An Experimental Investigation on Boundary Layer Flow by Using Hot-Wire Anemometer and Neural Network

In this research، turbulence parameters such as turbulence intensity، Kolmogorov length scale، dissipation rate and velocity profiles at a cross section of flow over a flat plate are analyzed by using hot wire anemometer. Furthermore، the behaviors of parameters at unknown heights of plate are predicted by utility of advanced neural networks. One can find that there is well agreement between results of neural network at unidentified points and experimental data that guaranties the use of neural network to determine turbulent parameters at each point that there are not any experimental data for them. In addition to، frequency analysis and the effect of number of samples on the turbulence parameters are considered. The results show that the turbulence intensity، Kolmogorov length scale and Kurtosis are decreased with increase the height where dissipation rate and mean velocity are increased. Furthermore، the amplitude of FFT is increased near the plate.