Modeling capillary-driven particle agglomeration under shear in immiscible fluids using discrete multiphysics

In this study, we introduce a discrete multiphysics (DMP) model designed to simulate particulate systems where solid particles are immersed in a sheared primary fluid (water) and coated by an immiscible secondary fluid (oil). When dispersed particles come into contact with each other, the secondary fluid around the particles merges into a liquid bridge that induces particle agglomeration through capillary interaction. The model employs smoothed particle hydrodynamics to represent the primary liquid and the discrete element method for the solid particles. The secondary fluid is not explicitly modeled. Instead, we consider its impact indirectly by incorporating the attractive forces generated by the liquid bridges. These forces, arising when particles come into contact, are treated as additional attractive interactions within the DMP framework. Two liquid-bridge force models are selected for the simulations and validated against experimental observations in a granular collapse scenario. Subsequently, these validated models are integrated into the DMP framework to simulate particle agglomeration under shear, revealing three distinct agglomeration regimes based on varying Reynolds and elastocapillary numbers. These regimes are characterized by the formation of aggregates with diverse sizes and shapes, from elongated cylinders to spheroids. Results are presented in “agglomeration maps,” which facilitate the prediction of aggregate characteristics based on known Reynolds and elastocapillary numbers.

Authors

Institutions

Publication Details

Journal
Physics of Fluids
Published
2025-03-01
DOI
https://doi.org/10.1063/5.0247290
Citations
1
Primary Topic
Granular flow and fluidized beds
Type
article
Field-Weighted Citation Impact
1.33
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Modeling capillary-driven particle agglomeration under shear in immiscible fluids using discrete multiphysics

Alessio Alexiadis, Peter J. Scales, Anthony D. Stickland, Yunzhou Qian et al.
1 citations
Physics of Fluids
Granular flow and fluidized beds
1.33
article

Modeling capillary-driven particle agglomeration under shear in immiscible fluids using discrete multiphysics

Alessio Alexiadis, Peter J. Scales, Anthony D. Stickland, Yunzhou Qian, Shane P. Usher
article en
1 citations

Abstract

In this study, we introduce a discrete multiphysics (DMP) model designed to simulate particulate systems where solid particles are immersed in a sheared primary fluid (water) and coated by an immiscible secondary fluid (oil). When dispersed particles come into contact with each other, the secondary fluid around the particles merges into a liquid bridge that induces particle agglomeration through capillary interaction. The model employs smoothed particle hydrodynamics to represent the primary liquid and the discrete element method for the solid particles. The secondary fluid is not explicitly modeled. Instead, we consider its impact indirectly by incorporating the attractive forces generated by the liquid bridges. These forces, arising when particles come into contact, are treated as additional attractive interactions within the DMP framework. Two liquid-bridge force models are selected for the simulations and validated against experimental observations in a granular collapse scenario. Subsequently, these validated models are integrated into the DMP framework to simulate particle agglomeration under shear, revealing three distinct agglomeration regimes based on varying Reynolds and elastocapillary numbers. These regimes are characterized by the formation of aggregates with diverse sizes and shapes, from elongated cylinders to spheroids. Results are presented in “agglomeration maps,” which facilitate the prediction of aggregate characteristics based on known Reynolds and elastocapillary numbers.

Physics of FluidsVol. 37(3)
The University of Melbourne (AU), ARC Centre of Excellence for Enabling Eco-Efficient Beneficiation of Minerals (AU), University of Birmingham (GB)
Openalex Percentile: Top 26%
Granular flow and fluidized beds
1.33
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.