【摘要】 根据催化裂化反应机理和产物分布特点,建立了包含54条虚拟反应路径的重油催化裂化12集总反应网络。以Davison Circulating Riser(DCR)试验装置数据为基础,基于Python平台,将模型数学方程转化为程序语言,采用四阶Runge-Kutta法求解模型微分方程、BFGS法优化目标函数,求取了模型的动力学参数。采用小型试验数据验证模型动力学参数,结果表明主要产品产率的计算值与实验值之间的相对误差均小于5%。说明所建模型的动力学参数是可靠的,能较好地反映重油催化裂化的反应规律,可用于对实际生产过程进行模拟优化。更多还原

【Abstract】 Based on the catalytic cracking reaction mechanism and product distribution characteristics,a 12-lump reaction network for heavy oil catalytic cracking including 54 virtual reaction paths was established.The mathematical equations of the model are transformed into a programming language with the Python platform on the basis of experiment data in Davison Circulating Riser(DCR)apparatus.The kinetic parameters of the model were calculated by the fourth order Runge-Kutta algorithm applied to sovle the model differential equations and the BFGS algorithm applied to optimize the objective function.Validation of model parameters showed that the relative errors between the calculated and experimental values for the main products were all below 5%.This indicates that the kinetic parameters of the model are reliable,and can better reflect the reaction rules for heavy oil catalytic cracking.The model can be further used to simulate and optimize practical production processes.更多还原