Alumina–di water-based nanofluid process parameter optimization for stability

• Published in: Journal of the Brazilian Society of Mechanical Sciences and Engineering Vol. 44; no. 6
• Main Authors: Pawar, Jagdish B., Tungikar, Vinod B.
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.06.2022; Springer Nature B.V
• Subjects: Aluminum oxide; Crystallites; Engineering; Mechanical Engineering; Nanofluids; Nanoparticles; Optimization; Parameter identification; Process parameters; Sedimentation; Sedimentation & deposition; Signal to noise ratio; Stability analysis; Statistical methods; Stirring; Surfactants; Technical Paper; Variance analysis; Sonication; Nanofluid; ANOVA; Sedimentation; Taguchi array design
• ISSN: 1678-5878; 1806-3691
• DOI: 10.1007/s40430-022-03541-8

This paper presents an optimization of the alumina–di water-based nanofluid process parameters for enhancing its stability. The process parameters considered for enhancing the stability of nanofluid are nanoparticle concentration in a base fluid, nanoparticle size, surfactant concentration, stirring time, and sonication time. The Taguchi methodology is used to identify and prepare the eighteen samples of nanofluid with various parameter settings, utilizing a two-step method of nanofluid preparation. The sedimentation photograph technique is used to investigate the nanofluid’s stability behaviour by taking pictures at equal intervals of time. Due to gravity, sedimentation will be formed at the bottom of the liquid column, which is the basis for this approach. The time taken to develop sedimentation is a measure of the stability of the nanofluid. A longer time indicates better stability. X-ray diffraction (XRD) was used to study the structure and crystallite size of alumina nanoparticles. The morphology and size of alumina nanoparticles are studied using scanning electron microscopy (SEM). The main effect plot and the signal-to-noise ratio (S/N ratio) are used to examine the effect of each parameter on stability. The statistical contribution percentage of each parameter on stability is determined using an analysis of variance (ANOVA). The signal-to-noise (S/N) ratio demonstrated that the nanoparticle concentration in a base fluid is the most affecting parameter with a delta value of 2.46. Also, the nanoparticle’s size, surfactant concentration, and sonication time play significant roles on nanofluid stability with delta values of 0.93, 0.79, and 0.52, respectively. The results of ANOVA show that the nanofluid concentration in base fluid imparts the most significant influence on nanofluid stability with a contribution of 67.66%, followed by nanoparticle size with a contribution of 15.99% and surfactant concentration with a contribution of 9.11%, and sonication time has 4.78% on nanofluid stability, while initial stirring time has not been statistically significant as its p -value exceeded 0.5. Finally, a confirmation test is performed with optimal parameter values to ensure that the stability of the nanofluid is improved as the time required for the sedimentation of nanoparticles is increased.