Clustering and preferential concentration of finite-size particles in forced homogeneous-isotropic turbulence

Abstract

We have performed interface-resolved direct numerical simulations of forced homogeneousisotropic turbulence in a dilute suspension of spherical particles in the Reynolds number range Re λ = 115 − 140. The solid-fluid density ratio was set to 1.5, gravity was set to zero, and two particle diameters were investigated corresponding to approximately 5 and 11 Kolmogorov lengths. Note that these particle sizes are clearly outside the range of validity of the point-particle approximation, as has been shown by Homann & Bec (2010). At the present parameter points the global effect of the particles upon the fluid flow is weak. We observe that the dispersed phase exhibits clustering with moderate intensity. The tendency to cluster, which was quantified in terms of the standard deviation of Voronoï cell volumes, decreases with the particle diameter. We have analyzed the relation between particle locations and the location of intense vortical flow structures. The results do not reveal any significant statistical correlation. Contrarily, we have detected a small but statistically significant preferential location of particles with respect to the 'sticky points' proposed by Goto & Vassilicos (2008), i.e. points where the fluid acceleration field is acting such as to increase the local particle concentration in one-way coupled point-particle models under Stokes drag. The presently found statistical correlation between the 'sticky points' and the particle locations further increases when focusing on regions with high local concentration. Our results suggest that small finite-size particles can be brought together along the expansive directions of the fluid acceleration field, as previously observed only for the simplest model for sub-Kolmogorov particles. We further discuss the effect of density ratio and collective particle motion upon the basic Eulerian and Lagrangian statistics.

Pitfalls Measuring 1D Inertial Particle Clustering

“…the peak shifts with decreasing concentration as expected. The peak location is also close to previous reported characteristic cluster sizes obtained by means of 2DVOA [32,33,2], and 3DVOA [34]. However, it depends on Re λ , as these and previous studies shown.…”

“…It also suggests that a commonly-used cluster detection algorithm [18] would find power law behavior when applied to a random set, not only in 1D but in higher dimensions. Previous works [46,34,8] have reported this power law behavior for 3DVOA applied on a finite size RPP-3D, but did not completely explain its…”

Modeling the effects of small turbulent scales on the drag force for particles below and above the Kolmogorov scale

“…As pointed out in Refs. [56,57], the point-particle approximation with the usual drag law is clearly not valid for these sizes of particle. The results from the LES with the model are compared with experimental results from Refs.…”

“…[56,57] for large particles dominantly swept by the large scales of the flow. Of course, this limit is beyond the validity of the "large pointwise" particle approach considered in this paper.…”

An infrared scattering by evaporating droplets at the initial stage of a pool fire suppression by water sprays

“…It is also interesting that turbulence can not only mitigate the particle collection. On the contrary, the transient effect of the so-called ''preferential concentration" of particles with Stokes number about unity may be significant even in the homogeneous and isotropic turbulence [22][23][24].…”