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

  • Song Zhen Tang
  • , Fei Long Wang
  • , Ya Ling He*
  • , Yang Yu
  • , Zi Xiang Tong
  • *Corresponding author for this work
  • Xi'an Jiaotong University

Research output: Contribution to journalArticlepeer-review

Abstract

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.

Original languageEnglish
Pages (from-to)908-918
Number of pages11
JournalApplied Energy
Volume239
DOIs
StatePublished - 1 Apr 2019
Externally publishedYes

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 7 - Affordable and Clean Energy
    SDG 7 Affordable and Clean Energy

Keywords

  • Genetic algorithms
  • H-type finned tube
  • Longitudinal vortex generators
  • Response surface
  • Waste heat utilization

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