Assessment of thermal conductivity of polyethylene glycol-carbon dot nanofluid through a combined experimental-data mining investigation
Amin Shahsavar, 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 (φ) and temperature on the thermal conductivity of polyethylene glycol (PEG)-carbon dot nanofluid (NF). The considered range for temperature and φ is 20–60 °C and 0–7%, respectively. The results indicated an ascending trend of NF thermal conductivity with boosting both temperature and φ. The percentage of increase in thermal conductivity of NF with temperature and φ compared to the base fluid was in the range of 7.23–13.43% and 75.08–85.17%, 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 = 0.984 and RMSE = 0.013 W/m.K), due to taking into account the interaction between volume fraction and temperature, yielded more accuracy than MLR (R = 0.960 and RMSE = 0.021 W/m.K).