the problem. Nearly neutrally buoyant

cylinders of the order of the Taylor microscale show small slip velocities in isotropic

turbulence (Byron et al. 2019), which may suggest nonlinear drag is not so important.

Similarly, particles describing falling styles that reﬂect strong interactions with the media,

where particle orientation plays a crucial role, also show an inconsistent behaviour with

the velocity ratio proposed for small spherical particles. More speciﬁcally, disks falling

in anisotropic turbulence where Vq/u

rms >1 settle more rapidly than in quiescent ﬂuid

(Esteban et al. 2020). Focusing on the frequency content of the trajectories, Esteban et al.

(2020) found that as turbulence intensity increases, the dominant frequency of the particles

reduces, and this leads to enhanced settling. However, as different types of motions may

occur in a single trajectory, the relation between the dominant frequency and the descent

styles is not entirely clear.

922 A30-4

Settling behaviour of thin curved particles

Particle no. Symbol R(mm) θ(◦)D(mm) I∗

119 29 22 5.62

217 73 39 0.36

321 82 48 0.20

419 115 51 0.09

Table 1. Dimensions of the particles dropped. Here Ris roughly constant at 19 mm while θand Dare varied.

The uncertainty is captured by the number of digits reported.

Given these contrasting results, it is obvious that a better understanding on how

turbulence affects settling particles is needed, especially for complex geometries like

non-spherical particles with curvature.

We therefore study the kinematics of freely falling curved particles resembling bottle

fragments. This paper is organised as follows. In § 2, we present the experimental details

of the quiescent ﬂuid cases, discuss the results and propose a simple model for the motions

observed. Next, we show the effects of background turbulence on the settling kinematics

of the curved particles and discuss the results obtained in § 3. Last, this paper concludes

in § 4with the main experimental ﬁndings and directions for future research.

2. Settling in quiescent ﬂuid

2.1. Methods

To analyse the settling behaviour of thin curved objects, we drop bottle-fragment-like

particles in a tank ﬁlled with tap water at room temperature (17◦C).

Figure 2(a) shows the geometry used to model a broken cylindrical bottle. The particle

has a parallelogramic projection and one non-zero principal curvature oriented along one

of the diagonals of the parallelogram. Hence it is completely deﬁned by the radius of

curvature of the original cylinder R, the subtended angle θ, the diagonal length Dand

the thickness h. The values of these parameters are selected to mimic the dimensions of

fragments processed in recycling plants (Esteban et al. 2016). To delineate the effect of the

different variables, Ris kept largely constant at approximately 19 mm and θ(thus D)is

varied between 29◦and 115◦. The thickness also remains the same for all cases at h=1

mm, resulting in aspect ratios D/h=22 to 51. It has been shown that the kinematics of

freely falling disks at low Re may differ even for very large aspect ratios near the ‘steady

fall–zigzag motion’ transition (Auguste et al. 2013). However, the Re of the particles

concerned are far from this boundary and small differences in the aspect ratio have little

effect on their kinematics. Furthermore, thinner particles are not sufﬁciently rigid to

withstand ﬂow perturbations without deformation. We 3D-print all particles (Formlabs

Form 2 printer) using a glass-reinforced rigid resin which results in a material with a

ﬂexural modulus E≈3.7 GPa. A print resolution of 0.05 mm is used and the objects are

wet sanded with P800 sandpaper for a smooth ﬁnish. Black spray paint, which amounts

to less than 5 % of the particle mass, is applied to aid object detection. Table 1 shows

the particle dimensions determined post-production. The density ratios are also measured

and found to be nearly constant across all the cases, with ρ∗=ρp/ρf=1.70 ±0.05. For

the particle dimensionless moment of inertia, I∗=I/I0,whereIis the object’s moment of

inertia and I0is the reference moment of inertia. Their precise deﬁnitions will be discussed

below.

922 A30-5

T.T.K. Chan and others

(e)(a)(b)

(c)

Axis

rotation

(d)

Axis

rotation

45°

Wire mesh

Pumps

Cameras

1 m

2 m

0.85 m

1 m × 0.9 m

Mirror

To syringe

3 cm

Figure 2. (a) Bottle-fragment-like particle considered in this study. The dash–dot line is the axis of revolution

used to obtain the dimensionless moment of inertia I∗, whereas αand βare the pitch and roll angles,

respectively. (b) Front view and (c) top view of particle with β=0. (d)Drawings (to scale) of the four tested

particles whose dimensions are listed in table 1.(e) Tank and release mechanism employed. Pumps and wire

meshes are installed on both sides for symmetry, though only those on the right are shown to reduce clutter.

The distance between the pumps is 165 cm. The tank rests on a steel frame with a rectangular window at the

bottom to allow optical access. The coordinate system is shown on the top left.

Choosing a suitable I∗is challenging without employing any assumptions regarding the

particle behaviour, so past studies generally assume the particle concerned would mainly

oscillate about a predetermined axis. Disks are supposed to rotate about its diameter.

Presumably using this as an inspiration, for spheroids, Zhou et al. (2017) incorporated

the ratio between the moment of inertia about the equatorial and polar axes in I∗so the

same axis of rotation is considered in the limit of disks. For n-sided polygons, Esteban

et al. (2018) adopted an analogous axis of rotation to disks when calculating the particle

moment of inertia, but considered the perimeter of the particle relative to a circumscribed

disk to correct for the characteristic length scale in the non-dimensionalisation. To select

the appropriate Iand I0, we made an educated guess of the particle motion. Due to the

presence of a dihedral, the particle should be more stable against rotations around its

uncurved axis. We therefore expect it to rotate about the ‘axis of rotation’ indicated in

ﬁgure 2(a). Hence, in our case, Iis the object’s moment of inertia about an axis passing

through its centre of gravity and parallel to the line marked ‘axis of rotation’ in ﬁgure 2(a)

and I0is the moment of inertia of a ﬂuid-ﬁlled ellipsoid-like object generated by rotating

the arc in ﬁgure 2(b) about its vertices.

We release the particles in the glass tank shown in ﬁgure 2(e). The tank, measuring

2m×1m×0.85 m, is mounted on a steel frame with a central 1 m ×0.9 m rectangular

window at the bottom to enable optical access. In preparation for experiments in

turbulence, the tank is equipped with an 8 ×6 bilge pump array (Rule 24, 360 GPH) on

either side with a 13 mm square wire mesh 3 cm downstream of the nozzles. The pumps

are turned off for experiments in quiescent ﬂuid, and the method of turbulence generation

will be introduced later.

To hold the particle, a pressure mechanism consisting of a syringe pump connected

to a suction cup is used. First, the particle is afﬁxed at 0 pitch angle (α,seeﬁgure 2a)

to the suction cup by imposing a pressure deﬁcit. Then, by slowly pushing the plunger

of the syringe, the pressure is equalised to the atmosphere and the particle is released.

Similar to the work by Lau, Huang & Xu (2018), surface–particle interaction is minimised

922 A30-6

Settling behaviour of thin curved particles

by adjusting the position of the suction cup to at least 1.5Dbelow the water level and

particle transient kinematics are discarded prior to the data post-processing. The object’s

surface is carefully veriﬁed to be bubble-free before release. Conﬁnement effects are also

negligible as the sidewalls of the tank remained at least 4Dfrom the object. A minimum

of eight minutes separate releases to allow any residual ﬂow to dampen, and each particle

is dropped at least 25 times to reduce random error.

During each descent, the motion is recorded by two cameras operating at 60 Hz using

AF Nikkor 50 mm objectives. While the top camera (JAI GO-5000M-USB; pixel size =

5µm) captures the front view, the lower one (JAI GO-2400M-USB; pixel size =5.86 µm)

records the bottom view through a mirror inclined 45◦. The camera aperture is set so

that the contrast and the depth of ﬁeld are sufﬁciently large for the entire descent,and

the exposure times are adjusted accordingly. To ensure the three-dimensional particle

motion reconstruction is accurate, the cameras are synchronised with a 5 V external signal

(National Instruments USB-6212), aligned with respect to the tank by a vertical post and

calibrated using a square grid. For the bottom camera, the resolution at ﬁve different

heights is calculated and a linear ﬁt is used to obtain the image resolution as a function

of depth. The resolution of both cameras is ≈0.2mmpixel−1, which corresponds to a

magniﬁcation of ≈1/40.

The three-dimensional position and orientation of the particle are extracted using

MATLAB. The image processing protocol to obtain the particle’s centre of gravity is

similar to the one proposed in Esteban et al. (2020), where a background image is ﬁrst

subtracted from all frames. Then, a Gaussian ﬁlter with a standard deviation of 3 pixels

is applied and the resulting images are binarised before calculating the centres of gravity.

