Performance Prediction of Open Rotor Enabled by Neural Network

Qihang Wang, Li Zhou, Zhanxue Wang

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

Abstract

In this paper, the prediction of the aerodynamic performance of a contra-rotating open rotor is accomplished based on the neural network. To complete the prediction from design parameters to aerodynamic performance, a neural network is established through a limited set of sample points. The results show that the neural network is able to accurately predict the aerodynamic performance of the contra-rotating open rotor. The constructed neural network depends on the selected design parameters and performance parameters. The number of hidden layers and the number of nodes in the hidden layers greatly affects the accuracy of the prediction.

Original languageEnglish
Title of host publication23rd International Conference on Control, Automation and Systems, ICCAS 2023
PublisherIEEE Computer Society
Pages1644-1649
Number of pages6
ISBN (Electronic)9788993215274
DOIs
StatePublished - 2023
Event23rd International Conference on Control, Automation and Systems, ICCAS 2023 - Yeosu, Korea, Republic of
Duration: 17 Oct 202320 Oct 2023

Publication series

NameInternational Conference on Control, Automation and Systems
ISSN (Print)1598-7833

Conference

Conference23rd International Conference on Control, Automation and Systems, ICCAS 2023
Country/TerritoryKorea, Republic of
CityYeosu
Period17/10/2320/10/23

Keywords

  • Aerodynamic performance prediction
  • Contra-rotating open rotor
  • Design method
  • Neural network
  • Numerical simulation

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