LAPSE:2023.36296
Published Article
LAPSE:2023.36296
An Investigation on Optimized Performance of Voluteless Centrifugal Fans by a Class and Shape Transformation Function
Meijun Zhu, Zhehong Li, Guohui Li, Xinxue Ye, Yang Liu, Ziyun Chen, Ning Li
July 7, 2023
Class and shape transformation functions are proposed to carry out the parametric design of the blade profiles because fan efficiency is closely related to the shape of blade profiles. An optimization with the objectives of fan efficiency and static pressure based on the Kriging models was established, and numerical simulation data were applied to construct the Kriging models. The dissipation function was used to analyze the fan energy loss. The prediction results show that the maximum accuracy error between the Kriging model and the experimental data is approximately 0.81%. Compared with the prototype fan, the optimized fan was able to ameliorate the distribution of the flow field pressure and velocity; the outlet static pressure increased by 9.03%, and the efficiency increased by 2.35%. The dissipation function is advantageous because it can intuitively indicate the location and amount of energy loss in the fan, while effectively obtaining the total energy loss as well. The situation of energy loss was mutually validated with the density of the static pressure contours and the streamline distribution. The flow fields at the leading edge of the optimized fans were improved by analysis of the dissipation function, and the leading edges of the three impellers selected from the Pareto front were narrower and flatter than those of the prototype fan.
Keywords
centrifugal fan, class-shape-transformation function, dissipation function, Kriging model, Optimization
Suggested Citation
Zhu M, Li Z, Li G, Ye X, Liu Y, Chen Z, Li N. An Investigation on Optimized Performance of Voluteless Centrifugal Fans by a Class and Shape Transformation Function. (2023). LAPSE:2023.36296
Author Affiliations
Zhu M: School of Intelligent Manufacturing, Taizhou University, Taizhou 318000, China
Li Z: School of Intelligent Manufacturing, Taizhou University, Taizhou 318000, China [ORCID]
Li G: School of Electronic and Information Engineering, Dalian Jiaotong University, Dalian 116028, China
Ye X: Zhejiang Yilida Ventilator Co., Ltd., Taizhou 318056, China
Liu Y: School of Intelligent Manufacturing, Taizhou University, Taizhou 318000, China
Chen Z: School of Intelligent Manufacturing, Taizhou University, Taizhou 318000, China
Li N: School of Intelligent Manufacturing, Taizhou University, Taizhou 318000, China
Journal Name
Processes
Volume
11
Issue
6
First Page
1751
Year
2023
Publication Date
2023-06-08
Published Version
ISSN
2227-9717
Version Comments
Original Submission
Other Meta
PII: pr11061751, Publication Type: Journal Article
Record Map
Published Article

LAPSE:2023.36296
This Record
External Link

doi:10.3390/pr11061751
Publisher Version
Download
Files
[Download 1v1.pdf] (17.3 MB)
Jul 7, 2023
Main Article
License
CC BY 4.0
Meta
Record Statistics
Record Views
111
Version History
[v1] (Original Submission)
Jul 7, 2023
 
Verified by curator on
Jul 7, 2023
This Version Number
v1
Citations
Most Recent
This Version
URL Here
https://psecommunity.org/LAPSE:2023.36296
 
Original Submitter
Calvin Tsay
Links to Related Works
Directly Related to This Work
Publisher Version