Abstract
C4 olefin is an important feedstock for the chemical industry. Designing an effective and stable industrial process for preparing C4 olefin from renewable ethanol is crucial for further sustainable chemical production. In this study, a comprehensive evaluation system of an experimental scheme was constructed based on the Analytic Hierarchy Process/Entropy Weight Method-Technique for Order Preference by Similarity to Ideal Solution (AHP/EWM-TOPSIS) and Chemical production indicators. Using this evaluation system, a Back Propagation Neural Network (BPNN) based on a Genetic Algorithm (GA) was constructed after simulating C4 olefin production conditions using the Improved Mixed Congruential method. Subsequently, the production scheme with the highest evaluation score was determined when the temperature was not limited and when the temperature was lower than 350°C through a series of mathematical models. Overall, our mathematical models provide guidance for the commercial production of ethanol to butene and effectively reduce the risk of scaling up the chemical process to pilot or industrial scale.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
