Acceleration for microflow simulations of high-order moment models by using lower-order model correction

Zhicheng Hu, Ruo Li, Zhonghua Qiao

Research output: Journal article publicationJournal articleAcademic researchpeer-review

3 Citations (Scopus)

Abstract

� 2016 Elsevier Inc. We study the acceleration of steady-state computation for microflow, which is modeled by the high-order moment models derived recently from the steady-state Boltzmann equation with BGK-type collision term. By using the lower-order model correction, a novel nonlinear multi-level moment solver is developed. Numerical examples verify that the resulting solver improves the convergence significantly thus is able to accelerate the steady-state computation greatly. The behavior of the solver is also numerically investigated. It is shown that the convergence rate increases, indicating the solver would be more efficient, as the total levels increases. Three order reduction strategies of the solver are considered. Numerical results show that the most efficient order reduction strategy would be ml−1=⌈ml/2⌉.
Original languageEnglish
Pages (from-to)225-244
Number of pages20
JournalJournal of Computational Physics
Volume327
DOIs
Publication statusPublished - 15 Dec 2016

Keywords

  • Boltzmann equation
  • Globally hyperbolic moment method
  • Lower-order model correction
  • Microflow
  • Multigrid

ASJC Scopus subject areas

  • Physics and Astronomy (miscellaneous)
  • Computer Science Applications

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