Rheological characteristics of MgO/oil nanolubricants: Experimental study and neural network modeling. (August 2017)

• Record Type: Journal Article
• Authors: Hemmat Esfe, Mohammad; Bahiraei, Mehdi; Hajmohammad, Mohammad Hadi; Afrand, Masoud
• Is Part Of: International communications in heat and mass transfer. Volume 86(2017)
• Page Start: 245
• Page End: 252
• Publication Date: 2017-08
• Subjects: Synthetic motor oil -- MgO nanoparticles -- Experimental study -- Neural network; Heat -- Transmission -- Periodicals; Mass transfer -- Periodicals; Chaleur -- Transmission -- Périodiques; Transfert de masse -- Périodiques; Heat -- Transmission; Mass transfer; Periodicals; 621.4022
• DOI: 10.1016/j.icheatmasstransfer.2017.05.017
• Languages: English
• ISSNs: 0735-1933

Abstract

Abstract: The present paper deals with the rheological behavior of MgO nanoparticles suspended in synthetic motor oil. First, the viscosity of prepared nanofluids is measured at different concentrations and temperatures. The experiments are performed in the temperatures ranging from 5 °C to 65 °C, shear rates approximately up to 13, 000 s − 1, and concentrations of 0.25%, 0.5%, 0.75%, 1%, 1.5%, and 2.0%. The viscosity measurements revealed that all nanofluid samples exhibit shear-thinning behavior. The consistency and the power law index were obtained by curve-fitting. The curve-fitting results show that all power law indices were in the range of 0.8 to 0.91. Finally, artificial neural network (ANN) is used to model the experimental results.