Thermal Conductivity Of Hybrid Nanofluid Research Articles

Experimental Analysis of Nanofluids in PEMFC Cooling Plate Integrated with Thermoelectric Generator

A thermoelectric generator (TEG) is considered a feasible option to recover waste heat from a Proton exchange membrane fuel cell (PEMFC) into electrical energy. However, its application is limited due to its low efficiency. Meanwhile, nanofluids have emerged as an alternative coolant in heat transfer due to their superior thermal conductivity characteristics. Thus, this study aims to improve the efficiency of the TEG using nanofluids. The experimental study was conducted on a test bench that coupled a PEMFC cooling plate and TEG which was subjected to a 0.5% volume concentration of 𝐴𝑙2𝑂3∶𝑆𝑖𝑂2 hybrid nanofluids at a flow rate of Re 300 to 1000. The mixture ratio of 𝐴𝑙2𝑂3∶𝑆𝑖𝑂2 hybrid nanofluids studied was 10:90 ratio, single nanofluids of 𝐴𝑙2𝑂3 and 𝑆𝑖𝑂2 and also the base fluid of water. Upon completion, the improvement in power output due to an improved temperature difference of the thermoelectric generator (TEG) is observed. The highest TEG performance was shown by hybrid nanofluids of 10:90 (𝐴𝑙2𝑂3∶𝑆𝑖𝑂2) with a 17% improvement as compared to the base fluid of water. This is due to the bigger temperature difference which is caused by better thermal conductivity of hybrid nanofluids as compared to the base fluid.

Investigation into the underlying mechanisms of the improvement of thermal conductivity of the hybrid nanofluids

More and more applications of hybrid nanofluids are emerging in various fields such as energy engineering, chemical engineering, and automotive engineering. However, the existing literature only employs the term "synergistic effect" to explain the improvement of thermal conductivity of hybrid nanofluids. In order to elucidate the underlying reasons behind the improvement in thermal conductivity of hybrid nanofluids compared to that of conventional ones (mono nanofluids), molecular dynamics simulations were conducted to examine three types of hybrid nanofluids, including Ag-Cu nanocomposites, Au-Cu Janus nanoparticles, and Ag-Cu binary nanoparticles. The results suggest that hybrid nanofluids including Ag-Cu nanocomposites, Au-Cu Janus nanoparticles, and Ag-Cu binary nanoparticles improve the thermal conductivity of 2 vol% nanofluid by 34.3 %, 12.1 %, and 10.4 %, respectively, compared to Cu monofluid. The improvement in thermal conductivity for hybrid nanofluids containing nanocomposites in single-particle systems can be attributed primarily to the stronger Brownian motion, while the improvement in thermal conductivity for hybrid nanofluids containing Au-Cu Janus nanoparticles and Ag-Cu binary nanoparticles is due to the looser aggregation morphology in multi-particle systems. This observation allows us to appreciate the significance of aggregation morphology as a crucial mechanism when considering interactions between nanoparticles. It provides a theoretical basis for the preparation of high-performance nanofluids as heat transfer media.

Mechanism of enhanced thermal conductivity of hybrid nanofluids by adjusting mixing ratio of nanoparticles

At certain mixing ratios, hybrid nanofluids exhibit superior thermal conductivity performance compared with mono nanofluids, without significant enhancements in viscosity. Studying the microstructures formed by nanoparticles in the base fluid is key to revealing the mechanism of enhanced heat transfer in nanofluidic systems. Here, effects of varying the nanoparticle volume fraction (0.5–2.0 vol%) and Cu:Al volume mixing ratio (20:80, 40:60, 50:50, 60:40, and 80:20) of Cu-Al/Ar hybrid nanofluids were investigated using non-equilibrium molecular dynamics (NEMD) simulations at a temperature of 85 K. The mechanism of thermal conductivity enhancement was elucidated through quantitative analysis of the nanolayer structure and atom trajectory. The results showed that the thermal conductivities of Cu-Al/Ar hybrid nanofluids with a mixing ratio of 20:80 were lower than those of the corresponding Cu/Ar mono nanofluids with volume fraction below 1.3 vol% due to the low quantity of Cu nanoparticles. However, when the quantity of Cu nanoparticles was increased by using mixing ratios from 40:60 to 80:20, the thermal conductivities were higher at all volume fractions. Compared to Cu/Ar nanofluids, the thermal conductivity of Cu-Al/Ar hybrid nanofluids improved from 0.149 to 0.166 W/(m·K) which was higher 2.76 % to 14.48 % as the mixing ratio increased from 20:80 to 80:20 at 2.0 vol%. Radial distribution function (g(r)), the number density and diffusion rate calculations indicated that the density and velocity of Ar atoms around Cu atoms were higher than those of Al atoms due to stronger interactions between Cu-Ar atoms. The main reason for the enhanced thermal conductivity of hybrid nanofluids with increasing mixing ratio was the higher unit nanolayer density and Brownian motion velocity.

