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基于分子水平模型生成催化重整Delta-Base数据

GENERATING DELTA-BASE DATA FOR CATALYTIC REFORMING BASED ON MOLECULAR-LEVEL MODEL

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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,产品中的芳烃含量也增加,可以利用分子水平机理模型生成Delta-Base数据.
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.

molecular levelcatalytic reformingDelta-BaseShannon entropy

宋雨雨、崔晨、吕文进、宋建、周祥

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中石化石油化工科学研究院有限公司,北京 100083

分子水平 催化重整 Delta-Base 信息熵

国家重点研发计划资助项目

2021YFA1501201

2024

石油炼制与化工
中国石油化工股份有限公司石油化工科学研究院

石油炼制与化工

CSTPCD北大核心
影响因子:0.825
ISSN:1005-2399
年,卷(期):2024.55(7)