Experiments are carried out behind a square cylinder mounted in the freestream of a wind tunnel, and hot-wire anemometry is used to determine the profiles of the mean and statistical turbulence quantities. Artificial neural networks and fuzzy-logic models successfully predict the statistical quantities like mean velocity profiles and Reynolds stresses. The fuzzy-logic modeling is more convenient to use, is less computationally intensive, and gives a higher correlation coefficient in comparison to the neural network.
Prediction of Turbulence Statistics Behind a Square Cylinder Using Neural Networks and Fuzzy Logic
Contributed by the Fluids Engineering Division for publication in the JOURNAL OF FLUIDS ENGINEERING. Manuscript received by the Fluids Engineering Division March 19, 2002; revised manuscript received August 28, 2002. Associate Editor: G. Karniadakis.
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Panigrahi, P. K., Dwivedi , M., Khandelwal , V., and Sen , M. (March 27, 2003). "Prediction of Turbulence Statistics Behind a Square Cylinder Using Neural Networks and Fuzzy Logic ." ASME. J. Fluids Eng. March 2003; 125(2): 385–387. https://doi.org/10.1115/1.1537251
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