Search Results (20)

In this paper, we consider the flow of a nanofluid in an enclosed lid-driven cavity using a single-phase model. Two cases are considered: one in which the top and bottom walls are kept at adiabatic conditions, and a second case in which the left- and right-side walls are kept in adiabatic conditions. The impact of different viscosity models on the mixed convection heat transfer is examined, and numerical methods are used to obtain solutions for the Navier–Stokes equations for various parameter ranges. Using our robust methods, we are able to obtain novel solutions for large Reynolds numbers and very small Richardson numbers. Using water as the base fluid and aluminium oxide nanoparticles, our results suggest that heat transfer enhancement occurs with increasing particle concentration and decreasing Richardson numbers. There are also significant differences depending on the viscosity model used in terms of the impact of reducing corner recirculation regions in the cavity. Full article

Hybrid nanofluids contain more than one type of nanoparticle and have shown improved thermofluidic properties compared to more conventional ones that contain a single nanocomponent. Such hybrid systems have been introduced to improve further the thermal and mass transport properties of nanoparticulate systems that affect a multitude of applications. The impact of a second particle type on the effective thermal conductivity of nanofluids is investigated here using the reconstruction of particle configurations and prediction of thermal efficiency with meshless methods, placing emphasis on the role of particle aggregation. An algorithm to obtain particle clusters of the core–shell type is presented as an alternative to random mixing. The method offers rapid, controlled reconstruction of clustered systems with tailored properties, such as the fractal dimension, the average number of particles per aggregate, and the distribution of distinct particle types within the aggregates. The nanoparticle dispersion conditions are found to have a major impact on the thermal properties of hybrid nanofluids. Specifically, the spatial distribution of the two particle types within the aggregates and the shape of the aggregates, as described by their fractal dimension, are shown to affect strongly the conductivity of the nanofluid even at low volume fractions. Cluster configurations made up of a high-conducting core and a low-conducting shell were found to be advantageous for conduction. Low fractal dimension aggregates favored the creation of long continuous pathways across the nanofluid and increased conductivity. Full article

This study reports an experimental investigation of pool boiling (PB) heat transfer performance of hybrid (two types of particles) and mono (single-particle) nanofluids consisting of Boron nitride (BN) and Silicon dioxide (SiO₂) nanoparticles (NPs). While hybrid nanofluids (HNFs) were prepared in a total particle concentration of 0.05 vol.% with four different percentages of these two types of NPs (are 0.01/0.04, 0.02/ 0.03, 0.03/0.02, and 0.04/0.01 (BN vol.%/SiO₂ vol.%)), two mono nanofluids (MNFs) of BN and SiO₂ nanoparticles were prepared at the same total concentration of 0.05 vol.% for each NP type. Both nanofluids (NFs) were prepared in the base fluid (BF), which is the mixture of 15 vol.% of ethylene glycol (EG) and 85 vol.% of distilled water (DW). Then, the boiling heat transfer performance of these MNFs and HNFs was assessed by experimentation in a pool boiling test rig. The obtained results demonstrated good improvements in critical heat flux (CHF) and burnout heat flux (BHF) of both types of NFs. The CHF increased by up to 80% for BN-based MNF and up to 69% for HNF at 0.04 vol.% BN, which is the maximum percentage of BN into HNF, while the lowest improvement in CHF was 48% for the SiO₂-based MNF compared to the BF. Similarly, the BHF was found to increase with the increasing in the loading of BN nanoparticles and a maximum enhancement of BHF of 103% for BN-based MNF was observed. These HNFs and MNFs exhibited significantly improved pool boiling heat transfer performance compared to this BF, and it became lower by increasing the percentage of SiO₂ NPs in the HNFs. Full article

