Discrete particle simulation of particulate systems: a review of major applications and findings

H. P. Zhu, Z. Y. Zhou, R. Y. Yang, A. B. Yu

    Research output: Contribution to journalArticle

    1349 Citations (Scopus)

    Abstract

    Understanding and modelling the dynamic behaviour of particulate systems has been a major research focus worldwide for many years. Discrete particle simulation plays an important role in this area. This technique can provide dynamic information, such as the trajectories of and transient forces acting on in- dividual particles, which is difficult to obtain by the conventional experimental techniques. Consequently, it has been increasingly used by various investigators for different particulate processes. In spite of the large bulk volume, little effort has been made to comprehensively review and summarize the progress made in the past. To overcome this gap, we have recently completed a review of the major work in this area in two separate parts. The first part has been published [Zhu, H.P., Zhou, Z.Y., Yang, R.Y., Yu, A.B., 2007. Discrete particle simulation of particulate systems: theoretical developments. Chemical Engineering Science 62, 3378-3392.], which reviews the major theoretical developments. This paper is the second one, aiming to provide a summary of the studies based on discrete particle simulation in the past two decades or so. The studies are categorized into three subject areas: particle packing, particle flow, and particle-fluid flow. The major findings are discussed, with emphasis on the microdynamics including packing/flow structure and particle-particle, particle-fluid and particle-wall interaction forces. It is con- cluded that discrete particle simulation is an effective method for particle scale research of particulate matter. The needs for future research are also discussed.
    Original languageEnglish
    Pages (from-to)5728-5770
    Number of pages43
    JournalChemical Engineering Science
    Volume63
    Issue number23
    Publication statusPublished - 2008

    Keywords

    • computational fluid dynamics
    • data analysis

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