Reduced particle settling speed in turbulence

Fornari, Walter; Picano, Francesco; Sardina, Gaetano; Brandt, Luca

doi:10.1017/jfm.2016.648

Cited by 51 publications

(56 citation statements)

References 36 publications

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“…They are all in good agreement with the results of the present investigation. It is also remarkable that the major features of the PDFs of the total fluctuations of the liquid velocity observed in an array of fixed spheres -namely the exponential tail in the negative vertical direction and the exponential behaviour in the horizontal direction -are similar to those of the PDFs of the velocity of particles sedimenting in a fluid otherwise at rest computed by direct numerical simulations by Fornari, Picano & Brandt (2016a, figure 10) and Fornari et al (2016b), for a low particle volume fraction (α 1 %), a particle to fluid density ratio of 1.02, and a particulate Reynolds number between 150 and 200. This suggests that the particle motions show the signature of a fluid agitation which is similar to that observed in the present work.…”

Section: Probability Density Functions Of Velocity Fluctuationsmentioning

confidence: 62%

Velocity fluctuations generated by the flow through a random array of spheres: a model of bubble-induced agitation

et al. 2017

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To cite this version:Zouhir Amoura, Cédric Besnaci, Frédéric Risso, Véronique Roig. Velocity fluctuations generated by the flow through a random array of spheres: a model of bubble-induced agitation. Journal of Fluid Mechanics, Cambridge University Press (CUP), 2017, 823, pp.592-616. <10.1017/jfm.2017 This work reports an experimental investigation of the flow through a random array of fixed solid spheres. The volume fraction of the spheres is 2 %, and the Reynolds number Re based on the sphere diameter and the average flow velocity is varied from 120 to 1040. Using time and spatial averaging, the fluctuations have been decomposed into two contributions of different natures: a spatial fluctuation that accounts for the strong inhomogeneity of the flow around each sphere, and a time fluctuation that comes from the instability of the flow at large enough Reynolds numbers. The evolutions of these two contributions with the Reynolds number are different, so that their relative importance varies. However, when each is normalized by using its own variance and the integral length scales of the fluctuations, their spectra and probability density functions (PDFs) are almost independent of Re. The spatial fluctuation mostly comes from the velocity deficit in the wakes of the spheres, and is thus dominated by scales larger than one or two sphere diameters. It is found to be responsible for the asymmetry of the PDFs of the vertical fluctuations and of the major part of the anisotropy level between the vertical and the horizontal components of the fluctuations. The time fluctuation dominates at scales smaller than the integral length scale. It is isotropic and its PDFs, well described by an exponential distribution, are non-Gaussian. The spectra of the spatial and the time fluctuations both show an evolution as the power −3 of the wavenumber, but not exactly in the same subrange. All these properties are found in remarkable agreement with the results of both experimental investigations and large eddy simulations (LES) of a homogeneous bubble swarm. This confirms that the main mechanism responsible for the production of bubble-induced fluctuations is the interaction of the velocity disturbances caused by obstacles immersed in a flow and that the structure of this agitation is weakly dependent on the precise nature of the obstacles. The understanding and the modelling of the agitation generated by the motion of a dispersed phase, such as the bubble-induced agitation, therefore require one to distinguish between the roles of these two contributions.

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Section: Probability Density Functions Of Velocity Fluctuationsmentioning

confidence: 62%

Velocity fluctuations generated by the flow through a random array of spheres: a model of bubble-induced agitation

et al. 2017

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“…Fornari et al [17] perform a force analysis which shows that unsteady forces are significant in their parameter range. The analysis in the study of Fornari et al [18] suggests that the horizontal velocity perturbations are mainly responsible for an average drag increase in this low-excess-density and high-turbulence-intensity case, hence causing the reduced settling speed.…”

Section: Introductionmentioning

confidence: 92%

“…Fornari et al [17] and Fornari et al [18] have performed particle-resolved DNS of forced homogeneous-isotropic turbulence with several hundred nearly neutrally-buoyant particles (solidto-fluid density ratio less than 1.04) with a diameter equivalent to approximately 12 Kolmogorov length scales. While particle clustering was not detected, they observed a reduction in the average settling velocity of up to 55% percent at the smallest value of the Galileo number (measuring 19), for which the relative turbulence intensity was approximately 5 times as large as the average settling velocity.…”

Section: Introductionmentioning

confidence: 99%

On the influence of forced homogeneous-isotropic turbulence on the settling and clustering of finite-size particles

Chouippe

Uhlmann

2018

Acta Mech

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We investigate the motion of heavy particles with a diameter of several multiples of the Kolmogorov length scale in the presence of forced turbulence and gravity, resorting to interfaceresolved direct numerical simulation based on an immersed boundary method. The values of the particles' relative density (1.5) and of the Galileo number (180) are such that strong wakeinduced particle clustering would occur in the absence of turbulence [56]. The forced turbulence in the two present cases (with Taylor-scale Reynolds number 95 and 140) would lead to mild levels of clustering in the absence of gravity [55]. Here we detect a tendency to cluster with an intensity (quantified via the standard deviation of the distribution of Voronoï cell volumes) which is intermediate between these two limiting cases, meaning that forced background turbulence decreases the level of clustering otherwise observed under ambient settling. However, the clustering strength does not monotonously decay with the relative turbulence intensity. Various mechanisms by which coherent structures can affect particle motion are discussed. It is argued that the reduced interaction time due to particle settling through the surrounding eddy (crossing trajectories) has the effect of shifting upwards the range of eddies with a time scale matching the characteristic time scale of the particle. In the present cases this shift might bring the particles into resonance with the energetic eddies of the turbulent spectrum. Concerning the average particle settling velocity we find very small deviations (of the order of one percent) from the value obtained for an isolated particle in ambient fluid when defining the relative velocity as an apparent slip velocity (i.e. as the difference between the averages computed separately for the velocities of each phase). This is consistent with simple estimates of the non-linear drag effect. However, the relative velocity based upon the fluid velocity seen by each particle (computed via local averaging over a particle-attached sphere) has on average a smaller magnitude (by 5-7%) than the ambient single-particle value.

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“…These studies show that even for the relatively simple case of small particles settling in turbulence, the role of turbulence on the average particle settling speed is subtle, and a number of issues remain to be solved. Moreover, there are other additional complexities that can modify particle settling speeds in turbulence, including finite particle size effects (Fornari et al 2016), particle-fluid two-way coupling (Monchaux & Dejoan 2017) and collective particle interaction effects (Huck et al 2018), all of which significantly complicate the problem.…”

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confidence: 99%

Multiscale preferential sweeping of particles settling in turbulence

Tom

Bragg

2019

J. Fluid Mech.

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In a seminal article, Maxey (1987, J. Fluid Mech., 174:441-465) 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. (2016b, J. Fluid Mech., 796:659-711) 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 λ . The analysis of Maxey does not explain these issues, partly since it was restricted to particle Stokes numbers St ≪ 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 λ , and show how the saturation of this dependence at sufficiently large R λ 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 coarsegrained 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.

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Reduced particle settling speed in turbulence

Cited by 51 publications

References 36 publications

Velocity fluctuations generated by the flow through a random array of spheres: a model of bubble-induced agitation

Velocity fluctuations generated by the flow through a random array of spheres: a model of bubble-induced agitation

On the influence of forced homogeneous-isotropic turbulence on the settling and clustering of finite-size particles

Multiscale preferential sweeping of particles settling in turbulence

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