Core-shell equivalent reactor network model to bridging CFD and process simulations of a fluidized bed reactor

• Published in: Chemical engineering science Vol. 287; p. 119772
• Main Authors: Du, Yupeng, Cheng, Hao, Li, Shuo, Chen, Xiaoping, Li, Yanjun, Ren, Wanzhong, Yang, Chaohe
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 05.04.2024
• Subjects: CFD/Process simulation; Core-shell compartment model; Equivalent reactor network; Fluidized bed reactor; Propane dehydrogenation; Core-shell compartment model; Fluidized bed reactor; Propane dehydrogenation; CFD/Process simulation; Equivalent reactor network
• ISSN: 0009-2509; 1873-4405
• DOI: 10.1016/j.ces.2024.119772

[Display omitted] •A core–shell ERN model is proposed to bridge CFD and process simulations.•Procedures for constructing a core–shell ERN model are addressed in detail.•The core–shell ERN model equivalently reproduces the non-ideal flow in FBR.•The core–shell ERN model is incorporated into Aspen Plus via User2 module.•PDH reactor performance and process efficiency are evaluated by the process model. Equivalent reactor network (ERN) is expected to narrow the gap between the computational fluid dynamics (CFD) and process simulations of a fluidized bed reactor (FBR). In view of this, a novel CFD-based core–shell ERN framework is proposed, where the core compartment is represented by a variable cross-section PFR (vPFR) and shell zones are simulated by CSTRs. The CFD simulation indicates that the gas phase flow in a propane dehydrogenation (PDH) FBR deviates significantly from the ideal plug-flow. The developed core–shell ERN is reliable to reproduce the non-ideal flow. With the process model integrating the core–shell ERN, the PDH reactor performance and process efficiency are evaluated. Process defects are found mainly in the heat exchange section because of the largest lost work (i.e., 45.34 %) and lowest second-law efficiency (i.e., 20.75 %). Overall, the core–shell ERN is capable of bridging CFD and process simulations of an FBR and detecting process weakness.