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.
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Received: 15 December 1997/Accepted: 30 December 1998
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Chattopadhyay, M., Dey, J. & Mani, V. Transitional intermittency detection by neural network. Experiments in Fluids 26, 549–552 (1999). https://doi.org/10.1007/s003480050322
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DOI: https://doi.org/10.1007/s003480050322