Toward predicting thermal conductivity of hybrid nanofluids: Application of a committee of robust neural networks, theoretical, and empirical models

In this work, three optimized intelligent models on the basis of multilayer perceptron (MLP), two radial basis function (RBF) models (including RBF- particle swarm optimization (PSO) and RBF- farmland fertility algorithm (FFA)), and a committee machine intelligent system (CMIS) were used to estimate Thermal Conductivity (TC) of hybrid nanofluids. Base fluid TC, TC of first and second nanoparticles, size of first and second nanoparticles, volume fractions of first and second nanoparticles, and temperature were considered as inputs to model TC of hybrid nanofluids. Based on the results, the CMIS model emerged as the most accurate model for predicting TC coefficient of hybrid nanofluids, boasting an average absolute percent relative error (AAPRE) of just 1.064%. Comparison with various empirical and theoretical models further highlighted the superior predictive performance of the CMIS model in assessing the TC of hybrid nanofluids. Ultimately, the leverage technique underscored the reliability of the CMIS model.

Enhanced thermal conductivity of plasma generated ZnO–MgO based hybrid nanofluids: An experimental study

Hybrid nanofluids (HNFs) of metallic oxide-based nanoparticles (NPs) have been prepared in different basefluids (BFs) employing the thermal plasma technique. NPs of ZnO–MgO were directly dispersed into pristine coolant, engine oil, distilled water (DW), and coconut oil. Plasma was generated between two identical electrodes applying 8.0 kV at the ambient conditions and proved economically viable in preparing stable HNFs. X-ray Diffractometry (XRD) showed ZnO and MgO NPs possessed hexagonal and cubic crystal structures, respectively. The band gap is calculated through UV-visible spectroscopy. The thermal conductivity (TC) of the HNFs has been measured using a thermal conductivity analyzer based on the transient hot wire method. The band gaps of pristine coolant and its HNFs were obtained to be 3.35 eV and 3.33 eV, respectively. In engine oil and its HNFs, band gaps of 3.16 eV and 3.02 eV have been extracted. There appears to be a slight reduction in band gap for coolant and engine oil-based HNFs. The band gap value of coconut oil-based HNFs was 4.05 eV, which showed a higher value than the pristine coconut oil-based HNFs (3.95 eV). The band gap calculated in the case of DW-based HNFs was 3.79 eV. TC of HNFs with volume concentration of 0.019 % for DW, 0.020 % for coolant, 0.016 % for engine oil, and 0.017 % for coconut oil were tested between 20 and 60 °C. An increase in TC was observed with the rise in temperature of the HNFs. Maximum increment in TC was observed at 60 °C for coolant-based HNFs, which was 19 %, followed by DW (18%), coconut oil (18%), and engine oil (16%), respectively. DW-based HNFs can be used as a coolant and optical filter for optoelectronics devices like photovoltaic cells for better performance. The study underscores precise control of NPs size as pivotal for band gap influence. HNFs hold promise as the next-gen heat transfer fluids (HTFs), revolutionizing thermal conductivity across industries. This research lays a firm foundation for plasma-synthesized HNFs' application in enhanced heat transfer and optoelectronic devices. Coolant-based HNFs excel in thermal conductivity, addressing heat transfer challenges.

