Effects of fractal network channel on heat and mass transfer in methanol steam reforming. (30th September 2022)

• Record Type: Journal Article
• Authors: Yin, Bifeng; Chen, Zhiling; Xu, Sheng; Zhang, Senhao; Dong, Fei
• Is Part Of: International journal of hydrogen energy. Volume 47:Number 82(2022)
• Page Start: 34810
• Page End: 34824
• Publication Date: 2022-09-30
• Subjects: Fractal structure -- Methanol steam reforming -- Response surface optimization -- Hydrogen production; Hydrogen as fuel -- Periodicals; Hydrogène (Combustible) -- Périodiques; Hydrogen as fuel; Periodicals; 665.81
• DOI: 10.1016/j.ijhydene.2022.08.089
• Languages: English
• ISSNs: 0360-3199

Abstract

Abstract: Hydrogen production by methanol steam reforming is one of the best choices for portable proton exchange membrane fuel cells (PEMFC). The channel is a dominant role in hydrogen production performance as the main reaction site. In this study, a fractal network channel architecture was designed and a three-dimensional (3D) numerical simulation was conducted in accordance with the Uniform Latin Hypercube design simulation scheme to explore the influence mechanism of branch grade ( m ), branch angle ( θ ), branch length ratio ( α ) and branch width ratio ( β ) on hydrogen production performance. Furthermore, four factors ( m, θ, α, β ) for the hydrogen production performance of fractal network channel were optimized by combining response surface method and non dominated sorting genetic algorithm II. The results showed that the hydrogen production performance is most sensitive to changes in β with the growth of the fractal network, followed by m, α, and θ . And the optimum parameter combination in terms of yield hydrogen is m of 3, θ of 134°, α of 0.88, and β of 0.85. The mechanism of the influence of fractal network structure parameters on the methanol reforming reaction as revealed in this study may provide a workable guideline for effective heat and mass transfer in new fractal reaction channel. Graphical abstract: Image 1 Highlights: A fractal network was developed with constant reaction area and initial width. The influence mechanism is a trade-off between fluid velocity and channel length. Combining RSM and NSGA-Ⅱ algorithms to optimize the structural parameters. Hydrogen production performance is most sensitive to variations in β