Analog and numerical experiments investigating force chain influences on the bed physics of dense granular flows

• Main Author: Estep, Joseph Jeremiah
• Other Authors: Dufek, Josef
• Format: Others
• Language: en_US
• Published: Georgia Institute of Technology 2014
• Subjects: Force chains; Granular flows; Granular flow; Force and energy; Photoelasticity; Computer simulation
• Online Access: http://hdl.handle.net/1853/51768

Granular materials are composed of solid, discrete particles and exhibit mechanical properties that range from fluid to solid behavior. Some of the complexity exhibited by granular systems arises due to the long-range order that develops due to particle-particle contact. Inter-particle forces in granular materials often form a distributive network of filamentary force-accommodating chains (i.e. force chains), such that a fraction of the total number of particles accommodates the majority of the forces in the system. The force chain network inherent to a system composed of granular materials controls the macroscopic behavior of the granular material. Force transmission by these filamentary chains is focused (or localized) to the grain scale at boundaries such as the granular flow substrate. Recent laboratory experiments have shown that force chains transmit extreme localized forces to the substrates of free surface granular flows. In this work we combine analog and numeric experimental approaches to investigate the forces at the bed of a simplified granular flow. A photoelastic experimental approach is used to resolve discrete forces in the granular flows. We also conduct discrete element method (DEM) simulations, using input parameters derived from measureable physical material properties of experimental and natural materials, which successfully reproduce the analog experimental results. This work suggests that force chain activity may play an unexpected and important role in the bed physics of dense granular flows through substrate modification by erosion and entrainment, and that DEM numerical methods effectively treat force chain processes in simulated granular flows.