In the present study, the thermal conductivity of two distinct water-based nanofluids of single-walled CNTs and Al₂O₃, as well as their hybrid solution, was investigated experimentally. The Al₂O₃ and CNTs nanoparticle concentrations are taken to be 2%v/v, while the hybrid solution contained 2%v/v of both Al₂O₃ and CNTs nanoparticles. A PSS (Polly styrene sulphonic acid) solution was used as a surfactant to increase the suspension time of the nanoparticles to avoid sedimentation. The dispersion and breaking of the particles of CNT and Al₂O₃ into nano size were performed employing a probe sonicator and bath sonicator. Moreover, a hot plate magnetic stirrer was used to obtain a consistent liquid mixture. The experiments are performed on the Computer Controlled Thermal Conductivity of Liquid and Gases (TCLGC) unit available in the heat transfer lab at GIKI. The results concluded that the thermal conductivity of water-based single-walled CNT nanofluids was higher compared to Al₂O₃ and their hybrid solution. Therefore, Al₂O₃ and a hybrid solution are less desirable for thermal conduction compared to CNTs. Full article

Nanofluids have attracted significant attention from researchers due to their ability to significantly enhance heat transfer, especially in jet impingement flows, which can improve their cooling performance. However, there is a lack of research on the use of nanofluids in multiple jet impingements, both in terms of experimental and numerical studies. Therefore, further investigation is necessary to fully understand the potential benefits and limitations of using nanofluids in this type of cooling system. Thus, an experimental and numerical investigation was performed to study the flow structure and heat transfer behavior of multiple jet impingement using MgO-water nanofluids with a 3 × 3 inline jet array at a nozzle-to-plate distance of 3 mm. The jet spacing was set to 3, 4.5, and 6 mm; the Reynolds number varies from 1000 to 10,000; and the particle volume fraction ranges from 0% to 0.15%. A 3D numerical analysis using ANSYS Fluent with SST k-ω turbulent model was presented. The single-phase model is adopted to predict the thermal physical nanofluid. The flow field and temperature distribution were investigated. Experimental results show that a nanofluid can provide a heat transfer enhancement at a small jet-to-jet spacing using a high particle volume fraction under a low Reynolds number; otherwise, an adverse effect on heat transfer may occur. The numerical results show that the single-phase model can predict the heat transfer trend of multiple jet impingement using nanofluids correctly but with significant deviation from experimental results because it cannot capture the effect of nanoparticles. Full article

The wide variety of uses for nanoparticles (NPs) is due to their unique combination of features in a single assembly. The arc melted copper-cobalt ingot sample were qualitatively studied using laser induced breakdown spectroscopy (LIBS). Later, using the fabricated alloy as a target material for Nd:YAG laser ablation, CuCo₂O₄ NPs were synthesized. The magnetic properties of the synthesized NPs were studied using a vibrating sample magnetometer (VSM). To determine the composition and morphology of the synthesized NPs, X-ray diffraction (XRD), energy dispersive X-ray (EDX) analysis, transmission electron microscopy (TEM), scanning electron microscopy (SEM), and dynamic light scattering (DLS) techniques were used. The TEM and DLS showed that particles were spherical in shape with an average size of 32 nm and 28 nm, respectively. The antibacterial activity of the synthesized NPs was studied against S. aureus and E. coli strains as positive and negative controls using a standard approach. CuCo₂O₄ nanoparticles exhibited non-mutagenic potential against S. typhimurium TA-98 and TA-100 strains. Furthermore, the magnetic hyperthermia study of CuCo₂O₄ nanofluid was examined using a lab-made apparatus. The specific absorption rates (SAR) of 4.57 and 5.17 W/g were determined for the magnetic field strength of 230 μT and 247 μT, respectively. The study shows antibacterial activity and magnetic hyperthermia potential of the synthesized nanoparticles. Full article

