Multiphase soil-water interaction in granular media
Creators: name: Wang, Qiuyu, 1995-
name: 0000-0003-0985-3539
Publisher: name: The University of Texas at Austin
Year: 2023
Subjects: Multiphase lattice Boltzmann method
Unsaturated granular soils
Water retention behavior
X-ray Computed Tomography
LBM-DEM
Submarine landslide
Granular column collapse
Runout potential
Inverse analysis
Automatic Differentiation
Lattice Boltzmann method
Taichi programming

description: The study of soil-water interaction has been a fundamental and longstanding issue in the field of geotechnical engineering. It plays a critical role by affecting the shear strength, compressibility, permeability, and volumetric changes in soils, thereby influencing the design and safety of structures like dams, embankments, and foundations. Investigation into soil-water interaction typically employs experimental techniques and continuum mechanics-based models, such as Finite Element and Finite Difference Methods. However, these traditional methods face challenges in dealing with the heterogeneity and nonlinearity of the soil, complicated boundary conditions, and transient or non-equilibrium processes. Therefore, the development of more realistic models to better capture soil-water interaction remains crucial. This dissertation focuses on the development and application of advanced numerical algorithms utilizing the lattice Boltzmann Method (LBM) and Discrete Element Method (DEM) across three primary areas of study. These include 1) The investigation of water retention behavior and the source of hysteresis by multiphase LBM; 2) The evaluation of submarine landslides through modeling granular column collapse by coupling LBM with DEM; and 3) The reverse analysis of fluid flow in complex granular media by integrating automatic differentiation (AD) with LBM. First, we focus on the investigation of water retention behavior in granular soils, leveraging both Computed Tomography (CT) experiments and the multiphase lattice Boltzmann Method (LBM). We conduct a CT experiment on Hamburg sand to acquire its water retention curve, then apply LBM simulations based on the CT-derived grain skeleton. These simulations successfully capture hysteresis and other pore-scale behaviors seen in the experimental data. Our LBM analysis reveals how variations in the spatial distribution and morphology of gas clusters between drainage and imbibition processes underpin hysteresis. Next, we turn our attention to submarine landslides, which despite their low slope angles, transport vast amounts of sediment across continental shelves, potentially causing significant infrastructural damage and loss of life. We use a two-dimensional coupled lattice Boltzmann and discrete element (LBM-DEM) method to understand how the initial volume of sediment affects the run-out characteristics of these landslides. Our approach allows for pore-scale resolution of fluid flow, aiding in understanding the grain-scale mechanisms behind these complex phenomena. Lastly, we introduce an effective method for inverse analysis of fluid flow problems. Our goal is to accurately determine boundary conditions and characterize the physical properties of granular media, such as permeability, and fluid components, like viscosity. By combining the lattice Boltzmann Method (LBM) with Automatic Differentiation (AD), facilitated by the GPU-capable Taichi programming language, we can backpropagate through the entire LBM simulation. This approach provides accurate estimates of boundary conditions, helping to derive macro-scale permeability and fluid viscosity for complex flow paths in porous media. The method offers significant advantages in prediction accuracy and computational efficiency, making it a potent tool for a wide range of applications.