Direct Numerical Simulation and Large Eddy Simulation on a Turbulent Wall-Bounded Flow Using Lattice Boltzmann Method and Multiple GPUs
Direct Numerical Simulation and Large Eddy Simulation on a Turbulent Wall-Bounded Flow Using Lattice Boltzmann Method and Multiple GPUs
复制标题
使用格子玻尔兹曼方法和多个 GPU 对湍流壁界流进行直接数值模拟和大涡模拟
DOI：
10.1155/2014/742432
复制
发表时间：
2014-04
影响因子：
--
通讯作者：
Aoki Takayuki
中科院分区：
文献类型：
--
作者：
shangguan Yan Qin;Onodera Naoyuki;Kobayashi Hiromochi;Aoki Takayuki
采用格子Boltzmann方法(LBM)和多个图形处理器(GPU)对壁面边界流动进行了直接数值模拟和大涡模拟。在域名系统中，采用了8个K20M图形处理器。最大网格数为，这将导致整个解域的无量纲网格大小。GPU-LBM求解器模拟LBM步长耗时24小时。为了得到准确的解析结果，测试了分辨率域的纵横比。结果，平均速度和湍流变量，如雷诺应力和速度波动，都与Kim等人的结果完全一致。(1987)，当沿流向和沿展宽方向的纵横比分别为8和2时。对于大涡模拟，对局部网格加密技术进行了试验，并对其进行了应用。利用网格和斯马戈林斯基常数，得到了较好的结果。验证了LBM模拟湍流流动的能力和有效性。
Direct numerical simulation (DNS) and large eddy simulation (LES) were performed on the wall-bounded flow at using lattice Boltzmann method (LBM) and multiple GPUs (Graphic Processing Units). In the DNS, 8 K20M GPUs were adopted. The maximum number of meshes is , which results in the nondimensional mesh size of for the whole solution domain. It took 24 hours for GPU-LBM solver to simulate LBM 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. Using grids and Smagorinsky constant , good results were obtained. The ability and validity of LBM on simulating turbulent flow were verified.
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DOI：
10.1145/1201775.882363
发表时间：
2003-07
期刊：
ACM SIGGRAPH 2003 Papers
影响因子：
--
作者：
J. Krüger;R. Westermann
通讯作者：
J. Krüger;R. Westermann
影响因子：
1.8
作者：
M. Spasov;D. Rempfer;P. Mokhasi
通讯作者：
M. Spasov;D. Rempfer;P. Mokhasi
DOI：
10.1016/j.parco.2011.02.007
发表时间：
2011
期刊：
Parallel Comput.
影响因子：
--
作者：
Yian Wang;T. Aoki
通讯作者：
Yian Wang;T. Aoki
影响因子：
2.4
作者：
J. Somers
通讯作者：
J. Somers
影响因子：
4.1
作者：
Huidan Yu;S. Girimaji;Li-Shi Luo
通讯作者：
Huidan Yu;S. Girimaji;Li-Shi Luo