Transition point prediction in a multicomponent lattice Boltzmann model: Forcing scheme dependencies

Knut Küllmer, Andreas Krämer, Wolfgang Joppich, Dirk Reith, and Holger Foysi
Phys. Rev. E 97, 023313 – Published 28 February 2018

Abstract

Pseudopotential-based lattice Boltzmann models are widely used for numerical simulations of multiphase flows. In the special case of multicomponent systems, the overall dynamics are characterized by the conservation equations for mass and momentum as well as an additional advection diffusion equation for each component. In the present study, we investigate how the latter is affected by the forcing scheme, i.e., by the way the underlying interparticle forces are incorporated into the lattice Boltzmann equation. By comparing two model formulations for pure multicomponent systems, namely the standard model [X. Shan and G. D. Doolen, J. Stat. Phys. 81, 379 (1995)] and the explicit forcing model [M. L. Porter et al., Phys. Rev. E 86, 036701 (2012)], we reveal that the diffusion characteristics drastically change. We derive a generalized, potential function-dependent expression for the transition point from the miscible to the immiscible regime and demonstrate that it is shifted between the models. The theoretical predictions for both the transition point and the mutual diffusion coefficient are validated in simulations of static droplets and decaying sinusoidal concentration waves, respectively. To show the universality of our analysis, two common and one new potential function are investigated. As the shift in the diffusion characteristics directly affects the interfacial properties, we additionally show that phenomena related to the interfacial tension such as the modeling of contact angles are influenced as well.

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  • Received 28 November 2017
  • Revised 24 January 2018

DOI:https://doi.org/10.1103/PhysRevE.97.023313

©2018 American Physical Society

Physics Subject Headings (PhySH)

Fluid Dynamics

Authors & Affiliations

Knut Küllmer1,*, Andreas Krämer1,†, Wolfgang Joppich1,‡, Dirk Reith1,§, and Holger Foysi2,∥

  • 1Institute of Technology, Renewables and Energy-efficient Engineering (TREE), Bonn-Rhein-Sieg University of Applied Sciences, Grantham-Allee 20, 53757 Sankt Augustin, Germany
  • 2Department of Mechanical Engineering, University of Siegen, Paul-Bonatz-Straße 9-11, 57076 Siegen-Weidenau, Germany

  • *knut.kuellmer@h-brs.de
  • kraemer.research@gmail.com
  • wolfgang.joppich@h-brs.de
  • §Also at Fraunhofer Institute for Algorithms and Scientific Computing (SCAI), Schloss Birlinghoven, Konrad-Adenauer Straße, 53754 Sankt Augustin, Germany; dirk.reith@h-brs.de
  • holger.foysi@uni-siegen.de

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Issue

Vol. 97, Iss. 2 — February 2018

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