Thermal and hydraulic performance evaluation of heat sinks using nanofluids and innovative vortex generating fins

Heat transfer in electronic devices is of prime importance in thermal management domain. Compact design requirements of modern systems need performance enhancement of heat transfer devices. Heat transfer augmentation in heat sinks can be achieved by various means including use of efficient advanced cooling materials, like nanofluids and design parameters optimization. The aim of this study is to analyze the impact of numerous heat transfer augmentation techniques on performance of versatile heat sinks. Three different aluminum-based heat sinks are tested in a test rig, having cylindrical, elliptical and semicircular wavy finned heat sinks with four different coolants including water, water-based (Fe₂O₃ + TiO₂) hybrid nanofluid, ethylene glycol and water-based (1:1) MgO nanofluid and water-based SiO₂ nanofluid. Different heat input and flow rate levels (15 to 60 W and 2 to 10 LPM, respectively) are employed during experimentation. The results of this study indicate novel semicircular wavy finned design possesses lowest average wall temperature followed by elliptical finned heat sink while cylindrical finned heat sink possesses highest. But meanwhile pressure drop and hence pumping power requirement are highest for wavy finned and lowest for elliptical finned heat sink. The pressure drop is also impacted by the type of coolant, its lowest with water and highest in case of MgO nanofluids. Nusselt number is lowest for cylindrical finned heat sink in all cases while fluctuation occurs between rest two types at different parameters. In general, for viscous flows Nusselt number is higher for elliptical finned heat sinks compared to novel wavy finned heat pipes, and for less viscous flows novel finned heat sink outperforms. This is due to vortex generation in semicircular wavy finned heat sink as validated through numerical results. Statistical inference shows significance of experimental data, and based upon regression technique performance prediction models are developed for all heat sinks.