Prediction of stability parameters of ferric oxide nanofluids using response surface methodology based on desirability approach

Abstract

Nanofluids are well known for their enhanced thermal properties. In spite of their excellent properties, there are certain hindrances to their applications on large scale. The issue of nanoparticle agglomeration in the base fluid with the consequent stability related issues is one of the main obstacles to the usage of nanofluids. Stability is crucial because the longer the nanofluids remain stable, the better their capacity to retain their thermal properties. Hence there is a need to evolve long-term stable nanofluids. Since there are a lot of factors, which are affecting the stability of the nanofluids, there is a need to optimize the process parameters. In this regard, central composite rotatable design (CCRD) was applied in this study to optimize the independent parameters of stability of ferric oxide nanofluids. For this, the performance of nanofluids was assessed by measuring the nephelometric turbidity units (NTU), based on the independent variables such as percentage of intensity of the nanoparticle, pH of the base fluid, and percentage volume concentration of the surfactant. All the parameters that are affecting individually and mutually were validated statistically using analysis of variance (ANOVA). A regression equation to evaluate the NTU was developed. The obtained results showed that the values predicted by the model and that obtained from the experiments were in good agreement with each other. It is observed that more than 99.65% of the variation could be predicted by the model developed for NTU. The response surface methodology (RSM) has revealed that the ideal process parameters for greater stability of nanofluids are 0.01% particle volume intensity, pH 3.2, and 0.6% surfactant intensity.