IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v352y2026ics0360544226010534.html

Optimized split-flow deflector design for airflow drying systems using BP neural network coupled with NSGA-II algorithm

Author

Listed:
  • Wu, Xuehong
  • Yu, Dehua
  • Zhu, Yanyan
  • Xiao, Yiming
  • Liu, Yong
  • Mao, Shang
  • Du, Yanping

Abstract

The non-uniform distribution of hot airflow and the high intensity of turbulence critically affect the effectiveness of airflow drying systems. In this study, numerical simulations were conducted to analyze the internal flow field characteristics of an airflow dryer. A novel split-flow deflector plate structure was designed and optimized using Response Surface Methodology (RSM) integrated with a backpropagation (BP) neural network and the NSGA-II algorithm. The results indicated that the designed split-flow deflector structure demonstrated superior performance compared with conventional arc-shaped designs. The optimized performance was achieved with a rotation speed of 190 r/min, deflector plate angle of 92°, and split-flow plate length of 380 mm. Compared to both the arc-shaped and pre-optimized configurations, the optimized split-flow deflector increased average airflow velocity by 4% and 39.2% and improved the airflow uniformity index by 11.8% and 14.5%, respectively. Furthermore, transient thermal analysis confirmed enhanced thermal stability as the outlet temperature rapidly converged to the experimental benchmark (160 °C), effectively mitigating thermal oscillations and intensifying gas-solid heat exchange. The findings provide both theoretical insight into the dynamic control of particle flows in dryers and a practical basis for the structural optimization of industrial airflow drying equipment.

Suggested Citation

  • Wu, Xuehong & Yu, Dehua & Zhu, Yanyan & Xiao, Yiming & Liu, Yong & Mao, Shang & Du, Yanping, 2026. "Optimized split-flow deflector design for airflow drying systems using BP neural network coupled with NSGA-II algorithm," Energy, Elsevier, vol. 352(C).
    • Handle: RePEc:eee:energy:v:352:y:2026:i:c:s0360544226010534
    DOI: 10.1016/j.energy.2026.140948
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544226010534
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2026.140948?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.

    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:352:y:2026:i:c:s0360544226010534. 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.

    We have no bibliographic references for this item. You can help adding them by using 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.