Using a Lattice-Based Cellular Automata Approach to Model the Load Carrying Capacity of Granular Flows

Flows of solid granular particles are proposed as an alternate lubrication mechanism to conventional liquid lubrication in sliding contacts, because of their ability to carry loads and to accommodate surface velocities. Alternate lubrication is becoming necessary in extreme temperature environments where liquid lubricants fail and in micro/nanoscale environments were they promote stiction. However understanding granular behavior has been a challenge because of their ability to behave as solids, liquids and gases with varying circumstances. Cellular automata (CA), a deterministic rule based mathematics approach, has been successful in modeling some complex aspects of granular behavior. Our previous work successfully modeled granular shear with CA model. This work introduces a more versatile and novel cellular automata framework which combines the computational efficiency of CA with the power of particle dynamics to capture collision events. In the past, the load carrying capacity of granular flows was demonstrated in the experiments conducted by Yu and Tichy [2] and later, local flow properties were modeled using the granular kinetic lubrication continuum modeling approach. These results were used as a benchmark for determining the effectiveness of the current CA model.