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A Lagrangian experimental study of an axisymmetric turbulent water jet is performed to investigate the highly anisotropic and inhomogeneous flow field. The measurements were conducted within a Lagrangian exploration module, an icosahedron…

We consider $N$ identical inertialess rigid spherical particles in a Stokes flow in a domain $\Omega \subset \mathbb R^3$. We study the average sedimentation velocity of the particles when an identical force acts on each particle. If the…

偏微分方程分析 · 数学 2024-05-22 Matthieu Hillairet , Richard M. Höfer

In the present study, we perform direct numerical simulations of compressible turbulent boundary layers at the free stream Mach number of 2 ~ 6 laden with dilute phase of spherical particles to investigate the Mach number effects on…

流体动力学 · 物理学 2024-11-20 Ming Yu , Lihao Zhao , Xianxu Yuan , Chunxiao Xu

Aerosols are ubiquitous, and particle capture from particle-laden air as it flows past an obstacle is of widespread practical importance. Neglecting diffusion, previous work has shown that for a smooth curved surface in both Stokes flow and…

流体动力学 · 物理学 2025-02-26 Joshua F. Robinson , Patrick B. Warren , Matthew R. Turner , and Richard P. Sear

We study the dynamics and clustering of dust particles with inertia in shock-dominated compressible turbulence using the two-dimensional, stochastically forced Burgers equation. At small Stokes numbers, shock trapping leads to extreme…

流体动力学 · 物理学 2025-12-09 Anikat Kankaria , Samriddhi Sankar Ray

As most mathematically justifiable Lagrangian coherent structure detection methods rely on spatial derivatives, their applicability to sparse trajectory data has been limited. For experimental fluid dynamicists and natural scientists…

流体动力学 · 物理学 2024-11-20 Nikolas O. Aksamit , Alex P. Encinas-Bartos , George Haller , David E. Rival

We present a detailed investigation of the particle pair separation process in homogeneous isotropic turbulence. We use data from direct numerical simulations up to Taylor's Reynolds number 280 following the evolution of about two million…

混沌动力学 · 物理学 2009-11-11 L. Biferale , G. Boffetta , A. Celani , B. J. Devenish , A. Lanotte , F. Toschi

We propose a defiltering method of turbulent flow fields for Lagrangian particle tracking using machine learning techniques. Numerical simulation of Lagrangian particle tracking is commonly used in various fields. In general, practical…

流体动力学 · 物理学 2024-11-21 Tomoya Oura , Koji Fukagata

The aggregation properties of heavy inertial particles in the elastic turbulence regime of an Oldroyd-B fluid with periodic Kolmogorov mean flow are investigated by means of extensive numerical simulations in two dimensions. Both the small…

流体动力学 · 物理学 2018-10-03 Himani Garg , Enrico Calzavarini , Gilmar Mompean , Stefano Berti

The statistical properties of the Lagrangian acceleration vector of passive tracers in statistically-steady rotating turbulence is studied by Particle Tracking Velocimetry. Direct effects of the background rotation are the suppression of…

流体动力学 · 物理学 2013-07-29 Lorenzo Del Castello , Herman J. H. Clercx

We propose a one-way coupled model that tracks individual primary particles in a conceptually simple cellular flow setup to predict flocculation in turbulence. This computationally efficient model accounts for Stokes drag, lubrication,…

流体动力学 · 物理学 2020-04-22 K. Zhao , B. Vowinckel , T. -J. Hsu , T. Köllner , B. Bai , E. Meiburg

The main motivation of this work is the quantitative prediction and description of particle manipulation (displacement across streamlines) in microfluidic flow. Much attention has been paid recently to placing particles in fast oscillatory…

流体动力学 · 物理学 2026-03-24 Xuchen Liu

Cellular suspensions such as dense bacterial flows exhibit a turbulence-like phase under certain conditions. We study this phenomenon of "active turbulence" statistically by using numerical tools. Following Wensink et al. [Proc. Natl. Acad.…

流体动力学 · 物理学 2018-02-15 Martin James , Michael Wilczek

Models for prediction of drag forces within a particle cloud following shock-acceleration are evaluated with the aid of results from particle-resolved simulations in order to quantify how much the disturbances introduced by the proximity of…

流体动力学 · 物理学 2021-01-11 Andreas Nygård Osnes , Magnus Vartdal

We consider the sedimentation of $N$ spherical particles with identical radii $R$ in a Stokes flow in $\mathbb R^3$. The particles satisfy a no-slip boundary condition and are subject to constant gravity. The dynamics of the particles is…

偏微分方程分析 · 数学 2025-01-10 Richard M. Höfer , Richard Schubert

We study the motion of an inertial particle in a fractional Gaussian random field. The motion of the particle is described by Newton's second law, where the force is proportional to the difference between a background fluid velocity and the…

动力系统 · 数学 2012-03-20 Georg Schöchtel

We explore the self-propulsion of an active Ornstein-Uhlenbeck particle with a non-linear velocity dependent friction. Using analytical approach and numerical simulation, we have exactly investigated the dynamical behaviour of the particle…

软凝聚态物质 · 物理学 2024-05-15 N Arsha , M Sahoo

We develop a stochastic model for the velocity gradients dynamics along a Lagrangian trajectory. Comparing with different attempts proposed in the literature, the present model, at the cost of introducing a free parameter known in…

流体动力学 · 物理学 2018-02-23 Rodrigo M. Pereira , Luca Moriconi , Laurent Chevillard

The Lagrangian approach is natural to study issues of turbulent dispersion and mixing. We propose in this work a general Lagrangian stochastic model including velocity and acceleration as dynamical variables for inhomogeneous turbulent…

流体动力学 · 物理学 2020-05-01 Alessio Innocenti , Nicolas Mordant , Nick Stelzenmuller , Sergio Chibbaro

The statistical properties of fluid particles transported by a fully developed turbulent flow are investigated by means of high resolution direct numerical simulations. Single trajectory statistics is investigated in a time range spanning…

混沌动力学 · 物理学 2007-05-23 L. Biferale , G. Boffetta , A. Celani , A. Lanotte , F. Toschi