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The field of granular physics has burgeoned since its development in the late 1980s, when physicists first began to use statistical mechanics to study granular media. They are prototypical of complex systems, manifesting metastability, hysteresis and bistability, and a range of other fascinating phenomena. This 2007 book is a wide-ranging account of developments in granular physics, and lays out the foundations of the statics and dynamics of granular physics. It covers a wide range of subfields, ranging from fluidisation to jamming, and these are modelled through a range of computer simulation and theoretical approaches. Written with an eye to pedagogy and completeness, this book will be valuable asset to any researcher in this field. The book also contains contributions from Professor Sir Sam Edwards, with Dr Raphael Blumenfeld, Professor Isaac Goldhirsch and Professor Philippe Claudin.

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Bridges form dynamically in granular media as a result of spatiotemporal inhomogeneities. We classify bridges as linear and complex, and analyse their geometrical characteristics. In particular, we find that the length distribution of linear bridges is exponential. We then turn to the analysis of the orientational distribution of linear bridges and find that, in three dimensions, they are vertically diffusive but horizontally superdiffusive; thus, when they exist, long linear bridges form 'domes'. Our results are in good accord with Monte Carlo simulations of bridge structure; we make predictions for quantities that are experimentally accessible, and suggest that bridges are very closely related to force chains.

We present a stochastic model of dynamically interacting grains in one dimension, in the presence of a low vibrational intensity, to investigate the effect of shape on the statics and dynamics of the compaction process. Regularity and irregularity in grain shapes are shown to be centrally important in determining the statics of close-packing states, as well as the nature of zero-and low-temperature dynamics in this columnar model.

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