This award is funded under the American Recovery and Reinvestment Act of 2009 (Public Law 111-5).
Understanding how and when particulate matter such as sand or gravel will respond to stress and start to flow is an important problem in a wide range of fields such as earthquake prediction, rock avalanche hazard prediction, and civil engineering. This project will study the flow of granular matter by looking at the networks of contact points between particles, and examining how these networks change as the granular material flows. Other approaches to understand granular flow focus on the motion of individual particles or look at the system as a fluid-like continuum. The proposed research will apply the tools of network theory, which will highlight the intermediate scale ? ensembles of touching particles - and will thus provide a novel perspective on granular flow. The project will focus on two key processes that occur in granular materials, the breaking of the contact network during flow of granular material, and the segregation of particles by size in such a granular flow. The proposed research will train graduate students in state of the art experimental and computational research and in mentoring of undergraduate and high school students. The research team will also conduct public demonstrations of their work, highlighting -on simple examples- flows of sand that possesses fascinating, technologically important properties which are not yet fully understood.
The goal of this project is to measure three dimensional granular flow fields experimentally, and to utilize network theory to characterize the flow behavior. Network theory metrics focus on the large scale structure of ensembles of linked objects. Since granular matter derives its strength from a dense network of particle contacts, network theory will provide a novel viewpoint relevant to understanding granular materials properties. The focus will be on two key granular flow processes ? fracture and segregation. The first goal is to characterize the onset of fracture of a jammed granular material, i.e. the formation of large scale structural rearrangements such as shear zones when granular matter starts to flow. Understanding how and when granular matter will fracture and start to flow is important to a wide range of fields such as earthquake prediction, rock avalanche hazard prediction, and civil engineering. The second goal is to characterize the particle rearrangements that lead to segregation of a mixture of particle sizes during granular flows. Graduate students will be trained in a unique combination of experimental tools (3D imaging) and theoretical concepts (network theory), and will contribute to mentoring of undergraduate students. The group has developed demonstrations that highlight the most striking features of jamming and granular segregation, which will be presented at public lectures and outreach events.
