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Numerical and experimental analysis of fluid flow and flow visualization at low Reynolds numbers in a dimple pattern plate heat exchanger

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  • Močnik, Urban
  • Čikić, Ante
  • Muhič, Simon

Abstract

This research discusses single-phase fluid flow conditions at low Reynolds number (Re) in the heat exchanger with a dimple structure of the heat plate. Flow at 70 ≤ Re ≤ 469 was investigated with laboratory experiments and computational fluid dynamics. It was found that in such a channel, two flow regimes exist, i.e., dead and live regimes. The volumetric fraction of the deadly regime gets bigger with increasing Re. At Re ≥ 469, a fully developed turbulent flow was found in the channel. Numerical analysis was made with a laminar flow model and two turbulence models, Realizable k−ε with an enhanced wall treatment and k−ω SST. The Realizable k−ε turbulent model with an enhanced wall treatment predicts pressure drop and shape of the live and dead regime more consistent with the real conditions in the channel. At the lowest considered Re = 70, computational fluid dynamics solutions deviate from laboratory experiments by −10.3 %. As the Re increases, the difference increases and reaches −18.3 % at Re = 141. As Re continues to increase, the result decreases and stabilizes at −8.3 %.

Suggested Citation

  • Močnik, Urban & Čikić, Ante & Muhič, Simon, 2024. "Numerical and experimental analysis of fluid flow and flow visualization at low Reynolds numbers in a dimple pattern plate heat exchanger," Energy, Elsevier, vol. 288(C).
  • Handle: RePEc:eee:energy:v:288:y:2024:i:c:s0360544223032061
    DOI: 10.1016/j.energy.2023.129812
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    References listed on IDEAS

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    1. Fawaz, Ahmad & Hua, Yuchao & Le Corre, Steven & Fan, Yilin & Luo, Lingai, 2022. "Topology optimization of heat exchangers: A review," Energy, Elsevier, vol. 252(C).
    2. Guichet, Valentin & Delpech, Bertrand & Khordehgah, Navid & Jouhara, Hussam, 2022. "Experimental and theoretical investigation of the influence of heat transfer rate on the thermal performance of a multi-channel flat heat pipe," Energy, Elsevier, vol. 250(C).
    3. Wang, Jin & Yu, Kai & Ye, Mingzheng & Wang, Enyu & Wang, Wei & Sundén, Bengt, 2022. "Effects of pin fins and vortex generators on thermal performance in a microchannel with Al2O3 nanofluids," Energy, Elsevier, vol. 239(PE).
    4. Wajs, Jan & Kura, Tomasz & Mikielewicz, Dariusz & Fornalik-Wajs, Elzbieta & Mikielewicz, Jarosław, 2022. "Numerical analysis of high temperature minichannel heat exchanger for recuperative microturbine system," Energy, Elsevier, vol. 238(PA).
    5. Zhang, Tianyi & Chen, Lei & Wang, Jin, 2023. "Multi-objective optimization of elliptical tube fin heat exchangers based on neural networks and genetic algorithm," Energy, Elsevier, vol. 269(C).
    6. Wang, Zeyu & Diao, Yanhua & Zhao, Yaohua & Chen, Chuanqi & Wang, Tengyue & Liang, Lin, 2022. "Visualization experiment and numerical study of latent heat storage unit using micro-heat pipe arrays: Melting process," Energy, Elsevier, vol. 246(C).
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