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1. Clustering of inertial particles in turbulent flow through a porous unit cell

   Apte, SV; Oujia, T; Matsuda, K; Kadoch, B; He, X; Schneider, K (February 2022, Journal of fluid mechanics)

   Direct numerical simulation is used to investigate effects of turbulent flow in the confined geometry of a face-centred cubic porous unit cell on the transport, clustering and deposition of fine particles at different Stokes numbers ( 𝑆𝑡=0.01,0.1,0.5,1,2 ) and at a pore Reynolds number of 500. Particles are advanced using one-way coupling and the collision of particles with pore walls is modelled as perfectly elastic with specular reflection. Tools for studying inertial particle dynamics and clustering developed for homogeneous flows are adapted to take into account the embedded, curved geometry of the pore walls. The pattern and dynamics of clustering are investigated using the volume change of Voronoi tesselation in time to analyse the divergence and convergence of the particles. Similar to the case of homogeneous, isotropic turbulence, the cluster formation is present at large volumes, while cluster destruction is prominent at small volumes and these effects are amplified with the Stokes number. However, unlike homogeneous, isotropic turbulence, the formation of a large number of very small volumes was observed at all Stokes numbers and attributed to the collision of particles with the pore wall. Multiscale wavelet analysis of the particle number density indicates that the peak of the energy density spectrum, representative of enhanced particle clustering, shifts towards larger scales with an increase in the Stokes number. Scale-dependent skewness and flatness quantify the intermittent void and cluster distribution, with cluster formation observed at small scales for all Stokes numbers, and void regions at large scales for large Stokes numbers. 

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2. Particle pair statistics of inertial particles at small separation using stereoscopic particle tracking

   https://doi.org/10.18409/ispiv.v1i1.27  

   Hoffman, Davis W.; Eaton, John K. (September 2021, 14th International Symposium on Particle Image Velocimetry)

   null (Ed.)

   Particle pair statistics of inertial particles having average Stokes numbers of 2.1 and 14 are measured in isotropic turbulence at a Reynolds number of Reλ = 240. The radial distribution function (RDF) and mean relative approach velocity are obtained at small separation distances using 2-frame stereoscopic particle tracking velocimetry (stereo-PTV). At small separation distance, the RDF varies by an order of magnitude in the range of Stokes numbers investigated. However, the mean relative approach velocity is found to have a weak dependence on Stokes number. The results are shown to have high accuracy when compared to analogous mono-PTV datasets, and can be used to provide a more reliable estimate of the inter-particle collision rate. The main limitation of the measurement is observed at separation distances less than the laser sheet thickness, where the technique tended to underestimate the mean relative approach velocity. 

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3. Life and death of inertial particle clusters in turbulence

   Liu, Y; Shen, L; Zamansky, R; Coletti, F (December 2020, Journal of fluid mechanics)

   Clusters of inertial particles in turbulence are usually identified from the spatial coherence of the particle concentration field, neglecting their temporal persistence. The latter is in fact essential to the ability of the particles to interact with each other and to modify the flow. Here, we leverage simulations of homogeneous isotropic turbulence laden with small heavy particles and develop a Lagrangian framework to follow them before, during and after their time as part of a coherent cluster. We define a criterion to establish whether a cluster survives over successive time steps, and use it to characterize its lifetime. We find that cluster lives have typical durations of a few Kolmogorov time scales, with positive correlation between cluster size and lifetime. Increasing inertia and gravitational settling both lead to longer lifetimes. Small clusters emerge from the coagulation of non-clustered particles, quickly followed by disintegration into prevalently non-clustered particles. By contrast, large clusters result from the recombination of other large clusters. The birth of a cluster is preceded by an exponential contraction of the particle cloud, and its death coincides with the beginning of a slower exponential expansion, The contraction is simultaneous to a decline in the local small-scale turbulence activity, while the expansion is accompanied by its recovery. Therefore, during their lifetime, the clusters experience lower-than-average enstrophy and strain rate in the fluid. This relatively quiescent state of the flow is thus a necessary condition for the cluster survival, at least in the considered range of turbulence intensity and particle inertia. 

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4. Flocculation of suspended cohesive particles in homogeneous isotropic turbulence

   https://doi.org/10.1017/jfm.2021.487  

   Zhao, K.; Pomes, F.; Vowinckel, B.; Hsu, T.-J.; Bai, B.; Meiburg, E. (August 2021, Journal of Fluid Mechanics)

   null (Ed.)

   We investigate the dynamics of cohesive particles in homogeneous isotropic turbulence, based on one-way coupled simulations that include Stokes drag, lubrication, cohesive and direct contact forces. We observe a transient flocculation phase, followed by a statistically steady equilibrium phase. We analyse the temporal evolution of floc size and shape due to aggregation, breakage and deformation. Larger turbulent shear and weaker cohesive forces yield smaller elongated flocs. Flocculation proceeds most rapidly when the fluid and particle time scales are balanced and a suitably defined Stokes number is $O(1)$ . During the transient stage, cohesive forces of intermediate strength produce flocs of the largest size, as they are strong enough to cause aggregation, but not so strong as to pull the floc into a compact shape. Small Stokes numbers and weak turbulence delay the onset of the equilibrium stage. During equilibrium, stronger cohesive forces yield flocs of larger size. The equilibrium floc size distribution exhibits a preferred size that depends on the cohesive number. We observe that flocs are generally elongated by turbulent stresses before breakage. Flocs of size close to the Kolmogorov length scale preferentially align themselves with the intermediate strain direction and the vorticity vector. Flocs of smaller size tend to align themselves with the extensional strain direction. More generally, flocs are aligned with the strongest Lagrangian stretching direction. The Kolmogorov scale is seen to limit floc growth. We propose a new flocculation model with a variable fractal dimension that predicts the temporal evolution of the floc size and shape. 

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5. Settling and clustering of snow particles in atmospheric turbulence

   https://doi.org/10.1017/jfm.2020.1153  

   Li, Cheng; Lim, Kaeul; Berk, Tim; Abraham, Aliza; Heisel, Michael; Guala, Michele; Coletti, Filippo; Hong, Jiarong (April 2021, Journal of Fluid Mechanics)

   null (Ed.)

   The effect of turbulence on snow precipitation is not incorporated into present weather forecasting models. Here we show evidence that turbulence is in fact a key influence on both fall speed and spatial distribution of settling snow. We consider three snowfall events under vastly different levels of atmospheric turbulence. We characterize the size and morphology of the snow particles, and we simultaneously image their velocity, acceleration and relative concentration over vertical planes approximately $$30\ \textrm {m}^2$$ in area. We find that turbulence-driven settling enhancement explains otherwise contradictory trends between the particle size and velocity. The estimates of the Stokes number and the correlation between vertical velocity and local concentration are consistent with the view that the enhanced settling is rooted in the preferential sweeping mechanism. When the snow vertical velocity is large compared to the characteristic turbulence velocity, the crossing trajectories effect results in strong accelerations. When the conditions of preferential sweeping are met, the concentration field is highly non-uniform and clustering appears over a wide range of scales. These clusters, identified for the first time in a naturally occurring flow, display the signature features seen in canonical settings: power-law size distribution, fractal-like shape, vertical elongation and large fall speed that increases with the cluster size. These findings demonstrate that the fundamental phenomenology of particle-laden turbulence can be leveraged towards a better predictive understanding of snow precipitation and ground snow accumulation. They also demonstrate how environmental flows can be used to investigate dispersed multiphase flows at Reynolds numbers not accessible in laboratory experiments or numerical simulations. 

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