| Issue |
EPJ Web Conf.
Volume 340, 2025
Powders & Grains 2025 – 10th International Conference on Micromechanics on Granular Media
|
|
|---|---|---|
| Article Number | 08010 | |
| Number of page(s) | 4 | |
| Section | Particulate Multiphase Flows and Porous Media | |
| DOI | https://doi.org/10.1051/epjconf/202534008010 | |
| Published online | 01 December 2025 | |
https://doi.org/10.1051/epjconf/202534008010
On the attempts to reduce parasitic viscous forces in the oil-air capillary bridge simulations
1 Department of Civil and Environmental Engineering, Imperial College London
2 Department of Civil and Environmental Engineering, Institute of Science, Tokyo
Published online: 1 December 2025
Abstract
Setting up a stable multiphase Volume of Fluid (VoF) numerical simulation to quantify capillary bridge forces acting on soil particles in the pendular regime presents significant computational challenges. Non-physical currents in these surface tension dominated simulations generate parasitic viscous forces that compromise the total force predictive capability of the numerical model. This study examines a two-sphere system with an intervening capillary bridge as its primary test case. OpenFOAM’s Geometric (PLIC, isoAdvector) and Algebraic (MULES) VoF approaches using the CSF Surface Tension (ST) model proved insufficient, necessitating modifications to the ST model. Two specific advanced ST models for the algebraic VoF were investigated: Laplacian Smoothing (SCSF) and Sharpening with Smoothing (SSF) of the VoF field. The parameters of the ST model require tuning based on the specific fluid combination considered. For oil-air fluid combinations characterized by a high density ratio, high viscosity, and weak surface tension forces compared to water-air systems, careful calibration of solver parameters, mesh division, and time step are essential to minimize spurious currents while preserving interface curvature accuracy.
© The Authors, published by EDP Sciences, 2025
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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