Thermophysical Properties Of Nanofluids Research Articles

Enhancing Thermal Performance of Evacuated Tube Solar Collector using Novel Graphene Oxide Nanofluid

The research article investigates the thermal performance of heat pipe-based evacuated tube solar collector (ETSC) experimentally using graphene oxide (GO) and deionised (DI) water as working fluid with a mass flow rate of 0.5 lit/min, 0.75 lit/min, and 1 lit/min. The different volumetric concentrations of 0.001%, 0.002%, and 0.003% graphene oxide nanofluid samples were prepared in the deionised water. The X-ray diffraction (XRD) was used to determine the structural properties of graphene oxide and the morphology of graphene oxide was studied by scanning electron microscope (SEM). To evaluate the stability of nanofluid samples, the Zeta potential analysis was carried out which showed that prepared nanofluid samples remain stable for up to 30 days. The effect of different nanofluid concentrations on various thermo physical properties of nanofluid was studied and discussed. The thermal performance of ETSC was investigated by considering the effect of volumetric concentrations of nanofluid and mass flow rates. According to the findings, there is a significant increment in temperature difference and energy gain by using nanofluid samples, and the maximum thermal efficiency of ETSC was found to be 37.1% for a volumetric concentration of 0.003% at 1 lit/min mass flow rate as compared to water.

Effects of Al2O3 Concentration in Ethylene Glycol on Convection Heat Transfer Coefficient

The energy demand is more in the world due to increase in the populations. The sustainable and clean renewable energy is required to meet the demand. The solar energy with nanofluid used as heat transfer medium is the best alternative source to enhance the rate of heat transfer. The nanofluids are the suspended nano sized particles in the water, ethylene glycol or oil. The stability analysis of Al2O3 ethylene glycol carried out using zeta potential method. The 20nm sized Al2O3 nanoparticles with volume concentration from 0.01% to 1% in ethylene glycol is used as nanofluid to study the effects of concentration on convective heat transfer coefficient (HTC) and wall function HTC at temperature 298K and mass flow rate 0.033kg/s. The investigation also carried out to study the effects of concentration on its thermophysical properties of nanofluid. ANSYS fluent software used to carry out the numerical analysis with suitable thermal boundary conditions.

Nanofluids Minimal Quantity Lubrication Machining: From Mechanisms to Application

Minimizing the negative effects of the manufacturing process on the environment, employees, and costs while maintaining machining accuracy has long been a pursuit of the manufacturing industry. Currently, the nanofluid minimum quantity lubrication (NMQL) used in cutting and grinding has been studied as a useful technique for enhancing machinability and empowering sustainability. Previous reviews have concluded the beneficial effects of NMQL on the machining process and the factors affecting them, including nanofluid volume fraction and nanoparticle species. Nevertheless, the summary of the machining mechanism and performance evaluation of NMQL in processing different materials is deficient, which limits preparation of process specifications and popularity in factories. To fill this gap, this paper concentrates on the comprehensive assessment of processability based on tribological, thermal, and machined surface quality aspects for nanofluids. The present work attempts to reveal the mechanism of nanofluids in processing different materials from the viewpoint of nanofluids’ physicochemical properties and atomization performance. Firstly, the present study contrasts the distinctions in structure and functional mechanisms between different types of base fluids and nanoparticle molecules, providing a comprehensive and quantitative comparative assessment for the preparation of nanofluids. Secondly, this paper reviews the factors and theoretical models that affect the stability and various thermophysical properties of nanofluids, revealing that nanoparticles endow nanofluids with unique lubrication and heat transfer mechanisms. Finally, the mapping relationship between the parameters of nanofluids and material cutting performance has been analyzed, providing theoretical guidance and technical support for the industrial application and scientific research of nanofluids.

Experimental determination of NiFe2O4-water nanofluid thermophysical properties and evaluation of its potential as a coolant in polymer electrolyte membrane fuel cells

Heat is generated as a byproduct of the electrochemical reactions of a polymer electrolyte membrane fuel cell. This heat raises the temperature of the system, and if it is not properly removed from the cell, it can cause membrane damage and overheating. Thermal management is thus critical for PEM fuel cell stability, efficiency, and safety. This paper investigates the potential use of NiFe2O4-water nanofluid as a novel coolant for PEM fuel cells. To determine the nanofluid thermophysical properties, an experimental study for different mass% concentrations of NiFe2O4-water nanofluid is first performed. Then, a three-dimensional CFD model is built to demonstrate the effect of nanofluid use on the thermal performance of a cooling plate. Simulation results show that replacing water with 0.5% NiFe2O4 nanofluid improves temperature uniformity by 11.97%. Furthermore, nanofluid cooling reduces maximum surface temperature by up to 0.75 °C while increasing pressure drop by 5.6%, implying higher pumping power.

