(65d) Studies on Momentum Transfer with CO Axially Placed Entry Region Coil- DISC Assembly As Turbulence Promoter in TUBE FLOW By Using Artificial Neural Networks

Studies On Momentum Transfer With Co Axially Placed Entry Region Coil- Disc Assembly As Turbulence Promoter In Tube Flow By Using Artificial Neural Networks have been presented in this paper. An experimental work was carried out to examine the effects of pitch of the coil, length of the coil, diameter of the coil, diameter of the disc and Height of the disc on momentum transfer enhancement. The experimental data sets were extracted and were tested within a geometrical range pitch of the coil 0.015 < P_c < 0.035 m/turn; length of the coil 0.035 < L_c < 0.125 m, Coil diameter 0.02 < D_c < 0.04m, disc diameter 0.02 < D_d < 0.04m, Disc Height 0 < H_d < 0.15m and Reynolds numbers are varied from 1200 to 14,500. The experimental data sets have been used in training and validation of ANNs in order to predict the momentum transfer coefficient with entry region coil as insert promoter. The 126 experimental data sets have been used in training and 38 data sets for the validation of the Artificial Neural Networks by using MATLAB 7.7.0, particularly tool boxes. The training of neural network is used to minimize the error function with a learning rule. The generally used learning rule is gradient-based such as the popular back propagation algorithm. The results of this study reported that ANN configuration of 4_4_1 is recommended for the momentum transfer training for faster convergence and accuracy.