Topic
Nanofluid
About: Nanofluid is a research topic. Over the lifetime, 23986 publications have been published within this topic receiving 677384 citations.
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TL;DR: In this paper, an adaptive neuro-fuzzy inference system (ANFIS) and artificial neural network (ANN) were used for predicting the relative viscosity and electrical conductivity of the two types of hybrid ferrofluids.
Abstract: Recently, the suspension of hybrid nanoparticles in conventional fluids has been investigated as a technique for improving the thermophysical properties of nanofluids. The dearth of documentation on the trio influence of volume concentration, base fluid, and temperature on the electrical conductivity and viscosity of hybrid alumina–ferrofluids [Al2O3–Fe2O3 (25:75 mass%)] has led to this study. The effective viscosity and electrical conductivity of the deionized water (DW)-based and ethylene glycol (EG)–DW-based (50:50 vol%) hybrid alumina–ferrofluids were measured at temperatures of 20–50 °C and volume concentrations of 0.05–0.75%. Based on the importance of soft computing methods to engineers, adaptive neuro-fuzzy inference system (ANFIS) and artificial neural network (ANN) were used for predicting the relative viscosity and electrical conductivity of the two types of hybrid ferrofluids. The measured data for viscosity and electrical conductivity were used in the modeling. Model performances were evaluated using the root mean squared error index. Viscosity was enhanced by 3.23–43.64% and 2.79–49.38%, while electrical conductivity was increased by 163.37–1692.16% and 717.14–7618.89% for the DW- and EG–DIW-based hybrid ferrofluids, respectively, compared with the respective base fluids. Increasing volume concentration augmented the viscosity and electrical conductivity of all the hybrid alumina–ferrofluids, whereas a rise in temperature enhanced their electrical conductivity and detracted the viscosity. DW-based hybrid alumina–ferrofluid was observed to have a lower viscosity and higher electrical conductivity than the EG–DW-based counterpart. The results showed that the optimum ANN and ANFIS models have a maximum error of less than 4.5% and 3.9% for relative viscosity and electrical conductivity, respectively, which were lower than those proposed using regression analysis. With the hybrid alumina–ferrofluids possessing a lower viscosity relative to single-particle ferrofluids, they are recommended for engineering application.
154 citations
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TL;DR: In this article, the authors summarized the preparation, thermophysical and hydrothermal properties, mechanisms, factors responsible for obtaining stable and enhanced thermophysical properties furthermore and its benefits on integration with heat transfer applications.
154 citations
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TL;DR: Viscosity, density and thermal conductivity of MWCNT-COOH nanoparticles were studied without adding any surfactants or additives for a range of 20°C.
154 citations
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TL;DR: In this paper, an electric field effect on nanofluid forced convective heat transfer in an enclosure with sinusoidal wall is presented, where the Control Volume based Finite Element Method (CVFEM) is utilized to simulate this problem.
154 citations
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TL;DR: An overview of the remarkable progress on nanofluids during the past two decades is presented and factors enhancing the stability and lubrication mechanism have been delineated in detail.
Abstract: A nanofluid is a dispersion of nanoparticles in a base fluid and it has been a hot topic of great interest in recent years primarily due to its potential application in various fields. This review presents an overview of the remarkable progress on nanofluids during the past two decades. Nanoparticles have been investigated intensively as an additive for lubricants due to their special tribological properties. This article is focused on various synthetic methods and characterization techniques of nanofluids. Factors enhancing the stability and lubrication mechanism have been delineated in detail. Although nanofluids are potential candidates for tribological applications, there are still many challenges to overcome. These challenges involve the long term stability of nanofluids and validation of lubrication mechanisms. Especially, nanofluid stability and high costs of production are obstacles for the application of nanofluids. The current review also discusses the problems of nanofluids applied in lubrication.
154 citations