Simulation and Optimization of a Methyl Ethyl Ketone Synthesis Reactor Using Genetic Algorithm

Methyl Ethyl Ketone (MEK) and hydrogen are produced by the dehydrogenation reaction of secondary butanol (2-butanol) over copper, zinc or bronze catalysts. In this study, simulation and optimization of a MEK synthesis packed bed reactor are presented by developing a one-dimensional homogeneous mathematical model. Also, the 4th order Runge-Kutta method is employed to solve the governing mass balance, energy balance, and pressure drop equations. Afterward, the model validity is approved by comparing the simulation results with experimental plant data. In addition, genetic algorithm (GA) optimization technique is applied to optimize the reactor performance and determine the maximum MEK production with respect to the inlet temperature, operating pressure and total feed molar flow rate as decision variables. Finally, genetic algorithm resulted in 14.72% increase in MEK production compared with the non-optimized reactor