Abstract
Abstract The main objective of this study is modeling and optimization of methanol oxidation over iron-molybdenum oxide catalyst in a fixed bed reactor. The considered process is modeled based on the mass and energy balance equations at steady state condition. To verify accuracy of the proposed model and considered assumptions, the simulation results are compared with the plant data. Then, the effect of feed temperature, coolant temperature and air-to-methanol molar ratio on the reactor performance is investigated. In addition, considering formaldehyde production capacity and selectivity as objectives, a multi-objective optimization problem is formulated considering feed and coolant temperature, and air to methanol ratio as decision variables. Based on the developed mathematical model of the process and multi-objective optimization model, Pareto optimal front is obtained by non-sorting multi-objective genetic algorithm. Then, the single optimal point is selected from developed optimal Pareto front by TOPSIS decision-making method. The performance of the optimized reactor is compared with the conventional reactor at steady state condition.
Published Version
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