Computing of temperature-dependent thermal conductivity and viscosity correlation for solar energy and turbulence appliances via artificial neuro network algorithm

The growing popularity of artificial intelligence approaches has led to their application in a wide range of engineering fields. The most widely used artificial intelligence tool, artificial neural networks, can be used to predict data with high accuracy. An artificial neural network approach is being used to predict effective and accurate thermal conductivity and viscosity models for hybrid nanofluid systems. Here, new types of correlations relating to the thermophysical properties of Fly Ash–Cu nanoparticles with diameter sized 15.2[Formula: see text]nm and which are temperature-dependent are developed. The highest thermal conductivity and viscosity values were obtained for hybrid nanofluids with a mixture ratio of 20:80, with maximum amplification exceeding 83.2% and 65%, respectively, over the base fluid. The Fly Ash–Cu/water hybrid nanofluid’s viscosity and thermal conductivity are evaluated for a concentration range of 0–4%. The evaluation of the Fly Ash–Cu/water hybrid nanofluids system at concentrations ranging from 0 to 4% most likely entails a scientific or engineering study aimed at understanding the behavior and properties of this nanofluid mixture. Nanoparticles can agglomerate or settle in the base fluid over time, compromising the stability of the nanofluids. Researchers may be interested in determining how varied quantities of Fly Ash and Cu nanoparticles affect the nanofluid’s stability and sedimentation behavior. The heat transfer potential is examined within the optimistic range of temperatures of 30–80∘C. Many fruitful results for turbulence and solar energy have been drawn. The Mouromtseff number achieved an optimal value for all concentration levels. The heat transfers of turbulent flow and thermal conductivity of hybrid nanofluids increase with the augmented values of concentrations and temperature. Researchers found an increase in thermal conductivity of hybrid nanofluids at 0–4% concentrations, potentially impacting heat transfer applications. The conclusion explores the potential integration of the developed correlations and neural network model into practical engineering or industrial applications involving solar energy and turbulence appliances. In this work, we extend the work of Kanti et al. [Sol. Energy Mater. Sol. Cells 234 (2022) 111423] which is on the properties of water-based fly ash-copper hybrid nanofluid for solar energy applications.

Enhanced photothermal conversion performance of MWCNT/SiC hybrid aqueous nanofluids in direct absorption solar collectors

Nanofluids containing light-absorbing nanoparticles are potential alternative working fluids in solar collectors. In this work, a novel hybrid aqueous nanofluid containing multi-walled carbon nanotubes (MWCNTs) and SiC nanoparticles is prepared to improve the photothermal conversion ability of working fluids. The hybrid nanofluid overcomes the disadvantages of one-component nanofluids and achieves good solar absorption on the merit of the complementary optical property of MWCNTs and SiC nanoparticles. The prepared nanofluids show excellent stability due to the hydroxyl functionalization of MWCNTs, and the thermal conductivity of hybrid nanofluids is also enhanced. A high photothermal conversion efficiency of 64.7 % is achieved by the hybrid nanofluid after 1-hour irradiation, which is significantly higher than that of the reported MWCNT-based aqueous nanofluids in the literature. Meanwhile, the mechanism of efficiency enhancement in MWCNT/SiC hybrid nanofluids is analyzed. This study promotes the application of MWCNT/SiC hybrid nanofluids as light-absorbing working fluids in solar collectors.

Studies on Evaluation of the Thermal Conductivity of Alumina Titania Hybrid Suspension Nanofluids for Enhanced Heat Transfer Applications.

Extensive investigations were made and empirical relations were proposed for the thermal conductivity of mono-nanofluids. The effect of concentration, diameter, and thermal properties of participating nanoparticles is missing in the majority of existing thermal conductivity models. An attempt is made to propose a model that considers the influence of such missing parameters on the thermal conductivity of hybrid nanofluids. Al2O3-TiO2 hybrid nanofluids have a 0.1% particle volume concentration prepared with distinct particle volume ratios (k - 1:6 - k, k = 1 to 6) in DI water. The samples were characterized, and the size and shape of the nanoparticles were verified. Also, the influence of varying particle volume ratios and the fluid temperature (varying from 283 to 308 K) were examined. 2.4 and 2.1% enhancements were observed in the thermal conductivity of alumina (5:0) and titania (0:5) nanofluids (having 0.1% volume concentration), respectively. Due to the low thermal conductivity of titania nanoparticles, the conductivity of the hybrid solution is above that of titania and below that of alumina nanofluids. An empirical relation for the thermal conductivity of hybrid nanofluids is established and validated considering the individual particle size, volume ratio, and thermal conductivity of particles.

