Parallelization of Lattice Boltzmann method using MPI domain decomposition technology for a drop impact on a wetted solid wall

Author(s):  
Zhi Shang ◽  
Ming Cheng ◽  
Jing Lou

Lattice Boltzmann method (LBM) is a new attractive computational approach for simulating isothermal multi-phase flows in computational fluid dynamics (CFD). It is based on the kinetic theory and easy to be parallelized. This study aims to analyze the performance of parallel LBM programming for the incompressible two-phase flows at high density and viscosity ratio. For this purpose, a liquid drop impact on a wetted wall with a pre-existing thin film of the same liquid is simulated by using the parallel LBM code. During the simulations, the domain decomposition, data communication and parallelization of the LBM code using the message passing interface (MPI) library have been investigated. The computational results show that the parallel LBM code exhibits a good high performance computing (HPC) on the parallel speed-up.

2003 ◽  
Vol 17 (01n02) ◽  
pp. 129-133 ◽  
Author(s):  
ZHAOLI GUO ◽  
CHUGUANG ZHENG ◽  
BAOCHANG SHI

In this paper a domain-decomposition technique is proposed in the framework of the lattice Boltzmann method in order to handle flows in irregular geometries. The 2D flow in a channel with a square or slant branch cavity is simulated based on this technique.


Author(s):  
Anoosheh Niavarani-Kheirier ◽  
Masoud Darbandi ◽  
Gerry E. Schneider

The main objective of the current work is to utilize Lattice Boltzmann Method (LBM) for simulating buoyancy-driven flow considering the hybrid thermal lattice Boltzmann equation (HTLBE). After deriving the required formulations, they are validated against a wide range of Rayleigh numbers in buoyancy-driven square cavity problem. The performance of the method is investigated on parallel machines using Message Passing Interface (MPI) library and implementing domain decomposition technique to solve problems with large order of computations. The achieved results show that the code is highly efficient to solve large scale problems with excellent speedup.


2012 ◽  
Vol 207-208 ◽  
pp. 587-595 ◽  
Author(s):  
M.R. Kamali ◽  
S. Sundaresan ◽  
H.E.A. Van den Akker ◽  
J.J.J. Gillissen

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