A numerical simulation of convective heat transfer coefficient (h_conv) was studied with Cu-Water and TiO₂-Water nanofluids flowing through a circular tube subjected to uniform wall heat flux boundary conditions under laminar and turbulent regimes. Four different concentrations of nanofluids (ɸ = 0.5, 1, 1.5 and 2%) were used for the analysis and the Reynolds number (Re) was varied from laminar (500 to 2000) to turbulent flow regime (5000 to 20,000). The dependence of h_conv on Re and ɸ was investigated using a single-phase Newtonian approach. In comparison to base fluid, average h_conv enhancements of 10.4% and 7.3% were noted, respectively, for the maximum concentration (ɸ = 2%) and Re = 2000 for Cu-Water and TiO₂—water nanofluids in the laminar regime. For the same ɸ under the turbulent regime (Re = 20,000), the enhancements were noted to be 14.6% and 13.2% for both the nanofluids, respectively. The random motion (Brownian motion) and heat diffusion (thermophoresis) by nanosized particles are the two major slip mechanisms that have more influence on the enhancement of h_conv. In addition, the Nusselt number (Nu) of the present work was validated for water with the Shah and Dittus Boelter equation and found to have good agreement for both the regimes. Full article

This study reports the thermal performance of Al₂O₃ and TiO₂ nanofluids (NFs) flowing inside a compact plate heat exchanger (CPHE) by comparing the experimental and numerical investigations. The NF samples were prepared for five concentrations each of Al₂O₃ and TiO₂ nanoparticles dispersed in distilled water (DW) as a base fluid (BF). The stability of NF samples was ensured, and their viscosity and thermal conductivity were measured. Firstly, the experimental measurements were performed for the heat transfer and fluid flow of the NFs in the plate heat exchanger (PHE) system and then the numerical investigation method was developed for the same PHE dimensions and operation conditions of the experimental investigation. A finite volume method (FVM) and single-phase fluid were used for numerical modelling. The obtained experimental and numerical results show that the thermal performance of the CPHE enhances by adding nanoparticles to the BFs. Furthermore, numerical predictions present lower values of convection heat transfer coefficients than the experimental measurements with a maximum deviation of 12% at the highest flow rate. Nevertheless, the numerical model is suitable with acceptable accuracy for the prediction of NFs through PHE and it becomes better for relatively small particles’ concentrations and low flow rates. Full article

The light scattering properties of particles play important roles in radiative transfer in many dispersed systems, such as turbid atmosphere, ocean water, nanofluids, composite coatings and so on. As one of the scattering property parameters, the scattering phase functions of particles are strongly dependent on the particle size, size distribution, and morphology, as well as on the complex refractive indices of the particles and surrounding media. For the sake of simplicity, the empirical phase function models are widely used in many practical applications. In this work, we focus on the radiative transfer problem in dispersed systems composed of spherical particles, and give quantitative analyses of the impact of scattering phase functions on the radiative transfer process. We fit the scattering phase functions of four different types of practical dispersed systems using four previously proposed empirical phase function models, including the Henyey–Greenstein (HG) model, Cornette Shanks (CS) model, Reynold and McCormick (RM) model and two-term Reynolds–McCormick (TTRM) model. By comparing the radiative transfer characteristics (i.e., hemispherical reflectance, hemispherical transmittance and total absorptance) of dispersed layers calculated using the Monte Carlo method, the relative errors caused by using the empirical phase functions are systematically investigated. The results demonstrate that the HG, CS and RM models cause obvious errors in the calculation of hemispherical reflectance in many cases. Meanwhile, the induced errors show no obvious regularity, but are related to the particle size and layer optical thickness. Due to the good fitting effect in both forward and backward directions, the TTRM model provides significantly higher performances in fitting the phase functions of all considered cases than the widely used single-term parametrizations. Moreover, for different particle sizes and layer optical thicknesses, the induced errors of the TTRM model in radiative transfer characteristics are very small, especially for the case of polydisperse particles. Our results can be used to guide the design, analysis and optimization of dispersed systems in practical optics and photonics applications. Full article

