Lattice Boltzmann method for modelling droplets on chemically heterogeneous and microstructured surfaces with large liquid-gas density ratio

2011 ◽  
Vol 76 (5) ◽  
pp. 743-760 ◽  
Author(s):  
Y. Q. Zu ◽  
Y. Y. Yan
Keyword(s):  
Lattice Boltzmann Method ◽  
Lattice Boltzmann ◽  
Density Ratio ◽  
Gas Density ◽  
Microstructured Surfaces ◽  
Boltzmann Method

Rayleigh-Taylor Instability Studied With Multi-Relaxation Lattice Boltzmann Method

2013 ◽  
Author(s):  
Saeed J. Almalowi ◽  
Dennis E. Oztekin ◽  
Alparslan Oztekin
Keyword(s):  
Lattice Boltzmann Method ◽  
Lattice Boltzmann ◽  
Early Stage ◽  
Density Ratio ◽  
Side Wall ◽  
Immiscible Fluids ◽  
Distribution Functions ◽  
Lattice Arrangement ◽  
Boltzmann Method ◽  
Late Stages

Multi relaxation lattice Boltzmann method is implemented to study Rayleigh-Taylor instabilities. Two immiscible fluids (oil and water) are arrayed into three layers. D2Q9 lattice arrangement for two dimensional computational domains is employed. Density distribution functions for each fluid and distribution functions for the coloring step are determined. The evolution of the interface is identified with the coloring step. Buoyancy and other interaction forces, created by buoyancy, between phases are modeled. Two cases are studied one with periodic boundary condition instead of a side wall, and one bounded on all sides. The study is done with an aspect ratio of two and a density ratio of 1.2. The early and late stages of the instability are characterized. The early stage of both cases shows the initial periodic disturbance being amplified rapidly on the lower interface. The late stages show mushroom-like structures, with significant distortions occurring on the bounded case.

A Numerical Study of Jet Propulsion of an Oblate Jellyfish Using a Momentum Exchange-Based Immersed Boundary-Lattice Boltzmann Method

2014 ◽  
Vol 6 (3) ◽  
pp. 307-326 ◽  
Author(s):  
Hai-Zhuan Yuan ◽  
Shi Shu ◽  
Xiao-Dong Niu ◽  
Mingjun Li ◽  
Yang Hu
Keyword(s):  
Reynolds Number ◽  
Lattice Boltzmann Method ◽  
Lattice Boltzmann ◽  
Numerical Study ◽  
Mass Density ◽  
Density Ratio ◽  
Large Mass ◽  
Immersed Boundary ◽  
Momentum Exchange ◽  
Boltzmann Method

AbstractIn present paper, the locomotion of an oblate jellyfish is numerically investigated by using a momentum exchange-based immersed boundary-Lattice Boltzmann method based on a dynamic model describing the oblate jellyfish. The present investigation is agreed fairly well with the previous experimental works. The Reynolds number and the mass density of the jellyfish are found to have significant effects on the locomotion of the oblate jellyfish. Increasing Reynolds number, the motion frequency of the jellyfish becomes slow due to the reduced work done for the pulsations, and decreases and increases before and after the mass density ratio of the jellyfish to the carried fluid is 0.1. The total work increases rapidly at small mass density ratios and slowly increases to a constant value at large mass density ratio. Moreover, as mass density ratio increases, the maximum forward velocity significantly reduces in the contraction stage, while the minimum forward velocity increases in the relaxation stage.

Efficient graphic processing unit implementation of the chemical-potential multiphase lattice Boltzmann method

2020 ◽  
Vol 35 (1) ◽  
pp. 78-96
Author(s):  
Yutong Ye ◽  
Hongyin Zhu ◽  
Chaoying Zhang ◽  
Binghai Wen
Keyword(s):  
Lattice Boltzmann Method ◽  
Lattice Boltzmann ◽  
Chemical Potential ◽  
Graphic Processing Unit ◽  
Density Ratio ◽  
Processing Unit ◽  
Central Difference ◽  
Loop Unrolling ◽  
Boltzmann Method ◽  
Graphic Processing

The chemical-potential multiphase lattice Boltzmann method (CP-LBM) has the advantages of satisfying the thermodynamic consistency and Galilean invariance, and it realizes a very large density ratio and easily expresses the surface wettability. Compared with the traditional central difference scheme, the CP-LBM uses the Thomas algorithm to calculate the differences in the multiphase simulations, which significantly improves the calculation accuracy but increases the calculation complexity. In this study, we designed and implemented a parallel algorithm for the chemical-potential model on a graphic processing unit (GPU). Several strategies were used to optimize the GPU algorithm, such as coalesced access, instruction throughput, thread organization, memory access, and loop unrolling. Compared with dual-Xeon 5117 CPU server, our methods achieved 95 times speedup on an NVIDIA RTX 2080Ti GPU and 106 times speedup on an NVIDIA Tesla P100 GPU. When the algorithm was extended to the environment with dual NVIDIA Tesla P100 GPUs, 189 times speedup was achieved and the workload of each GPU reached 96%.

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