22.低圧ジメチルエーテル合成(18)単純遺伝的アルゴリズムとニューラルネットワークを併用する反応器温度勾配の最適化

概要

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Dimethyl ether from natural gas or coal via syngas (3CO+3H_2→DME+CO_2) attracts much attention as high quality diesel fuel of next generation. Considering the compact process based on the small-scale carbon resources, low pressure-operation (at 1-3MPa) and high one-pass conversion (90% CO conversion) are required to produce DME with high efficiency. Temperature-gradient reactor (TGR) was effective to overcome both equilibrium limit of the reaction at high temperature and the low activity of catalyst at low temperature. The temperature gradient was optimized using simple genetic algorithm (GA) and neural network (NN). Evolution of the temperature profile was accelerated and successfully optimized to give 71% CO conversion higher than that in a conventional isothermal reactor (66%).
一般社団法人日本エネルギー学会の論文
2002-10-29