Azarhoosh Mohammad Javad, Halladj Rouein, Askari Sima
Faculty of Chemical Engineering, Amirkabir University of Technology (Tehran Polytechnic), PO Box 15875-4413, Hafez Ave., Tehran, Iran.
J Phys Condens Matter. 2017 Oct 25;29(42):425202. doi: 10.1088/1361-648X/aa85f0. Epub 2017 Aug 14.
In this study, a new kinetic model for methanol to light olefins (MTO) reactions over a hierarchical SAPO-34 catalyst using the Langmuir-Hinshelwood-Hougen-Watson (LHHW) mechanism was presented and the kinetic parameters was obtained using a genetic algorithm (GA) and genetic programming (GP). Several kinetic models for the MTO reactions have been presented. However, due to the complexity of the reactions, most reactions are considered lumped and elementary, which cannot be deemed a completely accurate kinetic model of the process. Therefore, in this study, the LHHW mechanism is presented as kinetic models of MTO reactions. Because of the non-linearity of the kinetic models and existence of many local optimal points, evolutionary algorithms (GA and GP) are used in this study to estimate the kinetic parameters in the rate equations. Via the simultaneous connection of the code related to modelling the reactor and the GA and GP codes in the MATLAB R2013a software, optimization of the kinetic models parameters was performed such that the least difference between the results from the kinetic models and experiential results was obtained and the best kinetic parameters of MTO process reactions were achieved. A comparison of the results from the model with experiential results showed that the present model possesses good accuracy.
在本研究中，提出了一种基于Langmuir-Hinshelwood-Hougen-Watson（LHHW）机理的、用于多级SAPO-34催化剂上甲醇制轻质烯烃（MTO）反应的新动力学模型，并使用遗传算法（GA）和遗传编程（GP）获得了动力学参数。已经提出了几种用于MTO反应的动力学模型。然而，由于反应的复杂性，大多数反应被视为集总反应和基元反应，这不能被认为是该过程的完全准确的动力学模型。因此，在本研究中，提出了LHHW机理作为MTO反应的动力学模型。由于动力学模型的非线性和存在许多局部最优解，本研究使用进化算法（GA和GP）来估计速率方程中的动力学参数。通过在MATLAB R2013a软件中同时连接与反应器建模相关的代码以及GA和GP代码，对动力学模型参数进行了优化，从而使动力学模型结果与实验结果之间的差异最小，并获得了MTO过程反应的最佳动力学参数。模型结果与实验结果的比较表明，本模型具有良好的准确性。