Experimental investigation of thermo-physical and tribological properties of oil-based graphene oxide nano-fluid using two types of polysorbate (tween 20 and tween 80)

In this paper, the effect of adding Reduced Graphene Oxide (RGO) nano-particles to engine base oil (Poly-Alpha-Olefin-PAO) on the thermo-physical properties of nano-fluid such as viscosity, thermal conductivity, and friction coefficient, are investigated numerically and experimentally. To keep the nano-fluid stable, before using ultrasonic waves, two types of polysorbate (tween 20 and tween 80) as surfactants were added to four concentrations of 0.01, 0.02, 0.0375, and 0.05 wt%, and the effects of nano-particles were studied to find the best combination in terms of viscosity, thermal conductivity, and friction coefficient, which made the nan-fluid quite stable during the tests procedure. The results showed with good accuracy that the final nano-fluid was Newtonian and its viscosity was very similar to the base oil. An increase of 7% was observed between 25 °C and 75 °C and for the concentration of 0.02 wt%. Thermal conductivity was raised in all states with an increase in concentration and the highest effect was 8% in the concentration of 0.05 wt%. The friction tests proved a desirable decrease of as much as 45% in friction coefficient compared to base oil and 28% compared to common anti-friction material used in industry for the optimum concentration which was 0.02 wt%. In addition, experimental data were compared to the models presented in the literature and the models that could describe the behavior of this nano-fluid in the best way were reported, and an empirical equation (for each surfactant) is developed to show the variation of COF with nano-particles weight fraction in the nano-fluid.

Numerical computation on MHD natural convective ternary nanofluid flow and heat transfer in a porous square cavity: Marker-and-cell technique

PurposeThe analysis of fluid flow and thermal transport performance inside the cavity has found numerous applications in various engineering fields, such as nuclear reactors and solar collectors. Nowadays, researchers are concentrating on improving heat transfer by using ternary nanofluids. With this motivation, the present study analyzes the natural convective flow and heat transfer efficiency of ternary nanofluids in different types of porous square cavities.Design/methodology/approachThe cavity inclination angle is fixed ω = 0 in case (I) and in case (II). The traditional fluid is water, and is treated as a working fluid. Ternary nanofluid's thermophysical properties are considered, according to the Tiwari–Das model. The marker-and-cell numerical scheme is adopted to solve the transformed dimensionless mathematical model with associated initial–boundary conditions.FindingsThe average heat transfer rate is computed for four combinations of ternary nanofluids: and under the influence of various physical factors such as volume fraction of nanoparticles, inclined magnetic field, cavity inclination angle, porous medium, internal heat generation/absorption and thermal radiation. The transport phenomena within the square cavity are graphically displayed via streamlines, isotherms, local and average Nusselt number profiles with adequate physical interpretations.Practical implicationsThe purpose of this study is to determine whether the ternary nanofluids may be used to achieve the high thermal transmission in nuclear power systems, generators and electronic device applications.Social implicationsThe current analysis is useful to improve the thermal features of nuclear reactors, solar collectors, energy storage and hybrid fuel cells.Originality/valueTo the best of the authors’ knowledge, no research has been carried out related to the magneto-hydrodynamic natural convective ternary nanofluid flow and heat transmission filled in porous square cavities with an inclined cavity angle. The computational outcomes revealed that the average heat transfer depends not only on the nanoparticle’s volume concentration but also on the existence of heat source and sink.

Mathematical modeling and analysis of immiscible metallic based nanofluid flow in a microchannel with non-spherical nanoparticles

