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Investigation on pressure drop and heat transfer performances of plate-fin iron air preheater unit with experimental and Genetic Algorithm methods

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Listed:
  • Zeng, M.
  • Du, L.X.
  • Liao, D.
  • Chu, W.X.
  • Wang, Q.W.
  • Luo, Y.
  • Sun, Y.

Abstract

Air preheater is one of key elements in today’s energy-saving technology. Its performance deeply depends on the underlying configuration for heat transfer. In this paper, the pressure drop and heat transfer characteristics of a high-efficiency plate-fin structure used in an air preheater are experimentally investigated under a large variety of conditions. In particular, the critical Reynolds number for the conversion from laminar to turbulent flow in the system is obtained, and the heat transfer coefficients in the gas and air sides of the heat exchanger are successfully separated from the overall heat transfer coefficient using Genetic Algorithm method. The main conclusions drawn from this work will be helpful for future development and design of a high-efficiency heat preheater involving plate-fin structures.

Suggested Citation

  • Zeng, M. & Du, L.X. & Liao, D. & Chu, W.X. & Wang, Q.W. & Luo, Y. & Sun, Y., 2012. "Investigation on pressure drop and heat transfer performances of plate-fin iron air preheater unit with experimental and Genetic Algorithm methods," Applied Energy, Elsevier, vol. 92(C), pages 725-732.
    • Handle: RePEc:eee:appene:v:92:y:2012:i:c:p:725-732
    DOI: 10.1016/j.apenergy.2011.08.008
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    References listed on IDEAS

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    1. Rittidech, S. & Dangeton, W. & Soponronnarit, S., 2005. "Closed-ended oscillating heat-pipe (CEOHP) air-preheater for energy thrift in a dryer," Applied Energy, Elsevier, vol. 81(2), pages 198-208, June.
    2. Meena, P. & Rittidech, S. & Poomsa-ad, N., 2007. "Application of closed-loop oscillating heat-pipe with check valves (CLOHP/CV) air-preheater for reduced relative-humidity in drying systems," Applied Energy, Elsevier, vol. 84(5), pages 553-564, May.
    3. Meena, P. & Rittidech, S. & Poomsa-ad, N., 2007. "Closed-loop oscillating heat-pipe with check valves (CLOHP/CVs) air-preheater for reducing relative humidity in drying systems," Applied Energy, Elsevier, vol. 84(4), pages 363-373, April.
    4. Wang, Hong Yue & Zhao, Ling Ling & Zhou, Qiang Tai & Xu, Zhi Gao & Kim, Hyung Taek, 2008. "Exergy analysis on the irreversibility of rotary air preheater in thermal power plant," Energy, Elsevier, vol. 33(4), pages 647-656.
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    Cited by:

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    2. Li, Yong & Wang, Yanhong & Cao, Lihua & Hu, Pengfei & Han, Wei, 2018. "Modeling for the performance evaluation of 600 MW supercritical unit operating No.0 high pressure heater," Energy, Elsevier, vol. 149(C), pages 639-661.
    3. Chen, Heng & Qi, Zhen & Dai, Lihao & Li, Bin & Xu, Gang & Yang, Yongping, 2020. "Performance evaluation of a new conceptual combustion air preheating system in a 1000 MW coal-fueled power plant," Energy, Elsevier, vol. 193(C).
    4. Wang, Enhua & Zhang, Hongguang & Fan, Boyuan & Ouyang, Minggao & Yang, Kai & Yang, Fuyuan & Li, Xiaojuan & Wang, Zhen, 2015. "3D numerical analysis of exhaust flow inside a fin-and-tube evaporator used in engine waste heat recovery," Energy, Elsevier, vol. 82(C), pages 800-812.
    5. Chen, Heng & Zhang, Meiyan & Xue, Kai & Xu, Gang & Yang, Yongping & Wang, Zepeng & Liu, Wenyi & Liu, Tong, 2020. "An innovative waste-to-energy system integrated with a coal-fired power plant," Energy, Elsevier, vol. 194(C).
    6. Ma, Hongqiang & Liang, Nuo & Liu, Yemin & Luo, Xinmei & Hou, Caiqin & Wang, Gang, 2021. "Experimental study on novel waste heat recovery system for sulfide-containing flue gas," Energy, Elsevier, vol. 227(C).
    7. Sanjay Mukherjee & Abhishek Asthana & Martin Howarth & Jahedul Islam Chowdhury, 2020. "Techno-Economic Assessment of Waste Heat Recovery Technologies for the Food Processing Industry," Energies, MDPI, vol. 13(23), pages 1-26, December.
    8. Baklacioglu, Tolga & Turan, Onder & Aydin, Hakan, 2015. "Dynamic modeling of exergy efficiency of turboprop engine components using hybrid genetic algorithm-artificial neural networks," Energy, Elsevier, vol. 86(C), pages 709-721.

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