Droplet collisions and interaction with the turbulent flow within a two-phase wind tunnel

Bordás, Róbert; Hagemeier, Thomas; Wunderlich, Bernd; Thévenin, Dominique

doi:10.1063/1.3609275

Cited by 18 publications

(17 citation statements)

References 55 publications

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“…It has been proposed that inertial clustering of particles in turbulence is the result of particles being centrifuged out of regions of high fluid vorticity (highly rotating) as a result of their inertia and thus preferentially concentrating in the regions of high strain. In fact, evidence of inertial particles preferentially concentrating in regions of low vorticity and high strain is abundant (see, e.g., [9][10][11][12][13][14][15][16][17][18][19][20]). The detailed dependence of clustering on particle inertia and spatial scale, however, is still a subject of investigation.…”

Section: Theories and Quantification Of Inertial Clusteringmentioning

confidence: 99%

Spatial clustering of polydisperse inertial particles in turbulence: I. Comparing simulation with theory

et al. 2012

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Particles that are heavy compared to the fluid in which they are embedded (inertial particles) tend to cluster in turbulent flow, with the degree of clustering depending on the particle Stokes number. The phenomenon is relevant to a variety of systems, including atmospheric clouds; in most realistic systems particles have a continuous distribution of sizes and therefore the clustering of 'polydisperse' particle populations is of special relevance. In this work a theoretical expression for the radial distribution function (RDF) for mono-and bidisperse inertial particles in the low Stokes number limit (Chun et al 2005 J. Fluid Mech. 536 219-51) is compared with the results of a direct numerical simulation of particle-laden turbulence. The results confirm the power-law form of the RDF for monodisperse particles with St 0.3. The clustering signature occurs at scales 10-30 times the Kolmogorov scale, consistent with a dissipation-scale mechanism. The theory correctly predicts the decorrelation 5 International Collaboration for Turbulence Research 6

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Section: Theories and Quantification Of Inertial Clusteringmentioning

confidence: 99%

Spatial clustering of polydisperse inertial particles in turbulence: I. Comparing simulation with theory

et al. 2012

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“…Yoshimatsu et al (2009) reported that phase-shuffled turbulence does not preserve the acceleration's scaling behaviour, which implies that the acceleration physics, which are of central importance in particle clustering and collisions, are different from Navier-Stokes turbulence. Chen et al (2006) reported that, in kinematic simulations of turbulence, particle clustering results from the repelling action of velocity stagnation-point clusters, a clustering mechanism that is very different from those in Navier-Stokes turbulence. These facts suggest that synthetic simulations of turbulence are not the best option for a comparative discussion of the effect of intermittency on particle clustering and resulting Reynolds number dependences.…”

Section: Introductionmentioning

confidence: 96%

“…Those parameters are usually determined by direct numerical simulation (DNS) data. Data from laboratory experiments (Saw et al 2008;Lu et al 2010;Bordas et al 2011) would, of course, help, but available data are very limited.…”

Section: Introductionmentioning

confidence: 97%

“…Another option would have been to employ a synthetic flow simulation, such as a phase-shuffled simulation (Yoshimatsu et al 2009) or a kinematic simulation (Chen, Goto & Vassilicos 2006;Goto et al 2005, and references therein). The phase-shuffled flow can be obtained by decomposing the DNS velocity field into Fourier modes and randomizing the phases of the coefficients.…”

Section: Introductionmentioning

confidence: 99%

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Collision statistics of inertial particles in two-dimensional homogeneous isotropic turbulence with an inverse cascade

Onishi

Vassilicos

2014

J. Fluid Mech.

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This study investigates the collision statistics of inertial particles in inverse-cascading two-dimensional (2D) homogeneous isotropic turbulence by means of a direct numerical simulation (DNS). A collision kernel model for particles with small Stokes number (St) in 2D flows is proposed based on the model of Saffman & Turner (J. Fluid Mech., vol. 1, 1956, pp. 16-30) (ST56 model). The DNS results agree with this 2D version of the ST56 model for St 0.1. It is then confirmed that our DNS results satisfy the 2D version of the spherical formulation of the collision kernel. The fact that the flatness factor stays around 3 in our 2D flow confirms that the present 2D turbulent flow is nearly intermittency-free. Collision statistics for St = 0.1, 0.4 and 0.6, i.e. for St < 1, are obtained from the present 2D DNS and compared with those obtained from the three-dimensional (3D) DNS of Onishi et al. (J. Comput. Phys., vol. 242, 2013, pp. 809-827). We have observed that the 3D radial distribution function at contact (g(R), the so-called clustering effect) decreases for St = 0.4 and 0.6 with increasing Reynolds number, while the 2D g(R) does not show a significant dependence on Reynolds number. This observation supports the view that the Reynolds-number dependence of g(R) observed in three dimensions is due to internal intermittency of the 3D turbulence. We have further investigated the local St, which is a function of the local flow strain rates, and proposed a plausible mechanism that can explain the Reynolds-number dependence of g(R). Meanwhile, 2D stochastic simulations based on the Smoluchowski equations for St 1 show that the collision growth can be predicted by the 2D ST56 model and that rare but strong events do not play a significant role in such a small-St particle system. However, the probability density function of local St at the sites of colliding particle pairs supports the view that powerful rare events can be important for particle growth even in the absence of internal intermittency when St is not much smaller than unity.

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“…Hence, the present work is focused on that aspect: can current theoretical expressions for the collision rate of particles in turbulence and under the influence of gravity, account quantitatively for measured collision rates in a controlled laboratory experiment? This work is an extension of [2], in which a single measurement technique has been employed for a slightly different configuration and compared with classical theoretical correlations. The results have revealed noticeable differences between measurements and theory.…”

Section: Introductionmentioning

confidence: 99%

Experimental determination of droplet collision rates in turbulence

et al. 2013

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Inter-particle collisions in turbulent flows are of central importance for many engineering applications and environmental processes. For instance, collision and coalescence is the mechanism for warm rain initiation in cumulus clouds, a still poorly understood issue. This work presents measurements of droplet-droplet interactions in a laboratory turbulent flow, allowing reproducibility and control over initial and boundary conditions. The measured two-phase flow reproduces conditions relevant to cumulus clouds. The turbulent flow and the droplet size distribution are well characterized, and independently the collision rate is measured. Two independent experimental approaches for determining the collision rate are compared with each other: (i) a highmagnification shadowgraphy setup is employed, applying a deformation threshold as collision indicator. This technique has been specifically adapted to measure droplet collision probability in dispersed two-phase flows. (ii) Corresponding results are compared for the first time with a particle tracking approach, post-processing high-speed shadowgraphy image sequences. Using the measured turbulence and droplet properties, the turbulent collision kernel can be calculated for comparison. The two independent measurements deliver comparable orders of magnitude for the collision probability, highlighting the quality of the measurement process, even if the comparison between both

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Droplet collisions and interaction with the turbulent flow within a two-phase wind tunnel

Cited by 18 publications

References 55 publications

Spatial clustering of polydisperse inertial particles in turbulence: I. Comparing simulation with theory

Spatial clustering of polydisperse inertial particles in turbulence: I. Comparing simulation with theory

Collision statistics of inertial particles in two-dimensional homogeneous isotropic turbulence with an inverse cascade

Experimental determination of droplet collision rates in turbulence

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