Developing theory of probability density function for stochastic modeling of turbulent gas-particle flows

被引:0
|
作者
Zhou, Lixing [1 ]
机构
[1] Tsinghua Univ, Dept Engn Mech, Beijing 100084, Peoples R China
基金
中国国家自然科学基金;
关键词
probability density function (PDF) modeling; turbulent flow; gas-particle flow; SIMULATION;
D O I
10.1007/s10483-018-2344-8
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
Turbulent gas-particle flows are studied by a kinetic description using a probability density function (PDF). Unlike other investigators deriving the particle Reynolds stress equations using the PDF equations, the particle PDF transport equations are directly solved either using a finite-difference method for two-dimensional (2D) problems or using a Monte-Carlo (MC) method for three-dimensional (3D) problems. The proposed differential stress model together with the PDF (DSM-PDF) is used to simulate turbulent swirling gas-particle flows. The simulation results are compared with the experimental results and the second-order moment (SOM) two-phase modeling results. All of these simulation results are in agreement with the experimental results, implying that the PDF approach validates the SOM two-phase turbulence modeling. The PDF model with the SOM-MC method is used to simulate evaporating gas-droplet flows, and the simulation results are in good agreement with the experimental results.
引用
收藏
页码:1019 / 1030
页数:12
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