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Related papers: Are Continuum Predictions of Clustering Chaotic?

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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 · Physics 2007-05-23 E. Balkovsky , G. Falkovich , A. Fouxon

Studying particle-laden flows is essential to understand diverse physical processes such as rain formation in clouds, pathogen transmission, and pollutant dispersal. Distinct clustering patterns are formed in such flows with particles of…

Fluid Dynamics · Physics 2022-01-13 K Shri Vignesh , Shruti Tandon , Praveen Kasthuri , R. I. Sujith

We investigate the inelastic hard disk gas sheared by two parallel bumpy walls (Couette-flow). In our molecular dynamic simulations we found a sensitivity to the asymmetries of the initial condition of the particle places and velocities and…

Soft Condensed Matter · Physics 2009-10-31 M. Sasvari , J. Kertesz , D. E. Wolf

Dynamical systems on networks with adaptive couplings appear naturally in real-world systems such as power grid networks, social networks as well as neuronal networks. We investigate a paradigmatic system of adaptively coupled phase…

Adaptation and Self-Organizing Systems · Physics 2019-12-20 Rico Berner , Eckehard Schöll , Serhiy Yanchuk

Fluctuating hydrodynamics is used to describe the total energy fluctuations of a freely evolving gas of inelastic hard spheres near the threshold of the clustering instability. They are shown to be governed by vorticity fluctuations only,…

Statistical Mechanics · Physics 2009-11-11 J. Javier Brey , A. Dominguez , M. I. Garcia de Soria , P. Maynar

In a granular gas, inelastic collisions produce an instability in which the constituent particles cluster heterogeneously. These clusters then interact with each other, further decreasing their kinetic energy. We report experiments of the…

Soft Condensed Matter · Physics 2015-06-17 Justin C. Burton , Peter Y. Lu , Sidney R. Nagel

Dynamical chaos is a fundamental manifestation of gravity in astrophysical, many-body systems. The spectrum of Lyapunov exponents quantifies the associated exponential response to small perturbations. Analytical derivations of these…

Instrumentation and Methods for Astrophysics · Physics 2023-08-30 Tjarda C. N. Boekholt , Simon F. Portegies Zwart , Douglas C. Heggie

The predictability of weather and climate is strongly state-dependent: special and extremely relevant atmospheric states like blockings are associated with anomalous instability. Indeed, typically, the instability of a chaotic dynamical…

Chaotic Dynamics · Physics 2024-12-24 Chiara Cecilia Maiocchi , Valerio Lucarini , Andrey Gritsun , Yuzuru Sato

Statistical aspects of the dynamics of chaotic scattering in the classical model of $\alpha$-cluster nuclei are studied. It is found that the dynamics governed by hyperbolic instabilities which results in an exponential decay of the…

Nuclear Theory · Physics 2009-09-25 S. Drożdż , J. Okołowicz , T. Srokowski , A. Budzanowski

A review of some recent results and ideas about the expected behaviour of large chaotic systems and fluids.

chao-dyn · Physics 2009-10-30 Giovanni Gallavotti

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…

Chaotic Dynamics · Physics 2013-05-30 Grigory A. Sizov

Networks of caustics can occur in the distribution of particles suspended in a randomly moving gas. These can facilitate coagulation of particles by bringing them into close proximity, even in cases where the trajectories do not coalesce.…

Statistical Mechanics · Physics 2009-11-10 M. Wilkinson , B. Mehlig

We study the chaotic properties of a turbulent conducting fluid using direct numerical simulation in the Eulerian frame. The maximal Lyapunov exponent is measured for simulations with varying Reynolds number and magnetic Prandtl number. We…

Fluid Dynamics · Physics 2019-05-22 Richard Ho , Arjun Berera , Daniel Clark

We propose a simple model for periodic clustering of particles under forced oscillation. Effective viscosity is assumed to increase owing to neighboring particles by analogy with the Einstein viscosity law. The linear stability analysis and…

Pattern Formation and Solitons · Physics 2026-02-12 Hidetsugu Sakaguchi

From a kinematical point of view, the geometrical information of hamiltonian chaos is given by the (un)stable directions, while the dynamical information is given by the Lyapunov exponents. The finite time Lyapunov exponents are of…

Classical Physics · Physics 2009-10-31 X. Z. Tang , A. H. Boozer

Matter gets organized at several levels of structural rearrangements. At mesoscopic level one can distinguish between two types of rearrangements, conforming to different close-packing or densification conditions, appearing during different…

Soft Condensed Matter · Physics 2012-10-03 Adam Gadomski , Marcel Ausloos

We discuss the effects of finite perturbations in fully developed turbulence by introducing a measure of the chaoticity degree associated to a given scale of the velocity field. This allows one to determine the predictability time for…

chao-dyn · Physics 2009-10-28 E. Aurell , G. Boffetta , A. Crisanti , G. Paladin , A. Vulpiani

The linear stability of stratified two-phase flows in rectangular ducts is studied numerically. The linear stability analysis takes into account all possible infinitesimal three-dimensional disturbances and is carried out by solution of the…

Fluid Dynamics · Physics 2020-04-09 Alexander Gelfgat , Neima Brauner

A nonlinear model of modulational processes in the subsonic regime involving a linearly unstable wave and two linearly damped waves with different damping rates in a plasma is studied numerically. We compute the maximum Lyapunov exponent as…

Chaotic Dynamics · Physics 2015-06-12 Rodrigo A. Miranda , Erico L. Rempel , Abraham C. -L. Chian

Chaos and unpredictability are traditionally synonymous, yet large-scale machine learning methods recently have demonstrated a surprising ability to forecast chaotic systems well beyond typical predictability horizons. However, recent works…

Machine Learning · Computer Science 2023-11-27 William Gilpin
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