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A probabilistic approach for computing water retention of particulate systems from statistics of grain size and tessellated pore network
Authors:Richard Wan  Mehdi Pouragha  Mahdad Eghbalian  Jérôme Duriez  Tai Wong
Institution:1. Department of Civil Engineering, University of Calgary, Calgary, Alberta, Canada;2. Irstea, UR RECOVER, Aix-en-Provence, F-13182 France
Abstract:The paper offers an analytical determination of the hydraulic properties of an unsaturated soil with reference to its retention curve, which describes the relationship between the volumetric water content and capillarity through matric suction. The analysis combines a particulate approach focused on the physics at the pore scale, including microstructural aspects, with a probabilistic approach where the void space and grain size are considered as random variables. In the end, the soil water characteristic curve of an unsaturated granular medium along a drying path can be derived analytically based on the sole information of particle size distribution. The analysis hinges on the tessellation of a wet granular system into an assemblage of tetrahedral unit cells revealing a pore network upon which capillary physics are computed with respect to pore throat invasion by a non-wetting fluid with evolving pendular capillary bridges. The crux of the paper is to pass from particle size probability distribution to a matching void space distribution to eventually reveal key information such as void cell and solid volume statistics. Making reasonable statistically based assumptions to render calculations tractable, the water retention curve can be readily constructed. Model predictions compare quite favourably with experimental data available for actual soils, especially in the high saturation range. Having a sound scientific basis, the model can be made amenable to address a variety of soils with a wider range of particle sizes.
Keywords:discrete element method (DEM)  granular materials  micromechanics  soil water characteristic curve  water retention
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