摘要
作为重要的基础化工原料,C4烯烃被广泛应用于化工产品及医药中间体的生产。乙醇是生产制备C4烯烃的重要原料,在制备过程中,C4烯烃的收率一定程度上取决于反应温度和反应的催化剂组合,所以如何合理地设计催化剂组合及温度至为关键。本文为探究不同反应条件对乙醇转化率及C4烯烃选择性的影响,建立基于OLS + 稳健的标准误的多元线性回归模型,得到对乙醇转化率及C4烯烃选择性线性相关显著的影响因素,并计算标准化回归系数,对影响因素的重要程度进行排序。为确定最佳反应条件,建立逐步筛选模型,并用MATLAB分别对C4烯烃收率与单变量进行曲线拟合。采用粒子群优化算法,依次确定C4烯烃收率最高时,各变量的最佳取值。
As an important basic chemical raw material, C4 olefins are widely used in the production of chemical products and pharmaceutical intermediates. Ethanol is an important raw material for the production and preparation of C4 olefin. In the preparation process, the yield of C4 olefin depends on the reaction temperature and catalyst combination, so how to design the catalyst combination and temperature reasonably is the key. In order to explore the effects of different reaction conditions on ethanol conversion and C4 olefin selectivity, a multiple linear regression model based on OLS + robust standard error was established to obtain the influential factors with significant linear correlation on ethanol conversion and C4 olefin selectivity. The standardized regression coefficient is calculated to rank the importance of the influencing factors. In order to determine the optimal reaction conditions, a stepwise screening model was established, and the curve fitting between the yield of C4 olefin and single variable was carried out by MATLAB. Finally, particle swarm optimization algorithm was used to determine the optimal value of each variable when the yield of C4 olefin was the highest.
出处
《理论数学》
2022年第6期952-961,共10页
Pure Mathematics
