, Volume 26, Issue 6, pp 549-552

Transitional intermittency detection by neural network

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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.

Received: 15 December 1997/Accepted: 30 December 1998