Dynamics of small heavy particles in homogeneous turbulence: a Lagrangian experimental study

Berk, Tim; Coletti, Filippo

doi:10.1017/jfm.2021.280

Cited by 30 publications

(41 citation statements)

References 87 publications

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“…This applies in particular to the particle's acceleration which remains non-differentiable under the assumption of a simple exponential correlation function for the Lagrangian velocity, in contrast to empirical evidence which shows smooth behavior. These limitations have also been discussed recently in the broader context of particle settling in turbulent flows [34].…”

Section: Introductionmentioning

confidence: 89%

Single inertial particle statistics in turbulent flows from Lagrangian velocity models

Friedrich¹,

B.²,

Bourgoin³

et al. 2021

Preprint

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We present the extension of a modeling technique for Lagrangian tracer particles [B. Viggiano et al., J. Fluid Mech.(2020), vol. 900, A27] which accounts for the effects of particle inertia. Thereby, the particle velocity for several Stokes numbers is modeled directly by a multi-layered Ornstein-Uhlenbeck process and a comparison of key statistical quantities (second-order velocity structure function, acceleration correlation function, and root mean square acceleration) to expressions derived from Batchelor's model as well as to direct numerical simulations (DNS) is performed. In both approaches, Stokes' drag is treated by an approximate "linear filter" which replaces the particle position entering the fluid velocity field by the corresponding ideal tracer position. Effects of preferential concentration of inertial particles are taken into account in terms of an effective Stokes number that is determined from the zero crossing of the acceleration correlation function from DNS. This approximation thus allows the modeling of inertial particle statistics through stochastic methods and models for the Lagrangian velocity; the particle velocity is effectively decoupled from the particle position. In contrast to the ordinary filtering technique [Cencini et al., J. Turbul. (2006), 7, N36], our method captures the effects of preferential concentration of particles at low Stokes numbers which manifest themselves for instance by a sharp decrease of the acceleration variance for increasing Stokes numbers.

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Section: Introductionmentioning

confidence: 89%

Single inertial particle statistics in turbulent flows from Lagrangian velocity models

Friedrich¹,

B.²,

Bourgoin³

et al. 2021

Preprint

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show abstract

“…Petersen et al. (2019) and Berk & Coletti (2021) used this facility to investigate clustering and settling of inertial particles, and we adopt a similar set-up. The inertial particles (size-selected spherical glass micro-beads of density kg m) are dropped through a 3 m vertical chute and enter the chamber through a 152 mm circular opening in the ceiling.…”

Section: Methodsmentioning

confidence: 99%

“…the finite response time to fluid fluctuations, quantified by ) and gravity (i.e. the drift through the flow with crossing of fluid trajectories, quantified by ) are known to have competing effects on dispersion (Wang & Stock 1993; Berk & Coletti 2021); but the way their balance affects the turbulence is poorly understood. In a unique microgravity experiment, Hwang & Eaton (2006 b ) found that turbulence attenuation was stronger than in terrestrial gravity, pointing to the role of the particle potential energy in the fluid energy balance (Hwang & Eaton 2006 a ).…”

Section: Introductionmentioning

confidence: 99%

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Scale-to-scale turbulence modification by small settling particles

Hassaini

Coletti

2022

J. Fluid Mech.

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Despite decades of investigations, there is still no consensus on whether inertial particles augment or dampen turbulence. Here, we perform the first experimental study in which the particle concentration is varied systematically across a broad range of volume fractions $\varPhi _{v}$ , from nominally one-way coupled to heavily two-way coupled regimes, keeping all other parameters constant. We utilize a zero-mean flow chamber where steady, homogeneous and approximately isotropic air turbulence is realized, with a Taylor-microscale Reynolds number $Re_{\lambda } = 150\unicode{x2013}300$ . We consider spherical solid particles of two sizes, both much smaller than the Kolmogorov length, and yielding Stokes numbers $St_{\eta } = 0.3$ and 2.6 based on the Kolmogorov time scale. By adjusting the turbulent intensity, the settling velocity parameter is kept constant for both cases, $Sv_{\eta } = V_{t}/u_{\eta }\approx 3$ (where $V_{t}$ is the still-air terminal velocity, and $u_{\eta }$ is the Kolmogorov velocity scale). Unlike previous studies focused on massively inertial particles, we find that the turbulent kinetic energy increases with particle loading, being more than doubled at $\varPhi _{v} =5\times 10^{-5}$ . This is attributed to the energy input associated with gravitational settling: the particles release their potential energy into the fluid and increase its dissipation rate, while the time scale associated with the inter-scale energy transfer is not strongly changed. Two-point statistics indicate that the energy-containing eddies become vertically elongated in the presence of falling particles, and that the latter redistribute the energy more homogeneously across the scales compared to unladen turbulence. This is rooted in an enhanced cascade, as shown by the nonlinear inter-scale energy transfer rate.

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“…of invariants of the velocity gradient tensor near the wall. Lagrangian techniques have also been applied to study the collective particle dynamics by Berk & Coletti (2021).…”

Section: Identifying Particle Clustersmentioning

confidence: 99%

Spatial detection and hierarchy analysis of large-scale particle clusters in wall-bounded turbulence

2022

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Large-scale inertial particle clustering in a turbulent boundary layer (TBL) was investigated experimentally by two-colour particle-image velocimetry and particle-tracking velocimetry measurements in the wall-parallel plane of the log layer. The particle clusters were detected by Voronoi tessellation and a new application of a technique based on the spatial wavelet transform. Anisotropic wavelets spanning the range of measurable, large-scale particle clusters were applied to experimentally measured particle fields, and significance testing was used to identify hierarchies of particle clusters. Unlike the Voronoi tessellation, which primarily identified small-scale clusters, the wavelet technique also found a significant amount of anisotropic, large-scale clusters on the scale of the large-scale motions (LSMs) of the momentum field. The large-scale clusters were shown to be composed of a hierarchy of smaller clusters of varying degrees of isotropy. In addition to the cluster size distribution, the particle velocities within the clusters were studied as a function of cluster size. Larger clusters exhibited faster particle convection speeds, consistent with observations of the convection speeds of LSMs, thus providing additional evidence for the hypothesis that particles in the TBL accumulate on and are transported by large-scale, attached coherent structures.

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Dynamics of small heavy particles in homogeneous turbulence: a Lagrangian experimental study

Abstract: Abstract

Cited by 30 publications

References 87 publications

Single inertial particle statistics in turbulent flows from Lagrangian velocity models

Single inertial particle statistics in turbulent flows from Lagrangian velocity models

Scale-to-scale turbulence modification by small settling particles

Spatial detection and hierarchy analysis of large-scale particle clusters in wall-bounded turbulence

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