Data for Rheological behaviour of high concentration MWCNT/Water Nanofluids

In this work, 0.3, 0.5, 1 and 1.5 wt.% concentration samples of MWCNT/water nanofluids have been prepared. SDS Surfactant was used to stabilize the MWCNT particles. Rheological behaviour of MWCNT/water nanofluids have been examined at different temperatures under the controlled shear stress of 0-35 Pa. Higher viscosity results were found for higher concentration nanofluids. For all nanofluids, decrease in viscosity was observed with the increasing temperature. Non-Newtonian nature of prepared nanofluid samples was observed, to analyse this rheological characteristic of MWCNT/water nanofluid, Power law model based curve fitting was employed, which was found as the best fitted model on experimental results. From this curve fitting variation in MWCNT/water flow behaviour from Newtonian to non-Newtonian was observed over the different concentration and temperature. SDS was also responsible for this unlike rheological behaviour of MWCNT/water nanofluid at different concentration. An optimal Artificial Neural Network (ANN) was also designed to predict the dynamic viscosity of MWCNT/water nanofluid. The model accounts for the effect of particle %weight concentration, temperature, shear time and shear stress. The model was trained on a dataset of present experimental work and shows very accurate results in predicting the viscosity (for the testing data, obtained R2 and RMSE are 0.9993 and 0.0035). The model compliments the experimental results very well.