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Feedstock molecular reconstruction for secondary reactions of fluid catalytic cracking gasoline by maximum information entropy method

机译:最大信息熵法重构流化催化裂化汽油二次反应原料分子

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摘要

A novel methodology of maximum information entropy theory combined with structure oriented lumping (SOL) and Monte Carlo (MC) method was developed to simulate the feedstock for secondary reactions of fluid catalytic cracking (FCC) gasoline at the molecular level. The SOL method was applied to represent the feedstock configuration framework; a molecular library consisting of a large ensemble of computational molecules was created by stochastically assembling structural increments using MC method; then, the maximum information entropy method (MIEM) was introduced to adjust the mole fractions of the structural increments in the molecular library to achieve a closer matching with the actual analytical characteristics. Three samples of catalytic cracking gasoline from the industrial FCC units of China were used to validate and evaluate the proposed method. The simulation results of the feedstock properties, such as the average molecular weight and the weight fractions of main components including paraffin, olefins, naphthenes and aromatics agreed well with the experimental data. (C) 2015 Elsevier B.V. All rights reserved.
机译:提出了一种新的最大信息熵理论,并结合了结构定向集总(SOL)和蒙特卡洛(MC)方法,在分子水平上模拟了流体催化裂化(FCC)汽油二次反应的原料。 SOL方法用于表示原料配置框架。通过使用MC方法随机组装结构增量,创建了一个由大量计算分子组成的分子库。然后,引入最大信息熵方法(MIEM)来调整分子库中结构增量的摩尔分数,以实现与实际分析特征的更紧密匹配。从中国工业催化裂化装置的三个催化裂化汽油样品中,对所提出的方法进行了验证和评估。原料性能的模拟结果,如平均分子量和主要成分(包括石蜡,烯烃,环烷烃和芳烃)的重量分数与实验数据吻合良好。 (C)2015 Elsevier B.V.保留所有权利。

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