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Parametric optimization of H-type finned tube with longitudinal vortex generators by response surface model and genetic algorithm


  • Tang, Song-Zhen
  • Wang, Fei-Long
  • He, Ya-Ling
  • Yu, Yang
  • Tong, Zi-Xiang


Low-low temperature electrostatic precipitator technology is one of the important ways for energy saving and emission reduction of coal-fired power plants. In order to further improve the dust removal efficiency and enhance waste heat recovery performance, a novel H-type finned elliptical tube heat exchanger with longitudinal vortex generators is proposed. To achieve the maximum heat transfer enhancement with the minimum friction factor augmentation, the response surface model and multi-objective genetic algorithm are adopted to optimize the design parameters. Firstly, combined with the finite volume method and the central composite design method, the second-order response surface model between the design parameters (the length, height, angle, and position of longitudinal vortex generators) and the objective functions (Nusselt number and friction factor) is established. Then, based on the response surface model, the Pareto optimal solution set is obtained by the multi-objective genetic algorithm. Finally, by comprehensively comparing Nusselt number, friction factor and performance evaluation criteria of Pareto optimal solutions, the optimal combination is determined. Compared with the H-type finned tube heat exchanger, the performance evaluation criteria of the optimized novel heat exchanger is improved by 48–55%, which contributes to improve the overall performance of low-low temperature electrostatic precipitator system. The findings of this paper may provide practical guidelines for researchers and designers to develop efficient heat exchangers.

Suggested Citation

  • Tang, Song-Zhen & Wang, Fei-Long & He, Ya-Ling & Yu, Yang & Tong, Zi-Xiang, 2019. "Parametric optimization of H-type finned tube with longitudinal vortex generators by response surface model and genetic algorithm," Applied Energy, Elsevier, vol. 239(C), pages 908-918.
  • Handle: RePEc:eee:appene:v:239:y:2019:i:c:p:908-918
    DOI: 10.1016/j.apenergy.2019.01.122

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    References listed on IDEAS

    1. Ahmed, H.E. & Mohammed, H.A. & Yusoff, M.Z., 2012. "An overview on heat transfer augmentation using vortex generators and nanofluids: Approaches and applications," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(8), pages 5951-5993.
    2. Ma, Ting & Lu, Xing & Pandit, Jaideep & Ekkad, Srinath V. & Huxtable, Scott T. & Deshpande, Samruddhi & Wang, Qiu-wang, 2017. "Numerical study on thermoelectric–hydraulic performance of a thermoelectric power generator with a plate-fin heat exchanger with longitudinal vortex generators," Applied Energy, Elsevier, vol. 185(P2), pages 1343-1354.
    3. Tong, Zi-Xiang & Li, Ming-Jia & He, Ya-Ling & Tan, Hou-Zhang, 2017. "Simulation of real time particle deposition and removal processes on tubes by coupled numerical method," Applied Energy, Elsevier, vol. 185(P2), pages 2181-2193.
    4. Lotfi, Babak & Sundén, Bengt & Wang, Qiuwang, 2016. "An investigation of the thermo-hydraulic performance of the smooth wavy fin-and-elliptical tube heat exchangers utilizing new type vortex generators," Applied Energy, Elsevier, vol. 162(C), pages 1282-1302.
    5. Luo, Lei & Wen, Fengbo & Wang, Lei & Sundén, Bengt & Wang, Songtao, 2016. "Thermal enhancement by using grooves and ribs combined with delta-winglet vortex generator in a solar receiver heat exchanger," Applied Energy, Elsevier, vol. 183(C), pages 1317-1332.
    6. Zhao, X.B. & Tang, G.H. & Ma, X.W. & Jin, Y. & Tao, W.Q., 2014. "Numerical investigation of heat transfer and erosion characteristics for H-type finned oval tube with longitudinal vortex generators and dimples," Applied Energy, Elsevier, vol. 127(C), pages 93-104.
    7. Zhang, Pan & Ma, Ting & Li, Wei-Dong & Ma, Guang-Yu & Wang, Qiu-Wang, 2018. "Design and optimization of a novel high temperature heat exchanger for waste heat cascade recovery from exhaust flue gases," Energy, Elsevier, vol. 160(C), pages 3-18.
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    Cited by:

    1. Wang, Fei-Long & He, Ya-Ling & Tang, Song-Zhen & Kulacki, Francis A. & Tao, Yu-Bing, 2019. "Multi-objective optimization of a dual-layer granular filter for hot gas clean-up by using genetic algorithm," Applied Energy, Elsevier, vol. 248(C), pages 463-474.


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