Performance Evaluation of Nanofluids for Enhanced Heat Transfer in Microchannels: Experimental Validation and CFD Simulation

Abstract

Maintaining system reliability and efficiency in high-performance thermal environments depends on good thermal regulation in microchannel systems. Because of their modifiable thermophysical properties, nanofluids are more effective at heat transfer than many other fluids. In this work, three datasets were used, one of which was a Casson nanofluid dataset (61 rows × 118 columns) to explore non-Newtonian behavior. Using classical models and experimental observations, thermal conductivity, dynamic viscosity, density and specific heat were calculated for volume fractions from 0.1% to 5.0%. The tests found that nanofluids with CuO had the highest thermal conductivity (2.06 W/m·K at 4.75% volume fraction), while nanofluids with SiO₂ maintained the lowest viscosity (0.00056 Pa·s), making them suitable for low-resistance systems. Al₂O₃ provided a suitable balance, boosting the effect and keeping the viscosity workable. Using CFD-ready parameters, a dataset was built with the main fields: flow velocity (0.17–2.28 m/s), temperature (50–90°C) and calculated properties (e.g., ρ_nf ≈ 1000–2000 kg/m³). The data is designed so that it can be used with parametric analysis software such as ANSYS or OpenFOAM. The method avoids repeating the same experiments, allowing for easy and consistent heat transfer research.