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The optimization of fin-tube heat exchanger with longitudinal vortex generators using response surface approximation and genetic algorithm

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Abstract

Delta winglet works better than other vortex generators in improving the performance of fin-tube heat exchangers. In this paper, Response Surface Approximation is used to study the effects of the fin pitch, the ratio of the longitudinal tube pitch to transverse tube pitch, the ratio of both sides V 1 , V h of delta winglets and the attack angle of delta winglets on the performance of fin-tube heat exchanger. Firstly, Twenty-nine numerical group experiments including five times repeated experiments at the central point are conducted. Then, the analyses of variable (ANOVA) and regression are performed to verify the accuracy of the polynomial coefficients. Finally, the optimization of the fin-tube heat exchanger using the Genetic Algorithm is conducted and the best performance of j/f (1/3) is found to be 0.07945, which is consistent with the numerical result.

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Acknowledgements

The present work is supported by the Project of National Natural Science Foundation of China (No. 51476148) and Excellent Youth Foundation of He’nan Scientific Committee (154100510014) and Innovation Scientists and Technicians Troop Construction Project of Zhengzhou City (131PLJRC640).

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Authors and Affiliations

  1. School of Energy and Power Engineering, Zhengzhou University of Light Industry, Zhengzhou, 450002, Henan, China

    Xuehong Wu, DanDan Liu, Min Zhao & YanLi Lu

  2. Collaborative Innovation Center of Food Production and Safety of Henan Province, Zhengzhou, 450002, Henan, China

    Xuehong Wu, Min Zhao & YanLi Lu

  3. Institute of Electric Power, North China University of Water Resources and Electric Power, Zhengzhou, 450011, Henan, China

    Xiaoyong Song

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  1. Xuehong Wu
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  2. DanDan Liu
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  3. Min Zhao
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Correspondence to Xuehong Wu.

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Wu, X., Liu, D., Zhao, M. et al. The optimization of fin-tube heat exchanger with longitudinal vortex generators using response surface approximation and genetic algorithm. Heat Mass Transfer 52, 1871–1879 (2016). https://doi.org/10.1007/s00231-015-1709-x

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  • DOI: https://doi.org/10.1007/s00231-015-1709-x

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