Comparison of the thermal conductivity of hybrid nanofluids with a specific proportion ratio of MWCNT and TiO2 nanoparticles based on the price performance factor

Comparison of the thermal conductivity of hybrid nanofluids with a specific proportion ratio of MWCNT and TiO2 nanoparticles based on the price performance factor

A case study on analyzing the performance of microplate heat exchanger using nanofluids at different flow rates and temperatures

A microplate heat exchanger is one of the most compact types of heat exchanger used for cooling systems, and not much research was carried out to study the performance of this type of heat exchanger with hybrid nanofluids. In this regard, the performance analysis of the microplate heat exchanger is carried out by estimating the convective heat transfer coefficient in terms of Nusselt number using a hybrid nanofluid. In current research work, Microplate heat exchangers tested using TiO2/ethylene glycol, ZnO/ethylene glycol nanofluids, and a hybrid nanofluid with varied nanoparticle volume fractions. Based on the results, it was found that the thermal conductivity of hybrid nanofluids and the overall heat transfer coefficient by applying hybrid nanofluids show better enhancement than nanofluids. The maximum thermal conductivity ratio between the hybrid nanofluid and the base fluid is 2.10. The maximum Nusselt number of 35.8 was observed for hybrid (TiO2–ZnO/ethylene glycol) at 50 °C and a volume fraction of 4%.

Why can hybrid nanofluid improve thermal conductivity more? A molecular dynamics simulation

It has been widely recognized that the addition of nanoparticles to a base fluid can significantly enhance the thermal conductivity of nanofluids. However, the underlying mechanism is unclear, especially for hybrid nanofluids with nanoparticles composed of two or more materials. This is the first exploration of the microscopic mechanism responsible for the enhancement in the thermal conductivity of hybrid nanofluids. Firstly, the thermal conductivity and diffusion coefficient of Cu-Ag/Ar hybrid nanofluid were estimated by molecular dynamics. The results indicate that the maximum improvement in thermal conductivity of 69.72% can be achieved for a hybrid nanofluid with Cu-Ag 50% /Ar compared to liquid Ar, which is much larger than the 47.95% and 26.4% achieved for Ag/Ar and Cu/Ar nanofluids. Then, the radial distribution function demonstrates that the Ar atoms on the nanoparticle surface are in dynamical equilibrium. Finally, the nanolayer densities and diffusion coefficients are calculated for various hybrid nanofluids to explain the underlying mechanism of the enhancement in the thermal conductivity. The consistency of the thermal conductivity with the nanolayer density and diffusion coefficient indicates that nanolayer structure and diffusion of Ar are the two underneath mechanisms.

REVVING UP HEAT-TRANSFER PERFORMANCE OF DOUBLE PIPE HEAT EXCHANGER USING DIVERSE MOLAR Ag-GO HYBRID NANOFLUIDS: AN EMPIRICAL AND NUMERICAL STUDY USING CENTRAL COMPOSITE DESIGN

