THERMAL SCIENCE

International Scientific Journal

Thermal Science - Online First

Lele Zhang

,

Liang Hu

,

Jing Hu

,

Jianmin Zhao

,

Yangui Chen

,

Jieqing Zheng

online first only

Experimental and modelling study on optimization of glass fiber filter diversion structure

ABSTRACT
This study conducts an experimental and modeling investigation on the optimization of the glass fiber filter diversion structure. Addressing the critical issue in air filtration systems of enhancing the service life and performance of filter devices, this research rationally designs and optimizes the structural parameters of the diversion structure. Numerical simulation of the filter device was established through airflow organization experiments of glass fiber filters to explore the impact of various guide vane structure parameters on the system's air distribution uniformity and service life. Furthermore, machine learning was employed to optimize the guide structure of the filtration device based on the results of numerical simulations. The study demonstrates a good agreement between numerical simulation results and experimental outcomes, with an error of less than 10%. The optimal length and angle of the guide plate predicted by machine learning are 163.2 mm and 38.5°, respectively. This research not only injects new momentum into the continuous advancement of air filtration technology but also shows significant potential in energy efficiency and cost control.
KEYWORDS
Air Filtration Systems, Diversion Structure, numerical simulation, machine learning
PAPER SUBMITTED: 2024-11-18
PAPER REVISED: 2025-01-18
PAPER ACCEPTED: 2025-01-19
PUBLISHED ONLINE: 2025-02-16
DOI REFERENCE: https://doi.org/10.2298/TSCI241118024Z
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Experimental and modelling study on optimization of glass fiber filter diversion structure