Doing so, the script gives us the (x,y)and zcoordinates of the object from the recordings

of the bottom and top cameras, respectively.

On the other hand, the pitch and roll angles of the particle, which are sketched in

ﬁgure 2(a), are evaluated by measuring the diagonal lengths in each frame. To calculate

them, the corners of the particle are detected ﬁrst in the binary image and then reﬁned

using the greyscale one. Finally, the position of one diagonal’s midpoint relative to the

other diagonal provides the signs of the pitch and roll angles. The high-resolution image

allows the pitch angle to be determined to 3◦. All the data have been smoothed by

Gaussian ﬁlters to reduce high-frequency noise.

In this study, we are interested in the non-transient particle kinematics. To remove the

transient motions, we ﬁrst construct the cumulative average of the instantaneous vertical

velocity Vzc. By examining this magnitude, we observe that the particle descent velocity

is stable after descending 2/3 the tank depth (26Dand 11Dfor the smallest and largest

fragments, respectively). Then, the cumulative average Vzcat each vertical location

is compared with the stabilised velocity, and the initial part of the trajectories where

the deviation is greater than ±10% discarded. This threshold is robust, since halving it

to ±5 % did not affect the results signiﬁcantly. Similarly, the last particle oscillation is

ignored to eliminate motions affected by interactions with the bottom of the tank.

2.2. Results and discussion

Figure 3 shows the three-dimensional reconstruction of all 25 trajectories recorded for

particle no. 2 in quiescent ﬂuid after transient removal. All descents show periodic motions

with a constant mean vertical velocity. However, the solid sometimes drifts horizontally in

an apparently random direction as it settles. Similar trajectories are obtained for all types

of particles tested.

922 A30-7

T.T.K. Chan and others

–2

z/D

x/D

–2 –1 0y/D

Figure 3. Reconstructed three-dimensional trajectories of particle no. 2 (θ=73◦,D=39 mm) in quiescent

ﬂuid.

Particle no. Vdrift (mm s−1)Ag/Rg˙γ(◦s−1)Iro ll (g mm2)

13.8±1.40.05 ±0.04 9.4±1.58.7×10−6

23.2±1.40.04 ±0.03 7.4±0.98.4×10−5

33.8±2.00.02 ±0.02 0.8±0.52.0×10−4

42.5±1.10.03 ±0.02 2.8±0.73.9×10−4

Table 2. The mean horizontal drift velocity Vdrift, the dimensionless gliding section amplitude Ag/Rg,the

precession rate ˙γof each particle and the moment of inertia of rotating it about an axis passing through its

centre of gravity and parallel to its uncurved diagonal Iroll.

To ensure this motion can be neglected, we obtain the velocity associated with the

horizontal drift Vdrift for all trajectories, see table 2. The velocity magnitude appears

to be insensitive to particle geometry and the horizontal drift has no obvious preferred

direction. This suggests the drift is probably not inherent to the descent behaviour and

may have originated from minute ﬂows in the tank which are difﬁcult to eliminate. This

motion is unlikely to have been caused by the release mechanism since the ﬂow induced by

capillary waves decays exponentially in space. Experiments involving heavy cylinders in

Toupoint et al. (2019) also found similar behaviour and the authors argued this was related

to large-scale ﬂuid motions inside the tank. For the subsequent analysis, the trajectories

are dedrifted assuming Vdrift to be the average drift velocity over a square window centred

about the current location and capturing one full period.

We then plot the settling behaviour of particle no. 2 in quiescent ﬂuid in ﬁgure 4 (see also

the supplementary movies available at https://doi.org/10.1017/jfm.2021.520). As the object

falls, it oscillates periodically in the xy-plane with a constant amplitude (ﬁgure 4a–c).

At the beginning of each oscillation, the particle carries no horizontal velocity Vhand

shows a highly negative pitch angle α(pointing downwards). As the particle is not in

equilibrium, it accelerates both downwards and horizontally along a direction inside its

symmetry plane containing the uncurved diagonal until it reaches its maximum velocity,

which occurs roughly at the middle of each swing. The particle then decelerates as

922 A30-8

Settling behaviour of thin curved particles

z/D

z/Dα (°) rh /D

y/D

(a)

(b)

(c)

(d)(e)

–1

–2

–1

–2 1

–1 2 3–3 –2 1

–1 2 3–3

–1

0123456

–50

t (s)

x/D

Vy /Vz

Vx /VzVh /Vz

Vz /Vz

y/D

0.5 –0.5

0.5

–0.5

0.5

–0.5

0.5 0–0.5

x/D

Figure 4. Descent of particle no. 2 (θ=73◦,D=39 mm) after removing transient motions and dedrifting.

(a) Three-dimensional and (b) top view of the trajectory reconstruction. (c)(Fromtoptobottom)Theradial

displacement along the direction of motion rh, the depth zand the pitch angle αplotted against time t.No

rolling motions are observed. (d) Velocity in the y-direction Vyplotted against that in the x-direction Vx.(e)

Instantaneous vertical velocity Vzagainst the horizontal velocity Vh=±(V2

x+V2

y)1/2whose sign switches

every swing. All velocities and positions are normalised with the mean descent velocity Vzand diagonal

length Dof the particle, respectively.

αincreases, drawing an arc-like trajectory. This process repeats itself in the opposite

direction to complete one oscillation. In contrast to N-sided regular polygons (Esteban

et al. 2019c), the particles tested here always travel in a preferred orientation, that is, along

the ﬂat diagonal. Also, no rolling motions are detected, which agrees with our expectation

in the discussion on I∗.

While it is obvious that the particles fall in a zigzag fashion, whether the trajectories

observed are planar or three-dimensional is not evident. Here, we use an analogous

approach to the one proposed in Esteban et al. (2018) where each trajectory is split into

‘gliding’ and ‘turning’ sections by local extrema of the instantaneous descent velocity. The

amplitude of each gliding section Ag, deﬁned as half the planar displacement of the gliding

section, is compared with its radius of curvature Rgin the top-down view (ﬁgure 4b).

922 A30-9

T.T.K. Chan and others

All trajectories tested satisfy the criterion Ag/Rg<0.1(table 2), and therefore are

considered to be within the ‘planar zigzag’ mode.

Other features of ‘planar zigzag’ trajectories are also observed: oscillations in the

z-direction have twice the frequency of those in the horizontal (ﬁgure 4c) (Zhong et al.

2013), and the velocity phase plot describes a characteristic butterﬂy shape (ﬁgure 4e)

(Auguste et al. 2013). Despite these similarities, the motion of bottle-fragment particles

differ from disks in the sense that disks yaw almost 180◦at every horizontal extremum

(Zhong et al. 2013), but this does not occur for the particles tested.

While certain disks exhibit three-dimensional ‘hula-hoop’ descents which precess

(Auguste et al. 2013), and ﬁgure 4(d) somewhat resembles such a mode, it is clear that

the particles concerned do not fall this way. This is because ‘hula-hoop’ settling has an

ellipsoidal proﬁle of Vyagainst Vx. Instead, the precession observed here probably emerges

due to another reason.

To examine this feature, we further studied the gliding and turning sections. As

negligible rotation occurs in the gliding sections, they are approximated by straight lines

in the xy-plane. Therefore, rotations have to occur during the turning sections and the

precession rate ˙γcan be deﬁned as the rate at which the gliding sections rotate, see table

2. We observe that ˙γdecreases as the rotational inertia about an axis parallel to the ﬂat

diagonal Iroll increases. Thus, we hypothesise that tiny ﬂuid ﬂuctuations due to residual

ﬂows can explain the precession. These ﬂuctuations may imperceptibly cause the object to

roll, hence precess in the turning sections.

In ﬁgure 5 one can see the evolution of the mean descent velocity Vzwith the

characteristic length scale of the particles D. For smaller objects, Vzdecreases as D

increases, yet larger particles behave oppositely so a minimum at D≈38 mm appears.

To examine whether it is related to a change in descent style, the Reynolds number Re is

calculated and plotted against the Archimedes number in ﬁgure 6. The Archimedes number

is deﬁned as Ar =(gD3|1−ρ∗|)1/2/ν,wheregis the gravitational acceleration. Previous

research has usually observed a linear relation (Fernandes et al. 2005; Zhong et al. 2013;

Toupoint et al. 2019), and noted that a change in slope can suggest a transition to another

descent style (Auguste et al. 2013). The data in ﬁgure 6 indeed shows a linear relation

for the three smallest particles, but there is a modest increase in the slope for the largest

particle. This might reﬂect a physical transition in the particle dynamics, where the upper

vertices of the particle with θ>90◦may interact more with the wake generated by the

leading edge. Nonetheless, this feature does not match the local minimum in Vz, whose

origin remains unclear.

