Thermal efficiency of microchannel heat sink: Incorporating nano-enhanced phase change materials and porous foam gradient and artificial intelligence-based prediction

This study investigates the impact of incorporating phase change materials (PCMs), nano-particles (NPs) enhanced PCMs (nePCMs), and porous foam gradients on the thermal performance (TPEF) of microchannel heat sinks (MCHS). Specifically, the effect of different PCM types, hybrid NPs, and spiral microchannels on the TPEF is examined using numerical solutions based on the finite volume method. The results indicate that increasing Re and using spiral microchannels significantly enhance the TPEF. The incorporation of NPs-water and PCM can reduce the thermal resistance (R) of MCHS, with PCM significantly improving the TPEF. Among the PCMs, ENCAPSUL demonstrates the best performance for MCHS. The combination of hybrid nePCM increases TPEF by approximately 9%. The combination of PCM-aluminum oxide-iron oxide NPs exhibits the highest TPFE. The use of a porous medium with PCM can decrease the R by about 60 %, and it improves the TPEF by altering the conduction and convection mechanism. various scenarios of changes in the porosity coefficient have been considered for porous foam gradient and the best performance is achieved for the NYPC mode. Various scenarios of MCHS with PCM-water combinations have been explored, and the best performance is observed when PCM is situated in the microchannel. Additionally, artificial intelligence techniques, such as the Group Method of Data Handling (GMDH), have been utilized to estimate R, and a multivariate polynomial regression (MPR) equation has been developed to calculate R based on input variables. GMDH is more accurate compared to MPR.