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Optimization of a Membraneless Microfluidic Fuel Cell with a Double-Bridge Flow Channel

Author

Listed:
  • Ji-Hyun Oh

    (Department of Mechanical Engineering, Inha University, 100 Inha-ro, Michuhol-gu, Incheon 22212, Korea)

  • Tien-Dung Vuong

    (Department of Mechanical Engineering, Inha University, 100 Inha-ro, Michuhol-gu, Incheon 22212, Korea)

  • Kwang-Yong Kim

    (Department of Mechanical Engineering, Inha University, 100 Inha-ro, Michuhol-gu, Incheon 22212, Korea)

Abstract

In this work, a design optimization study was conducted to improve the performance of a membraneless microfluidic fuel cell with a double-bridge cross-section of the flow channel. Governing equations including Navier–Stokes, mass-transport, and Butler–Volmer equations were solved numerically to analyze the electrochemical phenomena and evaluate the performance of the fuel cells. Optimization was performed to maximize the peak power density using a genetic algorithm combined with a surrogate model constructed by radial basis neural network. Two sub-channel widths of the flow channel were selected as design variables for the optimization. As a result, a large increase in the inner channel width and a small decrease in the outer channel width effectively increased the peak power density of the MMFC. The optimal design increased the peak power density by 57.6% compared to the reference design.

Suggested Citation

  • Ji-Hyun Oh & Tien-Dung Vuong & Kwang-Yong Kim, 2022. "Optimization of a Membraneless Microfluidic Fuel Cell with a Double-Bridge Flow Channel," Energies, MDPI, vol. 15(3), pages 1-13, January.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:3:p:973-:d:737295
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    References listed on IDEAS

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    1. Sharaf, Omar Z. & Orhan, Mehmet F., 2014. "An overview of fuel cell technology: Fundamentals and applications," Renewable and Sustainable Energy Reviews, Elsevier, vol. 32(C), pages 810-853.
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    1. Wu, Baoxin & Xu, Xinhai & Dong, Guangzhong & Zhang, Mingming & Luo, Shijing & Leung, Dennis Y.C. & Wang, Yifei, 2024. "Computational modeling studies on microfluidic fuel cell: A prospective review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 191(C).

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