Since the descent styles of particles no. 1 to no. 3 appear the same based on the Ar–Re

plot, we further evaluate the descent velocity behaviour by comparing the radii of curvature

of the trajectories Lpend in the vertical cross-sections (after applying planar projection

and removing the mean descent velocity). We use the subscript ‘pend’ in allusion to

the pendulum model that will be introduced later. Similarly, the maximum pitch angles

αmax, the planar oscillation amplitudes Aand the dominant radial frequencies fare also

evaluated. These are made non-dimensional (except for αmax) and shown in ﬁgure 7,where

the particles are characterised by their Archimedes number Ar.NotethatAdiffers subtly

from Ag, which is shown in table 2, since Aincludes the turning sections as well. Both the

dimensionless radius of curvature of the particle gliding section Lpend /Dand amplitude

of the oscillations A/Dincrease with Ar. However, for the largest particle, these two

magnitudes appear to decrease considerably from the global trend. On the other hand,

αmax decreases with increasing Ar. The Strouhal number, deﬁned as St =fD/Vz, remains

nearly constant across the particles tested, which implies that fis highest for particle no. 1.

922 A30-10

Settling behaviour of thin curved particles

Vz (mm s–1)

D (mm)

25 30 35 40 45 5020

Figure 5. The mean settling velocities Vzof the particles. Unless further speciﬁed, the deﬁnitions of the

data markers follow table 1 and vertical error bars represent the standard deviation of the measurements.

0.5 1.0 1.5 2.0 2.5 3.0

×104

1500

2000

2500

3000

3500

1000

Figure 6. Plot of Re against Ar. A linear relation is observed for the ﬁrst three points and a kink seen for the

last, which suggests a transition in settling style. As Re(Ar)is one-to-one in the investigated range, the two are

used interchangeably.

Thus, a picture where the smallest particle oscillates rapidly about the vertical axis while

descending, and where the larger ones settle more gently emerges. The smallest particle

might not be fully gliding, and descends faster with less lift produced. As further evidence,

we calculate the average vertical slip angle in the gliding sections deﬁned as the difference

between the pitch angle and the angle of inclination of the velocity vector, i.e.

Δα =tan−1Vz

(V2

x+V2

y)1/2−|α|.(2.1)

922 A30-11

T.T.K. Chan and others

(a)(b)

(c)(d)

0.6

0.8

1.0

1.2

0.2

0.4

0.6

0.8

1.0

0.45

0.5 1.0 1.5 2.0 2.5 3.0

A/DL

pend /D

αmax (°)

α (°)

×104

×104×104

0.5 1.5 2.5

0.50

0.55

0.60

0.65

0.70

Figure 7. The (a) dimensionless radius of curvature of the trajectory in a vertical cross-section Lpend/D,

(b) magnitude of the maximum pitch angle αmax, (inset) average vertical slip angle over gliding sections Δα,

oscillation frequency, versus the Archimedes number Ar.

This is plotted in the inset of ﬁgure 7(b). The ﬁgure shows that Δα decreases slowly as

the particle diagonal length Dincreases for particles no. 1 to 3, therefore proving its pitch

attitude is more closely aligned with the velocity vector.

Indeed, such a difference in falling behaviour can explain the initial reduction of the

mean descent velocity at small Ar. When the particle’s curved surface area increases,

more lift is generated and the gliding motion is enhanced, leading to a reduction in Vz.

However, this argument alone cannot explain the minimum in Vz.

To understand why the descents become faster at larger Ar, we measure the maximum

horizontal speed in each swing Vh,max.Asﬁgure 8(a) illustrates, Vh,max/Vzgenerally

grows with Ar. This increase in Vh,max leads to a larger Vzbecause the particle pitches

down at the beginning of each swing, so the horizontal and vertical speeds are coupled to

each other. Therefore, the minimum in the descent velocity manifests through a delicate

balance between lift enhancement and a reduction of the particle’s horizontal speed during

the glide.

Settling behaviour at large Ar (or equivalently θ) is more complex. While Vzincreases

even for the largest object, the behaviour of particle no. 4 is different from the other ones.

Figure 7(a,c) demonstrate that Lpend/Dand A/Dare reduced as compared with the linear

extrapolation from the previous three. The trend in A/Dcould be related to the increase in

the slope of Re(Ar). If energy is conserved, a smaller A/Dimplies more potential energy

922 A30-12

Settling behaviour of thin curved particles

Ar Ar

×104×104

(a)(b)

1.8

2.1

2.4

2.7

1.5

600

800

1000

1200

400

0.5 1.0 1.5 2.0 2.5 3.0 0.5 1.0 1.5 2.0 2.5 3.0

500 700 900

Vh,max /Vz

az,max (mm s–2)

αmax (°)

Figure 8. (a) Plot of the non-dimensional maximum horizontal speed in a swing Vh,max /Vz.(b) Behaviour

of the maximum vertical acceleration az,max. The grey symbols represent the descending pendulum model

introduced in § 2.3. Inset shows αmax versus az,max together with the best-ﬁt line: αmax =(0.03 ±0.01)az,max +

(20.8±6.8).

is converted to vertical velocity instead of horizontal velocity. Since Re is based on Vz,

the Re(Ar)relation becomes steeper, as argued in Auguste et al. (2013). We hypothesise

that the differences observed are due to stronger interactions between the leading edge

vortex and the upper vertices of the particle. Further work is required to understand this

behaviour.

Since αmax indirectly determines the position of the slowest descent, linking it to a

more experimentally accessible quantity might be useful. As discussed, the larger particles

oscillate with a smaller αmax and descend more smoothly. This is also reﬂected by the

maximum vertical acceleration az,max displayed in ﬁgure 8(b). The inset shows αmax is

linearly related to az,max. This is somewhat expected for the gliding particles since a larger

initial pitch angle would mean a steeper descent near the extrema. However, it is worth

noting that the same slope extends to even the smallest particle which settles without

generating signiﬁcant lift based on our interpretation.

2.3. Modelling the settling behaviour

As the particles oscillate periodically while settling, pendulums whose pivots descend at

constant speeds are chosen to model their motions, as also proposed for freely falling disks

(Esteban 2019). Motivated by the fact that the amplitude of the motion does not vary in

time as the particle settles (see ﬁgure 4b), an idealised pendulum model is constructed

assuming that the system is non-dissipative. Thus, their equation of motion ignoring the

constant vertical descent velocity reads

d2φ

dt2=−

g(ρ∗−1)C

Lsin φ, (2.2)

where ρ∗>1. Here, φis the angular displacement from the vertical, Lis the (virtual)

pendulum length – i.e. the length from the swinging particle to the virtual origin

falling vertically with the particle – and Cis a constant to account for all accelerations

apart from gravity. By deﬁnition, Land the initial angular position correspond to

the measured quantities Lpend and αmax, respectively. This leaves only Cas a ﬁtting

parameter, whose value is found by matching the oscillation frequencies to experiments.

Although previous studies (Tanabe & Kaneko 1994; Belmonte, Eisenberg & Moses

1998) have used pendulums to describe the dynamics of settling particles, they focus

922 A30-13

T.T.K. Chan and others

–0.8 –0.4 0 0.4 0.8

rh/D

z/D

Figure 9. Model pendulum trajectory (grey line) overlaid on the experimental data of particle no. 2.

on the quasi-two-dimensional scenario involving ﬂat plates, as opposed to our fully

three-dimensional case with curved particles.

Figure 9 shows the pendulum trajectory overlaid on the experimental data of particle

no. 2. Although not shown, similar plots are obtained for all four particles. In view of

the reasonably good agreement between the experimental data and the model proposed,

‘planar zigzag’ descents can be viewed as simple harmonic motions superposed on

uniform descents, though higher-order quantities such as az,max are not accurately captured

by the model as indicated by the grey symbols in ﬁgure 8(b).

To examine whether the ﬁtted parameter Ccan be determined without frequency

matching, it is plotted against Ar in ﬁgure 10. Interestingly, a nearly linear relation exists,

meaning this model allows one to predict the particle velocity ﬂuctuations simply by

computing Ar without any a priori knowledge. In the context of undamped underwater

pendulums, C=(ρ∗+m∗

a)−1,wherem∗

ais the added-mass coefﬁcient characterising the

energy spent accelerating the surrounding ﬂuid. This can be obtained by comparing (2.2)

with the equation of motion of underwater pendulums as in Mathai et al. (2019),

d2φ

dt2=− g(ρ∗−1)

L(ρ∗+m∗

a)sin φ. (2.3)

The inset of ﬁgure 10 shows that m∗

adecreases with increasing Ar, suggesting that

enhanced gliding means less effort is required to move the neighbouring liquid. The

magnitude of this parameter is much larger than in objects like cylinders, since particle

volume and ρfare used to non-dimensionalise the added mass.

