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Droplet deformations caused by substrate vibrations are ubiquitous in nature and highly relevant for applications such as microreactors and single-cell sorting. The vibrations can induce droplet oscillations, a fundamental process that…

We measure the flow of granular materials inside a quasi-two dimensional silo as it drains and compare the data with some existing models. The particles inside the silo are imaged and tracked with unprecedented resolution in both space and…

Soft Condensed Matter · Physics 2007-05-23 Jaehyuk Choi , Arshad Kudrolli , Martin Z. Bazant

We introduce a system of shallow water-type equations to model laboratory experiments of particle-laden flows. We explore homogeneous liquid-solid suspensions of fine, non-cohesive, monodisperse glass beads which propagate as an equivalent…

Fluid Dynamics · Physics 2025-02-11 Andrea Bondesan , Laurence Girolami , François James , Loïc Rousseau

In this work, an efficient physics-constrained deep learning model is developed for solving multiphase flow in 3D heterogeneous porous media. The model fully leverages the spatial topology predictive capability of convolutional neural…

Geophysics · Physics 2021-05-21 Bicheng Yan , Dylan Robert Harp , Bailian Chen , Rajesh Pawar

The flow behaviors of polymer melt composed of short chains with ten beads between parallel plates are simulated by using a hybrid method of molecular dynamics and computational fluid dynamics. Three problems are solved: creep motion under…

Soft Condensed Matter · Physics 2014-01-20 Shugo Yasuda , Ryoichi Yamamoto

We study the dynamics of a single trapped probe surrounded by self-propelled active particles in two dimensions. In the limit of large size separation, we perform an adiabatic elimination of the small active particles to obtain an effective…

Soft Condensed Matter · Physics 2023-07-21 Ashreya Jayaram , Thomas Speck

A layer of granular material on a vertically vibrating sawtooth-shaped base exhibits horizontal flow whose speed and direction depend on the parameters specifying the system in a complex manner. Discrete-particle simulations reveal that the…

Soft Condensed Matter · Physics 2009-11-07 M. Levanon , D. C. Rapaport

Understanding particle transport and localisation in porous channels, especially at moderate Reynolds numbers, is relevant for many applications ranging from water reclamation to biological studies. Recently, researchers experimentally…

Fluid Dynamics · Physics 2019-01-30 Mike Garcia , Baskar Ganapathysubramanian , Sumita Pennathur

Dynamics of the particle phase in a particle laden turbulent flow is highly influenced by the fluctuating velocity and vorticity field of the fluid phase. The present work mainly focuses on exploring the possibility of applying a Langevin…

Fluid Dynamics · Physics 2021-06-08 Swagnik Ghosh , Partha Sarathi Goswami

We use molecular dynamics simulations to study the behavior of a compressible Lennard-Jones fluid in simple shear flow in a two-dimensional nanochannel. The system is equilibrated in the fluid phase close to the triple point at which gas,…

Soft Condensed Matter · Physics 2017-03-31 Madhu Priya , Yitzhak Rabin

This work is focused on the development of a dynamic criterion for the arching and bridging of spherical particles in a 3D suspension flow through a channel with plane walls. Elasticity of the particles and the channel walls are taken into…

Fluid Dynamics · Physics 2018-10-24 Igor A. Garagash , Andrei A. Osiptsov , Sergei A. Boronin

One key issue in the probability density function (PDF) approach for disperse two-phase turbulent flows is to close the diffusion term in the phase space. This study aimed to derive a kinetic equation for particle dispersion in turbulent…

Statistical Mechanics · Physics 2020-07-15 De-yu Zhong , Guang-qian Wang , Tie-jian Li , Ming-xi Zhang , You Xia

Active matter comprised of many self-driven units can exhibit emergent collective behaviors such as pattern formation and phase separation in both biologica and synthetic systems. While these behaviors are increasingly well understood for…

Soft Condensed Matter · Physics 2015-07-27 Syeda Sabrina , Matthew Spellings , Sharon C. Glotzer , Kyle J. M. Bishop

We develop a model of the forces on a spherical particle suspended in flow through a curved duct under the assumption that the particle Reynolds number is small. This extends an asymptotic model of inertial lift force previously developed…

Fluid Dynamics · Physics 2025-12-19 B. Harding , Y. M. Stokes , A. L. Bertozzi

Smoothed particle hydrodynamics (SPH) has been extensively studied in computer graphics to animate fluids with versatile effects. However, SPH still suffers from two numerical difficulties: the particle deficiency problem, which will…

Graphics · Computer Science 2020-01-29 Xiaowei He , Huamin Wang , Guoping Wang , Hongan Wang , Enhua Wu

Continuum fluid dynamic models based on the Navier-Stokes equations have previously been used to simulate granular media undergoing fluid-like shearing. These models, however, typically fail to predict the flow behaviour in confined…

Fluid Dynamics · Physics 2024-03-05 Duncan Dockar , M. H. Lakshminarayana Reddy , Matthew K. Borg , S. Kokou Dadzie

Lagrangian stochastic methods are widely used to model turbulent flows. Scarce consideration has, however, been devoted to the treatment of the near-wall region and to the formulation of a proper wall-boundary condition. With respect to…

Fluid Dynamics · Physics 2024-02-07 Guilhem Balvet , Jean-Pierre Minier , Yelva Roustan , Martin Ferrand

A central obstacle to understanding the route to turbulence in wall-bounded flows is that the flows are composed of complex, highly fluctuating, and strongly nonlinear states. In the case of pipe flow, models have deepened our understanding…

Fluid Dynamics · Physics 2026-02-24 Santiago J. Benavides , Dwight Barkley

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

A modeling paradigm is developed to augment predictive models of turbulence by effectively utilizing limited data generated from physical experiments. The key components of our approach involve inverse modeling to infer the spatial…

Computational Engineering, Finance, and Science · Computer Science 2016-11-08 Anand Pratap Singh , Shivaji Medida , Karthik Duraisamy