Computational analysis of car radiator coolant using nano fluids.

This study deployed the capabilities of ANSYS Fluent to construct a comprehensive thermal model of an automotive radiator, reflecting the software's potential in addressing intricate fluid dynamics and heat transfer challenges. The research evaluated the cooling efficiencies of different coolants, namely urea, ethylene glycol, and water. Findings highlighted the predominant efficacy of ethylene-glycol, outstripping the cooling efficiencies of water and urea liquid in the given thermal model. A nuanced examination of energy dissipation patterns underscored the month of December as the pinnacle of heat dissipation, where ethylene-glycol reached a zenith, dissipating 49.5% of cooling energy. This research elucidates pivotal considerations for enhancing thermal management in automotive radiators and emphasizes the vital role of judicious coolant selection. [ABSTRACT FROM AUTHOR]