Provided by: Creative Commons
Estimation of behavior of non-Newtonian fluids is a complex phenomenon & conventional models have deviated & shown non consistency. Present paper has addressed to the problem of pressure drop estimation for flow of CMC-water solution having different concentrations in a pipeline. Experimental runs are conducted & the data generated is divided into two parts; one for developing the model & another for testing. Two artificial neural network models S1 & C1 are developed having RMSE values for training data set of 0.021 & 0.013 respectively. The corresponding values for test data set are 0.035 & 0.08.