Entropic Lattice Boltzmann Method based high Reynolds number flow simulation using CUDA on GPU

2013 ◽  
Vol 88 ◽  
pp. 241-249 ◽  
Author(s):  
Yu Ye ◽  
Kenli Li
Keyword(s):  
Reynolds Number ◽  
Lattice Boltzmann Method ◽  
Lattice Boltzmann ◽  
High Reynolds Number ◽  
Flow Simulation ◽  
Reynolds Number Flow ◽  
Number Flow ◽  
High Reynolds ◽  
Boltzmann Method

Simulating High Reynolds Number Flow by Lattice Boltzmann Method

2005 ◽  
Vol 22 (6) ◽  
pp. 1456-1459 ◽  
Author(s):  
Kang Xiu-Ying ◽  
Liu Da-He ◽  
Zhou Jing ◽  
Jin Yong-Juan
Keyword(s):  
Reynolds Number ◽  
Lattice Boltzmann Method ◽  
Lattice Boltzmann ◽  
High Reynolds Number ◽  
Reynolds Number Flow ◽  
Number Flow ◽  
High Reynolds ◽  
Boltzmann Method

Simple and Robust Cut-Cell Method for High-Reynolds-Number-Flow Simulation on Cartesian Grids

AIAA Journal ◽  
2017 ◽  
Vol 55 (8) ◽  
pp. 2833-2841 ◽  
Author(s):  
Motoshi Harada ◽  
Yoshiharu Tamaki ◽  
Yuichi Takahashi ◽  
Taro Imamura
Keyword(s):  
Reynolds Number ◽  
High Reynolds Number ◽  
Flow Simulation ◽  
Cartesian Grids ◽  
Cell Method ◽  
Reynolds Number Flow ◽  
Cut Cell ◽  
Number Flow ◽  
High Reynolds

scholarly journals Lattice Boltzmann Method Simulations of High Reynolds Number Flows Past Porous Obstacles

2019 ◽  
Vol 11 (03) ◽  
pp. 1950028 ◽  
Author(s):  
N. M. Sangtani Lakhwani ◽  
F. C. G. A. Nicolleau ◽  
W. Brevis
Keyword(s):  
Reynolds Number ◽  
Lattice Boltzmann Method ◽  
Turbulent Flows ◽  
Lattice Boltzmann ◽  
High Reynolds Number ◽  
Reynolds Numbers ◽  
Navier Stokes Equation ◽  
High Reynolds ◽  
Boltzmann Method ◽  
Reynolds Number Flows

Lattice Boltzmann Method (LBM) simulations for turbulent flows over fractal and non-fractal obstacles are presented. The wake hydrodynamics are compared and discussed in terms of flow relaxation, Strouhal numbers and wake length for different Reynolds numbers. Three obstacle topologies are studied, Solid (SS), Porous Regular (PR) and Porous Fractal (FR). In particular, we observe that the oscillation present in the case of the solid square can be annihilated or only pushed downstream depending on the topology of the porous obstacle. The LBM is implemented over a range of four Reynolds numbers from 12,352 to 49,410. The suitability of LBM for these high Reynolds number cases is studied. Its results are compared to available experimental data and published literature. Compelling agreements between all three tested obstacles show a significant validation of LBM as a tool to investigate high Reynolds number flows in complex geometries. This is particularly important as the LBM method is much less time consuming than a classical Navier–Stokes equation-based computing method and high Reynolds numbers need to be achieved with enough details (i.e., resolution) to predict for example canopy flows.

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