Stochastic dynamics of granular hopper flows: hidden modes control the stability of clogs

Abstract

We introduce a phenomenological model for the stochastic dynamics of granular hopper flows. The flow rate fluctuates according to Langevin dynamics with multiplicative noise and an absorbing state that represents the clog. Granular flows in small-outlet hoppers exhibit intermittency, where a temporary clog forms for an extended period before flow spontaneously restarts. Our model provides a dynamical explanation for these extreme events: they arise due to coupling between the flow rate and a hidden mode that controls the stability of clogs. Using an automated recirculating hopper, we collect high resolution statistics of clog events, clogging times, and the instantaneous hopper flow rate. The theory fully captures these statistics, including nonexponentiality of the clogging times and the non-Gaussian flow rate distribution. Our work provides a new framework for extracting features of granular flow dynamics from experimental trajectories.