Inverse design of supercritical wing based on enhanced RBF neural network

Tihao Yang, Junqiang Bai, Dan Wang

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

A novel inverse design method is established based on enhanced RBF neural network and improved differential evolution algorithm. This method combines some advantages of inverse design and optimization. The inverse design problems are transformed into optimization problems to some extent and the dependence on reasonable target pressure distribution is reduced. With enhanced RBF neural network, the calculation efficiency is improved. The application in supercritical wing design shows that this method is reasonable and can be used to research the effect of pressure distribution. The improvement of the drag divergence characteristic is owing to the change of shock location.

Original languageEnglish
Title of host publicationProceedings - 2015 5th International Conference on Communication Systems and Network Technologies, CSNT 2015
EditorsGeetam Singh Tomar
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1172-1176
Number of pages5
ISBN (Electronic)9781479917976
DOIs
StatePublished - 28 Sep 2015
Event5th International Conference on Communication Systems and Network Technologies, CSNT 2015 - Gwalior, India
Duration: 4 Apr 20156 Apr 2015

Publication series

NameProceedings - 2015 5th International Conference on Communication Systems and Network Technologies, CSNT 2015

Conference

Conference5th International Conference on Communication Systems and Network Technologies, CSNT 2015
Country/TerritoryIndia
CityGwalior
Period4/04/156/04/15

Keywords

  • Aerodynamic drag
  • Differential evolution algorithm
  • Inverse design
  • RBF neural network

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