Clustering of heavy particles in random self-similar flow.

نویسندگان

  • J Bec
  • M Cencini
  • R Hillerbrand
چکیده

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 with a statistics that only depends on a local Stokes number, given by the ratio between the particles' response time and the turnover time associated with the observation scale. Particle clustering is reduced by the fluid roughness. Heuristic arguments supported by numerics explain this effect in terms of the algebraic tails of the probability density function of the velocity difference between two particles.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Clustering and collisions of heavy particles in random smooth flows

Finite-size impurities suspended in incompressible flows distribute inhomogeneously, leading to a drastic enhancement of collisions. A description of the dynamics in the full position-velocity phase space is essential to understand the underlying mechanisms, especially for polydisperse suspensions. These issues are studied here for particles much heavier than the fluid by means of a Lagrangian ...

متن کامل

Fractals or I.I.D.: Evidence of Long-Range Dependence and Heavy Tailedness from Modeling German Equity Market Volatility

Several studies find that return volatility of stocks tends to exhibit long-range dependence, heavy tailedness, and clustering. In this study, we use high-frequency data to empirically investigate whether a sample of stocks exhibit those characteristics. Because we do find those characteristics, as suggested by Rachev and Mittnik (2000) we employ self-similar processes to capture them in modeli...

متن کامل

Gravity-driven enhancement of heavy particle clustering in turbulent flow.

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, of particle inertia, and of the ratio between gravity and turbulent accelerations. By using analytical methods and detailed, state-of-the-art numerical simu...

متن کامل

Toward a phenomenological approach to the clustering of heavy particles in turbulent flows

A simple model accounting for the ejection of heavy particles from the vortical structures of a turbulent flow is introduced. This model involves a space and time discretization of the dynamics and depends on only two parameters: the fraction of space-time occupied by rotating structures of the carrier flow and the rate at which particles are ejected from them. The latter can be heuristically r...

متن کامل

Fractals or I.I.D.: Evidence of Long-Range Dependence and Heavy Tailedness from Modeling German Equity Market Returns

Several studies find that the return volatility of stocks tends to exhibit long-range dependence, heavy tails, and clustering. Because stochastic processes with self-similarity possess long-range dependence and heavy tails, Rachev and Mittnik (2000) suggest employing self-similar processes to capture these characteristics in return volatility modeling. In this paper, we find using high-frequenc...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:
  • Physical review. E, Statistical, nonlinear, and soft matter physics

دوره 75 2 Pt 2  شماره 

صفحات  -

تاریخ انتشار 2007