MP-PIC Modeling of Fluidization Behaviors of Binary Sand–Plastic Mixtures

Abstract

Fluidized beds are usually used in the thermochemical conversion of waste plastic due to their excellent conversion efficiency. The complex fluidization behaviors of sand–plastic binary mixtures are not fully understood. The multiphase particle-in-cell (MP-PIC) model was employed and validated in this study to investigate fluidization hydrodynamics. The MP-PIC model adopts a coarse-grained approach by lumping a certain number of particles into a parcel and uses a solid stress model instead of resolving direct particle contacts. The effects of key model settings and parameters in the solid stress model were evaluated by comparing the simulation results with the experimental data. The results show that the drag models significantly affect the model accuracy, and the Gidaspow–Ganser hybrid drag model performs best among the tested drag models. When the grid size is larger than 5 times the diameter of the sand parcel, the error increases significantly. The optimal solid stress model parameter P s is larger under a larger inlet gas velocity.

Multiscale Modeling of Plastic Pyrolysis with a Neural Network-Inspired Pyrolysis Kinetic Model and Coarse-Grained DEM-CFD

“…The sand–HDPE binary mixtures fluidization experiment conducted under controlled conditions and reported in our previous work was used to validate the coarse-grained DEM-CFD model. The experimental setup involved a fluidization column, gas supply system, and measurement devices to monitor pressure drop, bed height, and gas velocity.…”

“…The minimum fluidization velocity ( U mf ) of sand was measured through experiments. The fluidization case was simulated at different inlet gas velocities (2 U mf , 3 U mf , and 4 U mf ) according to the bubbling fluidization domain, based on a previous study by Ma et al The simulations were set to run for 15 s, and the model parameters and settings are shown in Table . Sliding, rolling friction, and restitution coefficients were selected according to the optimized parameters by Xu et al The last 5 s of simulation results were averaged to analyze pressure drops and particle axial distribution.…”