Competition analysis of grain flow versus clogging by means of information theory

Abstract

The different flow regimes in a two-dimensional silo with a vibrated base are studied in terms of the usual statistical techniquesand information theory. The passage of granular material through the mouth of the silo is analyzed by real-timeanalysis of images captured by a standard video camera. The brightness of these images is measured and recorded at verysmall time intervals (100 frames per second). The experiment is repeated for different values of the vibration intensity.Data recognizer wlzip directly treats the resulting b(t) files (brightness time series) based on data compressor techniques,yielding the information content measured by the mutability function. has not previously been considered as part of theconventional treatment of flow in granular media. The results obtained here clearly demonstrate the usefulness of mutabilityas a tool for distinguishing between different flowing regimes directly from the brightness sequence, with no manipulationof the series. This shows that information theory techniques can provide a complementary description of the discharge ofgranular materials and its control through data compression algorithms.