中文
相关论文

相关论文: Microstructure-based prediction of hydrodynamic fo…

200 篇论文

We present a new general model for the prediction of the drag coefficient of non-spherical solid particles of regular and irregular shapes falling in gas or liquid valid for sub-critical particle Reynolds numbers (i.e. $Re < 3 \times…

流体动力学 · 物理学 2018-10-23 Gholamhossein Bagheri , Costanza Bonadonna

A generalized physics-based expression for the drag coefficient of spherical particles moving in a fluid is derived. The proposed correlation incorporates essential rarefied physics, low-speed hydrodynamics, and shock-wave physics to…

We propose a method to parameterize a coarse grained model for the hydrodynamic friction between nearly touching rough spheres in suspension flows. The frictional resistance due to surface roughness primarily alters the sliding and rolling…

软凝聚态物质 · 物理学 2022-03-15 Madhu V. Majji , James W. Swan

In CFD simulations of two-phase flows, accurate drag force modeling is essential for predicting particle dynamics. However, a generally valid formulation is lacking, as all available drag force correlations have been established for…

流体动力学 · 物理学 2023-02-08 Gizem Ozler , Mustafa Demircioglu , Holger Grosshans

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…

流体动力学 · 物理学 2025-07-09 Charles Paul Moore , Hiba Belkadi , Brouna Safi , Gabriel Amselem , Charles N. Baroud

Laboratory experiments were conducted to study particle migration and flow properties of non- Brownian, non-colloidal suspensions ranging from 10% to 40% particle volume fraction in a pressure-driven flow over and through a porous structure…

流体动力学 · 物理学 2023-02-01 Parisa Mirbod , Nina C. Shapley

Three-dimensional Voronoi analysis is used to quantify the clustering of inertial particles in homogeneous isotropic turbulence using data from numerics and experiments. We study the clustering behavior at different density ratios and…

The experimental observation of collective behaviour in proton-proton and proton-nucleus collisions poses a fundamental theoretical question regarding the proper characterization of the initial state underlying hydrodynamic evolution. While…

高能物理 - 唯象学 · 物理学 2026-05-28 Gabriel Rabelo-Soares , Gojko Vujanovic , Giorgio Torrieri

We describe simulations of a microscopic elastic filament immersed in a fluid and subject to a uniform external force. Our method accounts for the hydrodynamic coupling between the flow generated by the filament and the friction force it…

软凝聚态物质 · 物理学 2009-11-11 M. Cosentino Lagomarsino , I. Pagonabarraga , C. P. Lowe

Turbulent flows consist of a wide range of interacting scales. Since the scale range increases as some power of the flow Reynolds number, a faithful simulation of the entire scale range is prohibitively expensive at high Reynolds numbers.…

流体动力学 · 物理学 2023-07-24 Dhawal Buaria , Katepalli R. Sreenivasan

Physics-based simulations are often used to model and understand complex physical systems and processes in domains like fluid dynamics. Such simulations, although used frequently, have many limitations which could arise either due to the…

机器学习 · 计算机科学 2019-11-12 Nikhil Muralidhar , Jie Bu , Ze Cao , Long He , Naren Ramakrishnan , Danesh Tafti , Anuj Karpatne

We have generalized a method for the numerical solution of hyperbolic systems of equations using a dynamic Voronoi tessellation of the computational domain. The Voronoi tessellation is used to generate moving computational meshes for the…

高能天体物理现象 · 物理学 2015-05-27 Paul C. Duffell , Andrew I. MacFadyen

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…

流体动力学 · 物理学 2019-01-30 Mike Garcia , Baskar Ganapathysubramanian , Sumita Pennathur

Patterned surfaces with large effective slip lengths, such as super-hydrophobic surfaces containing trapped gas bubbles, have the potential to reduce hydrodynamic drag. Based on lubrication theory, we analyze an approach of a hydrophilic…

流体动力学 · 物理学 2015-03-14 Aleksey V. Belyaev , Olga I. Vinogradova

A model for the pseudo-turbulent Reynolds stress tensor in compressible flows through monodisperse particle clouds is developed based on data from particle resolved numerical simulations. This model extends previous models for the…

流体动力学 · 物理学 2025-05-09 Andreas Nygård Osnes , Magnus Vartdal

Relativistic hydrodynamics of classic plasmas is derived from the microscopic model in the limit of ideal plasmas. The chain of equations is constructed step by step starting from the concentration evolution. It happens that the energy…

等离子体物理 · 物理学 2023-08-09 Pavel A. Andreev

This paper derives new correlations to predict the drag, lift and torque coefficients of axi-symmetric non-spherical rod-like particles for several fluid flow regimes and velocity profiles. The fluid velocity profiles considered are locally…

流体动力学 · 物理学 2023-12-18 Victor Chéron , Fabien Evrard , Berend van Wachem

The GENERIC structure allows for a unified treatment of different discrete models of hydrodynamics. We first propose a finite volume Lagrangian discretization of the continuum equations of hydrodynamics through the Voronoi tessellation. We…

统计力学 · 物理学 2007-05-23 Mar Serrano , Pep Español

An accurate prediction of the translational and rotational motion of particles suspended in a fluid is only possible if a complete set of correlations for the force coefficients of fluid-particle interaction is known. The present study is…

流体动力学 · 物理学 2020-09-24 Martyna Minakowska , Thomas Richter , Sebastian Sager

Low Reynolds number direct simulations of large populations of hydrodynamically interacting swimming particles confined between planar walls are performed. The results of simulations are compared with a theory that describes dilute…

流体动力学 · 物理学 2015-05-13 Juan P. Hernandez-Ortiz , Patrick T. Underhill , Michael D. Graham