中文
相关论文

相关论文: Dynamics and statistics of heavy particles in turb…

200 篇论文

We present a sweep-stick mechanism for heavy particles transported by a turbulent flow under the action of gravity. Direct numerical simulations show that these particles preferentially explore regions of the flow with close to zero…

流体动力学 · 物理学 2020-08-12 Florencia Falkinhoff , Martin Obligado , Mickaël Bourgoin , Pablo D. Mininni

The direct numerical simulation (DNS) of the Taylor--Couette flow in the fully turbulent regime is described. The numerical method extends the work by Quadrio & Luchini (Eur. J. Mech. B / Fluids, v.21, pp.413--427, 2002), and is based on a…

流体动力学 · 物理学 2009-11-13 Davide Pirro , Maurizio Quadrio

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

Particle tracking in turbulent flows is fundamental to the study of the transport of tracers, inertial particles or even active objects in space and time, i.e. the Lagrangian frame of reference. It provides experimental tests of theoretical…

流体动力学 · 物理学 2024-04-08 Christian Küchler , Antonio Ibanez Landeta , Jan Molacek , Eberhard Bodenschatz

We combine a DEM simulation with a stochastic process to model the movement of spherical particles in a turbulent channel flow. With this model we investigate the mixing properties of two species of particles flowing through the channel. We…

流体动力学 · 物理学 2011-06-20 Thomas Burgener , Dirk Kadau , Hans J. Herrmann

Modeling dispersed solid phases in fluids still represents a computational challenge when considering a small-scale coupling in wide systems, such as the atmosphere or industrial processes at high Reynolds numbers. A numerical method is…

流体动力学 · 物理学 2015-08-13 François Laenen , Giorgio Krstulovic , Jérémie Bec

Turbulence, the ubiquitous and chaotic state of fluid motions, is characterized by strong and statistically non-trivial fluctuations of the velocity field, over a wide range of length- and time-scales, and it can be quantitatively described…

流体动力学 · 物理学 2021-03-31 Alessandro Corbetta , Vlado Menkovski , Roberto Benzi , Federico Toschi

In-cylinder flow structures and turbulence characteristics are investigated using direct numerical simulations (DNS) in a laboratory-scale engine at technically relevant engine speeds (1500 and 2500 rpm at full load). The data is computed…

流体动力学 · 物理学 2025-06-05 Bogdan A. Danciu , George K. Giannakopoulos , Mathis Bode , Christos E. Frouzakis

Being able to accurately model and predict the dynamics of dispersed inclusions transported by a turbulent flow, remains a challenge with important scientific, environmental and economical issues. One critical and difficult point is to…

Turbulent flows preferentially concentrate inertial particles depending on their stopping time or Stokes number, which can lead to significant spatial variations in the particle concentration. Cascade models are one way to describe this…

流体动力学 · 物理学 2017-04-26 Thomas Hartlep , Jeffrey N. Cuzzi , Brian Weston

We investigate the preferential concentration of particles which are neutrally buoyant but with a diameter significantly larger than the dissipation scale of the carrier flow. Such particles are known not to behave as flow tracers (Qureshi…

It is a commonly observed phenomenon that spherical particles with inertia in an incompressible fluid do not behave as ideal tracers. Due to the inertia of the particle, the dynamics are described in a four dimensional phase space and thus…

混沌动力学 · 物理学 2009-11-13 Phanindra Tallapragada , Shane. D. Ross

We study the statistics of the vertical motion of inertial particles in strongly stratified turbulence. We use Kinematic Simulation (KS) and Rapid Distortion Theory (RDT) to study the mean position and the root mean square (rms) of the…

流体动力学 · 物理学 2017-08-28 F. C. G. A. Nicolleau , K. -S. Sung , J. C. Vassilicos

The sedimentation of a pair of rigid circular particles in a two-dimensional vertical channel containing a Newtonian fluid is investigated numerically, for terminal particle Reynolds numbers ranging from 1 to 10, and for a confinement ratio…

流体动力学 · 物理学 2016-11-30 Romuald Verjus , Sylvain Guillou , Alexander Ezersky , Jean-Régis Angilella

The dynamics of inertial particles in Rayleigh-B\'{e}nard convection, where both particles and fluid exhibit thermal expansion, is studied using direct numerical simulations (DNS). We consider the effect of particles with a thermal…

软凝聚态物质 · 物理学 2019-07-02 Kim M. J. Alards , Rudie P. J. Kunnen , Herman J. H. Clercx , Federico Toschi

We study the three-dimensional clustering of velocity stagnation points, of nulls of the vorticity and of the Lagrangian acceleration, and of inertial particles in turbulent flows at fixed Reynolds numbers, but under different large-scale…

We study the dynamics of inertial particles in turbulence using datasets obtained from both direct numerical simulations and laboratory experiments of turbulent swirling flows. By analyzing time series of particle velocity increments at…

In dilute turbulent particle-laden flows, such as atmospheric dispersion of pollutants or virus particles, the dynamics of tracer-like to low inertial particles are significantly altered by the fluctuating motion of the carrier fluid phase.…

流体动力学 · 物理学 2024-06-19 Josh Williams , Uwe Wolfram , Ali Ozel

Numerical simulations are made for forced turbulence at a sequence of increasing values of Reynolds number, R, keeping fixed a strongly stable, volume-mean density stratification. At smaller values of R, the turbulent velocity is mainly…

流体动力学 · 物理学 2016-09-08 Jean-Philippe Laval , James C. McWilliams

We consider Brownian particles immersed in the fluid which flow is turbulent. We study the limit where the particles' inertia is weak and their velocity relaxes fast to the velocity of the flow. The trajectories of the particles in this…

混沌动力学 · 物理学 2011-10-25 Itzhak Fouxon , Eugene Mednikov