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

doi:10.1007/s10483-018-2344-8

Applied Mathematics and Mechanics (English Edition) ›› 2018, Vol. 39 ›› Issue (7): 1019-1030.doi: https://doi.org/10.1007/s10483-018-2344-8

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

Lixing ZHOU

Department of Engineering Mechanics, Tsinghua University, Beijing 100084, China

收稿日期:2017-09-07 修回日期:2017-12-21 出版日期:2018-07-01 发布日期:2018-07-01
通讯作者: Lixing ZHOU E-mail:zhoulx@mail.tsinghua.edu.cn
基金资助:
Project supported by the National Natural Science Foundation of China (No. 51390493)

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

Lixing ZHOU

Department of Engineering Mechanics, Tsinghua University, Beijing 100084, China

Received:2017-09-07 Revised:2017-12-21 Online:2018-07-01 Published:2018-07-01
Contact: Lixing ZHOU E-mail:zhoulx@mail.tsinghua.edu.cn
Supported by:
Project supported by the National Natural Science Foundation of China (No. 51390493)

摘要/Abstract

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.

关键词: highly viscoelastic flow, lubricating approximation, varying thick slit channel, numerical simulation, probability density function(PDF) modeling, gas-particle flow, turbulent flow

Abstract: 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.

Key words: highly viscoelastic flow, lubricating approximation, varying thick slit channel, numerical simulation, turbulent flow, gas-particle flow, probability density function(PDF) modeling

中图分类号:

76T99

Lixing ZHOU. Developing theory of probability density function for stochastic modeling of turbulent gas-particle flows[J]. Applied Mathematics and Mechanics (English Edition), 2018, 39(7): 1019-1030.

参考文献

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

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

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