Utilizing the Explicit Finite Element Method for Studying Granular Flows

Abstract

Granular flows are systems of complex dry particulates whose behavior is difficult to predict during sliding contact. Existing computational tools used to simulate granular flows are particle dynamics, cellular automata (CA), and continuum modeling. In the present investigation, another numerical tool—the explicit finite element method (FEM)—is analyzed as a potential technique for simulating granular flow. For this purpose, explicit dynamic finite element models of parallel shear cells were developed. These models contained 52 particles and consisted of granules that are both round and multi-shaped (diamond, triangle, and rectangle). Each parallel shear cell consisted of a smooth stationary top wall and a rough bottom surface that was given a prescribed velocity of U = 0.7 in/sec (1.78 cm/s). The coefficient of friction (COF) between the particle–particle and particle–wall collisions was varied between 0.0 and 0.75. Utilizing the output of the simulations, results are presented for the shear behavior, particle kinetic energy, and particle stresses within the shear cell as a function of time. As a means of validating the explicit technique for granular flow, a 75 particle, zero roughness, couette shear cell model (solid fraction of 0.50) is subsequently presented for which direct comparisons are made to the results published by Lun. [Lun, C.K. et al.: Phys. Fluids 8, 2868–2883 (1996)] Overall, the results indicate that the explicit FEM is a powerful tool for simulating granular flow phenomena in sliding contacts. In fact, the explicit method demonstrated several advantages over existing numerical techniques while providing equivalent accuracy to the molecular dynamics (MD) approach. These advantages included being able to monitor the collision (sub-surface and surface) stresses and kinetic energies of individual particles over time, the ability to analyze any particle shape, and the ability to capture force chains during granular flow.