Multiphase Particle in Cell Simulations of Fluidized Beds: Studies on Bubble Rise Velocity and Minimum Fluidization Velocity

被引:5
|
作者
Pal, Kanjakha [1 ]
Theuerkauf, Jorg [2 ]
机构
[1] Dow Chem Co USA, 230 Abner Jackson Pkwy, Lake Jackson, TX 77566 USA
[2] Dow Chem Co USA, 693 Washington St, Midland, MI 48667 USA
关键词
Bayesian regularization; Bubbling; Fluidized bed; Machine learning; Minimum fluidization velocity; MODEL; CRYSTALLIZATION; GELDART;
D O I
10.1002/cite.202000201
中图分类号
TQ [化学工业];
学科分类号
0817 ;
摘要
Multiphase particle in a cell simulation of fluidized beds for different Geldart group particles (A, B and D) were investigated. The minimum fluidization velocities predicted by the Barracuda Virtual Reactor (R) were compared and contrasted by theoretical predictions with the Wen-Yu model. The optimal drag force coefficients based on the Wen-Yu model for MP-PIC simulations was further evaluated for different particle sizes and densities for Group A catalysts. A neural network model was constructed for the optimal model constants as a function of the explanatory variables for group A catalysts. This work illustrates the importance of choosing the correct value for the drag force coefficients to obtain realistic simulation results for fluidized beds. This work clearly demonstrates that the Barracuda simulation results are very sensitive to the value of the Wen-Yu parameter. Using multiphase particle in cell simulations in conjunction with a neural network model can be directly used in further studies as a rapid tool to get the correct values for realistic drag force coefficients based on the Wen-Yu model.
引用
收藏
页码:237 / 246
页数:10
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