Transitional intermittency detection by neural network


Autoria(s): Chattopadhyay, M; Dey, J; Mani, V
Data(s)

01/05/1999

Resumo

A neural network has been used to predict the flow intermittency from velocity signals in the transition zone in a boundary layer. Unlike many of the available intermittency detection methods requiring a proper threshold choice in order to distinguish between the turbulent and non-turbulent parts of a signal, a trained neural network does not involve any threshold decision. The intermittency prediction based on the neural network has been found to be very satisfactory.

Formato

application/pdf

Identificador

http://eprints.iisc.ernet.in/38903/1/Transitional_intermittency_detection.pdf

Chattopadhyay, M and Dey, J and Mani, V (1999) Transitional intermittency detection by neural network. In: Experiments in Fluids, 26 (6). pp. 549-552.

Publicador

Springer

Relação

http://www.springerlink.com/content/hec7nuk4g32y5axv/

http://eprints.iisc.ernet.in/38903/

Palavras-Chave #Aerospace Engineering (Formerly, Aeronautical Engineering)
Tipo

Journal Article

PeerReviewed