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相关论文: Stochastic Stokes' drift with inertia

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We investigate the large-scale transport of inertial particles. We derive explicit analytic expressions for the eddy diffusivities for generic Stokes times. These latter expressions are exact for any shear flow while they correspond to the…

流体动力学 · 物理学 2017-01-11 Simone Boi , Andrea Mazzino , Paolo Muratore-Ginanneschi

Classical Stokes' drift is the small time-averaged drift velocity of suspended non-diffusing particles in a fluid due to the presence of a wave. We consider the effect of adding diffusion to the motion of the particles, and show in…

经典物理 · 物理学 2009-10-31 Kalvis M. Jansons , G. D. Lythe

The large-scale/long-time transport of inertial particles of arbitrary mass density under gravity is investigated by means of a formal multiple-scale perturbative expansion in the scale-separation parametre between the carrier flow and the…

流体动力学 · 物理学 2019-02-13 Marco Martins Afonso , Andrea Mazzino , Paolo Muratore-Ginanneschi

We study the effect of surface gravity waves on the motion of inertial particles in an incompressible fluid. Using the multiple-scale technique, we perform an analytical calculation which allows us to predict the dynamics of such particles;…

流体动力学 · 物理学 2013-01-25 G. Boffetta , M. Martins Afonso , A. Mazzino , M. Onorato , F. Santamaria

We consider the stochastic Stokes drift of a flexible dumbbell. The dumbbell consists of two isotropic Brownian particles connected by a linear spring with zero natural length, and is advected by a sinusoidal wave. We find an asymptotic…

概率论 · 数学 2009-11-11 Kalvis M. Jansons

Stochastic Stokes' drift and hypersensitive transport driven by dichotomous noise are theoretically investigated. Explicit mathematical expressions for the asymptotic probability density and drift velocity are derived including the…

统计力学 · 物理学 2007-05-23 I. Bena , R. Kawai , C. Van den Broeck , Katja Lindenberg

Stokes drift is a classical fluid effect in which travelling waves transfer momentum to tracers of the fluid, resulting in a non-zero drift velocity in the direction of the incoming wave. This effect is the driving mechanism allowing…

流体动力学 · 物理学 2023-06-21 Umberto Giuriato , Giorgio Krstulovic , Miguel Onorato , Davide Proment

Simultaneous diffusive and inertial motion of Brownian particles in laminar Couette flow is investigated via Lagrangian and Eulerian descriptions to determine the effect of particle inertia on diffusive transport in the long-time. The…

统计力学 · 物理学 2010-08-13 Yannis Drossinos , Michael W. Reeks

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 study a generalization of the Brownian bridge as a stochastic process that models the position and velocity of inertial particles between the two end-points of a time interval. The particles experience random acceleration and are assumed…

系统与控制 · 计算机科学 2014-07-15 Yongxin Chen , Tryphon Georgiou

We study exclusion processes on the integer lattice in which particles change their velocities due to stickiness. Specifically, whenever two or more particles occupy adjacent sites, they stick together for an extended period of time, and…

概率论 · 数学 2016-08-11 Miklós Z. Rácz , Mykhaylo Shkolnikov

We investigate the large-scale transport properties of quasi-neutrally-buoyant inertial particles carried by incompressible zero-mean periodic or steady ergodic flows. We show how to compute large-scale indicators such as the…

Small heavy particles in a fluid flow respond to the flow on a time-scale proportional to their inertia, or Stokes number St. Their behaviour is thought to be gradually modified as St increases. We show, in the steady spatially-periodic…

流体动力学 · 物理学 2023-04-20 Anu V. S. Nath , Anubhab Roy , S. Ravichandran , Rama Govindarajan

We compare experiments and direct numerical simulations to evaluate the accuracy of the Stokes-drag model, which is used widely in studies of inertial particles in turbulence. We focus on statistics at the dissipation scale and on extreme…

流体动力学 · 物理学 2016-08-03 Ewe-Wei Saw , Gregory P. Bewley , Eberhard Bodenschatz , Samriddhi Sankar Ray , Jérémie Bec

We derive a perturbative approach to study, in the large inertia limit, the dynamics of solid particles in a smooth, incompressible and finite-time correlated random velocity field. We carry on an expansion in powers of the inverse square…

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

We investigate the transport of inertial particles by cellular flows when advection dominates over inertia and diffusion, that is, for Stokes and P\'eclet numbers satisfying $\mathrm{St} \ll 1$ and $\mathrm{Pe} \gg 1$. Starting from the…

流体动力学 · 物理学 2020-05-26 Antoine Renaud , Jacques Vanneste

We introduce order-based diffusion processes as the solutions to multidimensional stochastic differential equations, with drift coefficient depending only on the ordering of the coordinates of the process and diffusion matrix proportional…

概率论 · 数学 2014-03-11 Benjamin Jourdain , Julien Reygner

Low Stokes number particles at dilute concentrations in turbulent flows can reasonably be approximated as passive scalars. The added presence of a drift velocity due to buoyancy or gravity when considering the transport of such passive…

流体动力学 · 物理学 2024-11-20 Omkar B. Shende , Liam Storan , Ali Mani

A simple theory, based on observations of snowflake distribution in a turbulent flow, is proposed to model the growth of inertial particles as a result of dynamic clustering at scales larger than the Kolmogorov length scale. Particles able…

流体动力学 · 物理学 2015-10-16 Michele Guala , Jiarong Hong

Diffusion of colloidal particles in a complex environment such as polymer networks or biological cells is a topic of high complexity with significant biological and medical relevance. In such situations, the interaction between the…

统计力学 · 物理学 2015-11-10 Andreas M. Menzel
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