scholarly journals Analysis of the clustering of inertial particles in turbulent flows

2016 ◽  
Vol 1 (8) ◽  
Author(s):  
Mahdi Esmaily-Moghadam ◽  
Ali Mani
Keyword(s):  
Turbulent Flows ◽  
Inertial Particles

scholarly journals Heavy inertial particles in turbulent flows gain energy slowly but lose it rapidly

2018 ◽  
Vol 97 (3) ◽  
Author(s):  
Akshay Bhatnagar ◽  
Anupam Gupta ◽  
Dhrubaditya Mitra ◽  
Rahul Pandit
Keyword(s):  
Turbulent Flows ◽  
Inertial Particles ◽  
Gain Energy

scholarly journals Effects of forcing time scale on the simulated turbulent flows and turbulent collision statistics of inertial particles

2015 ◽  
Vol 27 (1) ◽  
pp. 015105 ◽  
Author(s):  
B. Rosa ◽  
H. Parishani ◽  
O. Ayala ◽  
L.-P. Wang
Keyword(s):  
Turbulent Flows ◽  
Time Scale ◽  
Inertial Particles

Wall accumulation and spatial localization in particle-laden wall flows

2012 ◽  
Vol 699 ◽  
pp. 50-78 ◽  
Author(s):  
G. Sardina ◽  
P. Schlatter ◽  
L. Brandt ◽  
F. Picano ◽  
C. M. Casciola
Keyword(s):  
Turbulent Flows ◽  
Pair Correlation ◽  
Turbulent Channel Flow ◽  
Wall Turbulence ◽  
Small Scale ◽  
Wall Region ◽  
Inertial Particles ◽  
Wall Flows ◽  
Domain Truncation ◽  
Near Wall

AbstractWe study the two main phenomenologies associated with the transport of inertial particles in turbulent flows, turbophoresis and small-scale clustering. Turbophoresis describes the turbulence-induced wall accumulation of particles dispersed in wall turbulence, while small-scale clustering is a form of local segregation that affects the particle distribution in the presence of fine-scale turbulence. Despite the fact that the two aspects are usually addressed separately, this paper shows that they occur simultaneously in wall-bounded flows, where they represent different aspects of the same process. We study these phenomena by post-processing data from a direct numerical simulation of turbulent channel flow with different populations of inertial particles. It is shown that artificial domain truncation can easily alter the mean particle concentration profile, unless the domain is large enough to exclude possible correlation of the turbulence and the near-wall particle aggregates. The data show a strong link between accumulation level and clustering intensity in the near-wall region. At statistical steady state, most accumulating particles aggregate in strongly directional and almost filamentary structures, as found by considering suitable two-point observables able to extract clustering intensity and anisotropy. The analysis provides quantitative indications of the wall-segregation process as a function of the particle inertia. It is shown that, although the most wall-accumulating particles are too heavy to segregate in homogeneous turbulence, they exhibit the most intense local small-scale clustering near the wall as measured by the singularity exponent of the particle pair correlation function.

scholarly journals Spatial and velocity statistics of inertial particles in turbulent flows

2011 ◽  
Vol 333 ◽  
pp. 012003 ◽  
Author(s):  
J Bec ◽  
L Biferale ◽  
M Cencini ◽  
A S Lanotte ◽  
F Toschi
Keyword(s):  
Turbulent Flows ◽  
Inertial Particles ◽  
Velocity Statistics

scholarly journals A Lagrangian probability-density-function model for collisional turbulent fluid–particle flows

2019 ◽  
Vol 862 ◽  
pp. 449-489 ◽  
Author(s):  
A. Innocenti ◽  
R. O. Fox ◽  
M. V. Salvetti ◽  
S. Chibbaro
Keyword(s):  
Probability Density Function ◽  
Probability Density ◽  
Density Function ◽  
Turbulent Flows ◽  
Isotropic Turbulence ◽  
Fluid Phase ◽  
Stochastic Modelling ◽  
Inertial Particles ◽  
Particle Phase ◽  
Dense Particle

Inertial particles in turbulent flows are characterised by preferential concentration and segregation and, at sufficient mass loading, dense particle clusters may spontaneously arise due to momentum coupling between the phases. These clusters, in turn, can generate and sustain turbulence in the fluid phase, which we refer to as cluster-induced turbulence (CIT). In the present work, we tackle the problem of developing a framework for the stochastic modelling of moderately dense particle-laden flows, based on a Lagrangian probability-density-function formalism. This framework includes the Eulerian approach, and hence can be useful also for the development of two-fluid models. A rigorous formalism and a general model have been put forward focusing, in particular, on the two ingredients that are key in moderately dense flows, namely, two-way coupling in the carrier phase, and the decomposition of the particle-phase velocity into its spatially correlated and uncorrelated components. Specifically, this last contribution allows us to identify in the stochastic model the contributions due to the correlated fluctuating energy and to the granular temperature of the particle phase, which determine the time scale for particle–particle collisions. The model is then validated and assessed against direct-numerical-simulation data for homogeneous configurations of increasing difficulty: (i) homogeneous isotropic turbulence, (ii) decaying and shear turbulence and (iii) CIT.

Reynolds number scaling of inertial particle statistics in turbulent channel flows

2014 ◽  
Vol 758 ◽  
Author(s):  
Matteo Bernardini
Keyword(s):  
Reynolds Number ◽  
Turbulent Flows ◽  
Large Scale ◽  
Spatial Organization ◽  
Reynolds Numbers ◽  
Stokes Number ◽  
Wall Region ◽  
Inertial Particles ◽  
Turbulent Channel Flows ◽  
Strong Segregation

AbstractThe effect of the Reynolds number on the behaviour of inertial particles in wall-bounded turbulent flows is investigated through large-scale direct numerical simulations (DNS) of particle-laden canonical channel flow spanning almost a decade in the friction Reynolds number, from $\def \xmlpi #1{}\def \mathsfbi #1{\boldsymbol {\mathsf {#1}}}\let \le =\leqslant \let \leq =\leqslant \let \ge =\geqslant \let \geq =\geqslant \def \Pr {\mathit {Pr}}\def \Fr {\mathit {Fr}}\def \Rey {\mathit {Re}}\mathit{Re}_{\tau } = 150$ to $\mathit{Re}_{\tau } = 1000$. Lagrangian particle tracking is used to study the motion of six different particle sets, described by a Stokes number in the range $\mathit{St} = 1\text {--}1000$. At all Reynolds numbers a strong segregation in the near-wall region is observed for particles characterized by intermediate Stokes number, in the range $\mathit{St} =10\text {--}100$. The wall-normal concentration profiles of such particles collapse in inner scaling, thus suggesting the independence of the turbophoretic drift from the large-scale outer motions. This observation is also supported by the spatial organization of the suspended phase in the inner layer, which is found to be universal with the Reynolds number. The deposition rate coefficient increases with $\mathit{Re}_{\tau }$ for a given $\mathit{St}$. Suitable inner and outer scalings are proposed to collapse the deposition curves across the available ranges of Reynolds and Stokes numbers for the different deposition regimes.

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