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Network modeling of flow in a packed bed

Authors

  • António A. Martins,

    1. Laboratory of Separation and Reaction Engineering, Departamento de Engenharia Química, Faculdade de Engenharia da Universidade do Porto, Rua Dr. Roberto Frias, 4200-465 Porto, Portugal
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  • Paulo E. Laranjeira,

    1. Laboratory of Separation and Reaction Engineering, Departamento de Engenharia Química, Faculdade de Engenharia da Universidade do Porto, Rua Dr. Roberto Frias, 4200-465 Porto, Portugal
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  • José Carlos B. Lopes,

    1. Laboratory of Separation and Reaction Engineering, Departamento de Engenharia Química, Faculdade de Engenharia da Universidade do Porto, Rua Dr. Roberto Frias, 4200-465 Porto, Portugal
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  • Madalena M. Dias

    Corresponding author
    1. Laboratory of Separation and Reaction Engineering, Departamento de Engenharia Química, Faculdade de Engenharia da Universidade do Porto, Rua Dr. Roberto Frias, 4200-465 Porto, Portugal
    • Laboratory of Separation and Reaction Engineering, Departamento de Engenharia Química, Faculdade de Engenharia da Universidade do Porto, Rua Dr. Roberto Frias, 4200-465 Porto, Portugal
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Abstract

The characterization of the flow inside a packed bed requires a full description of the pore geometrical characteristics, and of the flow phenomena at local level. A two-dimensional (2-D) network model for describing the flow phenomena in unconsolidated-packed beds has been developed. The network model consists of two different types of elements: chambers modeled as spheres, and channels modeled as cylinders. The size distributions of the network elements are obtained considering a geometrical model that uses the porosity, and the average-particle diameter as input data. A flow simulator was developed, based on this network model. Results show that since the inertial effects due to connections between channels and chambers are taken into account, this simulator is capable of describing single-phase flow in all the possible flow regimes, from laminar to turbulent. Results also show a good agreement between predicted values of the network model and experimental data available in literature. © 2006 American Institute of Chemical Engineers AIChE J 2007

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