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Rheological Behavior of SAE50 Oil-SnO2-CeO2 Hybrid Nanofluid: Experimental Investigation and Modeling Utilizing
Mojtaba Sepehrnia1,2, Mohammad Lotfalipour3, Mahdi Malekiyan3
1Department of Mechanical Engineering, Shahabdanesh University, Qom, Iran. m.sepehrnia@shdu.ac.ir.
This study investigates SAE50-SnO2-CeO2 hybrid nanofluid, revealing temperature and nanopowder volume fraction effects on viscosity. Higher temperatures reduce viscosity, while increased nanopowder concentration enhances it, showing pseudo-plastic behavior.
Area of Science:
- Materials Science
- Fluid Dynamics
- Nanotechnology
Background:
- Lubricant viscosity is critical for engine performance and efficiency.
- Developing advanced lubricants with tailored properties is essential for modern machinery.
- Hybrid nanofluids offer potential for enhanced thermophysical properties.
Purpose of the Study:
- To experimentally investigate the impact of temperature and nanopowder volume fraction (NPSVF) on the viscosity and rheological behavior of SAE50-SnO2-CeO2 hybrid nanofluid.
- To analyze the non-Newtonian characteristics of the nanofluid.
- To evaluate predictive models for dynamic viscosity.
Main Methods:
- Preparation of SAE50-SnO2-CeO2 hybrid nanofluids using a two-step method with NPSVFs from 0.25% to 1.5%.
- Experimental measurements of viscosity and shear stress at temperatures ranging from 25 to 67°C and shear rates from 1333 to 2932.6 s⁻¹.
- Application of Response Surface Method, curve fitting, ANFIS, and Gaussian Process Regression (GPR) for viscosity prediction.
Main Results:
- Shear stress increases with shear rate and decreases with temperature for both base fluid and nanofluid.
- A significant viscosity reduction of 89.36% was observed at 42°C with 1.5% NPSVF.
- Viscosity increased by 37.18% at 25°C with increasing NPSVF, exhibiting pseudo-plastic behavior across all conditions.
- Gaussian Process Regression (GPR) demonstrated superior performance in predicting dynamic viscosity compared to other models.
Conclusions:
- SAE50-SnO2-CeO2 hybrid nanofluid exhibits temperature-dependent viscosity and non-Newtonian pseudo-plastic behavior.
- Temperature significantly influences viscosity reduction, while NPSVF enhances viscosity.
- GPR is the most effective model for predicting the dynamic viscosity of this hybrid nanofluid.
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