Methanol synthesis via sorption-enhanced reaction process: Modeling and multi-objective optimization

Since liquid hydrocarbon fuels dominate the transportation sector for the foreseeable future, methanol could potentially be used as a much cleaner fuel than conventional petroleum-based fuels. Thus, development of methanol synthesis process to improve the methanol productivity has attracted increasing attention. This paper describes a steady-state mathematical model of a gas-flowing solids-fixed bed reactor (GFSFBR) with in situ water adsorption for methanol synthesis. Simulation result demonstrates that selective adsorption of water from methanol synthesis in GFSFBR leads to a significant enhancement in methanol production compared to zero solids mass flux condition. The remarkable advantage of GFSFBR over the conventional sorption-enhanced reaction process is the continuous adsorbent regeneration in this system. In the next step, a multi-objective optimization of GFSFBR is performed in order to maximize the methanol production rate and selectivity. Consequently, non-dominated sorting genetic algorithm-II (NSGA-II) is applied as a powerful method to optimize the GFSFBR. Optimization result has shown that there are optimal values of inlet temperature of gas and flowing solid phases, mass flux of flowing solids, flowing solid diameter, and pressure under which the highest methanol production rate and selectivity can be achieved. This paper shows how the concept of in situ water adsorption could be feasible and beneficial for methanol synthesis. (C) 2013 Taiwan Institute of Chemical Engineers. Published by Elsevier B.V. All rights reserved.