Direct numerical simulation of the self-propelled Janus particle: use of grid-refined fluctuating lattice Boltzmann method

2019 ◽  
Vol 23 (5) ◽  
Author(s):  
Li Chen ◽  
Chenyu Mo ◽  
Lihong Wang ◽  
Haihang Cui
Keyword(s):  
Numerical Simulation ◽  
Direct Numerical Simulation ◽  
Lattice Boltzmann Method ◽  
Lattice Boltzmann ◽  
The Self ◽  
Janus Particle ◽  
Boltzmann Method

Direct Numerical Simulation by Three-Dimensional Lattice Boltzmann Method

2003 ◽  
Vol 2003 (0) ◽  
pp. 101
Author(s):  
Takeshi TSUCHIYA ◽  
Osamu TERASHIMA ◽  
Seiichiro IZAWA ◽  
Yu FUKUNISHI ◽  
Ao kui XIONG
Keyword(s):  
Numerical Simulation ◽  
Direct Numerical Simulation ◽  
Lattice Boltzmann Method ◽  
Lattice Boltzmann ◽  
Three Dimensional ◽  
Dimensional Lattice ◽  
Boltzmann Method

scholarly journals Direct Numerical Simulation and Large Eddy Simulation on a Turbulent Wall-Bounded Flow Using Lattice Boltzmann Method and Multiple GPUs

2014 ◽  
Vol 2014 ◽  
pp. 1-10 ◽  
Author(s):  
Xian Wang ◽  
Yanqin Shangguan ◽  
Naoyuki Onodera ◽  
Hiromichi Kobayashi ◽  
Takayuki Aoki
Keyword(s):  
Numerical Simulation ◽  
Large Eddy Simulation ◽  
Direct Numerical Simulation ◽  
Lattice Boltzmann Method ◽  
Lattice Boltzmann ◽  
Graphic Processing Units ◽  
Multiple Gpus ◽  
Eddy Simulation ◽  
Large Eddy ◽  
Boltzmann Method

Direct numerical simulation (DNS) and large eddy simulation (LES) were performed on the wall-bounded flow atReτ=180using lattice Boltzmann method (LBM) and multiple GPUs (Graphic Processing Units). In the DNS, 8 K20M GPUs were adopted. The maximum number of meshes is6.7×107, which results in the nondimensional mesh size ofΔ+=1.41for the whole solution domain. It took 24 hours for GPU-LBM solver to simulate3×106LBM steps. The aspect ratio of resolution domain was tested to obtain accurate results for DNS. As a result, both the mean velocity and turbulent variables, such as Reynolds stress and velocity fluctuations, perfectly agree with the results of Kim et al. (1987) when the aspect ratios in streamwise and spanwise directions are 8 and 2, respectively. As for the LES, the local grid refinement technique was tested and then used. Using1.76×106grids and Smagorinsky constant(Cs)=0.13, good results were obtained. The ability and validity of LBM on simulating turbulent flow were verified.

Direct Numerical Simulation of an Open-Cell Metallic Foam through Lattice Boltzmann Method

2015 ◽  
Vol 18 (3) ◽  
pp. 707-722 ◽  
Author(s):  
Daniele Chiappini ◽  
Gino Bella ◽  
Alessio Festuccia ◽  
Alessandro Simoncini
Keyword(s):  
Numerical Simulation ◽  
Porous Media ◽  
Direct Numerical Simulation ◽  
Lattice Boltzmann Method ◽  
Lattice Boltzmann ◽  
Media Analysis ◽  
Metallic Foam ◽  
Computational Domain ◽  
Open Cell ◽  
Boltzmann Method

AbstractIn this paper Lattice Boltzmann Method (LBM) has been used in order to perform Direct Numerical Simulation (DNS) for porous media analysis. Among the different configurations of porous media, open cell metallic foams are gaining a key role for a large number of applications, like heat exchangers for high performance cars or aeronautic components as well. Their structure allows improving heat transfer process with fruitful advantages for packaging issues and size reduction. In order to better understand metallic foam capabilities, a random sphere generation code has been implemented and fluid-dynamic simulations have been carried out by means of a kinetic approach. After having defined a computational domain the Reynolds number influence has been studied with the aim of characterizing both pressure drop and friction factor throughout a finite foam volume. In order to validate the proposed model, a comparison analysis with experimental data has been carried out too.

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