Particle-resolved simulation of freely evolving particle suspensions: Flow physics and modeling

TL;DR

This study uses particle-resolved simulations to analyze the flow physics of freely evolving particle suspensions, focusing on drag forces, particle interactions, and developing a new drag correlation for improved CFD modeling.

Contribution

It introduces a novel drag correlation derived from simulations that accounts for particle motion, clustering, and velocity fluctuations in particle suspensions.

Findings

Drag force varies with particle clustering and velocity fluctuations.

Particle motion significantly influences interphase drag.

A new correlation for drag force based on volume fraction, Reynolds number, and density ratio.

Abstract

The objective of this study is to understand the dynamics of freely evolving particle suspensions over a wide range of particle-to-fluid density ratios. The dynamics of particle suspensions are characterized by the average momentum equation, where the dominant contribution to the average momentum transfer between particles and fluid is the average drag force. In this study, the average drag force is quantified using particle-resolved direct numerical simulation in a canonical problem: a statistically homogeneous suspension where an imposed mean pressure gradient establishes a steady mean slip velocity between the phases. The effects of particle velocity fluctuations, particle clustering, and mobility of particles are studied separately. It is shown that the competing effects of these factors could decrease, increase, or keep constant the drag of freely evolving suspensions in comparison to fixed beds at different flow conditions. It is also shown that the effects of particle clustering and particle velocity fluctuations are not independent. Finally, a correlation for interphase drag force in terms of volume fraction, Reynolds number, and density ratio is proposed. Two different approaches (symbolic regression and predefined functional forms) are used to develop the drag correlation. Since this drag correlation has been inferred from simulations of particle suspensions, it includes the effect of the motion of the particles. This drag correlation can be used in computational fluid dynamics simulations of particle-laden flows that solve the average two-fluid equations where the accuracy of the drag law affects the prediction of overall flow behavior.