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Published on: December 4, 2017
9.1K
Grain-scale modeling of arbitrary fluid saturation in random packings
Konstantin Melnikov1, Roman Mani1, Falk K Wittel1
1Computational Physics for Engineering Materials, ETH Zürich, Stefano-Franscini-Platz 3, 8093 Zürich, Switzerland.
Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics
|September 19, 2015
Summary
This study introduces a new model for liquid saturation in granular materials, capturing complex liquid structures beyond simple capillary bridges. It accurately predicts liquid redistribution and Haines jumps in porous media.
Area of Science:
- Pore-scale physics
- Multiphase flow in porous media
- Granular materials science
Background:
- Understanding liquid saturation in granular packings is crucial for various industrial and environmental processes.
- Existing models often simplify liquid behavior, particularly beyond the capillary bridge regime.
- Accurate modeling requires accounting for complex liquid structures and dynamic redistribution.
Purpose of the Study:
- To develop a comprehensive model for liquid saturation in granular packings.
- To extend beyond the limitations of the capillary bridge regime.
- To accurately simulate liquid redistribution and pore-scale phenomena.
Main Methods:
- A novel model is proposed to resolve capillary bridges, menisci, and saturated pores.
- The model incorporates liquid film-mediated volume exchange driven by local Laplace pressure gradients.
- Haines jumps are included to simulate discontinuous liquid front evolution.
Main Results:
- The model successfully represents local liquid clusters of arbitrary shapes.
- It accounts for liquid redistribution beyond the capillary bridge regime.
- Simulations show good agreement with experimental data for individual liquid structures and larger systems.
Conclusions:
- The proposed model provides a more accurate representation of liquid saturation dynamics in granular materials.
- It offers a valuable tool for studying multiphase flow in porous media.
- The model's ability to capture complex phenomena like Haines jumps enhances its applicability.
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