IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v337y2025ics0360544225042987.html

Study on enhanced heat transfer mechanism for crossflow-counterflow combined mechanical draft cooling tower

Author

Listed:
  • Chen, Hongming
  • Wang, Youhao
  • Yuan, Xiaojing
  • He, Suoying
  • Gao, Ming

Abstract

This paper proposes a crossflow-counterflow combined mechanical draft cooling tower structure, aiming to reconstruct the flow field within the tower and enhance air-water heat transfer. Through numerical simulation, the study deeply investigates the influence mechanisms of five key parameters (middle zone water-spraying density q2, outer zone water-spraying density q3, middle zone water-spraying width L, crossflow filling height H, and crossflow filling width D) on the aerodynamic field and air-water temperature field within the tower, identifying an optimal parameter combination within the study scope. The results showed these parameters significantly affected the aerodynamic field distribution by regulating the balance between ventilation resistance and water-spraying density, thereby optimizing airflow organization. Concurrently, adjustments in the flow field led to adjustments in ventilation rate, which combined with the water-spraying density to reconfigure the air-water temperature field and in turn influenced heat and mass transfer efficiency. Orthogonal analysis obtained the optimized parameter combination: D = 2 m, H = 1 m, L = 1.5 m, q2 = 3 kg/(m2·s), q3 = 3 kg/(m2·s). Under this configuration, the circulating water temperature drop reached 12.12 °C, showing a 3.5 % improvement compared to the original counterflow mechanical draft cooling tower, significantly enhancing the thermal performance of the cooling tower. This research provides crucial theoretical foundations and engineering application references for optimizing cooling tower designs.

Suggested Citation

  • Chen, Hongming & Wang, Youhao & Yuan, Xiaojing & He, Suoying & Gao, Ming, 2025. "Study on enhanced heat transfer mechanism for crossflow-counterflow combined mechanical draft cooling tower," Energy, Elsevier, vol. 337(C).
    • Handle: RePEc:eee:energy:v:337:y:2025:i:c:s0360544225042987
    DOI: 10.1016/j.energy.2025.138656
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544225042987
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2025.138656?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to

    for a different version of it.

    References listed on IDEAS

    as
    1. Yu, J.H. & Qu, Z.G. & Zhang, J.F. & Hu, S.J. & Guan, J., 2022. "Comprehensive coupling model of counter-flow wet cooling tower and its thermal performance analysis," Energy, Elsevier, vol. 238(PB).
    2. Wang, Youhao & Yang, Jichong & Xu, Qinghua & Zhang, Qiang & He, Suoying & Gao, Ming, 2023. "Numerical simulation on the enhancement of heat transfer performance by deflector plates for the mechanical draft cooling towers," Energy, Elsevier, vol. 283(C).
    3. Wu, Zhiyong & Lu, Zhibin & Zhang, Bingjian & He, Chang & Chen, Qinglin & Yu, Haoshui & Ren, Jingzheng, 2022. "Stochastic bi-objective optimization for closed wet cooling tower systems based on a simplified analytical model," Energy, Elsevier, vol. 250(C).
    4. Weipeng Deng & Fengzhong Sun, 2021. "Comparative Study on the Cooling Characteristics of Different Fill Layout Patterns on a Single Air Inlet Induced Draft Cooling Tower," Energies, MDPI, vol. 14(19), pages 1-17, October.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Xu, Guiying & Dai, Fengxia & Wang, Cong & Li, Mingsong & Li, Jiyuan & Liu, Xueyang, 2025. "Fabrication, machine learning modeling, and operational sensitivity analysis of a Maisotsenko cycle-based water-cooling tower," Energy, Elsevier, vol. 331(C).
    2. Zhang, Zhengqing & Cui, Yingwei & Wang, Youhao & Gao, Ming, 2025. "A novel performance improvement technology of wet cooling towers with the dry-wet hybrid rain zone by auxiliary fans," Energy, Elsevier, vol. 340(C).
    3. Liu, Hua & Wu, Zhiyong & Zhang, Bingjian & Chen, Qinglin & Pan, Ming & Ren, Jingzheng & He, Chang, 2023. "A large-scale stochastic simulation-based thermodynamic optimization for the hybrid closed circuit cooling tower system with parallel computing," Energy, Elsevier, vol. 283(C).
    4. Yao, Shunyu & Zhang, Wenjie & Xu, Lei & Du, Xiaoze & Wei, Huimin, 2024. "Theoretical modeling and investigation of the influence of deaerator on the transient process in power plants," Applied Energy, Elsevier, vol. 376(PB).
    5. Duan, Zhiyin & Huang, Ke & Xian, Genqiang & Shan, Keqin & Zhao, Xudong, 2025. "Numerical and experimental study of a high permeable MOF/PVDF flat-sheet membrane module for enhanced evaporative cooling," Energy, Elsevier, vol. 340(C).
    6. Pirouz, Behzad & Guerriero, Francesca, 2026. "Multi-objective stochastic optimization problem: a systematic literature review," Applied Energy, Elsevier, vol. 405(C).
    7. Wang, Youhao & Yang, Jichong & Xu, Qinghua & Zhang, Qiang & He, Suoying & Gao, Ming, 2023. "Numerical simulation on the enhancement of heat transfer performance by deflector plates for the mechanical draft cooling towers," Energy, Elsevier, vol. 283(C).
    8. Wu, Zhiyong & Lu, Zhibin & Zhang, Bingjian & He, Chang & Chen, Qinglin & Yu, Haoshui & Ren, Jingzheng, 2022. "Stochastic bi-objective optimization for closed wet cooling tower systems based on a simplified analytical model," Energy, Elsevier, vol. 250(C).

    More about this item

    Keywords

    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:energy:v:337:y:2025:i:c:s0360544225042987. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/energy .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.