Review of models for predicting the discharge rates of bulk particulates from silos and bins

Various models for predicting discharge rates have been developed over the last four decades by many research workers (notably Beverloo [1], Johanson [2], Brown [3], Carleton [4], Crewdson [5], Nedderman [6], Gu [7].). In many cases these models offer comparable approaches to the prediction of discharge rates of bulk particulates from storage equipment when solely gravity is acting to initiate flow (since they invariably consider the use of mass-flow design equipment). The models that have been developed consider a wide range of bulk particulates (coarse, incompressible, fine, cohesive) and most contemporary works have incorporated validation against test programmes. Research currently underway at The Wolfson Centre for Bulk Solids Handling Technology, University of Greenwich, has considered the relative performance of these models with respect to a range of bulk properties and with particular focus upon the flexibility of the models to cater for different geometrical factors for vessels.

Some models for discretized series of events

A discretized series of events is a binary time series that indicates whether or not events of a point process in the line occur in successive intervals. Such data are common in environmental applications. We describe a class of models for them, based on an unobserved continuous-time discrete-state Markov process, which determines the rate of a doubly stochastic Poisson process, from which the binary time series is constructed by discretization. We discuss likelihood inference for these processes and their second-order properties and extend them to multiple series. An application involves modeling the times of exposures to air pollution at a number of receptors in Western Europe.