LAPSE:2018.0267
Published Article
LAPSE:2018.0267
Optimization through Response Surface Methodology of a Reactor Producing Methanol by the Hydrogenation of Carbon Dioxide
July 31, 2018
Carbon dioxide conversion and utilization is gaining significant attention worldwide, not only because carbon dioxide has an impact on global climate change, but also because it provides a source for potential fuels and chemicals. Methanol is an important fuel that can be obtained by the hydrogenation of carbon dioxide. In this research, the modeling of a reactor to produce methanol using carbon dioxide and hydrogen is carried out by way of an ANOVA and a central composite design. Reaction temperature, reaction pressure, H₂/CO₂ ratio, and recycling are the chosen factors, while the methanol production and the reactor volume are the studied responses. Results show that the interaction AC is common between the two responses and allows improvement of the productivity in reducing the volume. A mathematical model for methanol production and reactor volume is obtained with significant factors. A central composite design is used to optimize the process. Results show that a higher productivity is obtained with temperature, CO₂/H₂ ratio, and recycle factors at higher, lower, and higher levels, respectively. The methanol production is equal to 33,540 kg/h, while the reactor volume is 6 m³. Future research should investigate the economic analysis of the process in order to improve productivity with lower costs.
Keywords
ANOVA analysis, carbon capture and utilization, methanol production, Optimization, process simulation, response surface methodology
Suggested Citation
Leonzio G. Optimization through Response Surface Methodology of a Reactor Producing Methanol by the Hydrogenation of Carbon Dioxide. (2018). LAPSE:2018.0267
Author Affiliations
Leonzio G: Department of Industrial and Information Engineering and Economics, University of L’Aquila, Via Giovanni Gronchi 18, 67100 L’Aquila, Italy [ORCID]
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Journal Name
Processes
Volume
5
Issue
4
Article Number
E62
Year
2017
Publication Date
2017-10-23
Published Version
ISSN
2227-9717
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PII: pr5040062, Publication Type: Journal Article
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LAPSE:2018.0267
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doi:10.3390/pr5040062
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Jul 31, 2018
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