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Analysis of thermal efficiency of a corrugated double-tube heat exchanger with nanofluids

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  • Zheng, Dan
  • Du, Jianqiang
  • Wang, Wei
  • Klemeš, Jiří Jaromír
  • Wang, Jin
  • Sundén, Bengt

Abstract

This research investigated convective heat transfer and hydraulic resistance of smooth and corrugated double-tube heat exchangers at various flow rates from 60 L/h to 200 L/h. The inner tube with a thread structure is designed with three pitches, i.e., 4 mm, 6 mm and 8 mm. Nanofluids are used as tube-side fluids to analyze the enhancement of heat transfer on the inner tube side. Results show that the boundary layer is destroyed by the thread structure, and the heat flux is intensified at the outer tube side. For the double-tube heat exchanger, the combined enhancement technology using thread structure at the side of the outer tube and nanofluids at the side of the inner tube contributes to improvement in the overall heat transfer performance. The maximum increment in the comprehensive performance index is 59% for the case of 1.5 wt% SiC-water nanofluid with a thread pitch of 4 mm at a flow rate of 200 L/h. Finally, the distribution of local temperature difference is analysed theoretically for nanofluids with the optimum particle concentrations, which confirmed the rationality of 1.5 wt% SiC-water nanofluid with a thread pitch of 4 mm. Results reveal that the combined enhancement of using nanofluids and a thread structure has great potential in enhancing the thermal performance of double-tube heat exchangers.

Suggested Citation

  • Zheng, Dan & Du, Jianqiang & Wang, Wei & Klemeš, Jiří Jaromír & Wang, Jin & Sundén, Bengt, 2022. "Analysis of thermal efficiency of a corrugated double-tube heat exchanger with nanofluids," Energy, Elsevier, vol. 256(C).
    • Handle: RePEc:eee:energy:v:256:y:2022:i:c:s0360544222014256
    DOI: 10.1016/j.energy.2022.124522
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    References listed on IDEAS

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    Cited by:

    1. 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).
    2. Wang, Jin & Yang, Xian & Klemeš, Jiří Jaromír & Tian, Ke & Ma, Ting & Sunden, Bengt, 2023. "A review on nanofluid stability: preparation and application," Renewable and Sustainable Energy Reviews, Elsevier, vol. 188(C).

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