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Granular materials can behave as harmless sand dunes or as devastating landslides. A granular avalanche marks the transition between these distinct solid-like and fluid-like states. The solid-like state is typically described using plasticity models from critical state theory. In the fluid regime, granular flow is commonly captured using a visco-plastic model. However, due to our limited understanding of the mechanism governing the solid-fluid-like transition, characterizing the material behavior throughout the life cycle of an avalanche remains an open challenge. Here, we employ laboratory experiments of transient avalanches spontaneously generated by a rotating drum. We report measurements of dilatancy and grain kinematics before, during, and after each avalanche. Those measurements are directly incorporated into a rate-dependent plasticity model that quantitatively predicts the granular flow measured in experiments. Furthermore, we find that dilatancy in the solid-like state controls the triggering of granular avalanches and therefore plays a key role in the solid-fluid-like transition. With the proposed approach, we demonstrate that the life cycle of a laboratory avalanche, from triggering to run out, can be fully explained. Our results represent an important step toward a unified understanding of the physical phenomena associated with transitional behavior in granular media. [ABSTRACT FROM AUTHOR]

Particle shape, as one of the most important physical ingredients of granular materials, can greatly alter the characteristic of inter-particle force distribution which is of vital importance in understanding the mechanical behavior of granular materials. However, currently both experimental and numerical studies remain limited in this regard. In this paper, we for the first time validate the ability of the level set discrete element method (LS-DEM) on capturing the inter-particle force distribution among particles of arbitrary shape. We first present the technical detail of LS-DEM; we then apply LS-DEM to simulate experiments of shearing granular materials composed of arbitrarily shaped particles. The proposed approach directly links experimentally measured material properties to model parameters such as contact stiffness without any calibration. Our results show that LS-DEM is able to not only capture the macro scale response such as stress and deformation, but also to reproduce the particle scale contact information such as the distribution of contact force magnitude, contact orientation and contact friction mobilization. Our work demonstrates the promising potential of LS-DEM on studying the mechanics and physics of natural granular material and on aiding design granular particle shape for novel macro-scale mechanical property. [ABSTRACT FROM AUTHOR]