Aerodynamic Shape Optimization and Knowledge Data Mining of a Centrifugal Fan

• SUGIMURA Kazuyuki

  (株)日立製作所　機械研究所　高度設計シミュレーションセンタ

Bibliographic Information

Other Title

• 遠心送風機の空力形状最適設計と知識マイニング
• エンシン ソウフウキ ノ クウリキ ケイジョウ サイテキ セッケイ ト チシキ マイニング

Abstract

An aerodynamic optimization system for centrifugal fans consisting of an impeller and a diffuser has been developed. A fan's three-dimensional shape is represented by a non-uniform rational B-spline curve, which enhances the freedom of the blades' leading and trailing edge profiles. The fan's aerodynamic performance is predicted using commercial software, "STAR-CD." The optimization system uses a new algorithm that is a hybrid of a simulated annealing algorithm and a neural network. The hybrid algorithm not only can learn the design-space to predict better solutions, but also can analyze the space's statistical characteristics, such as its sensitivity and non-linearity. Applying this system to centrifugal fan design problems, we obtained novel fan shapes in which the leading edge of the impellers and the trailing edge of the diffusers were bent unconventionally. Important design parameters were simultaneously revealed using design-space analysis.

Journal

• Turbomachinery

  Turbomachinery 34 (6), 357-365, 2006

  Turbomachinery Society of Japan

Keywords

• Design
• Optimization
• Simulated Annealing
• Neural Network
• Data Mining

Details

• CRID: 1390282679521104384
• NII Article ID: 10017570477
• NII Book ID: AN00004836
• DOI: 10.11458/tsj.34.357
• ISSN: 18802338
• ISSN: 03858839
• NDL BIB ID: 7973596
• Web Site: https://ndlsearch.ndl.go.jp/books/R000000004-I7973596
• Text Lang: ja
• Data Source:
  • JaLC
  • NDL
  • CiNii Articles
  • Crossref
• Abstract License Flag: Disallowed