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首页> 外文期刊>Arabian Journal for Science and Engineering. Section A, Sciences >A Detailed Reaction Kinetic Model of Heavy Naphtha Reforming
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A Detailed Reaction Kinetic Model of Heavy Naphtha Reforming

机译：重型石脑油重整的详细反应动力学模型

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摘要

A detailed reaction kinetic model was developed to describe heavy naphtha reforming reactions. The kinetic model involved 32 lumps and 132 reactions; the lumps were one to 11 carbon atoms n-paraffins, four to 11 carbon atoms iso-paraffins, methylcyclopentene, and six to 11 carbon atoms for naphthenes and aromatics. All computations in the present study were predicted using the particle swarm optimization (PSO) method coded by MATLAB 2015a software. This optimization method was used to estimate the optimum set of kinetic parameters of heavy naphtha reforming reactions. All 150 kinetic and deactivation parameters that were predicted in this work were fine-tuned using PSO. The proposed kinetic model was validated by benchmarking the model results with the data collected over 5 years for a commercial naphtha reforming unit. The mean absolute error for all component compositions within the process was found to be 0.0079. The catalyst deactivation rate was also predicted. It was found that catalyst activity decayed to 58.8% after 1225 operating days.
机译：开发了一种详细的反应动力学模型来描述重型石脑油重整反应。动力学模型涉及32个肿块和132个反应;肿块是一至11个碳原子N-链烷烃，4至11个碳原子是环烷烃，甲基环戊烯和六至11个碳原子用于环烷烃和芳烃。使用由Matlab 2015A软件编码的粒子群优化（PSO）方法预测本研究中的所有计算。这种优化方法用于估计重型石脑油重整反应的最佳动力学参数集。在这项工作中预测的所有150个动力学和停用参数使用PSO进行了微调。通过基准测试模型结果与商业石脑油重整单位超过5年的数据进行基准测试，验证了拟议的动力学模型。该过程中所有组分组合物的平均绝对误差被发现为0.0079。还预先预测催化剂失活率。发现催化剂活性在1225次经营后衰减至58.8％。

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