Collective Rotation Networks in Dense Granular Flow Experiments: Connecting Rotation and Translation Across Scales

University Of Maryland, College Park, College Park MD

Investigators

Abstract

Nontechnical Abstract: Transport and processing of granular materials costs the United States approximately one trillion dollars annually. Further, granular flows are implicated in many catastrophic events, such as avalanches and earthquakes. Thus, improvements in the predictive modeling of granular flow is valuable for a diverse set of engineering challenges, from the mixing of powders in the pharmaceutical industry, to rock avalanche hazard prediction and assessment. Most other efforts in this area focus primarily on the translational motion of grains from one location to another. This project, by contrast, explores the role of the rotational motion of grains in macroscale granular flows. The specific goals are to (1) measure and quantify rotations in 3D granular flows at the particle scale, (2) characterize and analyze collective rotations at the mesoscale and (3) connect rotational and translational motion across scales. The project trains the next generation of scientists in experimental and modeling techniques that are highly transferable to a broad range of fields, e.g. to measure collective cell migration, collective firing of neurons, or to analyze social media via network analysis. The research team develops a boot camp to disseminate these approaches of measuring particle and rotational dynamics. Technical Abstract: The goal of the project is to explore how important macroscale characteristics of granular flows emerge from the collective behavior of individual particle rotations. Recent research indicates that particle rotations may play an important role in granular flows: in some granular configurations, rotations can facilitate rearrangements with minimal frictional dissipation, while in other configurations torques can enhance jamming. Rotational motion at the scale of individual grains is poorly characterized in three-dimensional systems, yet just like forces and translational motion, torques and rotations couple from grain to grain, and thus, particle scale rotations naturally connect to mesoscale and macroscale dynamics. The project provides new insights into key bulk flow properties like reversibility and segregation, and also explores how preferred shear planes connect to rotational alignments. The research team expects that insights into the statistics of collective rotations will have a transformative impact on the materials science of granular matter. Identifying the role of cooperative rearrangements in granular flows also has direct applications in a broad range of engineering, geophysical, and astrophysical contexts. The project's first objective, to accurately measure the 3D rotations inside a flowing granular material, builds directly on the research team's established expertise in measuring 3D granular flows. The rotational statistics and dynamics measured from careful experimental observations on 3D rotation dynamics have the potential to provide important validations for current and future models of granular flows. The second objective, analysis of the collective behavior of rotations, has the potential to yield transformational insights into hidden mesoscale structures that could facilitate jamming or flow. We expect collective features of rotations to be as important as but distinct from collective translational motion since rotations couple in loops, while translational motion tends to couple in chains. The approach to characterizing collective rotations is based on the team's expertise in nonlinear dynamics and network theory. Finally, the third objective is to connect rotational dynamics across scales to gain new insights into bulk flow phenomena. Here, the team benefits from prior in-depth studies of translational particle dynamics across scales in the context of reversibility, convective flow, and segregation.