Optimization Design of Centrifugal Fan Blades Based on Bézier Curve Method

In order to improve the aerodynamic performance of the voluteless centrifugal fan, a multi-objective optimization design system was established by combining parametric modeling, experimental design, surrogate models, and optimization algorithms, with the static pressure and static pressure efficienc...

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Bibliographic Details
Main Authors: Jiaju Wang, Kunfeng Liang, Tao He, Haijiang He, Dayuan Zheng, Min Li, Dewu Gong, Lihua Jiang
Format: Article
Language:English
Published: MDPI AG 2025-05-01
Series:Applied Sciences
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Online Access:https://www.mdpi.com/2076-3417/15/9/5052
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Summary:In order to improve the aerodynamic performance of the voluteless centrifugal fan, a multi-objective optimization design system was established by combining parametric modeling, experimental design, surrogate models, and optimization algorithms, with the static pressure and static pressure efficiency of the fan as the optimization objectives. The design parameters of the blade profile were obtained by fitting the blade profile with a Bézier curve. A mapping relationship between design parameters and optimization objectives was established by combining numerical simulation with a radial basis function neural network, and a genetic algorithm was used to optimize the blade profile. The results indicated a highly significant correlation between design parameters and optimization objectives, with a prediction error of no more than 1% for the surrogate model. The determination coefficients for static pressure and static pressure efficiency were 0.98 and 0.96, respectively. After optimization, the static pressure of the fan increased by 12.7 Pa at the design operating point, and the static pressure efficiency increased by 3.2%. The separation vortex decreased near the trailing edge of the blade suction surface, and the airflow impact at the leading edge of the blade decreased. The entropy production in the flow channel decreased, and the overall flow state of the fluid was improved.
ISSN:2076-3417