Performance Optimization Design of Diagonal Flow Fan Based on Ensemble of Surrogates Model

Due to the advantages of a high total pressure coefficient, large flow coefficient, and high efficiency, the diagonal flow fan is widely used in people’s livelihood and industrial fields. However, the design of the diagonal flow fan is mostly empirical, multi-solution, and comprehensive. The traditi...

Full description

Bibliographic Details
Main Authors: Shuiqing Zhou, Laifa Lu, Biao Xu, Jiacheng He, Ding Xia
Format: Article
Language:English
Published: MDPI AG 2022-09-01
Series:Applied Sciences
Subjects:
Online Access:https://www.mdpi.com/2076-3417/12/19/9732
_version_ 1797480706982543360
author Shuiqing Zhou
Laifa Lu
Biao Xu
Jiacheng He
Ding Xia
author_facet Shuiqing Zhou
Laifa Lu
Biao Xu
Jiacheng He
Ding Xia
author_sort Shuiqing Zhou
collection DOAJ
description Due to the advantages of a high total pressure coefficient, large flow coefficient, and high efficiency, the diagonal flow fan is widely used in people’s livelihood and industrial fields. However, the design of the diagonal flow fan is mostly empirical, multi-solution, and comprehensive. The traditional optimization design process often consumes huge computing resources. In this paper, the diagonal flow fan blade is parameterized, the design variables are determined, and the accuracy of the parameterization method is verified. The maximum fitting error is controlled at approximately 0.1%. Based on the parametric design of blades, this paper organically integrates the traditional Kriging model and RBF model, and introduces the Ensemble of surrogates model (ES) to verify that the ES model has higher prediction accuracy in the prediction of fan flow and total pressure efficiency than the traditional prediction model. Subsequently, the Pareto optimal solution set of the approximate model within the global design scope is searched by NSGA-II. The numerical simulation and experimental verification show that the actual flow of the fan increases by 10% and the efficiency of the full pressure increases by 3.2% under the design condition of the optimized blade. The optimized model can significantly improve its air performance.
first_indexed 2024-03-09T22:03:57Z
format Article
id doaj.art-d249d97743bf48eaa66e4c22e926c9dc
institution Directory Open Access Journal
issn 2076-3417
language English
last_indexed 2024-03-09T22:03:57Z
publishDate 2022-09-01
publisher MDPI AG
record_format Article
series Applied Sciences
spelling doaj.art-d249d97743bf48eaa66e4c22e926c9dc2023-11-23T19:44:44ZengMDPI AGApplied Sciences2076-34172022-09-011219973210.3390/app12199732Performance Optimization Design of Diagonal Flow Fan Based on Ensemble of Surrogates ModelShuiqing Zhou0Laifa Lu1Biao Xu2Jiacheng He3Ding Xia4College of Mechanical Engineering, Zhejiang University of Technology, Hangzhou 310023, ChinaCollege of Mechanical Engineering, Zhejiang University of Technology, Hangzhou 310023, ChinaCollege of Mechanical Engineering, Zhejiang University of Technology, Hangzhou 310023, ChinaCollege of Mechanical Engineering, Zhejiang University of Technology, Hangzhou 310023, ChinaCollege of Mechanical Engineering, Zhejiang University of Technology, Hangzhou 310023, ChinaDue to the advantages of a high total pressure coefficient, large flow coefficient, and high efficiency, the diagonal flow fan is widely used in people’s livelihood and industrial fields. However, the design of the diagonal flow fan is mostly empirical, multi-solution, and comprehensive. The traditional optimization design process often consumes huge computing resources. In this paper, the diagonal flow fan blade is parameterized, the design variables are determined, and the accuracy of the parameterization method is verified. The maximum fitting error is controlled at approximately 0.1%. Based on the parametric design of blades, this paper organically integrates the traditional Kriging model and RBF model, and introduces the Ensemble of surrogates model (ES) to verify that the ES model has higher prediction accuracy in the prediction of fan flow and total pressure efficiency than the traditional prediction model. Subsequently, the Pareto optimal solution set of the approximate model within the global design scope is searched by NSGA-II. The numerical simulation and experimental verification show that the actual flow of the fan increases by 10% and the efficiency of the full pressure increases by 3.2% under the design condition of the optimized blade. The optimized model can significantly improve its air performance.https://www.mdpi.com/2076-3417/12/19/9732diagonal flow fanparametric designensemble of surrogates modelexperimental verification
spellingShingle Shuiqing Zhou
Laifa Lu
Biao Xu
Jiacheng He
Ding Xia
Performance Optimization Design of Diagonal Flow Fan Based on Ensemble of Surrogates Model
Applied Sciences
diagonal flow fan
parametric design
ensemble of surrogates model
experimental verification
title Performance Optimization Design of Diagonal Flow Fan Based on Ensemble of Surrogates Model
title_full Performance Optimization Design of Diagonal Flow Fan Based on Ensemble of Surrogates Model
title_fullStr Performance Optimization Design of Diagonal Flow Fan Based on Ensemble of Surrogates Model
title_full_unstemmed Performance Optimization Design of Diagonal Flow Fan Based on Ensemble of Surrogates Model
title_short Performance Optimization Design of Diagonal Flow Fan Based on Ensemble of Surrogates Model
title_sort performance optimization design of diagonal flow fan based on ensemble of surrogates model
topic diagonal flow fan
parametric design
ensemble of surrogates model
experimental verification
url https://www.mdpi.com/2076-3417/12/19/9732
work_keys_str_mv AT shuiqingzhou performanceoptimizationdesignofdiagonalflowfanbasedonensembleofsurrogatesmodel
AT laifalu performanceoptimizationdesignofdiagonalflowfanbasedonensembleofsurrogatesmodel
AT biaoxu performanceoptimizationdesignofdiagonalflowfanbasedonensembleofsurrogatesmodel
AT jiachenghe performanceoptimizationdesignofdiagonalflowfanbasedonensembleofsurrogatesmodel
AT dingxia performanceoptimizationdesignofdiagonalflowfanbasedonensembleofsurrogatesmodel