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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…

Chaotic Dynamics · Physics 2011-10-25 Itzhak Fouxon , Eugene Mednikov

Grouping similar objects is a fundamental tool of scientific analysis, ubiquitous in disciplines from biology and chemistry to astronomy and pattern recognition. Inspired by the torque balance that exists in gravitational interactions when…

Machine Learning · Computer Science 2020-04-29 Jie Yang , Chin-Teng Lin

Gas-solid multiphase flows are prone to develop an instability known as clustering. Two-fluid models, which treat the particulate phase as a continuum, are known to reproduce the qualitative features of this instability, producing…

Chaotic Dynamics · Physics 2017-03-23 William D. Fullmer , Christine M. Hrenya

Cosmological constraints from cluster surveys rely on accurate mass estimates from the mass-observable relations. In order to avoid systematic biases and reduce uncertainties, we study the form and physical origin of the intrinsic scatter…

Cosmology and Nongalactic Astrophysics · Physics 2015-05-20 H. -Y. Karen Yang , Suman Bhattacharya , Paul M. Ricker

Influence of volume capture on a process of volume reflection of ultrarelativistic particles moving in bent single crystals was considered analytically. Relations describing various distributions of particles involving in the process, the…

Accelerator Physics · Physics 2008-08-12 Yu. A. Chesnokov , V. A. Maisheev , I. A. Yazynin

We use the Matryoshka run to study the time dependent statistics of structure-formation driven turbulence in the intracluster medium of a 10$^{15}M_\odot$ galaxy cluster. We investigate the turbulent cascade in the inner Mpc for both…

Cosmology and Nongalactic Astrophysics · Physics 2015-06-22 Francesco Miniati

In cluster tomography, we propose measuring the number of clusters $N$ intersected by a line segment of length $\ell$ across a finite sample. As expected, the leading order of $N(\ell)$ scales as $a\ell$, where $a$ depends on microscopic…

Disordered Systems and Neural Networks · Physics 2024-02-13 Helen S. Ansell , Samuel J. Frank , István A. Kovács

We investigate the behavior of microscopic heavy particles settling in homogeneous air turbulence. The regimes are relevant to the airborne transport of dust and droplets: the Taylor-microscale Reynolds number is Re = 289 - 462, the…

Fluid Dynamics · Physics 2021-05-12 Tim Berk , Filippo Coletti

We perform direct numerical simulations (DNS) of passive heavy inertial particles (dust) in homogeneous and isotropic two-dimensional turbulent flows (gas) for a range of Stokes number, ${\rm St} < 1$, using both Lagrangian and Eulerian…

Fluid Dynamics · Physics 2018-04-18 Dhrubaditya Mitra , Prasad Perlekar

Usual formulations of the clustering coefficient can be shown to be insufficient in the task of describing the local topology of very simple networks. Motivated by this, we review some alternatives in order to present an extension, the…

Data Analysis, Statistics and Probability · Physics 2007-05-23 Alexandre H. Abdo , A. P. S. de Moura

We propose an experimental study on the gravitational settling velocity of dense, sub-Kolmogorov inertial particles under different background turbulent flows. We report Phase Doppler Particle Analyzer measurements in a low-speed wind…

Fluid Dynamics · Physics 2022-07-18 Amélie Ferran , Nathanaël Machicoane , Alberto Aliseda , Martín Obligado

The collective diffusion coefficient $D_\mathrm{coll}$ is a key quantity for describing the macroscopic transport properties of soft matter systems. However, measuring $D_\mathrm{coll}$ is a fundamental experimental and numerical challenge,…

Soft Condensed Matter · Physics 2025-03-26 Adam Carter , Eleanor K. R. Mackay , Brennan Sprinkle , Alice L. Thorneywork , Sophie Marbach

One basic requirement of many studies is the necessity of classifying data. Clustering is a proposed method for summarizing networks. Clustering methods can be divided into two categories named model-based approaches and algorithmic…

Machine Learning · Computer Science 2013-02-19 Raheleh Namayandeh , Farzad Didehvar , Zahra Shojaei

Turbulent signals are known to exhibit burst-like activities, which affect the turbulence statistics at both large and small scales of the flow. In our study, we pursue this problem from the perspective of an event-based framework, where…

Fluid Dynamics · Physics 2023-01-26 Subharthi Chowdhuri , Tirtha Banerjee

Aggregation and disaggregation of clusters of attractive particles under flow are studied from numerical and theoretical points of view. Two-dimensional molecular dynamics simulations of both Couette and Poiseuille flows highlight the…

Floating particles that are initially distributed uniformly on the surface of a turbulent fluid, subsequently coagulate, until finally a steady state is reached. This being so, they manifestly form a compressible system. In this experiment,…

Fluid Dynamics · Physics 2015-05-20 Jason Larkin , Walter I. Goldburg

Clustering is an essential data mining tool that aims to discover inherent cluster structure in data. For most applications, applying clustering is only appropriate when cluster structure is present. As such, the study of clusterability,…

Machine Learning · Statistics 2018-10-30 A. Adolfsson , M. Ackerman , N. C. Brownstein

Strongly interacting binary mixtures of superparamagnetic colloidal particles confined to a two-dimensional water-air interface are examined by theory, computer simulation and experiment. The mixture exhibits a partial clustering in…

Soft Condensed Matter · Physics 2009-11-11 Norman Hoffmann , Florian Ebert , Christos N. Likos , Hartmut Löwen , Georg Maret

Meso-scale turbulence was originally observed experimentally in various suspensions of swimming bacteria, as well as in the collective motion of active colloids. The corresponding large-scale dynamical patterns were reproduced in a simple…

Soft Condensed Matter · Physics 2021-03-30 Vasco M. Worlitzer , Gil Ariel , Avraham Be'er , Holger Stark , Markus Bär , Sebastian Heidenreich

This paper exposes a novel exploratory formalism, which end goal is the numerical simulation of the dynamics of a cloud of particles weakly or strongly coupled with a turbulent fluid. Giventhe large panel of expertise of the list of…

Analysis of PDEs · Mathematics 2019-10-21 Ludovic Goudenège , Adam Larat , Julie Llobell , Marc Massot , David Mercier , Olivier Thomine , Aymeric Vié