Automotive heat removal levels are of high importance for maximizing fuel consumption. Current radiator designs are constrained by air-side impedance, and a large front field must meet the cooling requirements. The enormous demand for powerful engines in smaller hood areas has caused a lack of heat dissipation in the vehicle radiators. As a prediction, exceptional radiators are modest enough to understand coolness and demonstrate great sensitivity to cooling capacity. The working parameters of the nano-coated tubes are studied using Computational Fluid Dynamics (CFD) and Taguchi methods in this article. The CFD and Taguchi methods are used for the design of experiments to analyse the impact of nano-coated radiator parameters and the parameters having a significant impact on the efficiency of the radiator. The CFD and Taguchi methodology studies show that all of the above-mentioned parameters contribute equally to the rate of heat transfer, effectiveness, and overall heat transfer coefficient of the nanocoated radiator tubes. Experimental findings are examined to assess the adequacy of the proposed method. In this study, the coolant fluid was transmitted at three different mass flow rates, at three different coating thicknesses, and coated on the top surface of the radiator tubes. Thermal analysis is performed for three temperatures as heat input conditioning for CFD. The most important parameter for nanocoated radiator tubes is the orthogonal array, followed by the Signal-to-Noise Ratio (SNRA) and the variance analysis (ANOVA). A proper orthogonal array is then selected and tests are carried out. The findings of ANOVA showed 95% confidence and were confirmed in the most significant parameters. The optimal values of the parameters are obtained with the help of the graphs.
Thermal Analysis and Optimization of Nano Coated Radiator Tubes Using Computational Fluid Dynamics and Taguchi Method