To better understand the behaviour of bottle fragments in industrial facilities, the same

objects are dropped in the water tank with background turbulence. In the following section,

the ﬂow characteristics are presented and the dynamics of the particles discussed.

3. Settling in turbulent ﬂow

The experiments are conducted in a random jet array facility (ﬁgure 2e), where turbulence

is generated by the continuous action of submerged water pumps as in Esteban, Shrimpton

922 A30-14

Settling behaviour of thin curved particles

0.5 1.0 1.5 2.0 2.5 3.0

0.16

0.20

0.24

0.28

0.12

123

×104

Figure 10. Fitting parameter Cas a function of Ar. In the context of underwater pendulums, Cis related to

the added-mass coefﬁcient m∗

a. Inset shows m∗

aversus Ar.

& Ganapathisubramani (2019a). However, the addition of a pulse-width modulation

system allows us to control turbulence intensity while the facility is in operation. The

characteristics of the turbulence generated are in table 3, and further details can be

found in Appendix A. Turbulence is produced so that all the particles’ characteristic

length scales are smaller than the horizontal integral length scale Lx. As mentioned in

§2.1, these particles have sizes comparable to the ones processed in actual recycling

facilities. The experimental procedure to release particles in this section is analogous

to the one previously presented. However, as turbulent ﬂow quantities can only be

predicted statistically, the number of repeated experiments per particle is increased to at

least 49. The minimum waiting time between releases is reduced to three minutes since

the background turbulence washes residual ﬂows away rapidly. Nonetheless, to ensure

statistical stationarity, the pumps are switched on for no less than 10 minutes before the

ﬁrst drop. We position the lower camera further back which resulted in a resolution of

≈0.35 mm pixel−1and a magniﬁcation of ≈1/60. We also monitor the water temperature

for accurate estimation of the dimensionless parameters.

Data analysis is very similar to the cases in quiescent ﬂuid, with the main differences

being the identiﬁcation of the transients, and that the trajectories are no longer detrended

to account for horizontal drifts. The presence of background turbulence means any

transient effects are conﬁned to an even smaller section of the trajectory. Despite this,

for each descent in turbulence, we still remove the mean length of the transients for the

corresponding quiescent experiments from the trajectory.

3.1. Results and discussion

Several particle descents in turbulence are plotted in ﬁgure 11 (see the supplementary

videos). The ‘planar zigzag’ mode found in quiescent ﬂuid is still present, with the

dominant oscillation frequency over each trajectory nearly unchanged in all particles

tested. However, their motions are diversiﬁed by ﬂow ﬂuctuations and therefore trajectories

are no longer repeatable. Still, four types of special events are identiﬁed across all the

particles investigated: (1) ‘slow descents’, where the quiescent settling style remains but

922 A30-15

T.T.K. Chan and others

Turbulence statistics Values

ux/uz1.34

u

rms =(ux+2uz)/315.9mms

−1

MFF 0.48

HD 0.07

Lturb 45.0mm

(Lx,Lz)(65.3,34.8)mm

(Lxx,Lzx )(93.9,45.4)mm

(Lzz,Lxz )(44.3,27.4)mm

(λf,λg)(6.8,6.5)mm

(λxx,λzx )(8.1,7.8)mm

(λzz,λxz )(6.1,5.8)mm

Reλ98

(Reλ,x,Reλ,y)(139,77)

Table 3. Statistics of the background turbulence such as the r.m.s. velocity ﬂuctuations, the mean ﬂow factor

(MFF), homogeneity deviation (HD), integral length scales and Taylor microscales. Here λfand λgdenote the

longitudinal and transverse Taylor microscales, respectively. The reader is referred to Appendix A for the full

deﬁnitions. The values in brackets correspond to the respective quantities in the column on the left.

x/D0

y/D

024

–1

x/D

y/D

–1

y/D

012

x/D

z/D

(a)

(b)

(c)

(d)

y/D

x/D

–1 –1

Figure 11. Trajectories of particles in turbulent ﬂow. Four special types of motions are observed though the

underlying zigzag mode seen in quiescent ﬂuid remains: (a) ‘slow descent’, (b) ‘rapid rotation’, (c) ‘vertical

descent’ and (d) ‘long gliding motion’. The positions of the events within the trajectories are marked by square

brackets on the side. Square markers denote locations corresponding to local minima of Vz.

vertical velocity is attenuated (ﬁgure 11a); (2) ‘rapid rotation’, where the direction of the

oscillations changes rapidly at the end of a swing (ﬁgure 11b); (3) ‘vertical descents’,

where the planar motion diminishes and the particle essentially falls straight down

(ﬁgure 11c); and (4) ‘long gliding motions’, where the gliding section in the ‘planar zigzag’

motion is especially long (≈4.8Din the illustrated case) and is sometimes preceded by a

large α(ﬁgure 11d). Apart from vertical descents, which we do not observe for particle

no. 1, these events occur for all the particles. Multiple types of the motions listed may

occur in a single descent. Remarkably, the particles never ﬂip over, possibly due to their

dihedral conﬁguration.

Slow descents probably occur when the object encounters strong incident ﬂows that

enhance lift. As the smallest particle does not generate sufﬁcient lift to fully glide in

quiescent ﬂuid, it indeed rarely exhibits this behaviour. Rapid rotations can emerge when

the solid enters a region of horizontal shear, causing it to rotate and sometimes roll slightly.

922 A30-16

Settling behaviour of thin curved particles

Efluc(mm2 s–2)

0.2

0.4

0.6

0.8

(a)(b)

p.d.f.

123456 0.5 1.0 1.5 2.0 2.5 3.0

900

800

700

600

500

Ar ×104

Turbulent

Quiescent

///

1234

rh/D

0.1

0.2

0.3

0.4

p.d.f.

Figure 12. (a) The p.d.f.s of rh/Dalong the descent. The solid line and solid data points are for quiescent ﬂuid

while the dotted one and hollow data points are for turbulent settling. The p.d.f.s of particles no. 1 (turbulent

case only) and no. 3 are displayed. The inset shows the same quantity but for all the objects dropped. The

symbols follow those introduced in table 1.(b) Vertical ﬂuctuation kinetic energy per unit mass Eﬂuc of the

various particles.

This kind of motion becomes more likely the smaller the Iroll or the larger the distance

between the centre-of-gravity and the centre-of-pressure (i.e. a longer moment arm).

Heuristically, assuming the centre-of-pressure coincides with the centre of the solid’s

circle of curvature when viewed at the front (ﬁgure 2b), the smallest particle has the

longest moment arm. Either way, the smallest object should be the most sensitive to

such shear. Long gliding motions appear possibly as the local background ﬂow has a

signiﬁcant component along the particle’s direction of motion, pushing it along. Finally,

we hypothesise that vertical descents happen when the object encounters a downdraught.

Slow descents and long gliding motions have also been found for disks falling under

background turbulence (Esteban et al. 2020). However, we noticed key distinctions in the

settling characteristics between these two geometries. First, rapid rotations have not yet

been observed for disks. Second, fast descents of disks differ from vertical descents of the

particles tested here. This type of motion for disks is always preceded by an especially large

α, so the disks are aligned with the direction of motion. However, this is not necessarily

the case for the bottle-fragment-like particles.

To assess the effect of turbulence on all the descents collectively, the height-integrated

radial probability density functions (p.d.f.s) and the speciﬁc kinetic energy ﬂuctuations

of Vz(i.e. half of the variance of ﬂuctuations of Vz), Eﬂuc, are shown in ﬁgure 12.To

accurately capture the radial displacement rh, non-transient parts of the trajectories are

centred so the origin coincides with the mean position of the ﬁrst swing.

