A recent granular rheology based on an implicit 'granular fluidity' field has been shown to quantitatively predict many nonlocal phenomena. However, the physical nature of the field has not been identified. Here, the granular fluidity is found to be a kinematic variable given by the velocity fluctuation and packing fraction. This is verified with many discrete element simulations, which show the operational fluidity definition, solutions of the fluidity model, and the proposed microscopic formula all agree. Kinetic theoretical and Eyring-like explanations shed insight into the obtained form.

Sediment transport by wind and water shapes many of Earth's landscapes. Models that predict how rapidly a flow can move sediments are essential for understanding the evolution of Earth's surface (Anderson & Anderson, 2010; Bridge & Demicco, 2008), mitigating risks posed by natural hazards, designing engineering structures that will interact with moving sediment (

We derive a general dimensionless form for granular locomotion, which is validated in experiments and Discrete Element Method (DEM) simulations. The form instructs how to scale size, mass, and driving parameters in order to relate dynamic behaviors of different locomotors in the same granular media. The scaling can be derived by assuming intrusion forces arise from Resistive Force Theory (RFT) or equivalently by assuming the granular material behaves as a continuum obeying a frictional yield criterion. The scalings are experimentally confirmed using pairs of wheels of various shapes and sizes under many driving conditions in a common sand bed. We discuss why the two models provide such a robust set of scaling laws even though they neglect a number of the complexities of granular rheology. Motivated by potential extra-planetary applications, the dimensionless form also implies a way to predict wheel performance in one ambient gravity based on tests in a different ambient gravity. We confirm this using DEM simulations, which show that scaling relations are satisfied over an array of driving modes even when gravity differs between scaled tests.

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Bedload sediment transport is ubiquitous in shaping natural and engineered landscapes, but the variability in the relation between sediment flux and driving factors is not well understood. At a given Shields number, the observed dimensionless transport rate can vary over a range in controlled systems and up to several orders of magnitude in natural streams. Here, we (a) experimentally validate a resolved fluid‐grain numerical scheme (Lattice Boltzmann Method‐Discrete Element Method or DEM‐LBM), and use it to (b) explore the parameter space controlling sediment transport in simple systems. Wide wall‐free simulations show the dimensionless transport rate is not influenced by the slope, fluid depth, mean particle size, particle surface friction, or grain‐grain damping for gentle slopes (0.01–0.03) at a medium to high fixed Shields number. (c) Examination of small‐scale fluid‐grain interactions shows fluid torque is non‐negligible for the entrainment and sediment transport near the threshold. And (d) the simulations guide the formulation of continuum models for the transport process. We present an upscaled two‐phase continuum model for grains in a turbulent fluid and validate it against bedload transport DEM‐LBM simulations. To model the creeping granular flow under the bed surface, we use an extension of the Nonlocal Granular Fluidity model, which was previously shown to account for flow cooperativity from grain‐size‐effects in dry media. The model accurately predicts the exponentially decaying velocity profile deeper into the bed.

This corrects the article DOI: 10.1103/PhysRevE.95.052901.

No abstract

Near the threshold of grain motion, sediment transport is “on‐off” intermittent, characterized by large but rare bursts separated by long periods of low transport. Without models that can account for the effects of intermittency, measurements of average sediment flux can be in error by up to an order of magnitude. Despite its known presence and impact, it is not clear whether on‐off intermittency arises from the grain activity (the number of moving grains) or grain velocities, which together determine the sediment flux. We use laboratory flume experiments to show that the on‐off intermittency has its origins in the velocity distributions of grains that move by rolling along the bed, whereas grain activity is not on‐off intermittent. Incorporating the types of intermittency we identify into stochastic models of sediment transport could yield improved predictions of sediment flux, including physically based estimates of the uncertainty in time‐averaged sediment flux.