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Validation of PCHE-Type CO 2 –CO 2 Recuperative Heat Exchanger Modeling Using Conductance Ratio Method

Author

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  • Viktoria Carmen Illyés

    (Institute for Energy Systems and Thermodynamics, Technische Universität Wien, Getreidemarkt 9, 1060 Wien, Austria)

  • Francesco Crespi

    (Department of Energy Engineering, University of Seville, Camino de los descubrimientos s/n, 41092 Seville, Spain)

  • Xavier Guerif

    (Kelvion Thermal Solutions, 25 Rue du Ranzay, 44300 Nantes, France)

  • Andreas Werner

    (Institute for Energy Systems and Thermodynamics, Technische Universität Wien, Getreidemarkt 9, 1060 Wien, Austria)

Abstract

Printed-circuit heat exchangers (PCHEs) are compact exchangers with exceptional heat-transfer properties that are important for supercritical CO 2 technology. Recalculating the heat transfer under off-design conditions is a common task. Thus, in this paper, traditional and PCHE-specific correlations are analyzed in a conventional, discretized one-dimensional model using the conductance ratio method. The predicted heat transfer is compared with the experimental data of a CO 2 –CO 2 heat exchanger with zigzag-type channels and one with s-shaped fin channels under various working conditions. The results demonstrate that all selected heat-transfer correlations predicted the transferred heat within +/−20% using the conventional model. The much simpler conductance ratio method yields better results, with heat transfer within +/−10%, even with conservative inputs to the model.

Suggested Citation

  • Viktoria Carmen Illyés & Francesco Crespi & Xavier Guerif & Andreas Werner, 2025. "Validation of PCHE-Type CO 2 –CO 2 Recuperative Heat Exchanger Modeling Using Conductance Ratio Method," Energies, MDPI, vol. 18(13), pages 1-26, July.
  • Handle: RePEc:gam:jeners:v:18:y:2025:i:13:p:3547-:d:1695177
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    References listed on IDEAS

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    1. Crespi, Francesco & Gavagnin, Giacomo & Sánchez, David & Martínez, Gonzalo S., 2017. "Supercritical carbon dioxide cycles for power generation: A review," Applied Energy, Elsevier, vol. 195(C), pages 152-183.
    2. Li, Qian & Zhan, Qi & Yu, Shipeng & Sun, Jianchuang & Cai, Weihua, 2023. "Study on thermal-hydraulic performance of printed circuit heat exchangers with supercritical methane based on machine learning methods," Energy, Elsevier, vol. 282(C).
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