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

摘要：在美国，颗粒物料的运输和加工每年花费约一万亿美元。此外，颗粒流与许多灾难性事件有关，如雪崩和地震。因此，颗粒流预测建模的改进对于各种工程挑战（从制药行业的粉末混合到岩石雪崩灾害预测和评估）都是有价值的。这一领域的大多数其他工作主要集中在颗粒从一个位置到另一个位置的平移运动上。相比之下，这个项目探索了宏观尺度颗粒流动中颗粒旋转运动的作用。具体目标是：(1)在颗粒尺度上测量和量化3D颗粒流中的旋转，(2)在中尺度上表征和分析集体旋转，(3)连接跨尺度的旋转和平移运动。该项目培养下一代科学家的实验和建模技术，这些技术高度可转移到广泛的领域，例如测量集体细胞迁移，集体神经元放电，或通过网络分析分析社交媒体。研究小组开发了一个训练营来传播这些测量粒子和旋转动力学的方法。技术摘要：该项目的目标是探索颗粒流动的宏观尺度特征从单个颗粒旋转的集体行为中产生的重要性。最近的研究表明，颗粒的旋转在颗粒流动中可能起着重要的作用：在一些颗粒构型中，旋转可以在最小的摩擦耗散下促进重排，而在另一些构型中，扭矩会加剧堵塞。单个颗粒尺度上的旋转运动在三维系统中很难表征，但就像力和平移运动一样，扭矩和旋转在颗粒之间是耦合的，因此，颗粒尺度上的旋转自然地与中尺度和宏观尺度动力学联系在一起。该项目提供了对可逆性和分离等关键体流特性的新见解，并探索了首选剪切面如何与旋转排列相连接。研究小组期望对集体旋转统计的见解将对颗粒物质的材料科学产生变革性的影响。确定协同重排在颗粒流中的作用，在工程、地球物理和天体物理学背景下也有广泛的直接应用。该项目的第一个目标是精确测量流动颗粒材料内部的3D旋转，这直接建立在研究团队在测量3D颗粒流动方面的专业知识之上。通过仔细的三维旋转动力学实验观察测量的旋转统计数据和动力学有可能为当前和未来的颗粒流动模型提供重要的验证。第二个目标是分析旋转的集体行为，这有可能对可能导致干扰或流动的隐藏中尺度结构产生革命性的见解。我们期望旋转的集体特征与集体平移运动一样重要，但又不同，因为旋转在环中耦合，而平移运动倾向于在链中耦合。描述集体旋转的方法是基于团队在非线性动力学和网络理论方面的专业知识。最后，第三个目标是跨尺度连接旋转动力学，以获得对整体流动现象的新见解。在这里，该团队受益于先前在可逆性、对流流动和分离背景下跨尺度的平移粒子动力学的深入研究。

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.