Transitional intermittency detection by neural network

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

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Abstract

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.

Item Type:	Journal Article
Publication:	Experiments in Fluids
Publisher:	Springer
Additional Information:	Copyright of this article belongs to Springer.
Department/Centre:	Division of Mechanical Sciences > Aerospace Engineering(Formerly Aeronautical Engineering)
Date Deposited:	03 Aug 2011 07:18
Last Modified:	03 Aug 2011 07:18
URI:	http://eprints.iisc.ac.in/id/eprint/38903

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