Grain Packing Resistance to Particle Mobility

Abstract:

We report model results for quantifying grain packing resistance to particle motion. Packing resistance was modeled as the difference between the total resistance acting on individual grains (measured with a load cell) and the resistance that occurs when grains interact with the geometry of their resting pocket (measured with a tilt board). Monte Carlo simulations were conducted to develop distributions of packing resistance from observed distributions of total and pocket angle resistance because paired measurements were not available. Results show that packing was the dominant form of resistance to grain motion, exceeding pocket angle resistance by up to 88%. Expressed as coefficients of friction, packing resistance was close to 18 times higher for smaller grains because such particles tend to be more embedded, increasing the extent of packing by surrounding grains. We developed a predictive equation from these data, expressing packing resistance as a function of grain size, embeddedness, and the standard deviation of grain sizes on the bed surface (sorting), which collectively control the frictional surface area of the grain. Including observed values of packing resistance in calculations of critical bed shear stress increased thresholds of grain motion by 8 to 46% (21% on average) over that calculated with pocket angle resistance. This has significant implications for bed load transport predictions, which are typically nonlinear functions of the difference between applied and critical shear stresses; as such, small differences in critical shear stress can cause large prediction errors. Given the importance of packing resistance, future studies are warranted to better understand the physical and biological controls on packing, as well as the mechanics of packing resistance.