Multiscale computational fluid dynamics and data-driven modeling of multiphase flows & reactors

Zhu L.T., Chen X.Z., Ouyang B., Yan W.C., Lei H., Chen Z., Luo Z.H., Review of machine learning for hydrodynamics, transport and reactions in multiphase flows and reactors. Industrial & Engineering Chemistry Research, 2022, 61(28), 9901-9949. Link

Zhu L.T., Ouyang B., Lei H., Luo Z.H., Conventional and data-driven modeling of mesoscale drag, heat transfer and reaction rate in gas-particle flows. AIChE Journal, 2021, 67(8), e17299. Link

Zhu L.T., Tang J.X., Luo Z.H., Machine learning to assist filtered two-fluid model development for dense gas-particle flows. AIChE Journal, 2020, 66(6), e16973. Link

Zhu L.T., Liu Y.X., Tang J.X., Luo Z.H., A material-property-dependent sub-grid drag model for coarse-grained simulation of 3D large-scale CFB risers. Chemical Engineering Science, 2019, 204, 228-245. Link

Zhu L.T., Y.X. Liu, Luo Z.H., An enhanced correlation for gas-particle heat and mass transfer in packed and fluidized bed reactors. Chemical Engineering Journal, 2019, 374, 531-544. Link

Zhu L.T., Liu Y.X., Luo Z.H., An effective three-marker drag model via sub-grid modeling for turbulent fluidization. Chemical Engineering Science, 2018, 192, 759-773. Link