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Turbulence facilitates collisions between particles suspended in a turbulent flow. Two effects have been proposed which can enhance the collision rate at high turbulence intensities: 'preferential concentration' (a clustering phenomenon)…

流体动力学 · 物理学 2016-04-06 Michel Voßkuhle , Alain Pumir , Emmanuel Lévêque , Michael Wilkinson

The influence of clustering on the collision rate of inertial particles in a smooth random velocity field, mimicking the smaller scales of a turbulent flow, is analyzed. For small values of the the ratio between the relaxation time of the…

统计力学 · 物理学 2009-11-13 Piero Olla

We investigate the response of large inertial particle to turbulent fluctuations in a inhomogeneous and anisotropic flow. We conduct a Lagrangian study using particles both heavier and lighter than the surrounding fluid, and whose diameters…

流体动力学 · 物理学 2016-04-20 Nathanaël Machicoane , Romain Volk

We consider inertial particles suspended in an incompressible turbulent flow. Due to inertia of particles, their velocity field acquires small compressible component. Its presence leads to a new qualitative effect --- possibility of…

chao-dyn · 物理学 2007-05-23 E. Balkovsky , G. Falkovich , A. Fouxon

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…

流体动力学 · 物理学 2019-01-30 Alessio Innocenti , Rodney O Fox , Sergio Chibbaro

Heavy particles suspended in a turbulent flow settle faster than in a still fluid. This effect stems from a preferential sampling of the regions where the fluid flows downward and is quantified here as a function of the level of turbulence,…

流体动力学 · 物理学 2015-06-18 Jeremie Bec , Holger Homann , Samriddhi Sankar Ray

We study the collision rates and velocities for point-particles of different sizes in turbulent flows. We construct fits for the collision rates at specified velocities (effectively a collisional velocity probability distribution) for…

地球与行星天体物理 · 物理学 2015-06-15 Alexander Hubbard

We consider advection of small inertial particles by a random fluid flow with a strong steady shear component. It is known that inertial particles suspended in a random flow can exhibit clusterization even if the flow is incompressible. We…

混沌动力学 · 物理学 2013-05-30 Grigory A. Sizov

We study the effect of turbulence on a sedimenting layer of particles by means of direct numerical simulations. A Lagrangian model in which particles are considered as tracers with an additional downward settling velocity is integrated…

流体动力学 · 物理学 2020-07-08 Alessandro Sozza , Gabor Drotos , Emilio Hernández-García , Cristóbal López

A theory of clustering of inertial particles advected by a turbulent velocity field caused by an instability of their spatial distribution is suggested. The reason for the clustering instability is a combined effect of the particles inertia…

混沌动力学 · 物理学 2007-05-23 Tov Elperin , Nathan Kleeorin , Victor S. L'vov , Igor Rogachevskii , Dmitry Sokoloff

Inertial particles advected in chaotic flows often accumulate in strange attractors. While moving in these fractal sets they usually approach each other and collide. Here we consider inertial particles aggregating upon collision. The new…

流体动力学 · 物理学 2009-11-13 Jens C. Zahnow , Rafael D. Vilela , Ulrike Feudel , Tamas Tel

We study the typical collisional velocities in a polydisperse suspension of droplets in two and three-dimensional turbulent flow and obtain precise theoretical estimates of the dependence of the impact velocity of particles-pairs on their…

流体动力学 · 物理学 2016-03-21 Martin James , Samriddhi Sankar Ray

When very small particles are suspended in a fluid in motion, they tend to follow the flow. How such tracer particles are mixed, transported, and dispersed by turbulent flow has been successfully described by statistical models. Heavy…

流体动力学 · 物理学 2023-12-21 J. Bec , K. Gustavsson , B. Mehlig

Finding a quantitative description of the rate of collisions between small particles suspended in mixing flows is a long-standing problem. Here we investigate the validity of a parameterisation of the collision rate for identical particles…

流体动力学 · 物理学 2016-06-01 K. Gustavsson , B. Mehlig

Our ability to numerically model and understand the complex flow behavior of solid-bearing suspensions has increased significantly over the last couple of years, partly due to direct numerical simulations that compute flow around individual…

计算物理 · 物理学 2019-03-21 Zhipeng Qin , Kali Alison , Jenny Suckale

Inertial particles suspended in many natural and industrial flows undergo coagulation upon collisions and fragmentation if their size becomes too large or if they experience large shear. Here we study this coagulation-fragmentation process…

混沌动力学 · 物理学 2009-08-20 Jens C. Zahnow , Rafael D. Vilela , Ulrike Feudel , Tamás Tél

Direct numerical simulations are used to study the interaction of a stream of small heavy inertial particles with the laminar and turbulent wakes of an immobile sphere facing an incompressible uniform inflow. Particles that do not collide…

流体动力学 · 物理学 2015-06-11 Holger Homann , Jérémie Bec

A statistical description of heavy particles suspended in incompressible rough self-similar flows is developed. It is shown that, differently from smooth flows, particles do not form fractal clusters. They rather distribute inhomogeneously…

混沌动力学 · 物理学 2007-05-23 J. Bec , M. Cencini , R. Hillerbrand

Understanding the dynamics of material objects advected by turbulent flows is a long standing question in fluid dynamics. In this perspective article we focus on the characterization of the statistical properties of non-interacting…

流体动力学 · 物理学 2024-03-18 Yaning Fan , Cheng Wang , Linfeng Jiang , Chao Sun , Enrico Calzavarini

We investigate the spatial distribution of inertial particles suspended in the bulk of a turbulent inhomogeneous flow. By means of direct numerical simulations of particle trajectories transported by the turbulent Kolmogorov flow, we study…

流体动力学 · 物理学 2016-03-23 Filippo De Lillo , Massimo Cencini , Stefano Musacchio , Guido Boffetta
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