2020
DOI: 10.1177/0957650920957465
|View full text |Cite
|
Sign up to set email alerts
|

Multidisciplinary assessment of blade number and manufacturing parameters for the performance of centrifugal fans

Abstract: This work targets the development of the multidisciplinary design for centrifugal fans, based on the calculation of the fan performance following changes in the fan structure and manufacture. A parametric method that starts from the blade number and manufacturing parameters is first developed to control the shape of fan assembly and its fluid domain. The parametric code, and the aerodynamic and structure analysing codes are then integrated, from the solution of which algorithms are developed to calculate the f… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1

Citation Types

0
1
0

Year Published

2021
2021
2023
2023

Publication Types

Select...
2
1

Relationship

0
3

Authors

Journals

citations
Cited by 3 publications
(1 citation statement)
references
References 27 publications
0
1
0
Order By: Relevance
“…The traditional strategies are primarily generated by a Bezier curve. A neural network algorithm is favorable for acquiring fan performance and further cutting the cost of fan testing based on the parameterized structure information, including blade installation angle, fan performance and structural parameters, and specific functions [10][11][12]. David developed a multi-objective automatic optimization process to enhance fan performance for rotating machinery based on a genetic algorithm, but it was limited for the blade profiles [13].…”
Section: Introductionmentioning
confidence: 99%
“…The traditional strategies are primarily generated by a Bezier curve. A neural network algorithm is favorable for acquiring fan performance and further cutting the cost of fan testing based on the parameterized structure information, including blade installation angle, fan performance and structural parameters, and specific functions [10][11][12]. David developed a multi-objective automatic optimization process to enhance fan performance for rotating machinery based on a genetic algorithm, but it was limited for the blade profiles [13].…”
Section: Introductionmentioning
confidence: 99%