A numerical simulation of heat transfer performance on MHD nanofluids in porous metal for enhancing CPU cooling efficiency

The main goal of this study is to enhance CPU cooling efficiency using nanofluids, and the novelty of the study lies in the investigation of heat transfer and convective flow of MHD nanofluid through porous metal structures and foam heat sink/source to improve CPU cooling efficiency. The governing equations for the flow model are solved using the BVP4C with MATLAB package through shooting techniques. The effects of various parameters on velocity, temperature fields, HT and drag force are discussed through graphical simulations. The results indicate that as the Reynolds and Darcy numbers rise, fluid flow velocity undergoes unique alterations. Higher Reynolds and Darcy numbers result in cooler temperatures, while higher heat generation lead to warmer temperatures.Boosting Prandtl number improves HT by 52% with Cu nanoparticles, whereas elevating heat generation values reduce HT by 6.43% more efficiently with Cu nanoparticles than Al2O3 nanoparticles. Raising the Hartmann number would boost drag force, but the Darcy number opposes it. An increase in Hartmann number leads to a decrease in HT by 30.16% for Al2O3-H2O nanofluids and 47.81% for Cu-H2O nanofluids. The findings contribute to the development of advanced computing devices, paving the way for more efficient and reliable electronic systems in various applications.