Analysis of collective dynamics of particulate systems modeled by Markov chains

This paper develops an approach to capturing and analyzing the collective dynamics of particulate systems, exemplified using a horizontal rotating drum. The dynamics of a particulate system is modeled stochastically via the Markov chains approach using data obtained from Discrete Element Method simulations. Quantitative measures are developed to characterize the features of collective dynamics based on eigenvalues and singular values analysis of the Markov chain operators. These features include the dynamic modes corresponding to the oscillatory behavior and the spatial distribution of particle movements. It is also shown that these quantitative measures can be linked to the classification of flow regimes in a horizontal rotating drum.