Assessment of thermal conductivity of polyethylene glycol-carbon dot nanofluid through a combined experimental-data mining investigation, By Amin Shahsavar Goldanloo

Research

Title	Assessment of thermal conductivity of polyethylene glycol-carbon dot nanofluid through a combined experimental-data mining investigation
Type	Article
Keywords	Carbon dot nanofluid Correlation Multi-linear regression Polyethylene glycol Response surface methodology Thermal conductivity
Researchers	Amin Shahsavar Goldanloo، Aidin Shaham، Mohamad Amin Mirzaei، Mehdi Jamei، Fatemeh Seifikar، Saeid Azizian

Abstract

The aim of this study is to determine the effect of nanoparticle concentration ð4Þ and temperature on the thermal conductivity of polyethylene glycol (PEG)-carbon dot nanofluid (NF). The considered range for temperature and 4 is 20e60 C and 0e7%, respectively. The results indicated an ascending trend of NF thermal conductivity with boosting both temperature and 4. The percentage of increase in thermal conductivity of NF with temperature and 4 compared to the base fluid was in the range of 7.23e13.43% and 75.08e85.17%, respectively. Moreover, two efficient data-driven approaches, namely Multi-variate linear regression (MLR) and response surface methodology (RSM) schemes were developed to simulate the thermal conductivity of the PEG-carbon dot NF and fit the predictive relationships. The outcomes of modeling revealed that RSM model (R ¼ 0.984 and RMSE ¼ 0.013 W/m.K), due to taking into account the interaction between volume fraction and temperature, yielded more accuracy than MLR (R ¼ 0.960 and RMSE ¼ 0.021 W/m.K). © 2022 The Author(s). Published by Elsevier B.V. This is an open access article under the CC