期刊
APPLIED THERMAL ENGINEERING
卷 111, 期 -, 页码 1202-1210出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.applthermaleng.2016.09.091
关键词
Hybrid nanofluid; SWCNT-MgO; Thermal conductivity; Neural network modeling; Sensitivity analysis; Price-performance analysis
The present study deals with the measurement of thermal conductivity of SWCNTs-MgO/EG hybrid nanofluids and the modeling of experimental data using artificial neural network (ANN). Hybrid nanofluids are produced and tested at volume fraction of 0.05-2% and temperature range from 30 to 50 degrees C. The nanofluid's obtained data has been compared with experimental outcomes of single particle nanofluids of MgO and SWCNT in base,fluid of Ethylene Glycol. A sensitivity analysis is done as a measure of variable changing effects on alterations gradient of the objective function. The analysis shows that the alterations gradient of thermal conductivity increases with the rise of volume fraction of up to 1%, and then, the sensitivity decreases. Generally, the current study is a combination of empirical studies along with the artificial neural network, sensitivity analysis, and proposing an empirical correlation for detailed understanding of the thermal behavior in SWCNT-MgO (20-80%)-EG hybrid nanofluids. (C) 2016 Elsevier Ltd. All rights reserved.
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