The non-spherical shaped nanoparticles have grown in popularity due to their ability to alter the nanofluid thermophysical properties. This nanofluid plays a beneficial role in biomedical imaging, cancer and tumor therapy. In the current study the effect of pressure gradient, transverse magnetic field and electroosmosis on the flow of two immiscible metallic based nanofluids (blood-based Au/Ag Casson nanofluid and water-based Au/Ag Newtonian nanofluid) of different viscosities in separate regions in a microchannel is addressed. The combined impact of electromagnetohydrodynamics (EMHD), modified Darcy’s law, Joule heating and Hall current have been considered into account. The mathematical modeling has been developed with the help of modified Navier Stoke’s equations, and simplified the complex problem using appropriate assumptions and non-dimensional parameters. The complementary function and particular integral concepts have been used to obtain the exact solutions of a non-dimensionalized system of coupled differential equations along with non-dimensionalized conditions. The dimensionless velocity, temperature and concentration profiles of nanofluids have been computed. The influence of numerous relevant fluid transport parameters has been graphically depicted. It is noticed that the magnetic strength declines the nanofluid velocity in both regions. Further, the radiation parameter exhibits an inverse effect on the rate of heat transfer in nanofluids. The heat transfer rate enhanced by 56% and 2% with rising volume fraction [0.01 to 0.02] and zeta potential [0.1 to 0.2], respectively. With increasing strength of magnetic field [2 to 3], thereby 31% increment in shear stress distribution. The results of the current study can be used to enhance the performance of various processes such as surface-enhanced Raman spectroscopy, drug delivery, sensors, and electrochemistry.

Numerical Investigation of the (Mono-Hybrid) Nanofluid Thermophysical Properties for Concentrated Solar Power Plant

Nanofluids became an essential solution for the improvement of efficient heat transfer fluids. Thus, it’s necessary to optimize their propreties. This paper investigates the effect of the temperature and the volume fraction on the thermo-physical properties of different nanofluids (Mono and hybrid) such as: Density, thermal conductivity, dynamic viscosity, kinematic viscosity, heat capacity and enthalpy in various nanoparticule concentrations and operating temperature. Two nanoparticles Al2O3, CuO were added to three different conventional base fluids namely: Therminol VP-1; Sylthrem 800; Dowtherm A, with several volume fractions, and various temperatures (200–400 °C). A numerical model was developed using MATLAB software, to evaluate the behavior of each thermo-physical property of the nanofluid that can be used as a working fluid in CSP applications and compared with their conventional fluids. The results show an improvement in thermo-physical properties compared to pure fluids for an optimal value of 4% for Al2O3. Also, the increase in temperature plays an important role in the decrease in viscosity, and their influence on other properties has also been noticed while the addition of nanoparticles to the pure fluid allow to increase the thermal conductivity by 13%. Finally, the (Al2O3 + CuO/Dowtherm A) hybrid nanofluid sems to be attractive to use in CSP applications.

Advances of nanofluid in food processing: Preparation, thermophysical properties, and applications

Nanofluids (NFs) are homogenous mixes of solid nanoparticles as well as base fluid in which the size of the solid nanoparticles (NPs) is smaller than 100 nm. These solid NPs are intended to enhance the thermophysical characteristics and heat transmission attributes of the base fluid. The thermophysical characteristics of nanofluids are influenced by their density, viscosity, thermal conductivity and specific heat. These colloidal solutions of nanofluids include condensed nanomaterials such as nanoparticles, nanotubes, nanofibers, nanowires, nanosheets, and nanorods. The effectiveness of NF is significantly influenced by temperature, shape, size, type, as well as the concentration of NPs or the thermal characteristics of the base fluid. Compared to oxide NPs, metal NPs have superior thermal conductivity. Many of these investigations revealed that hybrid NFs had enhanced thermal conductivity than traditional ones. Thermal conductivity values are reduced by the formation of clusters in nanofluid. When compared to spherically formed nanoparticles, cylindrically shaped nanoparticles produced superior outcomes. In food industries, NFs could be used in various unit operations where heat needs to be transported from a heating or cooling medium to food product using a heat exchanger, as in freezing, pasteurization, refrigeration, drying, thawing, sterilization, and evaporation. The objective of this review is to analyze the recent developments in the research of nanofluids including innovative production methods, stability assessment, enhancement approaches, and thermophysical properties of nanofluids.

Entropy generation analysis of hybrid nanofluid through flexible tube with convective conditions

Entropy generation analyses of hybrid nanofluids via compliant wall tubes are performed with peristalsis effects in this study. Thermophysical properties of nanofluid are incorporated in mathematical formulations for various shapes of nanoparticles. Convective conditions on the boundary are considered. Momentum and energy equations are modeled and simplified under the lubrication approach. Solutions are calculated numerically using MATHEMATICA. The impact of various related parameters on flow quantities is observed via graphs. The study reveals greater entropy generation for blade-shaped nanoparticles.

