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Cells and other soft particles are often forced to flow in confined geometries in both laboratory and natural environments, where the elastic deformation induces an additional drag and pressure drop across the particle. In contrast with…

Fluid Dynamics · Physics 2025-07-09 Charles Paul Moore , Hiba Belkadi , Brouna Safi , Gabriel Amselem , Charles N. Baroud

We consider a superstatistical dynamical model for the 3-d movement of a Lagrangian tracer particle embedded in a high-Reynolds number turbulent flow. The analytical model predictions are in excellent agreement with recent experimental data…

Statistical Mechanics · Physics 2009-11-11 Christian Beck

Numerical simulations are made for forced turbulence at a sequence of increasing values of Reynolds number, R, keeping fixed a strongly stable, volume-mean density stratification. At smaller values of R, the turbulent velocity is mainly…

Fluid Dynamics · Physics 2016-09-08 Jean-Philippe Laval , James C. McWilliams

We study the motion of a rigid sphere falling in a two-layer stratified fluid under the action of gravity in the potential flow regime. Experiments at a moderate Reynolds number of approximately 20 to 450 indicate that a sphere with the…

Particle-laden turbulent flow that separates due to a bump inside a channel is simulated to analyse the effects of the Stokes number and the lift force on the particle spatial distribution. The fluid friction Reynolds number is…

A statistical mechanics theory for a fluid stratified in density is presented. The predicted statistical equilibrium state is the most probable outcome of turbulent stirring. The slow temporal evolution of the vertical density profile is…

Fluid Dynamics · Physics 2014-09-23 Antoine Venaille , Louis Gostiaux , Joël Sommeria

Systematic deflection of microparticles off of initial streamlines is a fundamental task in microfluidics, aiming at applications including sorting, accumulation, or capture of the transported particles. In a large class of setups,…

Fluid Dynamics · Physics 2026-04-01 Partha Kumar Das , Xuchen Liu , Sascha Hilgenfeldt

We present particle-resolved simulations of dense frictional suspensions undergoing the viscous-inertial transition using pressure-imposed rheology. By varying the fluid viscosity, shear rate, and granular pressure, we find that the…

Direct numerical simulations of turbulent suspension flows are carried out with the Force-Coupling Method in plane Couette and pressure-driven channel configurations. Dilute to moderately concentrated suspensions of neutrally buoyant…

Fluid Dynamics · Physics 2018-08-15 Guiquan Wang , Micheline Abbas , Eric Climent

At finite Reynolds numbers, Re, particles migrate across laminar flow streamlines to their equilibrium positions in microchannels. This migration is attributed to a lift force, and the balance between this lift and gravity determines the…

We present a sweep-stick mechanism for heavy particles transported by a turbulent flow under the action of gravity. Direct numerical simulations show that these particles preferentially explore regions of the flow with close to zero…

Fluid Dynamics · Physics 2020-08-12 Florencia Falkinhoff , Martin Obligado , Mickaël Bourgoin , Pablo D. Mininni

Fluid deformation and strain history are central to wide range of fluid mechanical phenomena ranging from fluid mixing and particle transport to stress development in complex fluids and the formation of Lagrangian coherent structures…

Fluid Dynamics · Physics 2025-10-03 Daniel R. Lester , Marco Dentz , Tanguy Le Borgne , Felipe P. J. de Barros

The dynamics of inertial particles in turbulence is modelled and investigated by means of direct numerical simulation of an axisymmetrically expanding homogeneous turbulent strained flow. This flow can mimic the dynamics of particles close…

Fluid Dynamics · Physics 2023-07-19 Chung-min Lee , Ármann Gylfason , Prasad Perlekar , Federico Toschi

The modulation of drag through dispersed phases in wall turbulence has been a longstanding focus. This study examines the effects of particle Stokes number ($St$) and Froude number ($Fr$) on drag modulation in turbulent Taylor-Couette (TC)…

Fluid Dynamics · Physics 2025-05-27 Hao Jiang , Zhi-Ming Lu , Yuan Ma , Kai Leong Chong

The dispersion of Lagrangian particle pairs is a fundamental process in turbulence, with implications for mixing, transport, and the statistical properties of particles in geophysical and environmental flows. While classical theories…

Fluid Dynamics · Physics 2025-09-17 Christian Reartes , Pablo D. Mininni , Raffaele Marino

The turbulent diffusion of Lagrangian tracer particles has been studied in a flow on the surface of a large tank of water and in computer simulations. The effect of flow compressibility is captured in images of particle fields. The velocity…

Chaotic Dynamics · Physics 2009-11-10 John R. Cressman , Walter I. Goldburg , Joerg Schumacher

The macroscopic behaviour of foams is deeply related to rearrangements occurring at the bubble scale, which dynamics depends on the mobility of the interstitial phase. In this paper, we resort to drainage experiments to quantify this…

Soft Condensed Matter · Physics 2013-12-24 Y. Khidas , B. Haffner , O. Pitois

We investigate systems of self-propelled particles with alignment interaction. Compared to previous work, the force acting on the particles is not normalized and this modification gives rise to phase transitions from disordered states at…

Mathematical Physics · Physics 2014-09-25 Pierre Degond , Amic Frouvelle , Jian-Guo Liu

Dense suspensions of hard particles in a Newtonian liquid can be jammed by shear when the applied stress exceeds a certain threshold. However, this jamming transition from a fluid into a solidified state cannot be probed with conventional…

Soft Condensed Matter · Physics 2019-12-18 Endao Han , Nicole M. James , Heinrich M. Jaeger

We analyse the motion of a system of particles subjected a random force fluctuating in both space and time, and experiencing viscous damping. When the damping exceeds a certain threshold, the system undergoes a phase transition: the…

Disordered Systems and Neural Networks · Physics 2009-11-10 M. Wilkinson , B. Mehlig