Filtered model for the cold-model gas–solid flow in a large-scale MTO fluidized bed reactor

•A filtered TFM is developed to model a commercial cold-model MTO FBR.•Predictions are compared against data from classical models and experiments.•Four CFD models under the same coarse-grid condition are compared.•The dependence of filtered quantities on gas–solid flow in FBR is discussed.•Filtered TFM is used to optimize MTO reactor operating conditions.

In this work, a three-dimensional (3-D) filtered two-fluid model (TFM) was developed to describe the gas–solid flow behavior in a large-scale methanol-to-olefins (MTO) fluidized bed reactor (FBR). The cold-model flow behaviors were characterized successfully via the filtered TFM with a coarse grid. A coarse-grid sensitivity test was first carried out, and the filtered model was testified using predictions from classical models and the experimental data. Moreover, four drag models have been incorporated into the TFM for evaluating the effectiveness of these models at the same coarse-grid condition. Subsequently, the effects of some important model parameters including solid stresses, wall corrections and filter size on the flow behaviors were also investigated numerically. Finally, the filtered model was applied to predict the effects of the operating gas velocity, distributor shape and solid particle size. The results suggested the effectiveness of the sub-grid models for simulating large-scale MTO FBRs at coarse-grid conditions. This study further confirmed that the filtered drag coefficient correlation plays a significant role in capturing flow behaviors and the filter size is nearly independent on the grid size when the filter size is larger than or equal to twice the grid size. The simulation results by coarse-grid also show that the catalyst particles are easier to be fluidized with the increase of the operating gas velocity. It is also found that a triangle-shaped distributor strengthens the mixing behaviors and weakens the clustering of the near-wall regions. Additionally, our study indicates that the clustering phenomena near the wall regions are more obvious with the decrease of the catalyst particle size.

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