石油炼制与化工 ›› 2024, Vol. 55 ›› Issue (7): 99-105.
• 基础研究 • 上一篇 下一篇
宋雨雨,崔晨,吕文进,宋建,周祥
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摘要: 采用信息熵最大化理论和重整原料部分物性相结合的方法,研究了在生成Delta-Base数据过程中重整原料分子层面上的变化。模型计算过程中以信息熵最大化为目标,以重整原料的相对分子质量、H/C比、PIONA组成、密度以及芳烃潜含量作为约束条件,并以遗传算法作为优化方法进行模型求解,从分子层面计算两种不同芳烃潜含量重整原料的Delta-Base数据。结果显示,随着原料芳烃潜含量的增加,产品中芳烃含量也增加,可以利用分子水平机理模型生成Delta-Base数据。
关键词: 分子水平, 催化重整, Delta-Base, 信息熵
Abstract: Based on the maximum Shannon entropy states and partial physical properties of reforming feedstock, the change of molecular level of reforming feedstock during Delta-Base data generation was studied. The maximum Shannon entropy as the objective function was used, the relative molecular mass, the ratio of hydrogen to carbon, the composition and density of PIONA and the potential content of aromatics were taken as constraints, and the Delta-Base data of two different aromatics reforming feedstocks were calculated from the molecular level. The results showed that the mass fraction of aromatics in the product increased with the increase of the potential content of aromatics. The Delta-Base data can be generated by the molecular level mechanism model.
Key words: molecular level, catalytic reforming, Delta-Base, Shannon entropy
宋雨雨 崔晨 吕文进 宋建 周祥. 基于分子水平模型生成催化重整Delta-Base数据[J]. 石油炼制与化工, 2024, 55(7): 99-105.
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