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.
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Citation: ZHOU, L. X. Developing theory of probability density function for stochastic modeling of turbulent gas-particle flows. Applied Mathematics and Mechanics (English Edition), 39(7), 1019– 1030 (2018) https://doi.org/10.1007/s10483-018-2344-8
Project supported by the National Natural Science Foundation of China (No. 51390493)
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Zhou, L. Developing theory of probability density function for stochastic modeling of turbulent gas-particle flows. Appl. Math. Mech.-Engl. Ed. 39, 1019–1030 (2018). https://doi.org/10.1007/s10483-018-2344-8
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DOI: https://doi.org/10.1007/s10483-018-2344-8