重油催化裂化十二集总动力学模型研究

发布时间：2018-04-08 11:20

本文选题：重油催化裂化　切入点：集总　出处：《华东理工大学》2017年硕士论文

【摘要】：集总是解决催化裂化动力学问题较为有效的方法。将重油催化裂化反应体系划分为包含饱和分(HS)、芳香分(HA)、胶质+沥青质(HR)、柴油(DIESEL)、汽油饱和烃(GS)、汽油烯烃(GO)、汽油芳烃(GA)、干气(DGAS)、丙烯(L03)、丁烯(L04)、液化气中的烷烃(LPGD)、焦炭(COKE)等12个集总;基于催化裂化反应机理,构建包含54个虚拟反应路径的12集总反应网络,建立了模型的动力学方程。基于Python平台,将模型数学方程转化为程序语言,采用Runge-Kutta法求解模型微分方程、BFGS法优化模型的目标函数,并根据实验数据求得了模型的54组反应动力学参数(指前因子k0和活化能E)与3个催化剂失活常数。模型参数能较好地符合催化裂化反应的基本规律。模型的验证结果表明,柴油、汽油(汽油饱和烃、汽油烯烃、汽油芳烃)、丙烯和丁烯等主要产品计算值与实验值之间的相对误差均在5%范围内,说明所建模型的可靠性和外推性良好。改变反应温度、压力、剂油比和反应时间对产物分布影响的预测结果能较好地符合催化裂化反应机理。通过分步优化的方式可求取一定实验原料和催化剂下主要产品收率之和最大化对应的反应温度、压力、剂油比和反应时间等操作条件。研究结果为模型进一步指导工业过程的模拟优化打下了良好的基础。
[Abstract]:A more effective method in solving problems. Always kinetics of catalytic cracking of heavy oil catalytic cracking reaction system will be divided into contains saturated (HS) (HA), aromatics, resin + asphaltene (HR), (DIESEL), diesel gasoline saturated hydrocarbons (GS), olefin (GO), aromatics (GA) dry gas (DGAS), (L03), propylene, butene (L04), liquefied gas in alkanes (LPGD), coke (COKE) 12 in total; catalytic cracking reaction mechanism based on virtual construction contains 54 reaction paths 12 lumped reaction network, established the dynamic equation of the model. Based on the Python platform, the mathematical model of equation is transformed into a programming language, using Runge-Kutta method to solve differential equation model, the objective function optimization model BFGS method, and obtained the kinetic parameters of 54 sets of reaction model according to the experimental data (frequency factor K0 and activation energy E) with 3 catalyst deactivation constants. The model parameters can be better with catalysis The basic law of cracking reaction model. The verification results show that the diesel, petrol (gasoline gasoline gasoline olefin, saturated hydrocarbon, aromatic hydrocarbon, propylene and butylene) main products are calculated in the range of 5%. The relative error between the experimental values and the building model, reliability and good extrapolation. Changing the reaction temperature, pressure, solvent oil ratio and reaction time on the product distribution of the prediction results are in good coincidence with the catalytic cracking reaction mechanism. The reaction temperature, through a two-step optimization way can obtain some experimental materials and catalyst under the main product yield and maximum stress, operating conditions of solvent oil ratio and reaction time results. To guide further optimization of industrial process simulation model has laid a good foundation.

【学位授予单位】：华东理工大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TE624.41

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