Preferential concentration of heavy particles: A Voronoï analysis

By R. Monchaux, M. Bourgoin, A. Cartellier. 2010

317 citations recorded by the source corpus.

We present an experimental characterization of preferential concentration and clustering of inertial particles in a turbulent flow obtained from Voronoi diagram analysis. Several results formerly obtained from various data processing techniques are successfully recovered and further analyzed with Voronoi tesselations as the main single tool. We introduce a simple and nonambiguous way to identify particle clusters. We emphasize the maximum preferential concentration for particles with Stokes numbers around unity and the self-similar nature of clustering and we report new unpredicted results concerning clusters inner concentration dependence on Stokes number and global seeding density. Some of these experimental observations can be consistently interpreted in the context of the so-called sweep-stick mechanism. Finally, we stress the great potential of Voronoi analysis that offers important openings for new investigations of particle laden flows in terms, for instance, of simultaneous Lagrangian statistics of particle dynamics and local concentration field.

Subfields: Computational Mechanics, Earth-Surface Processes, Ocean Engineering

View Paper: https://www.semanticscholar.org/paper/6457eeda12907c7c15378eaab0adcf967559a8f5

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Citations in the corpus

Direct numerical simulation of horizontal open channel flow with finite-size, heavy particles at low solid volume fraction (2013, methodology): “Voronoi diagram analysis is widely utilized in many scientific areas and has been introduced as a tool for the analysis of preferential particle concentration in turbulent flows (Monchaux et al., 2010, 2012).”
Bubbly and Buoyant Particle–Laden Turbulent Flows (2020, methodology): “…et al. (2008b) using the KaplanYorke dimension and Minkowski functionals, while others have used Voronoï tessellations (Fiabane et al. 2012; Monchaux et al. 2010; Obligado et al. 2014; Tagawa et al. 2012) or simply the relative particle concentration in high vorticity flow regions…”
Exact regularized point particle method for multiphase flows in the two-way coupling regime (2014, background): “In these conditions the Stokes number Stη = τp/τη controls the dynamics of the disperse phase in terms of its preferential spatial accumulation, either small scale clustering in homogeneous flows [42, 28, 4, 29, 37] or turbophoresis in wall bounded flows [34, 25].”
Droplet growth in warm turbulent clouds (2012, unknown): “By analysing Voronoi diagrams of wind tunnel data, Monchaux et al. (2010) also find that clustering peaks at St ∼ 1.”
Analyzing preferential concentration and clustering of inertial particles in turbulence (2012, methodology): “The second approach based on the concentration along the particle trajectory is better adapted to experiments, in particular, and as shown by Monchaux et al. (2010), it can be implemented with the above described Voronoï analysis.”
Sedimentation of a dilute suspension of rigid spheres at intermediate Galileo numbers: the effect of clustering upon the particle motion (2014, methodology): “Monchaux et al. (2010a) have used the standard deviation of the p.d.f. of the normalized Voronöı cell volumes in order to quantify the particles’ tendency to cluster.”
The effect of Reynolds number on inertial particle dynamics in isotropic turbulence. Part 1. Simulations without gravitational effects (2015, unknown): “A variety of measures have been proposed to study particle clustering, including Voronöı diagrams (Monchaux et al. 2010), Lyapunov exponents (Bec et al.”