This study seamlessly integrates empirical and numerical approaches to enhance the efficiency of a double pipe heat exchanger (DPHX) using varied molar concentrations (0.03, 0.06, and 0.09 M) of Ag-doped GO hybrid nanofluids as the working fluids within the heat exchanger's annulus. Remarkable improvements in the heat exchanger's performance were achieved by increasing the molar concentration of Ag-GO hybrid nanoparticles, along with the Reynolds number (ranging from 250 to 1451) and the mass flow rate (ranging from 8 to 47 g/s) of the hybrid nanofluids. The utilization of a 0.09M Ag-GO hybrid nanofluid at a Reynolds number of 1451 and a flow rate of 47 g/s resulted in outstanding enhancements in heat-transfer coefficient (62.9%), and Nusselt number (33.55%) surpassing the base fluid. The empirical results of Nusselt number and heat-transfer coefficient were optimized and analyzed using the central composite design approach (CCD) with response surface method, incorporating the Graetz number, varied molar concentrations of Ag-GO, and thermal conductivity of the hybrid nanofluids as input factors. The optimized second-order polynomial quadratic equation model demonstrated excellent compatibility and optimal performance of the heat exchanger, supported by variance analysis. Additionally, CCD optimization confirmed a notable desirability function (0.99) and emphasized the significant influence of the input factors on the output responses. In conclusion, the Graetz number exhibited prominent influence among the input factors, alongside the molar concentration and thermal conductivity of hybrid nanofluids, effectively enhancing the performance of the DPHX.

Second law analysis on EMHD with variable viscosity and thermal conductivity of hybrid nanofluid over a rotating disk: an application in solar systems

This current attempt explores the characteristics of variable viscosity and variable thermal conductivity of EMHD flow in which the shape factors like spherical versus laminar is considered for comparison purpose. Also, non-uniform heat source/sink and entropy generation are taken into count. We consider ethylene glycol of 50% and water of 50% mixture as base fluid. To convert the governing equations into ordinary differential equations (ODEs), self-similarity variables are used. The RK Fehlberg method has been used successfully to solve numerical sequential of ODEs. Active parameters such as magnetic field, electric field, Biot number, variable viscosity and variable thermal conductivity parameters are plotted on velocity profile, entropy, temperature and Bejan number. For the variable viscosity and thermal conductivity factors, the temperature rate increases. At the highest values of these parameters, the heat transmission rate is extremely high. This theoretical study is important for solar energy collectors, solar water heaters, solar energy conversion devices, solar PV (Photovoltaic) systems, solar thermal power fabrication, solar thermoelectric cells and radiators, among other things.

Experimental study on the thermal properties of Al 2 O 3 ‐CuO /water hybrid nanofluids: Development of an artificial intelligence model

In this work, Al2O3 and CuO nanoparticles were synthesized by a novel sol-gel method. Then, water-based Al2O3 and Al2O3-CuO (50:50) nanofluids were produced by the two-step method. The viscosity and thermal conductivity of nanofluids were determined for the concentration and temperature range of 0-1.0 vol.% and 30-60°C, respectively. Sodium dodecylbenzene sulfonate surfactant was used to enhance the nanofluid stability. Field emission scanning electron microscopy, transmission electron microscopy, and x-ray diffraction techniques were used for the morphological characterization of the nanoparticles. The pH and zeta potential were used to determine the stability of the nanofluid. The outcomes show that the maximum augmentation in thermal conductivity and viscosity of hybrid nanofluid is 14.6 and 6.5% higher than Al2O3 nanofluid for 1.0 vol.% at 60 and 30°C, respectively. The maximum viscosity enhancement of Al2O3 and hybrid nanofluid is 14.9 and 21.4% is noticed at 30°C for a concentration of 1 vol. % relative to the base liquid. The novel equations were proposed to estimate the viscosity and thermal conductivity of hybrid nanofluid based on the experimental results with R2 values of 0.99 and 0.98, respectively. A cascaded forward neural network model was developed to predict the thermal properties using experimental datasets. The performance enhancement ratio of hybrid nanofluids indicated its potential for solar energy applications.

A Perspective Review on Thermal Conductivity of Hybrid Nanofluids and Their Application in Automobile Radiator Cooling