The diversiﬁcation of the settling dynamics by background turbulence is also evident

here. For the horizontal motion, focusing ﬁrst on ﬁgure 12(a), the radial p.d.f. in quiescent

and turbulent ﬂows of particle no. 3 reveal that the most likely radial position remains

unchanged. This conﬁrms that the quiescent zigzag motion is still signiﬁcant at the

current turbulence level. Yet, the p.d.f. is now much broader, with particle dispersion

reaching multiple Dinstead of only rh/D≈1. The inset in ﬁgure 12(a) shows how the

radial dispersion of the particles in turbulence reduces as Ar increases. However, the

vertical component of the velocity ﬂuctuations are modiﬁed differently. These are shown in

ﬁgure 12(b), and demonstrate a strong increase in velocity ﬂuctuations about Vz. Hence,

the motion is destabilised to a similar extent over most Ar tested. This difference may be

922 A30-17

T.T.K. Chan and others

(a)(b)

×104

D (mm)

25 35 45 55 0.5 1.0 1.5 2.0 2.5 3.0

1000

1500

2000

2500

3000

3500

Turbulent

Quiescent

///

Vz (mm s–1)

Figure 13. (a) Mean descent velocities Vzof the various particles in turbulence and quiescent ﬂuid. (b)

Dimensionless version of the descent velocity plot, Re(Ar).

attributed to gravity, which has been used by Byron et al. (2019) to explain an identical

trend for slip velocities of nearly neutrally buoyant cylinders in turbulence.

The effect of turbulence on the mean descent velocity Vzhas long been an area

of great interest. Figure 13(a) plots Vzagainst the particle characteristic length scale,

showing Vzreduces compared with the quiescent case, although the data lies within

the statistical deviation of the turbulent one. We note this result is congruent with the

slip velocity of nearly neutrally buoyant cylinders (Byron et al. 2019), and opposite

to Vzof inertial disks falling in background turbulence (Esteban et al. 2020). As

mentioned in § 1, Good et al. (2014) found that settling is hindered by turbulence when the

characteristic gravitational velocity is greater than the typical ﬂow velocity ﬂuctuations

u

rms. To compare this with our results, we formed an analogous quantity by replacing

the characteristic gravitational velocity with the mean descent velocity in quiescent ﬂuid

Vq.Here Vq/u

rms is found to lie in between 3.92 and 4.27. Hence, our results are in

agreement with the prediction by Good et al. (2014) which suggests that the mean descent

velocity would be reduced when Vq/u

rms >1. We recognise Vq/u

rms does not reﬂect

the multiscale nature of particle–turbulence interactions, and it may be more insightful to

employ a scale-dependent quantity instead. However, theoretically deriving such a quantity

for our particle geometry is highly non-trivial and is beyond the scope of this study.

To further investigate the cause of the hindered settling, the relation between Re and Ar

is shown in ﬁgure 13(b). The general trend observed is the same as in quiescent ﬂuid – with

an approximately linear relation for the three smallest particles and an increase in slope

for the last one – and an identical interpretation is employed. As considering quantities

averaged over entire trajectories do not seem to help explain the change in Vz, particle

motions are examined over trajectory sections. Esteban et al. (2020) studied the correlation

between Vzand the dominant frequency of each trajectory. Instead of following this

approach, where the existence of a single ‘weak’ event might be hidden by the presence of

more severe ones, we propose an alternative method to capture the effect of all the events,

the average descent velocities Vevent and the characteristic frequencies fevent conditioned

on each type of event. However, this leads to a practical question on the deﬁnition of an

‘event’.

Classifying events using the instantaneous vertical velocity provides reasonable results.

The positions corresponding to local minima of Vz(squares in ﬁgure 11) also match those

of the radial extrema reasonably well, and these are used to separate events. Each event

922 A30-18

Settling behaviour of thin curved particles

(a)(b)

Vevent /Vq

Vevent/Vq

Vevent /Vq

fevent/fqfevent/fq

fevent/fq

0.4

0.8

1.2

1.6

Particle no. 1 Particle no. 2

Particle no. 3 Particle no. 4

0.5

1.0

1.5

1230

0.5

1.0

1.5

0123

1230

Figure 14. (a) Scatter plots showing the relationship between the average descent velocities Vevent and

frequencies fevent per event. To better visualise the effect of background turbulence, these quantities are

normalised by the mean descent velocity Vqand the dominant vertical oscillation frequency fqin quiescent

ﬂuid. The points corresponding to the special events shown in ﬁgure 11 –slowdescent, rapid rotation, long

gliding motion and vertical descent – are annotated. (b) The average Vevent against fevent of all the events in

panel (a).

then essentially corresponds to a half-swing, with fevent being the inverse of its duration.

Figure 14(a) shows the mean descent velocity of each event Vevent versus fevent ,both

normalised by the corresponding mean values in quiescent liquid.

In general, events with small frequencies fevent can increase the descent velocity Vz,

while those with large fevent have the opposite effect. This is quantitatively illustrated by

ﬁgure 14(b) where the mean event velocity Veventis plotted against fevent. The same was

also found for disks in Esteban et al. (2020), although the trend here is less prominent

due to the moderate particle inertia. Also, particle no. 2 exhibits a wider variety of events

compared with particle no. 1 as reﬂected by the scatter in the data, in agreement with the

initial observation that certain types of motions are less frequent for smaller particles.

Contrary to the variation in the horizontal displacement (see ﬁgure 12a), turbulence

introduces more extreme events for the larger particles.

To correlate the four types of events with the modulation in frequency, ﬁgure 15 displays

the variation of Vzover their durations, the corresponding Vevent and fevent. Each type

of descent behaviour modiﬁes Vzdifferently: ‘slow descents’ have Vevent ≈0.5Vz

(ﬁgure 15a); rapid rotations have no signiﬁcant effects on Vz(ﬁgure 15b), meaning

the rotation is not coupled to the vertical motion; long gliding motions (ﬁgure 15c)

could considerably enhance settling, regardless of the initial pitch angle; vertical descents

(ﬁgure 15d) increase Vz. The behaviour of vertical descents is as expected since the

distance travelled is shorter compared with zigzag, and downdraughts force the particle

down. Although the limited depth of our tank means the vertical descent in ﬁgure 15(d)

is incomplete, we are conﬁdent that the complete event still increases Vzfor the reasons

above. In summary, as long gliding motions and vertical descents have small fevent/fq,they

correspond to points with small fevent and large Vevent in ﬁgure 14(a).

So far, it has been shown that low-frequency events such as long gliding motions and

vertical descents could enhance settling. However, Vzis smaller than the quiescent value

on the whole. This result is captured when plotting the p.d.f. of Vevent (ﬁgure 16). Before

proceeding, note that the deﬁnition of events used may overcount the slow ones. This is

mitigated by combining successive events with Vevent <0.4Vq. Though the threshold is

922 A30-19

T.T.K. Chan and others

Vz /VqVz /Vq

fevent/fq

= 1.14

fevent/fq

= 1.27

(a)

(d)

(c)

(b)2.5

2.9

3.3 0123

0123

5.5

5.9

6.3

z/Dz/D

2.5

3.0

3.5

4.0

4.5

5.0

5.5

fevent/fq

= 0.63

fevent/fq

= 0.40

0123 0123

6.0

6.5

7.0

7.5

8.0

8.5

9.0

Figure 15. The instantaneous descent velocities Vz(solid lines) and the mean values Vevent (dotted lines) of

the four types of events identiﬁed: (a) slow descent, (b) rapid rotation, (c) long gliding motion and (d) vertical

descent. The green lines show the locations of the events.

0.5 1.0 1.5 2.0

0.1

0.2

0.3

0.4

p.d.f.

0.5

Vevent /Vq

Figure 16. The p.d.f. of Vevent relative to Vq. To avoid overcounting slow events, the successive ones with

Vevent <0.4Vqhave been merged.

somewhat arbitrary, it does not affect the following discussion. The reduction in Vzis

manifested as a slight leftward shift of the entire p.d.f.

Among the four types of events identiﬁed, only slow descents reduce the settling speed.

However, we recognise that the events described are the most readily detected ones and

do not constitute an exhaustive list. Particle settling in turbulence is a highly complex

and multiscale phenomenon (Tom & Bragg 2019) that exhibits a number of more subtle

922 A30-20

Settling behaviour of thin curved particles

unclassiﬁed events. We therefore believe the attenuation in settling may be caused by the

less discernible events. As the falling particle resembles a swept-back wing in the direction

of motion and larger particles glide more in quiescent ﬂuid, it is possible that under most

conditions, the turbulence provides slightly more lift without considerably changing the

basic zigzag motion.

Admittedly, such a result is unexpected. Since the particle sizes are of the same order

as the integral length scale Lturb, we anticipated the solid to exhibit downward sweeping

motions triggered by interactions with large vortices. However, the object’s inherent

stability likely suppresses these motions.

4. Concluding remarks

Motivated by the numerous applications of particle settling, such as differentiating plastic

from glass in hydrodynamic separators, 3D-printed rigid thin curved solids resembling

bottle fragments were dropped in a water tank in quiescent ﬂuid and in homogeneous

anisotropic turbulence.

