Experimental Turbulent Field Modeling by Visualization and Neural Networks

Abstract

Turbulent flow field was modeled based on experimental flow visualization and radial-basis neural networks. Turbulent fluctuations were modeled based on the recorded concentration at various locations in the Karman vortex street, which were used as inputs and outputs of the neural network. From the measured and the modeled concentration the power spectra and spatial correlation functions were calculated. The measured and the modeled concentration power spectra correspond well to the −5/3 turbulence decay law, and exhibit the basic spectral peak of fluctuation power at the same frequency. The predicted and measured correlation functions of concentration exhibit similar behavior.