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Characterizing granular networks using topological metrics

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      Most cited references 31

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      Is Open Access

      Statistical mechanics of complex networks

      Complex networks describe a wide range of systems in nature and society, much quoted examples including the cell, a network of chemicals linked by chemical reactions, or the Internet, a network of routers and computers connected by physical links. While traditionally these systems were modeled as random graphs, it is increasingly recognized that the topology and evolution of real networks is governed by robust organizing principles. Here we review the recent advances in the field of complex networks, focusing on the statistical mechanics of network topology and dynamics. After reviewing the empirical data that motivated the recent interest in networks, we discuss the main models and analytical tools, covering random graphs, small-world and scale-free networks, as well as the interplay between topology and the network's robustness against failures and attacks.
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        A discrete numerical model for granular assemblies

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          The Statistical Mechanical Theory of Transport Processes. IV. The Equations of Hydrodynamics

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            Author and article information

            Journal
            PLEEE8
            Physical Review E
            Phys. Rev. E
            American Physical Society (APS)
            2470-0045
            2470-0053
            April 2018
            April 18 2018
            : 97
            : 4
            10.1103/PhysRevE.97.042903
            © 2018

            https://link.aps.org/licenses/aps-default-license

            https://link.aps.org/licenses/aps-default-accepted-manuscript-license

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