改进遗传算法在Claus脱硫反应动力学研究中的应用

Application of Improved Genetic Algorithm in the Study of Claus Desulfurization Reaction Kinetic

Claus工艺中硫化物会与气体中的甲烷反应生成少量的CS_2,从而对体系的反应速率产生影响。为了建立该复杂体系的完整宏观动力学以纠正反应器开发和放大过程中带来计算结果的偏差,本工作基于传统的Claus脱硫反应动力学模型,通过引入修正参数β来修正原料气中CS_2存在对反应速率的影响,并采用局部最优化算法与遗传算法相结合的算法对动力学模型参数进行了估值。统计检验和残差分析表明所建立的模型是适定的,估值结果是可信的。

The reactions between sulfides and methane in the Claus process produced a small amount of CS2,which affects the reaction rates of the system.In order to establish the complete macro-kinetics of this complicated system to correct deviations in the calculation results during the reactor development and scale-up,a correction coefficientβwas introduced based on the traditional kinetic models of Claus desulfurization reaction and the effect of CS2 in feed gas was thus eliminated.The parameters of the kinetic model have been estimated using the combination of local optimization algorithm and genetic algorithm.The statistic test and the residual analysis have demonstrated that the established model was appropriate,and the estimation results were credible.