Receiver parameter optimization for nanofluid-based parabolic trough concentrating plant: a case study

ABSTRACT The disadvantage of using nanofluids as a heat transfer fluid in the Parabolic Trough Concentrating solar power plant is increased pressure drops. Therefore, more attention should be paid to optimizing the receiver pipe diameter. The aim of this study was to optimize a new receiver to study the industrial process performance of nanofluid-based Parabolic Trough Concentrating plants in 4 different regions in southern Algeria (Hassi rmel, In salah, Tamnrasset, and Bechar). Nanoparticles (Al2O3, CuO) were added to both base liquids (Dowtherm A, Therminol VP-1). The methodology is based on a two-step approach: first, the effects of nanoparticles and temperature on the thermophysical properties of nanofluids, such as thermal conductivity, specific heat capacity, and density, are numerically investigated using the MATLAB program; second, nanofluids properties are integrated into SAM (System Advisor Model) software to perform a 50 MW parabolic trough solar power plant with 25% of a backup system and nanofluids in heat transfer system for the different representative locations of the climate of Algeria. The results of the first part show that the addition of nanoparticles increases the thermal conductivity and density of the nanofluid by 11% and 23%, respectively, and the specific heat capacity is proportional to temperature. The most favorable site is Insalah with an optimal SM egale to 3 and a capacity factor of 51%. Finally, the use of nanofluids as a heat transfer fluid in solar power plants plays a great role in improving its efficiency, the best choice for nanofluids under Algerian climates is CuO/Dowtherm A with an optimal tube diameter of 0.07 m.

Enhanced magneto-convective heat transport in porous hybrid nanofluid systems with multi-frequency nonuniform heating

In high-performance thermal systems, convective heat transport is a critical phenomenon for sustainable operation from an energy efficiency standpoint. This study examines the convective heat transport dynamics of a hybrid nanofluid (aluminum oxide-copper–water nanofluid) under spatially varying nonuniform temperature conditions within a porous thermal system in the presence of a magnetizing field. The flow domain experiences nonuniform heating (following a half-sinusoidal profile) from both sidewalls and is cooled from the top, while the lower wall remains adiabatic. The flow domain is filled with a porous substance and a hybrid nanoliquid. The non-dimensional governing equations are derived and numerically solved using a finite volume method-based solver. To accurately capture thermal behavior, available experimental data on hybrid nanofluid thermophysical properties are utilized. The study analyzes significant control variables such as half-sinusoidal heating amplitude, frequency, and offset temperature, as well as flow control variables such as Darcy number (Da), modified-Rayleigh number (Ram), and Hartmann number (Ha). The analysis shows that non-uniform heating consistently enhances transfer by up to approximately 722% compared to uniform heating. The three temperature-controlling parameters (amplitude, frequency, and offset temperature) play a crucial role in enhanced heat transfer, and the higher their magnitudes, the higher the heat transfer. Heat flow dynamics between the heat source and the heat sink are well visualized through heat function and heatlines. Heat transfer is an increasing function of Ram and frequency, which is opposite to the rising Da or Ha. An optimum frequency at which thermal convection is maximum is about 70 for the considered range of Ram. Furthermore, mathematical correlations that combine control variables are developed for predicting heat transfer characteristics.

Characterization of Thermophysical and Electrical Properties of SiC and BN Nanofluids

Experimental data associated with the thermophysical properties (TPPs) of various nanofluids (NFs) are essential for their diverse applications in energy storage and conversion, as well as thermal management. This study experimentally investigated important TPPs such as thermal conductivity (TC), thermal diffusivity, density and viscosity, as well as the electrical conductivity of two new types of NFs, namely silica (SiC) and boron nitride (BN) nanofluids. The NFs are prepared at five low concentrations of nanoparticles from 0.01 to 0.05 vol.% dispersed into a mixture of ethylene glycol (EG) and distilled water (DW). The TPPs are measured, and their enhancements are evaluated in comparison with their base fluids. The results show a good increase in TC and thermal diffusivity for both types of nanofluids with increasing concentrations until reaching the maximum enhancement of about 4.4% for the SiC nanofluid and about 7.0% for the BN nanofluid at the same concentration (0.05 vol.%). On other hand, a Newtonian rheological behaviour is observed, and viscosity and density are also found to increase for both types of NFs, where the maximum increase in viscosity and density at 0.05 vol.% are found to be 5.2% and 0.3%, respectively. The electrical conductivity also increases by up to 3.2 times for SiC nanofluids and 2.8 times for BN nanofluids at the maximum concentration of these nanoparticles (0.05 vol.%) compared with the base fluid (EG/DW). The overall evaluation of the obtained results demonstrates the great potential of these nanofluids in heat transfer applications.

