石脑油裂解过程一次反应选择性系数的估计

本论文提出了一种基于模糊匹配的石脑油裂解过程kumar模型一次反应选择性系数估计方法。首先根据石脑油裂解实验数据建立存有一定数目样本点的标准数据库，标准样本点的一次反应选择性系数是由基于kumar模型的裂解炉模型计算的；然后定义了模糊匹配的隶属度函数，以表征待估物料与标准物料之间的相似程度，通过匹配找出隶属度较大的几个标准样本，并据此估算待估物料的一次反应选择性系数。以某乙烯装置的生产工况为实例进行验证，计算结果町以较好地符合生产实际，证实了该估计方法的有效性。

Estimation of the selectivities of the first-order reaction in naphtha pyrolysis

A fuzzy matching based method for estimating the selectivities of the first-order reaction of the Kumar's model is proposed. First a database with a set of standard data of the selectivities should be established by calculating the historical samples with known feed characteristics, then membership functions are defined for the expression of the similarity degree of the naphtha to be estimated to the standard ones. After the matching, the estimation can be carried out based on the matched standard examples possessing relatively large values of the membership function. In a case study on the naphtha pyrolysis, the yields calculated based on the estimated selectivities of the first-order reaction are very close to the experimental results, which demonstrate the effectiveness of the proposed method.