The knowledge of bubble profiles in gas-liquid two-phase flows is crucial for analyzing the kinetic processes such as heat and mass transfer, and this knowledge is contained in field data obtained by surface-resolved ...The knowledge of bubble profiles in gas-liquid two-phase flows is crucial for analyzing the kinetic processes such as heat and mass transfer, and this knowledge is contained in field data obtained by surface-resolved computational fluid dynamics (CFD) simulations. To obtain this information, an efficient bubble profile reconstruction method based on an improved agglomerative hierarchical clustering (AHC) algorithm is proposed in this paper. The reconstruction method is featured by the implementations of a binary space division preprocessing, which aims to reduce the computational complexity, an adaptive linkage criterion, which guarantees the applicability of the AHC algorithm when dealing with datasets involving either non-uniform or distorted grids, and a stepwise execution strategy, which enables the separation of attached bubbles. To illustrate and verify this method, it was applied to dealing with 3 datasets, 2 of them with pre-specified spherical bubbles and the other obtained by a surface-resolved CFD simulation. Application results indicate that the proposed method is effective even when the data include some non-uniform and distortion.展开更多
The LBGK(lattice Bhatnagar-Gross-Krook)model of the lattice Boltzmann method including second-order boundary condition treatment for curve geometry was employed to investigate the flow around particle clusters.The dra...The LBGK(lattice Bhatnagar-Gross-Krook)model of the lattice Boltzmann method including second-order boundary condition treatment for curve geometry was employed to investigate the flow around particle clusters.The drag coefficient is a benchmark problem in the analysis of particle-fluid complex systems,especially,in a gas-solid fluidized bed.In the present work,the drag coefficient on a spherical particle in a cluster,was evaluated by using the momentum-exchange method directly.Two different configurations of cluster were measured based on the lattice Boltzmann method.Computational results indicated that the drag coefficient on an individual particle in a cluster depended heavily on the configuration of cluster.And the drag coefficient on the particle in the cluster was lower when that particle was shielded by other particles.Additionally,except for the configuration factor,both the inter-distance and Reynolds number had a strong effect on the drag coefficient on an individual particle as well.It was found that the drag coefficient on each particle varied drastically with clustering.Omitting the effect of clustering might result in incorrect drag forces in the simulation.展开更多
基金Projects(51634010,51676211) supported by the National Natural Science Foundation of ChinaProject(2017SK2253) supported by the Key Research and Development Program of Hunan Province,China
文摘The knowledge of bubble profiles in gas-liquid two-phase flows is crucial for analyzing the kinetic processes such as heat and mass transfer, and this knowledge is contained in field data obtained by surface-resolved computational fluid dynamics (CFD) simulations. To obtain this information, an efficient bubble profile reconstruction method based on an improved agglomerative hierarchical clustering (AHC) algorithm is proposed in this paper. The reconstruction method is featured by the implementations of a binary space division preprocessing, which aims to reduce the computational complexity, an adaptive linkage criterion, which guarantees the applicability of the AHC algorithm when dealing with datasets involving either non-uniform or distorted grids, and a stepwise execution strategy, which enables the separation of attached bubbles. To illustrate and verify this method, it was applied to dealing with 3 datasets, 2 of them with pre-specified spherical bubbles and the other obtained by a surface-resolved CFD simulation. Application results indicate that the proposed method is effective even when the data include some non-uniform and distortion.
文摘The LBGK(lattice Bhatnagar-Gross-Krook)model of the lattice Boltzmann method including second-order boundary condition treatment for curve geometry was employed to investigate the flow around particle clusters.The drag coefficient is a benchmark problem in the analysis of particle-fluid complex systems,especially,in a gas-solid fluidized bed.In the present work,the drag coefficient on a spherical particle in a cluster,was evaluated by using the momentum-exchange method directly.Two different configurations of cluster were measured based on the lattice Boltzmann method.Computational results indicated that the drag coefficient on an individual particle in a cluster depended heavily on the configuration of cluster.And the drag coefficient on the particle in the cluster was lower when that particle was shielded by other particles.Additionally,except for the configuration factor,both the inter-distance and Reynolds number had a strong effect on the drag coefficient on an individual particle as well.It was found that the drag coefficient on each particle varied drastically with clustering.Omitting the effect of clustering might result in incorrect drag forces in the simulation.