Stability and Thermophysical Properties of GNP-Fe2O3 Hybrid Nanofluid: Effect of Volume Fraction and Temperature

The study focused on the impact of concentration and temperature on the electrical conductivity, viscosity, and thermal conductivity of GNP/Fe2O3 hybrid nanofluids. The study found that nanofluids have better electrical conductivity, viscosity, and thermal conductivity than water. The electrical conductivity and thermal conductivity increase linearly with concentration for a constant temperature. However, the nanofluid's viscosity increases with the addition of the hybrid nanoparticles and decreases as the temperature increases. Furthermore, the study shows that the thermal conductivity of the nanofluid is enhanced with increased addition of hybrid nanoparticles in the base fluid and that the thermal conductivity ratio increases with increased addition of nanoparticles. Overall, the results suggest that GNP/Fe2O3 hybrid nanofluids could be used in various industrial applications to improve the heat transfer and energy efficiency of systems.

Particle-Size Effect of Nanoparticles on the Thermal Performance of Solar Flat Plate Technology

One of the cleanest and most efficient solar collector systems is the flat plate collector, which has applications in hot water production, drying, among others. Flat plate collectors have improved in terms of both their structural configurations and working fluids. Several studies have verified the comparatively higher efficiency of nanofluid-based flat plate collectors, relative to that of water and other thermal oils. Additionally, the influence of several nanofluid synthesis factors, such as volume fraction, pH, type of base fluid, hybridization, surfactants, and sonification, on the performance of these collectors has been highlighted in the literature. However, the effect of nanoparticle size on collector performance has received minimal research interest, despite its significant effect on both the cost of synthesis and the thermophysical properties of nanofluids. The uncertainties regarding the effect of nanoparticle size on thermal collectors have limited their practical applications. This study numerically investigates the effect of the nanoparticle size of silver (Ag) nanofluid with nanoparticle sizes between 20 nm and 100 nm on the performance of flat plate collectors. The effect of nanoparticle size on the mean fluid temperature resulted in a maximum temperature of 45.8 °C for the Ag-100 nm. An increase of 0.25 °C for the Ag-20 nm was recorded, relative to the Ag-100 nm. In addition, the Ag-100 nm was calculated to have resulted in the highest reduction in collector size (18.30%), relative to that of water.

Investigation of nanoparticles shape that influence the thermal conductivity and viscosity in argon-based nanofluids: A molecular dynamics simulation

The shape of nanoparticles plays an essential role in the thermophysical properties of nanofluids, yet their mechanisms and characteristics remain lacking in comprehensive studies. Molecular dynamics simulations of non-equilibrium molecular dynamics (NEMD) and reversing perturbation non-equilibrium molecular dynamics (RNEMD) calculation methods were used to study thermal conductivity and viscosity of Cu/Au-Argon based nanofluids, taking into account a variety of influencing factors, as well as nanoparticles shape and volume fraction. Through the analysis of the number density distribution, radial distribution function (RDF) and mean square displacement (MSD), the influences of nanoparticles shape (represented by the surface-to-volume ratio) were described and investigated: the highest value was 0.182 WK−1m−1 containing columnar particles of Au at 2% volume fraction, while the thermal conductivity of Cu nanofluids was 0.162 WK−1m−1 under the same conditions; the average values of viscosity had very close values of 2.82 × 10−4 Pa·s (Cu-Ar) and 2.86 × 10−4 Pa·s (Au-Ar) at 1.5% particle volume fraction for nanofluids containing spherical particles, respectively. Simulations of argon-based nanofluids containing five different shapes of Au nanoparticles indicate that the thermal conductivity improves with the growth of the surface-to-volume ratio. And the enhancement of the interfacial nanolayer density turns out to be the main factor that nanoparticles with higher S/V value facilitated the enhancement of the thermal conductivity of argon-based nanofluids. This study enriches the molecular dynamics studies of nanofluids and provides important insights for understanding the effect of nanoparticle's shape on the thermal properties of nanofluids.

