Proceedings of the 2022 8th International Conference on Humanities and Social Science Research (ICHSSR 2022)

A Maximum Yield Model for Coupled Ethanol to C4 Alkenes Based on BP Neural Network and Genetic Algorithm

Authors
Baiyang Xiao1, *, Yiran Chen2, Mingyuan Li3, JingBo Ma1, Xinyao Zhang1
1College of Mechanical and Electrical Engineering, Xi’an University of Architecture and Technology, Xi’an, Shaanxi, 710311
2School of Information and Control Engineering, Xi’an University of Architecture and Technology, Xi’an, Shaanxi, 710311
3School of Energy and Power Engineering, Northeast Electric Power University, Jilin, Jilin, 132000
*Corresponding author. Email: (xiaobaiyang121@163.com)
Corresponding Author
Baiyang Xiao
Available Online 1 June 2022.
DOI
https://doi.org/10.2991/assehr.k.220504.214How to use a DOI?
Keywords
Correlation analysis; Grey correlation model; BP neural network; Genetic algorithm
Abstract

The preparation of C4 alkenes using ethanol coupling is an important reaction in chemical production, and the catalyst combination and temperature have a significant impact on the extent and efficiency of the reaction. This paper provides a model for seeking the maximum C4 alkenes yield by designing the catalyst combination and setting the temperature. Firstly, we investigated the relationship of ethanol conversion and C4 alkenes selectivity with temperature. The correlation analysis and regression analysis were conducted. We obtained that temperature is positively correlated with ethanol conversion and C4 alkenes selectivity in a certain temperature range, and the most drastic effect point was obtained lies within the interval [350,400] °C. Moreover, we analyzed results from the perspective of the chemical reaction mechanism. Then, we analyzed the effect of different catalyst combinations and temperatures on ethanol conversion and C4 alkenes selectivity by the grey correlation model. We obtain the correlation ranking: temperature > Co loading > Co/SiO2 and HAP loading ratio > drop acceleration rate of ethanol. Finally, we set the maximum C4 alkenes yield as the objective function and established a BP neural network to solve this optimization problem with the genetic algorithm used for extreme value finding. The maximum C4 alkenes yield of 0.4580 was obtained with the catalyst combination of 200 mg 1wt% Co/SiO2, 200 mg HAP, and ethanol concentration 0.9 mL/min without temperature limitation. With a limiting temperature of less than 350°C, the maximum C4 alkenes yield is 0.1982 at a reaction temperature of 348.60°C with the catalyst combination of 200 mg 1wt% Co/SiO2, 200 mg HAP, and ethanol concentration 0.9 mL/min.

Copyright
© 2022 The Authors. Published by Atlantis Press SARL.
Open Access
This is an open access article distributed under the CC BY-NC 4.0 license.

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Volume Title
Proceedings of the 2022 8th International Conference on Humanities and Social Science Research (ICHSSR 2022)
Series
Advances in Social Science, Education and Humanities Research
Publication Date
1 June 2022
ISBN
978-94-6239-580-0
ISSN
2352-5398
DOI
https://doi.org/10.2991/assehr.k.220504.214How to use a DOI?
Copyright
© 2022 The Authors. Published by Atlantis Press SARL.
Open Access
This is an open access article distributed under the CC BY-NC 4.0 license.

Cite this article

TY  - CONF
AU  - Baiyang Xiao
AU  - Yiran Chen
AU  - Mingyuan Li
AU  - JingBo Ma
AU  - Xinyao Zhang
PY  - 2022
DA  - 2022/06/01
TI  - A Maximum Yield Model for Coupled Ethanol to C4 Alkenes Based on BP Neural Network and Genetic Algorithm
BT  - Proceedings of the 2022 8th International Conference on Humanities and Social Science Research (ICHSSR 2022)
PB  - Atlantis Press
SP  - 1172
EP  - 1178
SN  - 2352-5398
UR  - https://doi.org/10.2991/assehr.k.220504.214
DO  - https://doi.org/10.2991/assehr.k.220504.214
ID  - Xiao2022
ER  -