A new model for viscosity prediction for silica-alumina-MWCNT/Water hybrid nanofluid using nonlinear curve fitting

Abstract

One of the most crucial concerns is improving industrial equipment's ability to transmit heat at a faster rate, hence minimizing energy loss. Viscosity is one of the key elements determining heat transmission in fluids. Therefore, it is crucial to research the viscosity of nanofluids (NF). In this study, the effect of temperature (T) and the volume fraction of nanoparticles (φ) on the viscosity of the silica-alumina-MWCNT/Water hybrid nanofluid (HNF) is examined. In this study, a nonlinear curve fitting is accurately fitted using MATLAB software and is used to identify the main effect, extracting the residuals and viscosity deviation of these two input variables, i.e., temperature (T = 20 to 60 °C) and volume fraction of nanoparticles (φ = 0.1 to 0.5 %). The findings demonstrate that the viscosity of silica-alumina-MWCNT/ Water hybrid nanofluid increases as the φ increases. In terms of numbers, the μnf rises from 1.55 to 3.26 cP when the φ grows from 0.1 to 0.5 % (at T = 40 °C). On the other hand, the μnf decreases as the temperature was increases. The μnf of silica-alumina-MWCNT/ Water hybrid nanofluid reduces from 3.3 to 1.73 cP when the temperature rises from 20 to 60 °C (at φ = 0.3 %). The findings demonstrate that the μnf exhibits greater variance for lower temperatures and higher φ.

Keywords

• Curve-fitting model
• Rheological Behavior
• Silica-alumina-MWCNT/Water hybrid nanofluid
• Viscosity