摘要
建立了利用宏观物性数据对柴油烃类组成进行预测的方法,根据对柴油烃类组分的分析和各烃类组分的物性差异,选取分属正构烷烃、异构烷烃、环烷烃和芳烃4个族的168个真实组分来表示柴油的组成,建立了柴油组分表示模板。建立了柴油各宏观物性与组成之间的关联关系,利用柴油常用宏观物性:密度、折射率、十六烷值、分子量以及恩式蒸馏曲线等数据建立方程组,对该方程组求解得到各个组分的含量。结果表明,计算得到的柴油饱和烃组成分布与烃组成分析结果较为吻合,误差在5%以下;三环环烷烃和芳烃的误差相对较大,并对产生误差的原因进行了分析。所建立的方法基本可以对直馏柴油烃类组成进行预测。
This paper established the method of using the physical property data to predict the composition of the diesel. According to the analyzed result of diesel samples and the differences between the properties of The hydrocarbon composition, we selected 168 real components to represent the composition of diesel, which is including in N-paraffins, iso-paraffins, naphthenic and aromatic, established diesel composition presentation template. We established the relationship between bulk properties and diesel composition. Used conventional bulk properties data such as density, cetane number, refractive index, molecular weight and ASTM distillation curve build equations. Solve equations to get the composition content of the real components. The results showed that, the calculated results of diesel oil saturated hydrocarbon composition distribution agreed well compared to the hydrocarbon composition analysis, error is less than 5 %. Polycyclic cycloalkane and aromatics calculation error is bigger. At last, we analyzed the causes of error. The method can predict the composition of straight run diesel hydrocarbons
出处
《计算机与应用化学》
CAS
2015年第6期707-711,共5页
Computers and Applied Chemistry
关键词
柴油
组分模板
宏观物性
预测
diesel
composition presentation template
bulk property
predicting