Hybrid nanofluids developed with the fusion or suspension of two or more different nanoparticles in a mixture as a novel heat transfer fluid are currently of interest to researchers due to their proven better measured thermal conductivities. Several reviewed articles exist on the thermal conductivity of hybrid nanofluids, a vital property for which the heat transfer rate is directly dependent. This review aims to understand the current developments in hybrid nanofluids and their applications. An extensive literature survey was carried out of heuristic-based articles published in the last 15 years. The review reiterates topical research on the preparation methods and ways to improve the stability of readied fluid, thermophysical properties of mixture nanofluids, and some empirical correlations developed for estimating thermal conductivity. Hybrid nanofluid studies on heat transfer performance in automobile radiator cooling systems were also obtained and discussed. The review’s significant findings include the following: (1) hybrid nanofluids produce a noticeable thermal conductivity enhancement and a relatively higher heat transfer coefficient than mono nanofluids and regular liquids. Furthermore, through the uniform dispersion and stable suspension of nanoparticles in the host liquids, the maximum possible thermal augmentation can be obtained at the lowest possible concentrations (by <0.1% by volume). (2) An automobile radiator’s overall heat transfer accomplishment can thus be boosted by using a mixture of nanofluids as conventional coolants. Up-to-date literature results on the thermal conductivity enhancement of mixture fluids are also presented in this study. Nonetheless, some of the barriers and challenges acknowledged in this work must be addressed for its complete deployment in modern applications.

Guideline for selecting appropriate mixing ratio of hybrid nanofluids in thermal management systems

To investigate the effect of different nanoparticles on thermophysical properties of hybrid nanofluids, 15 groups of Al2O3-Cu-CuO/water (W) ternary hybrid nanofluids were prepared with 0.5 vol% and various mixing ratios of components using a two-step method. Moreover, CATREG (Category Regression) and sensitivity analysis were used to analyze the experimental data. The results showed that the contribution of the three particles to viscosity and thermal conductivity were found in the following ascending order: Cu < Al2O3 < CuO and CuO < Cu < Al2O3, respectively. Finally, the CATREG method was used to predict the values of viscosity and thermal conductivity of hybrid nanofluids. The average deviations between the experimental and predicted values were ±2.24% and ±0.53% for viscosity and thermal conductivity, respectively. The optimum mixing ratio of Al2O-Cu-CuO/W hybrid nanofluid was determined to be 20:50:30 for application in laminar and turbulent convective heat transfer applications.

The analogy of nanoparticle shapes on the theory of convective heat transfer of Au–Fe3O4 Casson hybrid nanofluid

AbstractIn recent times, Au nanoparticles have been commonly used for delivering the drug especially in the case of hypothermia of tumors, but low absorption of IR light does not solve destruction of tumor cells. However, nanoparticles such as Fe3O4 coated with Au could be used to deliver the drug to a specific spot due to applied external magnetic field. Due to these applications, boundary layer approximation is invoked to simplify the mathematical model. This paper presents the nanoparticle shape analysis and heat transfer features of the Au–Fe3O4–blood hybrid nanofluid flowing past a stretching surface on a magnetohydrodynamic medium. Numerical solutions of nonlinear differential equations are obtained by RKF‐45 method with the help of shooting technique. The behavior of emerging parameters is described graphically for velocity and temperature profiles. It is found that the blade‐shaped Au and Fe3O4 nanoparticles have better thermal conductance than brick, sphere, cylinder, needle, and platelet shapes. It is also observed that the Lorentz force generated due to magnetic field helps in controlling the flow and enhance the thermal conductivity of hybrid nanofluid.

Entropy generation minimization E.G.M. analysis of free convective hybrid nanofluid flow in a corrugated triangular annulus with a central triangular heater

All heat transfer phenomena are always escorted with entropy production and hence destruct the available work and energy resources. One way to minimize valuable energy rescores, especially in convective heat transfer augmentation situations, is to develop a thermal design that reduces the temperature differences inside the system and thus the entropy generation. This study analyzes an optimal thermal design for an augmented free convective situation considering a hybrid nanofluid flow in a corrugated triangular annulus heated by an underneath partial heater. Three approaches are applied to reduce entropy production: the corrugated walls, an inner heater at a lower non-uniform temperature, and the magnetic field effects. A numerical solution is presented for the normalized governing equations by a finite element method. A comparison with previously published investigation confirms the validity of results. The study reveals the influential role of the presented design in reducing entropy production due to the higher thermal conductivity of hybrid nanofluid. It is noticed that if the inner triangular body is heated at uniform or non-uniform temperature, keeping the magnitude of temperature lesser than the bottom heat source, the overall entropy significantly reduces. Moreover, overall, entropy is minimized if, instead of flat walls, corrugated walls are considered.

