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The use of artificial neural networks in experimental data acquisition and aerodynamic design

Author
Meade, Andrew J., Jr.
Published
Sep 1, 1991.
Physical Description
1 electronic document
Online Version

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Unclassified, Unlimited, Publicly available.
Free-to-read Unrestricted online access
Summary
It is proposed that an artificial neural network be used to construct an intelligent data acquisition system. The artificial neural networks (ANN) model has a potential for replacing traditional procedures as well as for use in computational fluid dynamics validation. Potential advantages of the ANN model are listed. As a proof of concept, the author modeled a NACA 0012 airfoil at specific conditions, using the neural network simulator NETS, developed by James Baffes of the NASA Johnson Space Center. The neural network predictions were compared to the actual data. It is concluded that artificial neural networks can provide an elegant and valuable class of mathematical tools for data analysis.
Other Subject(s)
Collection
NASA Technical Reports Server (NTRS) Collection.
Note
Document ID: 19920004630.
Accession ID: 92N13848.
Old Dominion Univ., NASA/American Society for Engineering Ed; Old Dominion Univ.,.
Terms of Use and Reproduction
No Copyright.
View MARC record | catkey: 15678022