Research on Preparation of C4 Olefins Based on Multiple Regression Analysis and Genetic Algorithm Optimization

Li Xiaokang, Tang Xin, Yuan Yukun
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引用次数: 1

Abstract

In this paper, aiming at the process of preparing C4 olefins from ethanol through coupling reaction, a multi-objective optimization model is established with the goal of C4 olefin yield, and the system parameters such as catalyst combination mode and temperature are searched and solved. Firstly, it is found that there is a certain relationship between ethanol conversion, C4 olefin selectivity and temperature change, and multiple functions are used for regression analysis. Taking catalyst A1 as an example, the best regression model between ethanol conversion and temperature is y1 = 0.003x2 – 1.193x + 141.807. The best regression model between C4 olefin selectivity and temperature is y2 = 0.001x2 – 0.681x + 88.406. Ethylene selectivity time optimal model: y3 = – 8.936e – 05x2 + 0.030x + 2.252. Then, the influence model of ethanol conversion rate is established, the model is solved by the least square method, and the genetic algorithm is used to optimize the model. The optimal model of ethanol conversion rate is:w1 = 83.9812pethanol + 0.9895t + 0.4925βCo/Sio2 – 84.2251. The optimal model of C4 olefin absorption is: w2 = –2.2047λco + 0.6778t + 0.5841βCo/Sio2 – 44.4423.
基于多元回归分析和遗传算法优化的C4烯烃制备研究
本文针对以乙醇为原料通过偶联反应制备C4烯烃的工艺过程,以C4烯烃产率为目标,建立了多目标优化模型,并对催化剂组合方式、温度等系统参数进行了搜索求解。首先,发现乙醇转化率、C4烯烃选择性与温度变化之间存在一定的关系,并利用多元函数进行回归分析。以催化剂A1为例,乙醇转化率与温度的最佳回归模型为y1 = 0.003x2 - 1.193x + 141.807。C4烯烃选择性与温度的最佳回归模型为y2 = 0.001x2 - 0.681x + 88.406。乙烯选择性时间最优模型:y3 = - 8.936e - 05x2 + 0.030x + 2.252。然后,建立了乙醇转化率的影响模型,采用最小二乘法对模型进行求解,并采用遗传算法对模型进行优化。乙醇转化率的最佳模型为:w1 = 83.9812 pe+ 0.9895t + 0.4925βCo/Sio2 - 84.2251。C4烯烃吸收的最佳模型为:w2 = - 2.2047λco + 0.6778t + 0.5841βCo/Sio2 - 44.4423。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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