Sensitivity analysis of Immersed Boundary Method simulations of fluid flow in dense polydisperse random grain packings
File(s)
Published version
Author(s)
Knight, C
Abdol Azis, MH
O'Sullivan, C
Van Wachem, B
Dini, D
Type
Conference Paper
Abstract
Polydisperse granular materials are ubiquitous in nature and industry. Despite this, knowledge of the momentum coupling between the fluid and solid phases in dense saturated grain packings comes almost exclusively from empirical correlations [2-4, 8] with monosized media. The Immersed Boundary Method (IBM) is a Computational Fluid Dynamics (CFD) modelling technique capable of resolving pore scale fluid flow and fluid-particle interaction forces in polydisperse media at the grain scale. Validation of the IBM in the low Reynolds number, high concentration limit was performed by comparing simulations of flow through ordered arrays of spheres with the boundary integral results of Zick and Homsy [10] . Random grain packings were studied with linearly graded particle size distributions with a range of coefficient of uniformity values (C u = 1.01, 1.50, and 2.00) at a range of concentrations (Φ ∈ [0.396; 0.681]) in order to investigate the influence of polydispersity on drag and permeability. The sensitivity of the IBM results to the choice of radius retraction parameter [1] was investigated and a comparison was made between the predicted forces and the widely used Ergun correlation [3].
Date Issued
2017-06-30
Date Acceptance
2017-06-01
Citation
EPJ Web of Conferences, 2017, 140
ISSN
2101-6275
Journal / Book Title
EPJ Web of Conferences
Volume
140
Copyright Statement
© The Authors, published by EDP Sciences. This is an open access article distributed under the terms of the Creative Commons Attribution License 4.0 (http://creativecommons.org/licenses/by/4.0/).
Source
Powders and Grains 2017 – 8th International Conference on Micromechanics on Granular Media
Place of Publication
EPD Sciencies
Publication Status
Published
Start Date
2017-07-03
Finish Date
2017-07-07
Coverage Spatial
Montpellier, South of France