Stability of the lattice kinetic scheme and choice of the free relaxation parameter

S. A. Hosseini, C. Coreixas, N. Darabiha, and D. Thévenin
Phys. Rev. E 99, 063305 – Published 12 June 2019

Abstract

The lattice kinetic scheme (LKS), a modified version of the classical single relaxation time (SRT) lattice Boltzmann method, was initially developed as a suitable numerical approach for non-Newtonian flow simulations and a way to reduce memory consumption of the original SRT approach. The better performances observed for non-Newtonian flows are mainly due to the additional degree of freedom allowing an independent control over the relaxation of higher-order moments, independently from the fluid viscosity. Although widely applied to fluid flow simulations, no theoretical analysis of LKS has been performed. The present work focuses on a systematic von Neumann analysis of the linearized collision operator. Thanks to this analysis, the effects of the modified collision operator on the stability domain and spectral behavior of the scheme are clarified. Results obtained in this study show that correct choices of the “second relaxation coefficient” lead, to a certain extent, to a more consistent dispersion and dissipation for large values of the first relaxation coefficient. Furthermore, appropriate values of this parameter can lead to a larger linear stability domain. At moderate and low values of viscosity, larger values of the free parameter are observed to increase dissipation of kinetic modes, while leaving the acoustic modes untouched and having a less pronounced effect on the convective mode. This increased dissipation leads in general to less pronounced sources of nonlinear instability, thus improving the stability of the LKS.

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  • Received 13 March 2019

DOI:https://doi.org/10.1103/PhysRevE.99.063305

©2019 American Physical Society

Physics Subject Headings (PhySH)

Fluid DynamicsStatistical Physics & Thermodynamics

Authors & Affiliations

S. A. Hosseini1,2,3, C. Coreixas4, N. Darabiha2, and D. Thévenin1

  • 1Laboratory of Fluid Dynamics and Technical Flows, University of Magdeburg “Otto von Guericke,” D-39106 Magdeburg, Germany
  • 2Laboratoire EM2C, CNRS, CentraleSupélec, Université Paris-Saclay, 3 rue Joliot Curie, 91192, Gif-sur-Yvette Cedex, France
  • 3International Max Planck Research School (IMPRS) for Advanced Methods in Process and Systems Engineering, Magdeburg, Germany
  • 4Department of Computer Science, University of Geneva, Geneva, Switzerland

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Issue

Vol. 99, Iss. 6 — June 2019

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