ABSTRACT

Non-technical abstract:
Granular materials like sands, grains, and powders are all around us, yet we still cannot predict precisely how they will flow or jam, unlike normal liquids. Both flow and jamming can create problems - clogging within a production line can be catastrophic, and flow from a rockslide can cause a state of emergency. Additionally many other systems are particulate in nature, such as cars and blood cells, and insights from the study of granular materials can give us insight into solving problems like traffic and blood clots. Part of the issue is that granular materials are difficult to image, and there is interesting physics happening at a wide range of time and length scales. This project will study the flow and jamming of granular materials with extremely fast video capture and high-definition resolution. The particles themselves are made of material that can appear to light up when they experience force. Thus the research team can not only detect the motion of every particle in the system, they can also measure the force on each individual particle. The acquisition and analysis of this data is critical for a more complete understanding of granular materials. The project is highly integrated with the broader educational goals of training future scientists and increasing science literacy in the public. Specifically, the principal investigator will provide training and mentorship to women undergraduate students involved in the research, and the project will support the training and mentorship of a postdoctoral researcher. The principal investigator will facilitate an immersive pre-college program for underrepresented groups interested in the physical sciences and engineering. Lastly, the principal investigator will continue to support and grow a monthly public science lecture series.

Technical abstract:
The overarching objective of this project is to advance the understanding of the dynamics of granular material flow and jamming with state-of-the-art time and spatial resolution, in addition to grain-scale force measurements. The long-term goal is to understand the structural and dynamical signatures at the mesoscale that control the clogging and flow of granular materials. The research team performs this work in the context of one particular flow geometry, though the methods are transferrable to other granular systems. In this system, the flowing state has been found to be described by the empirical Beverloo equation, but a sound theoretical footing for this behavior has not been established. Theoretical models of granular materials often use a continuum approach or a microscale "bottom-up" approach. However, it has become exceedingly clear that the behavior of granular materials depends on multiple length scales, and a functional predictive model must take various mesoscales into account. There has also been recent interest in the transition from flow to clogging in this system, and whether it is similar to (or different from) the jamming or glass transitions. This work will directly probe the nature of the clogging transition, and will contribute to forming better theoretical models of granular flow. The research team directly measures the microscopic particle motions, and mesoscale features such as the force network and rearranging clusters of particles, all with extremely high time and spatial resolution. The force network is measured by the use of photoelastic grains. In addition to experiments, the research team performs complementary molecular dynamics simulations for comparison. The data is analyzed for mesoscale features such as cooperative rearrangments, shear transformation zones, and particle segregation, and the initial packing structure of the system is modified as a control parameter. Network analysis techniques such as community detection algorithms are used to further analyze the evolution of the contact and force networks during flow and clogging events. In tandem, the research team is building a public library of collective motion metrics and documenting their use in disparate fields, with the goal of spawning more efficient implementation and cross-disciplinary collaborations.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

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