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Nonlinear Finite Element Analysis-Based Flow Distribution and Heat Transfer Model

Author

Listed:
  • Tomáš Létal

    (Institute of Process Engineering, Faculty of Mechanical Engineering, Brno University of Technology, Technická 2, 61669 Brno, Czech Republic)

  • Vojtěch Turek

    (Institute of Process Engineering, Faculty of Mechanical Engineering, Brno University of Technology, Technická 2, 61669 Brno, Czech Republic)

  • Dominika Babička Fialová

    (Institute of Process Engineering, Faculty of Mechanical Engineering, Brno University of Technology, Technická 2, 61669 Brno, Czech Republic)

  • Zdeněk Jegla

    (Institute of Process Engineering, Faculty of Mechanical Engineering, Brno University of Technology, Technická 2, 61669 Brno, Czech Republic)

Abstract

A new strategy for fast, approximate analyses of fluid flow and heat transfer is presented. It is based on Finite Element Analysis (FEA) and is intended for large yet structurally fairly simple heat transfer equipment commonly used in process and power industries (e.g., cross-flow tube bundle heat exchangers), which can be described using sets of interconnected 1-D meshes. The underlying steady-state model couples an FEA-based (linear) predictor step with a nonlinear corrector step, which results in the ability to handle both laminar and turbulent flows. There are no limitations in terms of the allowed temperature range other than those potentially stemming from the usage of fluid physical property computer libraries. Since the fluid flow submodel has already been discussed in the referenced conference paper, the present article focuses on the prediction of the tube side and the shell side temperature fields. A simple cross-flow tube bundle heat exchanger from the literature and a heat recovery hot water boiler in an existing combined heat and power plant, for which stream data are available from its operator, are evaluated to assess the performance of the model. To gain further insight, the results obtained using the model for the heat recovery hot water boiler are also compared to the values yielded by an industry-standard heat transfer equipment design software package. Although the presented strategy is still a “work in progress” and requires thorough validation, the results obtained thus far suggest it may be a promising research direction.

Suggested Citation

  • Tomáš Létal & Vojtěch Turek & Dominika Babička Fialová & Zdeněk Jegla, 2020. "Nonlinear Finite Element Analysis-Based Flow Distribution and Heat Transfer Model," Energies, MDPI, vol. 13(7), pages 1-20, April.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:7:p:1664-:d:340762
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    References listed on IDEAS

    as
    1. Karl Lindqvist & Zachary T. Wilson & Erling Næss & Nikolaos V. Sahinidis, 2018. "A Machine Learning Approach to Correlation Development Applied to Fin-Tube Bundle Heat Exchangers," Energies, MDPI, vol. 11(12), pages 1-16, December.
    2. Panagiotis Karvounis & Dimitrios Koubogiannis & Elias Hontzopoulos & Antonios Hatziapostolou, 2019. "Numerical and Experimental Study of Flow Characteristics in Solar Collector Manifolds," Energies, MDPI, vol. 12(8), pages 1-17, April.
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    Citations

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    Cited by:

    1. Dominika Babička Fialová & Zdeněk Jegla, 2021. "Experimentally Verified Flow Distribution Model for a Composite Modelling System," Energies, MDPI, vol. 14(6), pages 1-24, March.
    2. Yee Van Fan & Zorka Novak Pintarič & Jiří Jaromír Klemeš, 2020. "Emerging Tools for Energy System Design Increasing Economic and Environmental Sustainability," Energies, MDPI, vol. 13(16), pages 1-25, August.

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