8/14/2023 0 Comments Dynamic viscosity of air at 4.5 c![]() ![]() 31 assessed the \(\mu\) of H 2O-EG-iron-copper oxide BHNF in \(\varphi\) of 0.5 to 1.5% and T of 25 to 50 ☌. Given their findings, this BHNF has a non-Newtonian behavior (NNB) for \(\varphi\) > 6%, and the \(\mu\) of the BHNF lessens with mounting T. 30 explored the \(\mu\) of ethylene glycol-silver-iron oxide BHNF in \(\varphi\) of 0.0375 to 1.2% and T of 25 to 50 ☌. Augmenting \(\varphi\) makes a maximum 45% enhancement in the \(\mu\) of the NF compared to the \(\mu\) of the BF. ![]() ![]() ![]() Given their results, the \(\mu\) of NF decrements with growing T. Asadi 29 in a laboratory study estimated the \(\mu\) of ZnO-MWCNTs-oil in the T of 5 to 55 ☌ and \(\varphi\) of 0.125 to 1%. Also, their outcomes displayed that the relative \(\mu\) increased non-linearly with the rise in \(\varphi\).īinary hybrid nanofluids (BHNF) are actually created by the dispersion of two NPs in a base fluid. Esfe 28 explored the efficacy of T and \(\varphi\) on the viscosity ( \(\mu\)) of MWCNTs–Al 2O 3 (3:7)/EG fluid. In the past years, several analyses have been directed in the rheological manners of NFs in the T of 5 ☌ to 70 ☌ 27. In applied projects in the industry, fluid viscosity is important due to the pressure drop and power required for pumping. The amount of viscosity in the design of NF is very vital and important for fluid flow. This behavior depends on features such as the shape of NPs, their size distribution, volume fraction ( \(\varphi\)), temperature ( T), thermal conductivity coefficient of NPs and base fluid 25.ĭuring the last decade, the HT features of NFs have been extensively investigated 26. Based on analytical 21, numerical 22 and laboratory studies 23, researchers showed that NFs are superior to base fluids 24. The primary fluid is usually water 17, ethylene glycol 18, propylene glycol 19, and oil 20. Nanopowders (NPs) are usually metal particles such as Ni 1, Cu 2, Ag 3, AlN 4, CaCO 3 5, metals oxide such as CuO 6, SiO 2 7, Fe 2O 3 8, Fe 3O 4 9, BaTiO 3 10, TiO 2 11, Al 2O 3 12, carbon compounds such as SiC 13, MWCNTs 14, Graphene 15, and Graphite 16. Nanofluid (NF) is a mixture that is obtained by adding nanoscale (nanometer) particles to a base fluid with the aim of improving heat transfer (HT). Each model predicted the viscosity of the THNF well, and Rsquare > 0.99. Neural network (NN), Adaptive Neuro-Fuzzy Inference System (ANFIS), and Gaussian process regression (GPR) based on machine learning (ML) have been used to model viscosity. The findings of the test display that the wear rate and friction coefficient increased about 68% and 4.5% for \(\varphi\) = 1.5% compared to \(\varphi\) = 0. The efficacy of adding nanopowders (NPs) on the stability of the friction and wear behavior of the base oil has been studied. The estimated values of THNF viscosity at various SRs and temperatures show that its behavior is non-Newtonian. Also, the results showed that with the rise in SR, the shear stress increased and the viscosity decreased. By enhancing the temperature by 60 ☌, at \(\varphi\) = 1.2% and a shear rate (SR) of 50 rpm, a viscosity reduction of approximately 92% has been observed. The outcomes show that the viscosity increases with the increase in the \(\varphi\), and the reduction in temperature. The wear test was performed via a pin-on-disk tool according to the ASTM G99 standard. This THNF is made in a two-step method and a viscometer device made in USA is used for viscosity measurements. In the present study, the properties of ternary hybrid nanofluid (THNF) of oil (5W30) - Graphene Oxide (GO)-Silica Aerogel (SA)-multi-walled carbon nanotubes (MWCNTs) in volume fractions ( \(\varphi )\) of 0.3%, 0.6%, 0.9%, 1.2%, and 1.5% and at temperatures 5 to 65 ☌ has been measured. ![]()
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