Machine learning method to explore the process conditions of ethanol catalytic coupling to prepare C4 olefins
Konferenz: CAIBDA 2022 - 2nd International Conference on Artificial Intelligence, Big Data and Algorithms
17.06.2022 - 19.06.2022 in Nanjing, China
Tagungsband: CAIBDA 2022
Seiten: 6Sprache: EnglischTyp: PDF
Autoren:
Liu, Wenmin; Qian, Yishan; Yang, Zhiji (School of Statistics and Mathematics, Yunnan University of Finance and Economics, Kunming, China)
Wen, Xingkai (School of Mathematics and Statistics, Northeast Normal University, Changchun, China)
Inhalt:
C4 olefins are commonly used in chemical products and pharmaceutical production. Ethanol is the raw material for the production of C4 olefins. In the production process, changes of experimental conditions will have a significant impact on production efficiency. It can greatly optimize production efficiency and save the economy to screen appropriate reaction conditions and design catalyst combinations. For this issue, separate regression models were established to quantify the influence of various factors on the reaction performance from the perspectives of charging method, catalyst reaction time, reaction temperature and catalyst composition. The optimal process preparation conditions are obtained by solving the objective optimization problem. The results show that the C4 olefin yield can reach a maximum of 128.52%. When the temperature is set to 450 °C and the catalyst combination is "200mg 0.5wt%Co/SiO2-200mg HAP-ethanol concentration 0.3ml/min".