Optimal design of a large scale Fischer-Tropsch microchannel reactor module using a cell-coupling method

In this study, a C_{5 +}0.5 BPD microchannel Fishcer-Tropsch process with a U-type cooling system was modeled using a cell coupling method, and multi-objective optimization was conducted using an artificial neural network as a surrogate model. Two objective functions (reactor core volume and maximum process temperature rise, ΔT_max) were to be minimized using seven design variables as optimization variables. Reactor core volume represents a reactor's compactness, which is essential for a micro-channel reactor, whereas ΔT_maxis highly related to reactor stability. A Pareto optimal solution was obtained for a feasible ΔT_maxrange of 3.8–6.8 K. The optimal reactor core volume for ΔT_maxof 3.8 K was 1.45 times larger than that for ΔT_maxof 6.8 K. As ΔT_maxincreases, the total reactor length is shortened while the total width and height remain relatively constant. A sensitivity analysis of Pareto optimization was conducted for two types of parameters: 1) coolant flow rate, and 2) fixed design parameters. Coolant flowrates over 750 LPM were found to be inefficient for the given conditions. Fixed design parameters were closely related to the capabilities of the reactor fabricator. The present study suggested a priority order for modifying fixed design parameters to increase compactness. Suitable points can be selected based on the specific requirements of plant conditions.