Voronoi analysis of beads suspended in a turbulent square channel flow

Rabencov, B.; Hout, R. van

doi:10.1016/j.ijmultiphaseflow.2014.09.007

Cited by 14 publications

(10 citation statements)

References 19 publications

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“…Similar to the cases in HIT and TCF (Monchaux et al. 2010; Rabencov & van Hout 2015), the –p.d.f. profiles are compared with a random Poisson process (RPP) that has the approximate analytical expression As shown in figure 3( a ), there are always two intersections between the profiles of p.d.f.…”

Section: Voronoï Analysis Of Particle Structuressupporting

confidence: 76%

“…2017). As for two-phase wall-bounded turbulence, only Rabencov & van Hout (2015) reported a power-law scaling of particle clusters’ area distribution in TCF. The present observed -scaling and power law clearly indicate a self-similarity of the scales of particle clusters.…”

Section: Voronoï Analysis Of Particle Structuresmentioning

confidence: 99%

“…2017; Sumbekova et al. 2017) and turbulent channel flows (TCFs) (Rabencov & van Hout 2015; Yuan et al. 2018).…”

Section: Introductionmentioning

confidence: 99%

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Attached eddy-like particle clustering in a turbulent boundary layer under net sedimentation conditions

et al. 2021

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Section: Voronoï Analysis Of Particle Structuressupporting

confidence: 76%

Section: Voronoï Analysis Of Particle Structuresmentioning

confidence: 99%

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Attached eddy-like particle clustering in a turbulent boundary layer under net sedimentation conditions

et al. 2021

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“…The value A * , below which the probability of finding sub-average cell areas is higher than in a Poisson process, is usually taken as the threshold for particles to be considered clustered (Monchaux et al 2010, Rabencov & van Hout 2015, Sumbekova et al 2017. Individual clusters are then defined as connected groups of such particles, as shown in figure 3a.…”

Section: Voronoï Tessellation and Cluster Identificationmentioning

confidence: 99%

Experimental study of inertial particles clustering and settling in homogeneous turbulence

2019

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We study experimentally the spatial distribution, settling, and interaction of sub-Kolmogorov inertial particles with homogeneous turbulence. Utilizing a zero-mean-flow air turbulence chamber, we drop size-selected solid particles and study their dynamics with particle imaging and tracking velocimetry at multiple resolutions. The carrier flow is simultaneously measured by particle image velocimetry of suspended tracers, allowing the characterization of the interplay between both the dispersed and continuous phases. The turbulence Reynolds number based on the Taylor microscale ranges from Re λ ≈ 200 -500, while the particle Stokes number based on the Kolmogorov scale varies between St η = O(1) and O(10). Clustering is confirmed to be most intense for St η ≈ 1, but it extends over larger scales for heavier particles. Individual clusters form a hierarchy of self-similar, fractal-like objects, preferentially aligned with gravity and sizes that can reach the integral scale of the turbulence. Remarkably, the settling velocity of St η ≈ 1 particles can be several times larger than the still-air terminal velocity, and the clusters can fall even faster. This is caused by downward fluid fluctuations preferentially sweeping the particles, and we propose that this mechanism is influenced by both large and small scales of the turbulence. The particle-fluid slip velocities show large variance, and both the instantaneous particle Reynolds number and drag coefficient can greatly differ from their nominal values. Finally, for sufficient loadings, the particles generally augment the small-scale fluid velocity fluctuations, which however may account for a limited fraction of the turbulent kinetic energy.

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“…Using our DNS data, we perform a 3D Voronoï analysis of the particles, and then compute a range of statistical quantities using the information from the analysis. In order to address the issue of open Voronoï cells at the boundaries of the domain, the particles across the boundaries are periodically repeated to ensure that all the cells are closed and the sum of Voronoï volumes is equal to the domain volume ( [42,43,44]). Therefore, the Voronoï volumes associated with the particles adjacent to the boundaries are ill-defined and so are ignored in our analysis.…”

Section: Computational Detailsmentioning

confidence: 99%

Local analysis of the clustering, velocities, and accelerations of particles settling in turbulence

Momenifar

Bragg

2020

Phys. Rev. Fluids

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Using 3D Voronoï analysis, we explore the local dynamics of small, settling, inertial particles in isotropic turbulence using Direct Numerical Simulations (DNS). We independently vary the Taylor Reynolds number R λ ∈ [90, 398], Froude number F r ≡ a η /g ∈ [0.052, ∞] (where a η is the Kolmogorov acceleration, and g is the acceleration due to gravity), and Kolmogorov scale Stokes number St ≡ τ p /τ η ∈ [0, 3]. In agreement with previous results using global measures of particle clustering, such as the Radial Distribution Function (RDF), we find that for small Voronoï volumes (corresponding to the most clustered particles), the behavior is strongly dependent upon St and F r, but only weakly dependent upon R λ , unless St > 1. However, larger Voronoï volumes (void regions) exhibit a much stronger dependence on R λ , even when St ≤ 1, and we show that this, rather than the behavior at small volumes, is the cause of the sensitivity of the standard deviation of the Voronoï volumes that has been previously reported. We also show that the largest contribution to the particle settling velocities is associated with increasingly larger Voronoï volumes as the settling parameter Sv ≡ St/F r is increased.Our local analysis of the acceleration statistics of settling inertial particles shows that clustered particles experience a net acceleration in the direction of gravity, while particles in void regions experience the opposite. The particle acceleration variance, however, is a convex function of the Voronoï volumes, with or without gravity, which seems to indicate a non-trivial relationship between the Voronoï volumes and the sizes of the turbulent flow scales. Results for the variance of the fluid acceleration at the inertial particle positions are of the order of the square of the Kolmogorov acceleration and depend only weakly on Voronoï volumes. These results call into question the "sweep-stick" mechanism for particle clustering in turbulence which would lead one to expect that clustered particles reside in the special regions where the fluid acceleration is zero (or at least small).We then consider the properties of particles in clusters, which are regions of connected Voronoï cells whose volume is less than a certain threshold. The results show self-similarity of the clusters, and that the statistics of the cluster volumes depends only weakly on St, with a stronger dependance on F r and R λ . Finally, we compare the average settling velocities of all particles in the flow with those in clusters, and show that those in the clusters settle much faster, in agreement with previous work. However, we also find that this difference grows significantly with increasing R λ and exhibits a non-monotonic dependence on F r. The kinetic energy of the particles, however, are almost the

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Voronoi analysis of beads suspended in a turbulent square channel flow

Cited by 14 publications

References 19 publications

Attached eddy-like particle clustering in a turbulent boundary layer under net sedimentation conditions

Attached eddy-like particle clustering in a turbulent boundary layer under net sedimentation conditions

Experimental study of inertial particles clustering and settling in homogeneous turbulence

Local analysis of the clustering, velocities, and accelerations of particles settling in turbulence

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