In quiescent liquid, the particles underwent planar zigzag descent and their trajectories

were divided into gliding and turning sections. While one might expect the average

vertical velocity Vzto vary monotonically with particle size, a minimum was found at

D≈38 mm (Ar ≈1.8×104). Closer examination of the settling behaviour showed that

the horizontal oscillation amplitude Aand radius of curvature Lpend normalised by particle

size were generally enhanced for larger particles. On the contrary, the oscillation frequency

fand the maximum pitch angle αmax, which was directly proportional to az,max, decreased

monotonically. These suggested enhanced lift generation as the particle size grew, which

was supported by a closer alignment between αand the direction of motion. This led to

the initial reduction in Vz. The subsequent settling enhancement for the larger objects

was due to more rapid horizontal motion at midswing locations coupled with their initial

pitch down attitude at the beginning of each swing. All the trajectories observed could be

modelled reasonably well by undamped underwater pendulums descending at a constant

velocity.

The zigzag motion was also observed for settling in turbulence, but ﬂuctuations in the

ﬂow modiﬁed it so the radial dispersion increased considerably. Notably, the particles

never ﬂipped over although their sizes were comparable to Lturb. In agreement with Good

et al. (2014), Vzwas slightly lower than in quiescent ﬂuid for Vq/u

rms >1. Four special

types of events comprising slow descents, vertical descents, long gliding motions which

were sometimes preceded by large pitch angles, and rapid rotations, were identiﬁed. Also,

each type of motion was related to the particle kinematics and to the descent velocity.

In general, vertical descents and long gliding sections sped up settling. By dividing

each trajectory into a collection of events, those with a low frequency were found to be

capable of enhancing the descent, while the opposite occurred for high-frequency events.

Nevertheless, the p.d.f. of Vevent was unimodal and the reduction of Vzwas reﬂected

by a leftward shift. This may suggest the background ﬂow slightly modulated each event

by enhancing lift production, so the change in Vzcould not be simply connected to the

special events. The above also underlines the difﬁculty of studying descent behaviour with

background turbulence.

Future research may therefore focus on wake visualisation of these particles in both

turbulence and quiescent ﬂuid. As transitions in settling behaviour are usually correlated

to a change in wake structure (see e.g. Ern et al. 2012; Auguste et al. 2013;Leeet al.

2013; Esteban et al. 2019c; Toupoint et al. 2019)andαmax ∝az,max found here indirectly

supports this argument, observing the wake may reveal other types of events and the effects

922 A30-21

T.T.K. Chan and others

of anisotropic geometries. This may further explain the change of Vzin turbulence

and the lift enhancement as the particle size increased in quiescent ﬂuid. Moreover, it

may uncover why certain trends reversed for particle no. 4, where θ>90◦. Theoretical

development may concentrate on ﬁnding a suitable scale-dependent metric for anisotropic

particles to distinguish between enhanced and hindered settling in turbulence. Finally,

additional development of the pendulum model is desirable. An emphasis should be placed

on interpreting Cas it may complement the current experimental observations and improve

the predictive power of the model.

Supplementary movies. Supplementary movies are available at https://doi.org/10.1017/jfm.2021.520.

Acknowledgements. We thank J.B. Will for fruitful discussions and D. Krug for drawing our attention to

literature that modelled settling behaviour with pendulums.

Funding. T.T.K.C. thanks the Internship Ofﬁce at the University of Twente and the Faculty Ofﬁce of the

Faculty of Engineering and Physical Sciences at the University of Southampton. He is partially funded by the

University of Twente Scholarhip and the Erasmus+Traineeship Scholarship. S.G.H. acknowledges MCEC for

ﬁnancial support.

Declaration of interests. The authors report no conﬂict of interest.

Data availability statement. All data supporting this study are openly available from the University of

Southampton repository at https://doi.org/10.5258/SOTON/D1859.

Author ORCIDs.

Timothy T.K. Chan https://orcid.org/0000-0003-2363-0403;

Luis Blay Esteban https://orcid.org/0000-0003-4675-6957;

Sander G. Huisman https://orcid.org/0000-0003-3790-9886;

John S. Shrimpton https://orcid.org/0000-0003-2510-6373;

Bharathram Ganapathisubramani https://orcid.org/0000-0001-9817-0486.

Appendix A. Turbulence generation and characteristics

As explained in § 3, the experiments are conducted in a random jet array facility (ﬁgure 2e),

where turbulence is generated by the continuous action of submerged water pumps. These

pumps, arranged in two 8 ×6 arrays with vertical and horizontal mesh lengths of 10 cm

on either side of the tank, ﬁre independently according to the ‘sunbathing algorithm’ to

generate statistically stationary homogeneous anisotropic turbulence with negligible mean

ﬂow (Variano & Cowen 2008; Esteban et al. 2019a). The durations of the ‘on’ and ‘off’

signals are randomly selected from two separate Gaussian distributions with their mean

values and standard deviations denoted by μon/off and σon/off , respectively. In this case,

μon ±σon =(3±1)sandμoff ±σoff =(21 ±7)s. When the pumps are active, water is

drawn radially at their bases and expelled horizontally out of their cylindrical nozzles with

a diameter of 18 mm. To improve isotropy and protect the particles from collisions with the

pumps, a 13 mm square mesh is placed 3 cm downstream of the jets. Turbulence intensity

is controlled through modulating the power supplied by pulse-width modulation. For more

information on the turbulence facility, the reader is referred to Esteban et al. (2019a). The

equipment is identical apart from the addition of the mesh and the power control system.

Prior to releasing particles, the turbulence generated is characterised with particle image

velocimetry (PIV). The ﬂow was seeded with 56 µm polyamide particles (Vestosint 2157).

A laser sheet passing through the centre of the tank contained in the xz-plane is generated

(Litron BERN 200-15PIV), and 3000 image pairs are taken at 0.8 Hz (VC-Imager Pro

LX 16M). The interpulse time is set to 4000 µs to limit the tracer displacements to

approximately 6 pixels and reduce the out-of-plane displacements between image pairs.

922 A30-22

Settling behaviour of thin curved particles

(|Ux|+2|Uz|)/3 (mm s–1)

(|ux|+2|uz|)/3 (mm s–1)

(a)(b)

25 mm 25 mm

Figure 17. The PIV measurements of the ﬂow in the turbulence box. The time-averaged (a) r.m.s. ﬂow velocity

ﬂuctuation ﬁeld and (b) mean ﬂow ﬁeld at the middle of the tank. The subscripts (x,z)denote the corresponding

velocity components.

To characterise the turbulence generated, we decompose the ﬂow velocity into mean

and ﬂuctuating components Uf(x,t)=Umean(x,t)+uﬂuc (x,t),wherexis the position

vector. Figure 17 shows the two ﬁelds, where (Ux(x), Uz(x)) and (ux(x), uz(x)) are

the time-averaged (x,z)components of Umean and of the r.m.s. of uﬂuc, respectively.

The ﬂuctuations appear homogeneous although there is some horizontal mean ﬂow caused

by the synthetic jets emitted by the pumps. These are quantitatively expressed by the

homogeneity deviation HD and the mean ﬂow factor MFF. Assuming symmetry about

the x-axis (Carter & Coletti 2017), u

rms =(ux+2uz)/3, where the line above denotes

spatial averaging. Then HD =2σu/u

rms =0.07 1 (Esteban 2019), where σuis the

standard deviation of u

rms in space. Thus the turbulence is indeed homogeneous. Denoting

the mean ﬂow speed by U, the relative magnitude of the mean ﬂow is assessed by

MFF =U/u

rms =0.48. While a small mean ﬂow is present, velocity ﬂuctuations still

dominate so we believe it has no signiﬁcant effect on the settling characteristics of the

particles tested. Nonetheless, the global isotropy ux/uz=1.34 >1 shows the turbulence

is mildly anisotropic. This implies the integral length scales and Taylor microscales depend

on the direction of the velocity component and of the spatial separation.

Taking this into account, ﬁgure 18 gives the various autocorrelation functions along the

vertical and horizontal directions, ρij . They decay as rincreases and approach 0 at r→

+∞. Thus, we deﬁne the upper integration limit r0for the integral length scale Lij such that

ρij(r0)ﬁrst reaches 0.01. This is in line with the suggestion in O’Neill et al. (2004): taking

r0as the ﬁrst zero-crossing of ρij balances accuracy with ease of calculation. Furthermore,

if the directly measured autocorrelation does not reach ρij ≈0.01, an exponential tail is

ﬁtted for ρij ≤0.35. Table 3 includes the various Lij found.