Role of Nanofluid and Hybrid Nanofluid for Enhancing Thermal Conductivity towards Exponentially Stretching Curve with Modified Fourier Law Inspired by Melting Heat Effect

The intensive of this study is to examine the melting heat and second-order slip (SoS) effect at the boundary in nanofluid and hybrid nanofluid (HN) ethylene–glycol (EG) based fluid through a curved surface using the Modified Fourier Law (MFL) and dust particles. Considering similarity transformation, the PDEs are converted to ODEs and then solved numerically by using the finite element method (FEM). The effects of solid volume fraction (SVF), melting heat factor, curvature factor, first and second-order slip factor, fluid particle concentration factor, and mass concentration factor on the velocity field, dust phase velocity (DPV), temperature field, dust phase temperature (DPT), and the Ski Friction (SF) are investigated through graphs and tables. The thermophysical properties of nanofluid and HN are depicted in tables. The novelty of the present work is to investigate the dusty- and dusty-hybrid nanoliquids over the curved surface with a melting heat effect and MFL which has not yet been studied. In the limiting case, the present work is compared with the published work and a good correlation is found. The confirmation of the mathematical model error estimations has been computed.

Exergetic evaluation of the effect of nanofluid utilization for performance enhancement of a solar driven hydrogen production plant

Recently, research and development on progressive and efficient hydrogen production methods has been paid lots of attention due to carbon-free feature of hydrogen. Application of nanoparticles to enhance an integrated solar-based hydrogen production unit is suggested and investigated in this work. The integrated plant consists of parabolic trough collectors coupled with a Kalina cycle for electricity generation to be consumed in a polymer electrolyte membrane electrolyzer for hydrogen production. The system performance is apprised for nanofluid as the heat transfer media for solar collectors and is compared with the pure basefluid case. Thermal model for parabolic trough collectors as well as thermodynamic models for Kalina cycle and electrolyzer are developed and validated. Also, thermo physical properties of nanofluid is assessed based on volume fraction of the nanoparticles. Parametric analyses are implemented for system performance assessment in which influence of design variables related to solar collectors, nanoparticels as well as the Kalina cycle are appraised. The effect on the hydrogen rate and solar-to-hydrogen exergy efficiency of design variables are comprehensively examined and discussed. According to the obtained results, the ηex,STH is found to be 9.19% for the case with basefluid (without nanoparticles), whereas it can be improved to 9.63% with employment of 5% volume fraction of CuO nanoparticles. Such an efficiency improvement is due to the increment of hydrogen production from 0.669 kg/h to 0.702 kg/h using CuO-based nanofluid.

The effect of nanofluids reinforced with different surfactants on the machining and friction-wear properties of Waspaloy

In present investigation, a number of experiments were done to determine the impact of surfactants on Waspaloy machining characteristics and the friction-wear behavior on the ball-on-disc tester. The experiments were carried out in dry, base fluid (sunflower oil), Cuo, and ZnO nanofluid conditions with/without surfactant. Four distinct surfactants, including Gum Arabic (GA), Sodium Dodecyl Sulfate (SDS), CeTyltrimethylAmmonium Bromide (CTAB), and PolyVinyl Pyrrolidone (PVP), were employed to prepare the nanofluids with surfactant. In addition, viscosity, pH, and thermal conductivity measurements were made to determine the prepared nanofluid's thermo-physical properties. Tool wear and its mechanisms, surface roughness and cutting temperature in machining experiments, coefficient of friction (CoF), microhardness, and wear track width in ball-on-disk tests were choosen as evaluation criterias. From both the machining and ball-on-disk test results, it was determined that the ZnO + PVP nanofluid condition outperformed the other conditions. The ZnO + PVP nanofluid condition provided 53.9 %, 36.52 %, and 44 % improvement in tool wear, surface roughness, and cutting temperature, respectively, compared to the dry cutting condition. Also, considering the results of the ball-on-disk test, it was found that the CoF and width track width values for the ZnO+PVP nanofluid condition were both 76.02 % and 56.11 % lower than the dry condition.

A data-driven physics-informed neural network for predicting the viscosity of nanofluids

Nanofluids have been applied in various fields, such as solar collectors, petroleum engineering, and chemical engineering, due to their superior properties compared to traditional fluids. Among the various thermophysical properties of nanofluids, viscosity plays a critical role in thermal applications involving heat transfer and fluid flow. While several conventional machine learning (ML) techniques have been proposed to predict viscosity, these conventional models require many experimental measurements to be optimized and make accurate predictions. This study reports a novel ML method using a multi-fidelity neural network (MFNN) to accurately predict the viscosity of nanofluids by incorporating the physical laws into the model. The MFNN correlates a low-fidelity dataset derived from the prediction of the theoretical model with a high-fidelity dataset, which consists of experimental measurements. It is shown that the MFNN can recover the rheology of nanofluids and outperforms the conventional artificial neural network due to incorporating the underlying physics of nanofluids into a model.