Dynamics and statistics of heavy particles in turbulent flows

Cencini, Massimo; Bec, Jérémie; Biferale, Luca; Boffetta, G.; Celani, Antonio; Lanotte, Alessandra S.; Musacchio, Stefano; Toschi, Federico

doi:10.1080/14685240600675727

Cited by 74 publications

(62 citation statements)

References 50 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…However, this picture is not valid for developed turbulence at a higher Reynolds number, and the clustering is not a single-scale phenomenon but has a multiscale nature [5][6][7]. This is because not only the smallest-scale but also multiscale coherent eddies in developed turbulence play a role in the preferential concentration, and therefore clusters differ significantly in space from the locations of low-vorticity regions.On the other hand, it has been pointed out [7][8][9][10][11] that the clusterings of heavy particles and fluid acceleration are strongly related. Especially, Refs.…”

mentioning

confidence: 99%

See 1 more Smart Citation

Sweep-Stick Mechanism of Heavy Particle Clustering in Fluid Turbulence

2008

View full text Add to dashboard Cite

It is proposed that the inertial range clustering of small heavy particles in fluid turbulence occurs as a result of the sweep-stick mechanism which causes inertial particles to cluster so as to mimic the clusters of points where the fluid acceleration is perpendicular to the direction of highest contraction between neighboring particles. Direct numerical simulations of inertial particles subjected to linear Stokes drag and suspended in homogeneous isotropic turbulence support the validity of the sweep and stick properties on which the sweep-stick mechanism is based, and also support the clustering consequences of this mechanism. It also explains the observed Stokes-number dependence of inertial particle clustering. DOI: 10.1103/PhysRevLett.100.054503 PACS numbers: 47.27.ÿi, 47.10.ÿg Turbulence spreads suspended impurities, but it can also bring them together to form clusters. For example, bubbles, which are much lighter than the surrounding fluid, may be used to visualize eddies (see, e.g., [1]), since they tend to accumulate along the center line of swirls. It is also well known [2 -4] that particles heavier than the surrounding fluid cluster in turbulence. This phenomenon, sometimes called preferential concentration, is crucial in various processes where the particle collision rate is a significant factor (such as combustion or chemical reaction in turbulence, raindrop growth in clouds, planet formation in the early solar system, etc.). Thus, it has been studied extensively in many areas of physics and mechanics.In turbulence at a relatively low Reynolds number, the heavy particle clustering is due to the action of the smallest-scale (i.e. the Kolmogorov length ) eddies. Specifically, heavy particles are centrifuged out of the coherent eddies, and accumulate in low-vorticity (highstrain-rate) regions. However, this picture is not valid for developed turbulence at a higher Reynolds number, and the clustering is not a single-scale phenomenon but has a multiscale nature [5][6][7]. This is because not only the smallest-scale but also multiscale coherent eddies in developed turbulence play a role in the preferential concentration, and therefore clusters differ significantly in space from the locations of low-vorticity regions.On the other hand, it has been pointed out [7][8][9][10][11] that the clusterings of heavy particles and fluid acceleration are strongly related. Especially, Refs. [7,9] claim that the spatial distribution of heavy particles reflects that of the stagnation points of the fluid acceleration in twodimensional inverse-energy cascading turbulence. Here, we extend this picture to three-dimensional turbulence by extending and refining the sweep-stick mechanism proposed (but not named) in [7,9] to three-dimensional turbulence.In what follows, we deal with the clustering of heavy particles suspended in statistically stationary homogeneous isotropic turbulence (HIT), u x; t . We assume that only the Stokes drag drives the motion of the particles, and the equation of motion for a particle (the veloc...

show abstract

mentioning

confidence: 99%

“…On the other hand, it has been pointed out [7][8][9][10][11] that the clusterings of heavy particles and fluid acceleration are strongly related. Especially, Refs.…”

mentioning

confidence: 99%

Sweep-Stick Mechanism of Heavy Particle Clustering in Fluid Turbulence

2008

View full text Add to dashboard Cite

show abstract

“…͑1͒ for about 2 to 3 large-scale eddy turnover times before reaching a Lagrangian statistical steady state ͑see Ref. 24 for a detailed study of the transients͒. Once the particle dynamics has completely relaxed the measurements are started.…”

mentioning

confidence: 99%

Effects of vortex filaments on the velocity of tracers and heavy particles in turbulence

et al. 2006

View full text Add to dashboard Cite

show abstract

“…for the acceleration, the convolution of the acceleration measured for a give Stokes with the relative probability to find such a Stokes particle. Analysis in this direction has beet attempted in [8]. [6] and numerical data (solid line) at St = 0.16 from [7,8].…”

Section: Resultsmentioning

confidence: 99%

Acceleration Statistics of Inertial Particles from High Resolution DNS Turbulence

Toschi

Bec

Biferale

et al. 2008

IUTAM Symposium on Computational Physics and New Perspectives in Turbulence

View full text Add to dashboard Cite

Abstract. We present results from recent direct numerical simulations of heavy particle transport in homogeneous, isotropic, fully developed turbulence, with grid resolution up to 512 3 and R λ ≈ 185. By following the trajectories of millions of particles with different Stokes numbers, St ∈ [0.16 : 3.5], we are able to characterize in full detail the statistics of particle acceleration. We focus on the probability density function of the normalised acceleration a/arms and on the behaviour of their rootmean-squared acceleration arms as a function of both St and R λ . We explain our findings in terms of two concurrent mechanisms: particle clustering, very effective for small St, and filtering induced by finite particle response time, taking over at larger St.

show abstract

Dynamics and statistics of heavy particles in turbulent flows

Cited by 74 publications

References 50 publications

Sweep-Stick Mechanism of Heavy Particle Clustering in Fluid Turbulence

Sweep-Stick Mechanism of Heavy Particle Clustering in Fluid Turbulence

Effects of vortex filaments on the velocity of tracers and heavy particles in turbulence

Acceleration Statistics of Inertial Particles from High Resolution DNS Turbulence

Contact Info

Product

Resources

About