Flow Field Prediction of Gas-Solid Fluidized Bed Based on POD and Surrogate Model

Aiming at the problems of complex two-phase flow and high computational cost in CFD numerical simulation of gas-solid fluidized beds, a reduced-order model for investigating the fluid dynamics in a non-reactive gas-solid fluidized bed was established based on the proper orthogonal decomposition (POD) and the surrogate model. The gas-solid two-phase flow process in the fluidized bed was predicted by adopting the POD-RBF method and the POD-Kriging method, respectively. Besides, the reduced-order model solutions with different gas velocities were compared with the full-order model solutions, and the effect of gas velocity on the bed motion was also studied. The results show that the mean relative error (MRE) between the reduced-order model and the full-order model does not exceed 5% in the range of design parameters used to generate the POD, and the prediction accuracy of the two methods is higher for the design conditions than for the non-design conditions. For the distributions of pressure, solids content, and gas velocity in the fluidized bed, the prediction accuracy of the POD-RBF method is higher than that of the POD-Kriging method. The prediction for the pressure field has the highest accuracy and the velocity field has the lowest one in the fluidized bed by employing these two reduced-order methods. Moreover, the reduced-order model improves the computational efficiency by nearly 400 times while maintaining high reconstruction and prediction accuracy.