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Performance analysis of a micro-scale integrated hydrogen production system by analytical approach, machine learning, and response surface methodology

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  • Pourali, Mostafa
  • Esfahani, Javad Abolfazli

Abstract

Parametric study of micro-scale integrated hydrogen production systems requires great computational efforts due to complex phenomena such as reaction kinetics. In the present study, an innovative combined approach, including machine learning for data generation (pre-processing), analytical techniques (processing), and response surface methodology (post-processing) is developed to investigate an integrated hydrogen production system. In the pre-processing step, appropriate correlations are provided for the species’ net rate, mixture properties, and the heat of reactions considering the detailed reaction mechanism of methane steam reforming and combustion, using the decision tree algorithm. A 2D steady-state model for heat and mass transfer is employed to analytically solve the conservation equations in a thermally coupled micro-combustor and catalytic micro-reformer. The post-processing step investigates the effects of seven main operational parameters on CH4 conversion, system efficiency, and quenching distance. It is found that the wall thickness is the most influential parameter in CH4 conversion and system efficiency. Also, the combustor height is the most critical parameter to sustain combustion in the integrated system. The achievements can be employed as guidelines for the initial design of an integrated hydrogen production system. Finally, five optimized designs of the integrated system are suggested for the first time to construct experimental prototypes.

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  • Pourali, Mostafa & Esfahani, Javad Abolfazli, 2022. "Performance analysis of a micro-scale integrated hydrogen production system by analytical approach, machine learning, and response surface methodology," Energy, Elsevier, vol. 255(C).
    • Handle: RePEc:eee:energy:v:255:y:2022:i:c:s0360544222014566
    DOI: 10.1016/j.energy.2022.124553
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    References listed on IDEAS

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    1. Chein, Rei-Yu & Chen, Yen-Cho & Chang, Che-Ming & Chung, J.N., 2013. "Experimental study on the performance of hydrogen production from miniature methanol–steam reformer integrated with Swiss-roll type combustor for PEMFC," Applied Energy, Elsevier, vol. 105(C), pages 86-98.
    2. Pashchenko, Dmitry & Mustafin, Ravil & Mustafina, Anna, 2021. "Steam methane reforming in a microchannel reformer: Experiment, CFD-modelling and numerical study," Energy, Elsevier, vol. 237(C).
    3. E, Jiaqiang & Luo, Bo & Han, Dandan & Chen, Jingwei & Liao, Gaoliang & Zhang, Feng & Ding, Jiangjun, 2022. "A comprehensive review on performance improvement of micro energy mechanical system: Heat transfer, micro combustion and energy conversion," Energy, Elsevier, vol. 239(PE).
    4. Banerjee, Abhisek & Paul, Diplina, 2021. "Developments and applications of porous medium combustion: A recent review," Energy, Elsevier, vol. 221(C).
    5. Elmaz, Furkan & Yücel, Özgün & Mutlu, Ali Yener, 2020. "Predictive modeling of biomass gasification with machine learning-based regression methods," Energy, Elsevier, vol. 191(C).
    6. Carapellucci, Roberto & Giordano, Lorena, 2019. "Upgrading existing gas-steam combined cycle power plants through steam injection and methane steam reforming," Energy, Elsevier, vol. 173(C), pages 229-243.
    7. Yao, Ling & Wang, Feng & Wang, Long & Wang, Guoqiang, 2019. "Transport enhancement study on small-scale methanol steam reforming reactor with waste heat recovery for hydrogen production," Energy, Elsevier, vol. 175(C), pages 986-997.
    8. Sharifi, Shima & Rahimi, Rahbar & Mohebbi-Kalhori, Davod & Colpan, C. Ozgur, 2020. "Coupled computational fluid dynamics-response surface methodology to optimize direct methanol fuel cell performance for greener energy generation," Energy, Elsevier, vol. 198(C).
    9. Vo, Nguyen Dat & Oh, Dong Hoon & Hong, Suk-Hoon & Oh, Min & Lee, Chang-Ha, 2019. "Combined approach using mathematical modelling and artificial neural network for chemical industries: Steam methane reformer," Applied Energy, Elsevier, vol. 255(C).
    10. Ji, Guozhao & Zhao, Ming & Wang, Geoff, 2018. "Computational fluid dynamic simulation of a sorption-enhanced palladium membrane reactor for enhancing hydrogen production from methane steam reforming," Energy, Elsevier, vol. 147(C), pages 884-895.
    11. Wang, Chao & Liao, Mingzheng & Liang, Bo & Jiang, Zhiqiang & Zhong, Weilin & Chen, Ying & Luo, Xianglong & Shu, Riyang & Tian, Zhipeng & Lei, Libin, 2021. "Enhancement effect of catalyst support on indirect hydrogen production from propane partial oxidation towards commercial solid oxide fuel cell (SOFC) applications," Applied Energy, Elsevier, vol. 288(C).
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    Cited by:

    1. Roy, Dibyendu & Samanta, Samiran & Roy, Sumit & Smallbone, Andrew & Roskilly, Anthony Paul, 2023. "Multi-objective optimisation of a power generation system integrating solid oxide fuel cell and recuperated supercritical carbon dioxide cycle," Energy, Elsevier, vol. 281(C).
    2. Anita Šalić & Bruno Zelić, 2022. "A Game Changer: Microfluidic Technology for Enhancing Biohydrogen Production—Small Size for Great Performance," Energies, MDPI, vol. 15(19), pages 1-22, September.

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