On the effects of surface waviness upon catalytic steam reforming of methane in micro-structured reactors - a computational study

This study introduces an advanced methodology for optimizing catalytic coatings on microreactor walls used in the steam reforming of methane. By integrating computational fluid dynamics, data analytics, and multiobjective optimization, this approach significantly intensifies the process, reduces catalyst usage, and improves the economic and environmental aspects of hydrogen production. The challenge of identifying ideal catalytic coatings is addressed by employing surrogate functions created by extensive data sets from computational fluid dynamics and machine learning. These surrogate functions are rigorously validated, achieving 99.9% accuracy for both the total H 2 production rate and the H 2 production rate per coated surface area. The optimal catalyst coating demonstrates a 65.8% increase in the H 2 production rate per coated surface area, yet a 9% increase in total entropy generation compared to a fully coated channel. These findings underscore significant opportunities to enhance the cost-effectiveness and sustainability of future microreactors through the optimization of discrete catalytic coatings.

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On the effects of surface waviness upon catalytic steam reforming of methane in micro-structured reactors - a computational study

Cited by 4 publications

References 61 publications

Effect of noble gases on the transport and thermodynamic characteristics of microchannel reforming reactors for hydrogen production

Effect of noble gases on the transport and thermodynamic characteristics of microchannel reforming reactors for hydrogen production

The role of voronoi catalytic porous foam in reactive flow for hydrogen production through steam methane reforming (SMR): A pore-scale investigation

Maximization of Hydrogen Production via Methane Steam Reforming in a Wavy Microreactor by Optimization of Catalyst Coating: A Combined Computational and Data Analytics Approach

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