Acceleration statistics of heavy particles in turbulence

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

doi:10.1017/s002211200500844x

Cited by 232 publications

(289 citation statements)

References 33 publications

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“…The values for the kurtosis are also in good agreement with the ones reported in the literature for isotropic turbulence at comparable Re λ (see, e.g., the inset of Fig. 2(a) in Bec et al (2006)). Similar trends are observed for the distributions of the velocity components, despite their values are more modest and closer to the ones of the Gaussian distribution.…”

Section: Pdfs Of Velocity and Acceleration Componentssupporting

confidence: 90%

Table-top rotating turbulence: an experimental insight through particle tracking

Castello

Clercx

Trieling

et al. 2009

Springer Proceedings in Physics

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Section: Pdfs Of Velocity and Acceleration Componentssupporting

confidence: 90%

Table-top rotating turbulence: an experimental insight through particle tracking

Castello

Clercx

Trieling

et al. 2009

Springer Proceedings in Physics

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“…These results are supported by the DNS of Bec et al (2006). Nevertheless, the tails are still strongly stretched compared with those of a Gaussian distribution and become increasingly so with increasing R λ .…”

Section: Laboratory Experimentssupporting

confidence: 62%

Droplet growth in warm turbulent clouds

Devenish

Bartello

Brenguier

et al. 2012

Quart J Royal Meteoro Soc

243

281

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In this survey we consider the impact of turbulence on cloud formation from the cloud scale to the droplet scale. We assess progress in understanding the effect of turbulence on the condensational and collisional growth of droplets and the effect of entrainment and mixing on the droplet spectrum. The increasing power of computers and better experimental and observational techniques allow for a much more detailed study of these processes than was hitherto possible. However, much of the research necessarily remains idealized and we argue that it is those studies which include such fundamental characteristics of clouds as droplet sedimentation and latent heating that are most relevant to clouds. Nevertheless, the large body of research over the last decade is beginning to allow tentative conclusions to be made. For example, it is unlikely that small-scale turbulent eddies (i.e. not the energy-containing eddies) alone are responsible for broadening the droplet size spectrum during the initial stage of droplet growth due to condensation. It is likely, though, that small-scale turbulence plays a significant role in the growth of droplets through collisions and coalescence. Moreover, it has been possible through detailed numerical simulations to assess the relative importance of different processes to the turbulent collision kernel and how this varies in the parameter space that is important to clouds. The focus of research on the role of turbulence in condensational and collisional growth has tended to ignore the effect of entrainment and mixing and it is arguable that they play at least as important a role in the evolution of the droplet spectrum. We consider the role of turbulence in the mixing of dry and cloudy air, methods of quantifying this mixing and the effect that it has on the droplet spectrum. Copyright

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“…Here we briefly recall recent results on the statistical properties of acceleration [7]. The main signature of inertia on acceleration can be appreciated from Fig.…”

Section: Resultsmentioning

confidence: 95%

“…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

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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.

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Acceleration statistics of heavy particles in turbulence

Cited by 232 publications

References 33 publications

Table-top rotating turbulence: an experimental insight through particle tracking

Table-top rotating turbulence: an experimental insight through particle tracking

Droplet growth in warm turbulent clouds

Acceleration Statistics of Inertial Particles from High Resolution DNS Turbulence

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