2024 : 11 : 25

Mehdi Bahiraei

Academic rank:
ORCID:
Education: PhD.
ScopusId:
HIndex:
Faculty:
Address:
Phone:

Research

Title
Rheological characteristics of MgO/oil nanolubricants: Experimental study and neural network modeling
Type
JournalPaper
Keywords
Synthetic motor oil MgO nanoparticles Experimental study Neural network
Year
2017
Journal INTERNATIONAL COMMUNICATIONS IN HEAT AND MASS TRANSFER
DOI
Researchers mohammad Hemmat Esfea ، Mehdi Bahiraei ، Mohammad Hadi Hajmohammad ، Masoud Afrand

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.