Radially layered configuration for improved performance of packed bed reactors

A particle-resolved computational fluid dynamics model is built and validated to investigate the coupled transfer processes and reactions in radially layered packed beds (RLPBs), with dry reforming of methane as a model reaction. RLPBs are 53.3-69.8% lower in pressure drop and 5.4-21.6 K higher in cold spot temperature than randomly packed beds (RPBs). The methane conversions for RLPBs are slightly lower than these for RPBs, but using smaller catalyst pellets in a RLPB can balance methane conversion and pressure drop. Besides, the diameter of separating wall in RLPBs can be adjusted to meet different requirements. The existence of separating wall in RLPBs makes catalyst pellets orderly distributed and then makes flow channels less tortuous, which leads to low flow resistances and good axial convective heat transfer. This work shows that RLPBs are advantageous in enhancing transfer processes and the results should serve to guide the optimal design of RLPBs. (C) 2022 Elsevier Ltd. All rights reserved.

Automated summary

A particle-resolved computational fluid dynamics model is used to study the transfer processes and reactions in radially layered packed beds (RLPBs). The results show that RLPBs have advantages in terms of pressure drop and cold spot temperature compared to randomly packed beds (RPBs). Although the methane conversion rate in RLPBs is slightly lower, using smaller catalyst pellets can balance the conversion rate and pressure drop.