(481g) Smart Reactor Design for Chemical Processes: Integrated CFD and Artificial Intelligence-Based Optimization Approach

Scaling up tubular reactors from lab to industrial scales requires drastic reactor geometry changes, such as the introduction of baffles, multiple tubes, tube pitches, baffle spacing, tube and shell diameters, and an appropriate coolant temperature. As a result, the design of such reactors involves a complex trade-off between the geometry, catalyst deactivation rate, pressure drop, equipment cost, temperature distribution (hotspots), and heat transfer area to meet desired product specifications. This research proposes a methodology for scaling up tubular reactors using economic, physical, and chemical constraints through a CFD and artificial intelligence integrated model for optimizing reactor configurations. The objective function is to maximize the yield of the desired product, minimize equipment cost and side product (CO₂) generation while eliminating the reaction zone hotspot (enhancing cooling efficiency). As a result, the optimal reactor length, tube diameter, number of tubes, shell diameter, baffle spacing, pitch spacing, and coolant temperature were computed. This strategy is extendable to all reactors where design and scale-up still present serious challenges.