摘要
为提高乙醇偶合制备C_(4)烯烃的生产收率,增加生产的经济价值,该文建立岭回归模型,分析催化剂组合与温度对产品制备的影响,又通过多层感知机模型对乙醇转化率、C_(4)烯烃选择性两者进行预测,优化计算出最佳的生产参数。研究表明,在反应温度不受限的情况下,可使乙醇转化率达到99.03%,C_(4)烯烃选择性达到58.09%,生产收率达到57.52%;在反应温度须小于350℃的情况下,可使乙醇转化率达到54.33%,C_(4)烯烃选择性达到38.52%,生产收率达到20.93%,最后发现温度对生产有着重要影响,实际生产时应保持最大温度。
In order to improve the yield of Colefin prepared by ethanol coupling and increase the economic value of production, a ridge regression model was established, and the effects of catalyst combination and temperature on product preparation were analyzed. The ethanol conversion and Colefin selectivity were predicted by the multi-layer perceptron model,and the best production parameters were optimized. Under the condition that the reaction temperature is not limited, the ethanol conversion can reach 99.03%, the selectivity of Colefins can reach 58.09%, and the production yield can reach 57.52%;under the condition that the reaction temperature must be less than 350 degrees Celsius, the conversion of ethanol can reach 54.33%.The selectivity of Colefins reaches 38.52%, and the production yield reaches 20.93%. Finally, it is found that temperature has an important effect on production, and the maximum temperature should be maintained in actual production.
出处
《科技创新与应用》
2022年第23期81-85,90,共6页
Technology Innovation and Application
关键词
乙醇
C_(4)烯烃
偶合反应
岭回归
多层感知机
alcohol
C_(4)olefin
coupling reaction
ridge regression
multilayer perceptron