Back to Search Start Over

A subgrid model with multiple relaxation time for lattice Boltzmann method based on the Cartesian grid.

Authors :
Qiu, Aoxiang
Sang, Weimin
Zhou, Feng
Li, Dong
Source :
Engineering Computations. 2023, Vol. 40 Issue 9/10, p2303-2327. 25p.
Publication Year :
2023

Abstract

Purpose: The paper aims to expand the scope of application of the lattice Boltzmann method (LBM), especially in the field of aircraft engineering. The traditional LBM is usually applied to incompressible flows at a low Reynolds number, which is not sufficient to satisfy the needs of aircraft engineering. Devoted to tackling the defect, the paper proposes a developed LBM combining the subgrid model and the multiple relaxation time (MRT) approach. A multilayer adaptive Cartesian grid method to improve the computing efficiency of the traditional LBM is also employed. Design/methodology/approach: The subgrid model and the multilayer adaptive Cartesian grid are introduced into MRT-LBM for simulations of incompressible flows at a high Reynolds number. Validated by several typical flow simulations, the numerical methods in this paper can efficiently study the flows under high Reynolds numbers. Findings: Some numerical simulations for the lid-driven flow of cavity, flow around iced GLC305, LB606b and ONERA-M6 are completed. The paper presents the investigation results, indicating that the methods are accurate and effective for the separated flow after icing. Originality/value: LBM is developed with the addition of the subgrid model and the MRT method. A numerical strategy is proposed using a multilayer adaptive Cartesian grid method and its treatment of boundary conditions. The paper refers to innovative algorithm developments and applications to the aircraft engineering, especially for iced wing simulations with flow separations. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
02644401
Volume :
40
Issue :
9/10
Database :
Academic Search Index
Journal :
Engineering Computations
Publication Type :
Academic Journal
Accession number :
174019173
Full Text :
https://doi.org/10.1108/EC-08-2022-0556