|
Title
|
Assessment of thermal conductivity of polyethylene glycol-carbon dot nanofluid through a combined experimental-data mining investigation
|
|
Type
|
JournalPaper
|
|
Keywords
|
Carbon dot nanofluid Correlation Multi-linear regression Polyethylene glycol Response surface methodology Thermal conductivity
|
|
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).
|
|
Researchers
|
Saeid Azizian (Not In First Six Researchers), (Fifth Researcher), Mehdi Jamei (Fourth Researcher), Mohamad Amin Mirzaei (Third Researcher), Aidin Shaham (Second Researcher), Amin Shahsavar (First Researcher)
|