Investigation of the Thermal Conductivity, Viscosity, and Thermal Performance of Graphene Nanoplatelet-Alumina Hybrid Nanofluid in a Differentially Heated Cavity

This paper investigates the thermophysical properties and heat transfer performance of graphene nanoplatelet (GNP) and alumina hybrid nanofluids at different mixing ratios. The electrical conductivity and viscosity of the nanofluids were obtained at temperatures between 15–55°C. The thermal conductivity was measured at temperatures between 20–40°C. The natural convection properties, including Nusselt number, Rayleigh number, and heat transfer coefficient, were experimentally obtained at different temperature gradients (20, 25, 30, and 35°C) in a rectangular cavity. The Mouromtseff number was used to theoretically estimate all the nanofluids’ forced convective performance at temperatures between 20–40°C. The results indicated that the thermal conductivity and viscosity of water are increased with the hybrid nanomaterial. On the other hand, the viscosity and thermal conductivity of the hybrid nanofluids are lesser than that of mono-GNP nanofluids. Notwithstanding, of all the hybrid nanofluids, GNP-alumina hybrid nanofluid with a mixing ratio of 50:50 and 75:25 were found to have the highest thermal conductivity and viscosity, enhancing thermal conductivity by 4.23% and increasing viscosity by 15.79%, compared to water. Further, the addition of the hybrid nanomaterials improved the natural convective performance of water while it deteriorates with mono-GNP. The maximum augmentation of 6.44 and 10.48% were obtained for Nuaverage and haverage of GNP-Alumina (50:50) hybrid nanofluid compared to water, respectively. This study shows that hybrid nanofluids are more effective for heat transfer than water and mono-GNP nanofluid.

Non-Fourier thermal and mass transport in hybridnano-Williamson fluid under chemical reaction in Forchheimer porous medium

Williamson stress-strain correlations are shear rate dependent correlations and describe the rheology of various polymers. In this article, generalized non-Fourier models are utilized here in this investigation to study heat and mass transport in Williamson fluid. The effect of a suspension of nano-sized hybrid particles on the thermal efficiency of the MoS2−SiO2−Williamson fluid is also examined. The Williamson fluid is assumed to exhibit thermal relaxation behavior due to which fluid avoids thermal changes in order to maintain its thermal equilibrium. Due to this characteristics fluid exhibits a decrease in its temperature field when thermal relaxation times of MoS2−SiO2−Williamson fluid and MoS₂-Williamson fluid. Simulations have shown that MoS₂-Williamson fluid has thermal relaxation time greater than the thermal relaxation time of MoS₂-SiO₂-Williamson fluid. Darcy and Forchheimer porous media are responsible for controlling boundary layer region due to the resistive force among the fluid particles and porous medium.Simulations can also be used to compare the resistive force exerted by the Darcy and Forchheimer porous medium. In terms of managing the momentum boundary layer, Forchheimer porous media is determined to be more effective than Darcy porous medium. Shear thinning and shear thickening behavior have significant decreasing and increasing impacts on the motion of fluid particles, respectively. It is also found from numerical simulations that effective thermal conductivity of hybrid nanofluid (MoS2−SiO2−Williamson fluid) than that of mono nanofluid (MoS₂-Williamson fluid). As a result, hybrid nanofluid is proposed for enhanced heat energy transmission. It's also discovered that hybrid nanofluid generates less heat than mono nanofluid. Solutal relaxation time (relaxation time associated with solute transport) has shown decreasing impact on concentration field. The solutal relaxation period of a MoS2−SiO2−polymers is longer than that of a MoS₂-polymer, according to numerical experiments. In both MoS₂-polymer and MoS2−SiO2−polymers, the influence of destructive chemical reactions on mass transport is the polar opposite of the impact of generative chemical reactions on mass transport in both types of fluid regimes. The effect of generative chemical reactions on mass mobility is analogous to the effect of heat generation on temperature. In a hybrid nanofluid, heat and mass fluxes are higher than in a mono nanofluid. Thus if hybrid nanofluid rather than mono nanofluid, for cooling systems as heat conducting material (working fluid) then efficiency of cooling system will be much improved.