Sensitivity analysis of Immersed Boundary Method simulations of fluid flow in dense polydisperse random grain packings
1 Department of Physics, Imperial College London, UK
2 Department of Mechanical Engineering, Imperial College London, UK
3 Department of Civil Engineering, Imperial College London, UK
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Published online: 30 June 2017
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 . Random grain packings were studied with linearly graded particle size distributions with a range of coefficient of uniformity values (Cu = 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  was investigated and a comparison was made between the predicted forces and the widely used Ergun correlation .
© The Authors, published by EDP Sciences, 2017
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