Assessment of thermal conductivity of polyethylene glycol-carbon dot nanofluid through a combined experimental-data mining investigation

被引:9
作者
Shahsavar, Amin [1 ]
Shaham, Aidin [1 ]
Mirzaei, Mohamad Amin [1 ]
Jamei, Mehdi [2 ]
Seifikar, Fatemeh [3 ]
Azizian, Saeid [3 ]
机构
[1] Kermanshah Univ Technol, Dept Mech Engn, Kermanshah, Iran
[2] Shahid Chamran Univ Ahvaz, Fac Engn, Shohadaye Hoveizeh Campus Technol, Dashte Azadegan, Iran
[3] Bu Ali Sina Univ, Fac Chem, Dept Phys Chem, Hamadan, Iran
来源
JOURNAL OF MATERIALS RESEARCH AND TECHNOLOGY-JMR&T | 2022年 / 19卷
关键词
Carbondotnanofluid; Correlation; Multi-linearregression; Polyethyleneglycol; Responsesurfacemethodology; Thermalconductivity; HEAT; CONVECTION;
D O I
10.1016/j.jmrt.2022.06.033
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
The aim of this study is to determine the effect of nanoparticle concentration (phi) and temperature on the thermal conductivity of polyethylene glycol (PEG)-carbon dot nanofluid (NF). The considered range for temperature and phi is 20-60 degrees C and 0-7%, respectively. The results indicated an ascending trend of NF thermal conductivity with boosting both temperature and phi. The percentage of increase in thermal conductivity of NF with temperature and phi 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). (C) 2022 The Author(s). Published by Elsevier B.V.
引用
收藏
页码:2695 / 2704
页数:10
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