Pair dispersion and preferential concentration of particles in isotropic turbulence

Zaichik, L. I.; Alipchenkov, V. M.

doi:10.1063/1.1569485

Cited by 147 publications

(123 citation statements)

References 23 publications

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“…In either case it involves the compressibility of the particle flow field along a particle trajectory. In contrast, the form derived by Zaichik and Alipchenkov (2003) is based on the droplet momentum equation (in the frame of reference moving with a colliding droplet) and in particular a force balance between the drag and the particle kinetic stresses. That is, given a uniform concentration of particles in an inhomogeneous flow, there would be a force acting on the particles due to gradients of the radial kinetic stresses.…”

Section: Droplet Clusteringmentioning

confidence: 99%

“…For St 1, both Chun et al (2005) and Zaichik and Alipchenkov (2003) predict that g(r) ∼ r −αSt 2 , although the values of the constantα differ. This reflects a fundamental difference between the two approaches.…”

Section: Droplet Clusteringmentioning

confidence: 99%

“…Neither Chun et al (2005) nor Zaichik and Alipchenkov (2003) take gravitational settling into account, which may decrease droplet clustering as it reduces the interaction time of a droplet with the turbulent eddies. This has been observed in DNS for sedimenting droplets (Vaillancourt et al, 2002;Wang et al, 2006a;Franklin et al, 2007;Ayala et al, 2008a).…”

Section: Droplet Clusteringmentioning

confidence: 99%

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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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Section: Droplet Clusteringmentioning

confidence: 99%

Section: Droplet Clusteringmentioning

confidence: 99%

Section: Droplet Clusteringmentioning

confidence: 99%

See 1 more Smart Citation

Droplet growth in warm turbulent clouds

Devenish

Bartello

Brenguier

et al. 2012

Quart J Royal Meteoro Soc

243

281

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“…8. We conclude this Section by noticing that in time-correlated random smooth flows, as well as in developed turbulence, the dimension deficit has been shown to be ∝ St 2 [5,11,39,40]. Therefore, including temporal correlations seems to be crucial to reproduce the details of the small-Stokes statistics of turbulent suspensions.…”

Section: Small Stokes Number Asymptoticsmentioning

confidence: 99%

Stochastic suspensions of heavy particles

Bec

Cencini

Hillerbrand

et al. 2008

Physica D: Nonlinear Phenomena

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Turbulent suspensions of heavy particles in incompressible flows have gained much attention in recent years. A large amount of work focused on the impact that the inertia and the dissipative dynamics of the particles have on their dynamical and statistical properties. Substantial progress followed from the study of suspensions in model flows which, although much simpler, reproduce most of the important mechanisms observed in real turbulence. This paper presents recent developments made on the relative motion of a pair of particles suspended in time-uncorrelated and spatially self-similar Gaussian flows. This review is complemented by new results. By introducing a time-dependent Stokes number, it is demonstrated that inertial particle relative dispersion recovers asymptotically Richardson's diffusion associated to simple tracers. A perturbative (homogeneization) technique is used in the small-Stokes-number asymptotics and leads to interpreting first-order corrections to tracer dynamics in terms of an effective drift. This expansion implies that the correlation dimension deficit behaves linearly as a function of the Stokes number. The validity and the accuracy of this prediction is confirmed by numerical simulations.

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“…The collision-related relative motions and pair distribution of heavy particles with the Stokes numbers ͑St K ϵ p / K , i.e., the ratio of heavy particle response time to flow Kolmogorov time͒ on the order of 1 is mainly determined by the smallscale eddies. [18][19][20] These particle-pair statistics and thus collision rate of heavy particles are unlikely to be properly simulated in LES. This is one of the main challenges in LES of particle-laden turbulent flows.…”

Section: Introductionmentioning

confidence: 99%

Large-eddy simulation of turbulent collision of heavy particles in isotropic turbulence

Jin

Wang

2010

Physics of Fluids

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The small-scale motions relevant to the collision of heavy particles represent a general challenge to the conventional large-eddy simulation ͑LES͒ of turbulent particle-laden flows. As a first step toward addressing this challenge, we examine the capability of the LES method with an eddy viscosity subgrid scale ͑SGS͒ model to predict the collision-related statistics such as the particle radial distribution function at contact, the radial relative velocity at contact, and the collision rate for a wide range of particle Stokes numbers. Data from direct numerical simulation ͑DNS͒ are used as a benchmark to evaluate the LES using both a priori and a posteriori tests. It is shown that, without the SGS motions, LES cannot accurately predict the particle-pair statistics for heavy particles with small and intermediate Stokes numbers, and a large relative error in collision rate ͑up to 60%͒ may arise when the particle Stokes number is near St K = 0.5. The errors from the filtering operation and the SGS model are evaluated separately using the filtered-DNS ͑FDNS͒ and LES flow fields. The errors increase with the filter width and have nonmonotonic variations with the particle Stokes numbers. It is concluded that the error due to filtering dominates the overall error in LES for most particle Stokes numbers. It is found that the overall collision rate can be reasonably predicted by both FDNS and LES for St K Ͼ 3. Our analysis suggests that, for St K Ͻ 3, a particle SGS model must include the effects of SGS motions on the turbulent collision of heavy particles. The spectral analysis of the concentration fields of the particles with different Stokes numbers further demonstrates the important effects of the small-scale motions on the preferential concentration of the particles with small Stokes numbers.

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Pair dispersion and preferential concentration of particles in isotropic turbulence

Cited by 147 publications

References 23 publications

Droplet growth in warm turbulent clouds

Droplet growth in warm turbulent clouds

Stochastic suspensions of heavy particles

Large-eddy simulation of turbulent collision of heavy particles in isotropic turbulence

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