| Understanding granular flows has always been important to predict natural phenomena such as avalanches, landslides, and soil erosion, in addition to industrial processes such as coal transporting and food processing. However, the nonlinear and multiphase behavior exhibited by these particulate systems makes them difficult to model and to predict. The current work attempts to understand the shearing of inelastic granular materials between rough surfaces in detail. More specifically, this work aims to uncover and study a phenomenon that suggests the existence of granular flow lubrication. Understanding this interaction can have implications on industrial-scale granular systems related to wheel-terrain interaction, agricultural processing, and coal transportation. Granular flows are composed of discrete particles that collectively behave as solids, liquids and gases under varying circumstances. Consequently, due to the lack of universally accepted and applicable equations of motion, researchers have used modeling and experimentation to gain insight into granular behavior. In this work, a discrete element type lattice-based cellular automata model has been developed to model granular flows under shear. Physics-based equations developed from first-principles are adopted to form the cellular automata local rules of interaction to combine the computational efficiency of lattice-based modeling with the accuracy of first-principle physics modeling. A two-dimensional annular granular shear cell was designed and fabricated to conduct shearing experiments. In these experiments, the effects of experimentally quantified roughness, shear rate, solid fraction and granular material were explored. In a separate attempt to more directly uncover hydrodynamic granular flow behavior, a granular lubricated journal bearing was designed and constructed; this apparatus demonstrated that granular flows entrained into a converging gap could exhibit lubrication behavior. Some results from this advanced apparatus are presented as well. |
