| Autor: |
Amin Shahsavar, Aidin Shaham, Mohamad Amin Mirzaei, Mehdi Jamei, Fatemeh Seifikar, Saeid Azizian |
| Jazyk: |
angličtina |
| Rok vydání: |
2022 |
| Předmět: |
|
| Zdroj: |
Journal of Materials Research and Technology, Vol 19, Iss , Pp 2695-2704 (2022) |
| Druh dokumentu: |
article |
| ISSN: |
2238-7854 |
| DOI: |
10.1016/j.jmrt.2022.06.033 |
| Popis: |
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). |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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