Integral length scales involving velocity ﬂuctuations along the x-direction are larger than

those along z. This was also found by Carter & Coletti (2017) in a similar facility despite

a different Reλ, suggesting eddies were elongated by the larger ﬂuctuations. Following

their suggestion, the geometric mean of integral length scales involving ﬂuctuations along

one direction is taken to represent the size of the largest vortices in that orientation,

i.e. Lx=(LxxLzx )1/2, for instance. To facilitate comparison with previous experiments,

a conventional integral length scale assuming axisymmetry

Lturb =Lx+2Lz

3(A1)

is evaluated too.

922 A30-23

T.T.K. Chan and others

r (mm)

1.0

ρxx

ρij

ρzx

ρxz

ρzz

0.8

0.6

0.4

0.2

–0.2 0 40 80 120 160 200

Figure 18. Autocorrelation functions ρij of the j-component velocity ﬂuctuations along the i-direction. The

solid lines give the measured data while the dashed line shows the exponential ﬁt. The spacing between markers

is not indicative of the resolution.

The Taylor microscale along the i-direction of j-component velocity ﬂuctuations, on

the other hand, is evaluated according to its deﬁnition λij =(−1

2(d2ρij/dr2)|r=0)−0.5.To

minimise PIV error, we only consider the ﬁrst two values of ρij with a positive separation

whose interrogation windows do not overlap (Adrian & Westerweel 2011). The horizontal

intercept of the ﬁtted parabola then equals λij. The conventional longitudinal and

transverse Taylor microscales λfand λgare found assuming axisymmetry in analogy to

(A1).

The related Reynolds number Reλis also determined using the measured water

temperature of 17 ◦C. The direction-dependent values Reλ,i=λg,iui/ν ,whereλg,iis

the transverse Taylor microscale involving i-component velocity ﬂuctuations ui.The

conventional axisymmetric Reλand all the quantities discussed above are displayed in

table 3.

All in all, these measurements show the background turbulence is homogeneous but

mildly anisotropic.

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922 A30-26

Orientation dynamics of two-dimensional concavo-convex bodies

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Full-text available

Dec 2022

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This paper describes an experimental investigation of the dynamics of freely falling thin circular disks settling through turbulence. The patterns of the three dimensional disk motion are studied using an orthogonal arrangement of two high speed cameras. Turbulence is generated in a water tank using a random jet array facility where the jets are mounted in a co-planar configuration. The facility is run continuously until turbulence reaches a statistically stationary state, then, all water pumps are turned off simultaneously and a disk is released after a given waiting time. Contrary to spherical particles, finite-size inertial disks show an increase in the descent velocity for turbulence velocity fluctuations smaller than the particle descent velocity in quiescent flow. Thus, we observe a severe increase of the mean descent velocity of the disk with increasing the magnitude of the turbulence velocity fluctuations (up to $20\%$ of the velocity in quiescent flow for the disk with higher dimensionless inertia $I^*$). We also observe descent events that do not exist for disks falling in still fluid; i.e. `slow tumbling' events and `levitating' events. Finally, we show that the dominant frequency of the particle oscillatory motion decreases for increasing descent velocity and that particles exhibit oscillatory frequencies that never exceed the dominant frequency in quiescent flow in more than $30\%$.

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The wake characteristics of various thin particles with identical material properties but different frontal geometries (disks, hexagonal plates and square plates) are examined by means of three dimensional measurements of the instantaneous velocity field. The reference particle is a circular disk that lies within the Reynolds number—dimensionless moment of inertia domain ($Re-I^*$) corresponding to the fluttering regime, as defined by Willmarth et al. (Phys Fluids 7:197–208, 1964). Hexagonal and square plates are manufactured to have the same frontal area and material properties of the reference particle. Three dimensional trajectories obtained from high-speed imaging show that disks preferably adopt a quasi-2D oscillatory descent; i.e. ‘planar zig-zag’, whereas particles with less circularity adopt three dimensional trajectories more frequently; i.e. ‘transitional’ and ‘spiral’ descent. The wake behind free-falling disks is found to be a succession of hairpin vortices shed off at every turning point linked by a pair of counter rotating vortices that grow downstream from the leading edge of the disk. In contrast, square plates describing ‘spiral’ descent show an almost time-independent wake morphology with large-scale vortex shedding around the entire perimeter of the particle. The large-scale wake structures of hexagonal plates resemble either the disks’ or the squares’ depending on the falling regime that they adopt. Finally, we compare the dimensionless vorticity distribution in the wake of the particles and found that this also depends on the falling style that the particle adopts during the descent. Graphic abstract Open image in new window

Dynamics of heavy and buoyant underwater pendulums

Article

Full-text available

Mar 2019

The humble pendulum is often invoked as the archetype of a simple, gravity driven, oscillator. Under ideal circumstances, the oscillation frequency of the pendulum is independent of its mass and swing amplitude. However, in most real-world situations, the dynamics of pendulums is not quite so simple, particularly with additional interactions between the pendulum and a surrounding fluid. Here we extend the realm of pendulum studies to include large amplitude oscillations of heavy and buoyant pendulums in a fluid. We performed experiments with massive and hollow cylindrical pendulums in water, and constructed a simple model that takes the buoyancy, added mass, fluid (nonlinear) drag and bearing friction into account. To first order, the model predicts the oscillation frequencies, peak decelerations and damping rate well. An interesting effect of the nonlinear drag captured well by the model is that, for heavy pendulums, the damping time shows a non-monotonic dependence on pendulum mass, reaching a minimum when the pendulum mass density is nearly twice that of the fluid. Small deviations from the model’s predictions are seen, particularly in the second and subsequent maxima of oscillations. Using time-resolved particle image velocimetry (TR-PIV), we reveal that these deviations likely arise due to the disturbed flow created by the pendulum at earlier times. The mean wake velocity obtained from PIV is used to model an extra drag term due to incoming wake flow. The revised model significantly improves the predictions for the second and subsequent oscillations.

Laboratory experiments on the temporal decay of homogeneous anisotropic turbulence

Article

Full-text available

Nov 2018

We experimentally investigate the temporal decay of homogeneous anisotropic turbulence, monitoring the evolution of velocity fluctuations, dissipation and turbulent length scales over time. We employ an apparatus in which two facing random jet arrays of water pumps generate turbulence with negligible mean flow and shear over a volume that is much larger than the initial characteristic turbulent large scale of the flow. The Reynolds number based on the Taylor microscale for forced turbulence is Reλ ≈ 580 and the axial-to-radial ratio of the root mean square velocity fluctuations is 1.22. Two velocity components are measured by particle image velocimetry at the symmetry plane of the water tank. Measurements are taken for both ‘stationary’ forced turbulence and natural decaying turbulence. For decaying turbulence, power-law fits to the decay of turbulent kinetic energy reveal two regions over time; in the near-field region (t/tL < 10, tL is the integral time scale of the forced turbulence) a decay exponent m ≈ −2.3 is found whereas for the far-field region (t/tL > 10) the value of the decay exponent was found to be affected by turbulence saturation. The near-field exhibits features of non-equilibrium turbulence with constant L/λ and varying C (dissipation constant). We found a decay exponent m ≈ −1.4 for the unsaturated regime and m ≈ −1.8 for the saturated regime, in good agreement with previous numerical and experimental studies. We also observe a fast evolution towards isotropy at small scales, whereas anisotropy at large scales remains in the flow over more than 100 tL. Direct estimates of dissipation are obtained and the decay exponent agrees well with the prediction m = m−1 throughout the decay process.

Progression of heavy plates from stable falling to tumbling flight

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Full-text available

Sep 2018

This study examines the transition of stable falling to tumbling flight for freely falling heavy plates in a two-dimensional viscous fluid, solved via direct numerical simulation with the immersed boundary method. The simulations are performed at a range of Reynolds number (Re) of up to 500 and a dimensionless moment of inertia (I*) up to 10. It is found that a plate may settle to stable falling or develop into tumbling descent depending on the initial angle of release. The characteristics and performance that distinguish two flight states are investigated. This bistability is analysed with phase portraits and the region mapped across the regime of I* and Re at a specific thickness ratio. In determining the flight state, the respective critical initial angle of release is found to follow a power law through I* and Re. It is suggested that the changing slope of the lift curve that the plate undergoes sets the two flight states apart. Flow fields also reveal that the recirculation behind the plate is confined by the vortex structures and provides an additional rotation to the plate. An experiment is performed suggesting that bistability also occurs at Re ~O(10^4) . Other shapes are also simulated and the different bistable effects are discussed.

