Reactor design of methanol steam reforming by evolutionary computation and hydrogen production maximization by machine learning

• Main Authors: Chen, Wei-Hsin, Chen, Zih-Yu, Hsu, Sheng-Yen, Park, Young-Kwon, Juan, Joon Ching
• Format: Article
• Published: John Wiley & Sons 2022
• Subjects: QA75 Electronic computers. Computer science; QC Physics
• Online Access: http://eprints.um.edu.my/41024/

A numerical model is developed to predict the methanol steam reforming for H-2 production. This research designs an methanol steam reforming reactor and uses the Nelder-Mead algorithm to find an equivalent steam tube radius by minimizing the error between the simulation and experimental data. The ef...