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Developing theory of probability density function for stochastic modeling of turbulent gas-particle flows
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作者 Lixing ZHOU 《Applied Mathematics and Mechanics(English Edition)》 SCIE EI CSCD 2018年第7期1019-1030,共12页
Turbulent gas-particle flows are studied by a kinetic description using a prob- ability density function (PDF). Unlike other investigators deriving the particle Reynolds stress equations using the PDF equations, the... Turbulent gas-particle flows are studied by a kinetic description using a prob- ability density function (PDF). Unlike other investigators deriving the particle Reynolds stress equations using the PDF equations, the particle PDF transport equations are di- rectly 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. 展开更多
关键词 probability density function(PDF)modeling turbulent flow gas-particleflow
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