An automotive radiator with multi-walled carbon-based nanofluids: A study on heat transfer optimization using MCDM techniques

In this work, multi-criteria decision-making (MCDM) techniques namely the additive ratio assessment (ARAS) method and the combinative distance-based assessment (CODAS) are applied for predicting the automobile radiator performance under 27 different operating conditions using multiwall carbon nanotubes (MWCNTs)- based nanofluid. The multiwall carbon nanotubes (MWCNTs) - SG-based nanofluids were prepared at different concentrations of 0.2, 0.4, and 0.6 vol %. Thermal transport properties namely density, specific heat capacity, thermal conductivity, and viscosity of solar glycol (SG) - MWCNTs based nanofluids were measured experimentally. The three different types of SG - MWCNTs based nanofluids used at different mass flow rates in the present study as 30, 60, and 90 g/s. The developed regression formulae for input parameters are inlet temperature of the nanofluids (degrees C), volume concentrations of the nanofluids (%), and the mass flow rate of the nanofluids (g/sec), and responses are Nusselt number and friction factor was determined. The optimum parameters from the MCDM technique are obtained at experiment number 21 as a temperature of nanofluid 70 degrees C, volume concentrations of the nanofluids 0.2%, and mass flow rate 90 g/s under ARAS and CODAS technique. The experimental outcomes displayed a maximal enhancement of the Nu by 18.39% with an inlet temperature of 70 degrees C, 0.6% of MWCNTs nanomaterials, and a mass flow rate of 90 g/s (Exp. number27). The maximal rise of ff by 0.25 with an inlet temperature of 70 degrees C, 0.6% of MWCNTs nanoparticles, and a mass flow rate of 30 g/s (Exp. number 25). The outcomes of the regression analysis designated those substantial input factors for enhancing the thermal transfer with the automobile radiator.

Automated summary

In this study, multi-criteria decision-making (MCDM) techniques were used to predict the performance of automobile radiators using multiwall carbon nanotubes (MWCNTs)-based nanofluid under different operating conditions. The thermal transport properties of the nanofluid were experimentally measured and regression analysis was performed to identify the important factors affecting thermal transfer. The results showed that the MCDM technique identified the optimum parameters for enhancing thermal transfer with the automobile radiator.