Applying Network Modeling to Determine Seepage-Induced Forces on Soil Particles

Abstract

A pore network model (PNM) idealizes the pore space in a soil as voids (network nodes) connected by pore throats (network edges). Along each edge the fluid flow rate is linearly related to the pressure drop by a hydraulic conductance. This study demonstrates the benefit of using a pore network model (PNM) with an appropriate conductance model in coupled particle–fluid simulations that use the discrete-element method (DEM) to simulate the particle phase. PNM simulations and fully resolved finite-volume method computational fluid dynamics (CFD) simulations are used to obtain the fluid–particle interaction force vectors on particles in virtual samples of sand created using DEM simulations. Linearly graded and bidisperse samples are considered. The study assesses the predictive capabilities of existing conductance models considering local flow rates, global permeability, and particle–fluid interaction force magnitude for the packings. A new refined conductance model that is developed upon models available in the literature is also proposed. Taking the fully resolved CFD data as a benchmark, the PNM approach is shown to better capture the heterogeneity in the magnitude of the particle–fluid interaction force acting on particles with a similar size than the coarse-grid CFD-DEM approach for all the samples considered. The orientation of particle–fluid interaction force vectors obtained from the fully resolved CFD is compared with the direction of the force vector predicted by a coarse-grid CFD-DEM and a PNM with the novel conductance model, where the PNM demonstrates a better accuracy. This work enables more realistic and more accurate coupled simulations of phenomena including liquefaction and internal erosion than has hitherto been possible.