Dynamics of Non-Spherical Particles in Turbulence

Book

Jan 2020

Luis Blay

Slip velocity of large low-aspect-ratio cylinders in homogeneous isotropic turbulence

Article

Sep 2019
INT J MULTIPHAS FLOW

Using laboratory experiments, we investigate the turbulent slip velocity of large (Taylor-scale), slightly negatively buoyant cylinders at two mass densities and four aspect ratios. Using refractive index matching and stereoscopic Particle Image Velocimetry, we simultaneously record the velocities of both the cylinders and the surrounding homogeneous isotropic turbulence. We find that despite the large size and concomitant inertia of the cylinders, the cylinder velocity is well predicted by the fluid velocity immediately surrounding it: the particle velocity is close to the fluid velocity across a large range of fluid velocities, barring a small slip velocity. We apply a decomposition to this slip velocity and find that its average is nonzero in the vertical direction, indicating gravitational settling, but is approximately zero in the two lateral directions, reflective of the isotropy in the turbulence. The average slip velocity is subtracted from instantaneous slip velocity to find the “true slip”, with the anisotropic effects of gravitational settling ostensibly removed. However, this true slip also shows the effects of gravity, indicating that large particles with even a small departure from neutral buoyancy may sample the flow anisotropically. In other words, gravity creates anisotropy in the slip velocity even without considering the effects of settling/sedimentation. We discuss potential mechanisms for this effect, including preferential concentration and resuspension, and conclude that gravity should be considered in studies of large particles even when the particles are very close to neutrally buoyant.

Multiscale preferential sweeping of particles settling in turbulence

Article

Jul 2019

In a seminal article, Maxey ( J. Fluid Mech. , vol. 174, 1987, pp. 441–465) presented a theoretical analysis showing that enhanced particle settling speeds in turbulence occur through the preferential sweeping mechanism, which depends on the preferential sampling of the fluid velocity gradient field by the inertial particles. However, recent direct numerical simulation (DNS) results in Ireland et al. ( J. Fluid Mech. , vol. 796, 2016 b , pp. 659–711) show that even in a portion of the parameter space where this preferential sampling is absent, the particles nevertheless exhibit enhanced settling velocities. Further, there are several outstanding questions concerning the role of different turbulent flow scales on the enhanced settling, and the role of the Taylor Reynolds number $R_{\unicode[STIX]{x1D706}}$ . The analysis of Maxey does not explain these issues, partly since it was restricted to particle Stokes numbers $St\ll 1$ . To address these issues, we have developed a new theoretical result, valid for arbitrary $St$ , that reveals the multiscale nature of the mechanism generating the enhanced settling speeds. In particular, it shows how the range of scales at which the preferential sweeping mechanism operates depends on $St$ . This analysis is complemented by results from DNS where we examine the role of different flow scales on the particle settling speeds by coarse graining the underlying flow. The results show how the flow scales that contribute to the enhanced settling depend on $St$ , and that contrary to previous claims, there can be no single turbulent velocity scale that characterizes the enhanced settling speed. The results explain the dependence of the particle settling speeds on $R_{\unicode[STIX]{x1D706}}$ , and show how the saturation of this dependence at sufficiently large $R_{\unicode[STIX]{x1D706}}$ depends upon $St$ . The results also show that as the Stokes settling velocity of the particles is increased, the flow scales of the turbulence responsible for enhancing the particle settling speed become larger. Finally, we explored the multiscale nature of the preferential sweeping mechanism by considering how particles preferentially sample the fluid velocity gradients coarse grained at various scales. The results show that while rapidly settling particles do not preferentially sample the fluid velocity gradients, they do preferentially sample the fluid velocity gradients coarse grained at scales outside of the dissipation range. This explains the findings of Ireland et al. , and further illustrates the truly multiscale nature of the mechanism generating enhanced particle settling speeds in turbulence.

Kinematics and wake of freely falling cylinders at moderate Reynolds numbers

Article

May 2019

We investigated experimentally the motion of elongated finite-length cylinders (length $L$ , diameter $d$ ) freely falling under the effect of buoyancy in a low-viscosity fluid otherwise at rest. For cylinders with densities $\unicode[STIX]{x1D70C}_{c}$ close to the density $\unicode[STIX]{x1D70C}_{f}$ of the fluid ( $\overline{\unicode[STIX]{x1D70C}}=\unicode[STIX]{x1D70C}_{c}/\unicode[STIX]{x1D70C}_{f}\simeq 1.16$ ), we explored the effect of the body volume by varying the Archimedes number $Ar$ (based on the body equivalent diameter) between 200 and 1100, as well as the effect of their length-to-diameter ratios $L/d$ ranging from 2 to 20. A shadowgraphy technique involving two cameras mounted on a travelling cart was used to track the cylinders along their fall over a distance longer than $30L$ . A dedicated image processing algorithm was further implemented to properly reconstruct the position and orientation of the cylinders in the three-dimensional space. In the range of parameters explored, we identified three main types of paths, matching regimes known to exist for three-dimensional bodies (short-length cylinders, disks and spheres). Two of these are stationary, namely, the rectilinear motion and the large-amplitude oscillatory motion (also referred to as fluttering or zigzag motion), and their characterization is the focus of the present paper. Furthermore, in the transitional region between these two regimes, we observed irregular low-amplitude oscillatory motions, that may be assimilated to the A-regimes or quasi-vertical regimes of the literature. Flow visualization using dye released from the bodies uncovered the existence of different types of vortex shedding in the wake of the cylinders, according to the style of path. The detailed analysis of the body kinematics in the fluttering regime brought to light a series of remarkable properties. In particular, when normalized with the characteristic velocity scale $u_{0}=\sqrt{(\overline{\unicode[STIX]{x1D70C}}-1)gd}$ and the characteristic length scale $l_{0}=\sqrt{dL}$ , the mean vertical velocity $\overline{u_{Z}}$ and the frequency $f$ of the oscillations become almost independent of $L/d$ and $Ar$ . The use of the length scale $l_{0}$ and of the gravitational velocity scale to build the Strouhal number $St^{\ast }=fl_{0}/u_{0}$ allowed us to generalize to short ( $0.1\leqslant L/d\leqslant 0.5$ ) and elongated cylinders ( $2\leqslant L/d\leqslant 12$ ), the result $St^{\ast }\simeq 0.1$ . An interpretation of $l_{0}$ as a characteristic length scale associated with the oscillatory recirculation thickness generated near the body ends is proposed. In addition, the rotation rate of the cylinders scales with $u_{0}/L$ , for all $L/d$ and $Ar$ investigated. Furthermore, the phase difference between the oscillations of the velocity component $u$ along the cylinder axis and of the inclination angle $\unicode[STIX]{x1D703}$ of the cylinder is approximately constant, whatever the elongation ratio $L/d$ and the Archimedes number $Ar$ .

Study of the circularity effect on drag of disk-like particles

Article

Sep 2018
INT J MULTIPHAS FLOW

This paper presents a study of the terminal fall velocity, drag coefficient and descent style of ‘wavy-edge’ flat particles. Being highly non-spherical and with a size of up to a few centimeters, these particles show strong self-induced motions that lead to various falling styles that result in distinct drag coefficients. This study is based on experimental measurements of the instantaneous 3D velocity and particle trajectory settling in water. A disk of diameter 30 mm, thickness 1.5 mm and density 1.38 g/cm3 is manufactured as a reference particle. The disk was initially designed to lie within the Galileo number - dimensionless moment of inertia (G-I*) domain corresponding to the fluttering regime. A total of 35 other particles with the same frontal area and material properties were manufactured. These are manufactured to have different amplitudes (a) of the sinusoidal wave on the edge and number of cycles (N) around the entire perimeter. Thus, 5 sets of particles are manufactured with different relative wave amplitudes; i.e. a/D= 0.03, 0.05, 0.1, 0.15, 0.2. Each set consisting of 7 particles from N=4 to N=10. The isoperimetric quotient is used as a measure of the particle circularity and is also linked with different characteristic settling behaviours. Disks and other planar particles with small a/D ratio were found to descent preferably with ‘Planar zig-zag’ behaviour with events of high tilted angle. In contrast, particles with high a/D ratio were found to follow a more uniform descent with low tilted angle to the vertical motion. The differences in projected frontal area were shown not to be sufficient to compensate the differences in descent velocity, leading to unequal drag coefficients. Therefore, we believe that the falling styles of these irregular particles go hand by hand with characteristic wake structures, as shown for disks with various dimensionless moment of inertia, that enhance the descent of particles with low circularity.

Settling behaviour of thin curved particles in quiescent fluid and turbulence

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