Numerical Simulation and Analysis of Flow Around an Cylinder at High Reynolds Number

WU Pin; GAO Sheng

Chinese

您当前的位置：

首页 >

文章列表页 >

Numerical Simulation and Analysis of Flow Around an Cylinder at High Reynolds Number

更新时间：2026-09-04

- Numerical Simulation and Analysis of Flow Around an Cylinder at High Reynolds Number
- Vol. 31, Issue 11, Pages: 139-142(2014)
- 作者机构：
  
  上海大学计算机工程与科学学院,上海,200072
- 作者简介：
- 基金信息：
- DOI：
  CLC：
- Published：2014
- 稿件说明：
移动端阅览
武频, 高升. 高雷诺数下圆柱绕流数值模拟与分析[J]. 微电子学与计算机, 2014, 31(11): 139-142,147.

WU Pin, GAO Sheng. Numerical Simulation and Analysis of Flow Around an Cylinder at High Reynolds Number[J]. 2014, 31(11): 139-142.
武频, 高升. 高雷诺数下圆柱绕流数值模拟与分析[J]. 微电子学与计算机, 2014, 31(11): 139-142,147. DOI：

WU Pin, GAO Sheng. Numerical Simulation and Analysis of Flow Around an Cylinder at High Reynolds Number[J]. 2014, 31(11): 139-142. DOI：

摘要

将大涡模拟(Large Eddy Simulation

LES)和多弛豫时间格子玻尔兹曼(Multiple Relaxation Time (MRT) LBM)方法相结合

用于解决LBM方法在高雷诺数流动模拟产生的数值不稳定的问题.结合D2Q9-MRT模型与Smargorinsky涡粘模型

对高雷诺数下二维圆柱绕流进行数值模拟.并根据实验结果

系统分析了圆柱绕流涡的脱落形态

以及Strouhal数和其阻力升力系数随雷诺数的变化情况.实验结果表明该方法可以很好增加LBM在高雷诺数模拟中数值稳定性.

Abstract

In this paper

large-eddy simulation combined with multi-relaxation time lattice Boltzmann (MRT-LBM) method is proposed for solving the poor stability problem in high Reynolds number flow simulation with LBM.The implementation is discussed in the context of 9-velocity (D2Q9) MRT-LBM model in conjunction with the Smargorinsky subgrid closure model.This model is used for doing the two-dimensional numerical simulation of flow around a cylinder with a high Reynolds number.According to the experimental results

a systematic analysis of the form of shed vortex of flow around cylinder is made

and the variation of the Strouhal number and the drag coefficient with the change of Reynolds number.The experimental results show that the method can well increase numerical stability in the simulation with LBM in a high Reynolds number.

关键词

Keywords

references

Views

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

Steganography model guided by attention mechanism and improved dense convolution

High gain stability high temperature operational amplifier based on reverse body bias

A feature-oriented context understanding and slice analysis network for tuberculosis detection

Monte carlo analysis of V-layout trench SiC neutron detector

Research on the design of blockchain-based AI-generated content traceability framework

Related Author

No data

Related Institution

No data

AI问答

Postal code：100079
Tel：（010）53879206 Email：tmw@bjxintong.com.cn
Technical support is provided by Beijing Founder electronics co., LTD 京ICP备09082226号-64 京公网安备11010602201714号
It is recommended to read the content of this site in Chrome&IE9+. Please switch to extreme mode in browser 360.
Cookies We use cookies to help provide and enhance our service and tailor content. By continuing, you agree to the use of cookies.

⁰