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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…

混沌动力学 · 物理学 2009-11-13 Jeremie Bec , Massimo Cencini , Rafaela Hillerbrand , Konstantin Turitsyn

We discuss the relation between three recent approaches of describing the dynamics and the spatial distribution of particles suspended in turbulent flows: phase-space singularities in the inertial particle dynamics (caustics), real-space…

流体动力学 · 物理学 2015-06-05 K. Gustavsson , E. Meneguz , M. Reeks , B. Mehlig

The motion of tiny heavy particles transported in a co-rotating vortex pair, with or without particle inertia and sedimentation, is investigated. The dynamics of non-inertial sedimenting particles is shown to be chaotic, under the combined…

流体动力学 · 物理学 2015-05-18 Jean-Regis Angilella

The stochastic dynamics of an active particle undergoing a constant speed and additionally driven by an overall fluctuating torque is investigated. The random torque forces are expressed by a stochastic differential equation for the angular…

统计力学 · 物理学 2011-12-22 Christian Weber , Paul K. Radtke , Lutz Schimansky-Geier , Peter Hänggi

We use direct numerical simulations to calculate the joint probability density function of the relative distance $R$ and relative radial velocity component $V_R$ for a pair of heavy inertial particles suspended in homogeneous and isotropic…

流体动力学 · 物理学 2018-02-21 Akshay Bhatnagar , K. Gustavsson , Dhrubaditya Mitra

In this two--part study, we present the development and analysis of a stochastic theory for characterizing the relative positions of monodisperse, low-inertia particle pairs that are settling rapidly in homogeneous isotropic turbulence. In…

流体动力学 · 物理学 2019-06-26 Sarma L. Rani , Vijay K. Gupta , Donald L. Koch

We present experimental observations of the velocity and spatial distribution of inertial particles dispersed in the turbulent downward flow through a vertical channel at $Re_{\tau} = 235$ and $335$. The working fluid is air laden with…

流体动力学 · 物理学 2019-04-16 Kee Onn Fong , Omid Amili , Filippo Coletti

We analyze the behavior of an ensemble of inertial particles in a one-dimensional smooth Gaussian velocity field, in the limit of large inertia, but considering a finite correlation time for the random field. We derive in this limit a…

统计力学 · 物理学 2009-11-13 Piero Olla , Raffaella Vuolo

It was recently suggested that the sign of particle drift in inhomogeneous temperature or turbulence depends on the particle inertia: weakly inertial particles localize near minima of temperature or turbulence intensity (effects known as…

混沌动力学 · 物理学 2016-03-17 Sergey Belan , Alexander Chernykh , Gregory Falkovich

Particle sedimentation in the vicinity of a fixed horizontal vortex with time-dependent intensity can be chaotic, provided gravity is sufficient to displace the particle cloud while the vortex is off or weak. This "stretch, sediment and…

流体动力学 · 物理学 2010-03-23 J. R. Angilella

The clustering of small heavy inertial particles subjected to Stokes drag in turbulence is known to be minimal at small and large Stokes number and substantial at $\rm St = \mathcal O(1)$. This non-monotonic trend, which has been shown…

流体动力学 · 物理学 2020-08-19 Mahdi Esmaily-Moghadam , Ali Mani

An asymptotic solution is derived for the motion of inertial particles exposed to Stokes drag in an unsteady random flow. This solution provides the finite-time Lyapunov exponents as a function of Stokes number and Lagrangian strain- and…

流体动力学 · 物理学 2016-12-28 Mahdi Esmaily-Moghadam , Ali Mani

Mixing of inertial point particles in a turbulent channel flow at Re{\tau} = 950 is investigated by means of direct numerical simulations. We consider inertial particles, at varying Stokes number, released from pairs of sources located at…

流体动力学 · 物理学 2023-06-19 D. Perrone , J. G. M Kuerten , L. Ridolfi , S. Scarsoglio

We use theory and Direct Numerical Simulations (DNS) to explore the average vertical velocities and spatial distributions of inertial particles settling in a wall-bounded turbulent flow. The theory is based on the exact phase-space equation…

流体动力学 · 物理学 2021-06-09 Andrew D Bragg , David H Richter , Guiquan Wang

Heavy particles suspended in turbulent flow possess inertia and are ejected from violent vortical structures by centrifugal forces. Once piled up along particle paths, this small-scale mechanism leads to an effective large-scale drift. This…

流体动力学 · 物理学 2024-04-25 Jérémie Bec , Robin Vallée

We analyse the tumbling of small non-spherical, axisymmetric particles in random and turbulent flows. We compute the orientational dynamics in terms of a perturbation expansion in the Kubo number, and obtain the tumbling rate in terms of…

流体动力学 · 物理学 2015-06-15 K. Gustavsson , J. Einarsson , B. Mehlig

We study experimentally the spatial distribution, settling, and interaction of sub-Kolmogorov inertial particles with homogeneous turbulence. Utilizing a zero-mean-flow air turbulence chamber, we drop size-selected solid particles and study…

流体动力学 · 物理学 2019-03-27 Alec J. Petersen , Lucia Baker , Filippo Coletti

The phenomenon of turbulent thermal diffusion in temperature-stratified turbulence causing a non-diffusive turbulent flux of inertial and non-inertial particles in the direction of the turbulent heat flux is found using direct numerical…

太阳与恒星天体物理 · 物理学 2012-11-28 N. E. L. Haugen , N. Kleeorin , I. Rogachevskii , A. Brandenburg

We compute the joint distribution of relative velocities and separations of identical inertial particles suspended in randomly mixing and turbulent flows. Our results are obtained by matching asymptotic forms of the distribution. The method…

流体动力学 · 物理学 2014-02-24 K. Gustavsson , B. Mehlig

Inertial particle data from three-dimensional direct numerical simulations of particle-laden homogeneous isotropic turbulence at high Reynolds number are analyzed using Voronoi tessellation of the particle positions, considering different…

流体动力学 · 物理学 2020-11-12 Thibault Oujia , Keigo Matsuda , Kai Schneider
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