Parabolic trough solar collectors (PTSCs) are generally utilized to reach high temperatures in solar-thermal applications. The current work investigates entropy production analysis and the influence of nano solid particles on a parabolic trough surface collector (PTSC) installed within a solar powered ship (SPS). For the current investigation, the non-Newtonian Maxwell type, as well as a porous medium and Darcy–Forchheimer effects, were used. The flow in PTSC was produced by a nonlinear stretching surface, and the Cattaneo–Christov approach was used to assess the thermal boundary layer’s heat flux. Similarity transformation approach has been employed to convert partial differential equations into solvable ordinary differential equations allied to boundary conditions. Partial differential and the boundary conditions have been reduced into a group of non-linear ordinary differential equations. A Keller-box scheme applied to solve approximate solutions of the ordinary differential equations. Single-walled carbon nanotubes -engine oil (SWCNT-EO) and Multiwalled carbon nanotubes/engine oil (MWCNT-EO) nanofluids have been utilized as working fluid. According to the findings, the magnetic parameter led to a reduction in the Nusselt number, as well as an increment in skin friction coefficient. Moreover, total entropy variance over the domain enhanced for flow rates through Reynolds number and viscosity fluctuations were monitored by using Brinkman number. Utilizing SWCNT-EO nanofluid increased the thermal efficiency between 1.6–14.9% in comparison to MWCNT-EO. Full article

The improvement in the quantitative and qualitative heat transfer performances of working fluids is trending research in the present time for heat transfer applications. In the present work, the first and second law analyses of a microplate heat exchanger with single-particle and hybrid nanofluids are conducted. The microplate heat exchanger with single-particle and hybrid nanofluids is analyzed using the computational fluid dynamics approach with symmetrical heat transfer and fluid flow analyses. The single-particle Al₂O₃ nanofluid and the hybrid Al₂O₃/Cu nanofluid are investigated for different nanoparticles shapes of sphere (Sp), oblate spheroid (OS), prolate spheroid (PS), blade (BL), platelet (PL), cylinder (CY) and brick (BR). The first law characteristics of NTU, effectiveness and performance index and the second characteristics of thermal, friction and total entropy generation rates and Bejan number are compared for Al₂O₃ and Al₂O₃/Cu nanofluids with considered different-shaped nanoparticles. The OS- and PL-shaped nanoparticles show superior and worse first and second law characteristics, respectively, for Al₂O₃ and Al₂O₃/Cu nanofluids. The hybrid nanofluid presents better first and second law characteristics compared to single-particle nanofluid for all nanoparticle shapes. The Al₂O₃/Cu nanofluid with OS-shaped nanoparticles depicts maximum values of performance index and Bejan number as 4.07 and 0.913, respectively. The first and second law characteristics of the best combination of the Al₂O₃/Cu nanofluid with OS-shaped nanoparticles are investigated for various volume fractions, different temperature and mass flow rate conditions of hot and cold fluids. The first and second law characteristics are optimum at higher hot fluid temperature, lower cold fluid temperature, lower hot and cold fluid mass flow rates. In addition, the first and second law characteristics have improved with increase in volume fraction. Full article

In the present study, the heat transfer characteristics, namely, heat transfer coefficient, Nusselt number, pressure drop, friction factor and performance evaluation criteria are evaluated for water, Al₂O₃ and Al₂O₃/Cu nanofluids. The effects of Reynolds number, volume fraction and composition of nanoparticles in hybrid nanofluid are analyzed for all heat transfer characteristics. The single particle and hybrid nanofluids are flowing through a plain straight tube which is symmetrically heated under uniform heat flux condition. The numerical model is validated for Nusselt number within 7.66% error and friction factor within 8.83% error with corresponding experimental results from the previous literature study. The thermophysical properties of hybrid nanofluid are superior to the single particle nanofluid and water. The heat transfer coefficient, Nusselt number and pressure drop show increasing trend with increase in the Reynolds number and volume fraction. The friction factor shows the parabolic trend, and the performance evaluation criteria shows small variations with change in Reynolds number. However, both friction factor and performance evaluation criteria have increased with increase in the volume fraction. The 2.0% Al₂O₃/Cu with equal composition of both nanoparticles (50/50%) have presented superior heat transfer characteristics among all working fluids. Further, the heat transfer characteristics of 2.0% Al₂O₃/Cu hybrid nanofluid are enhanced by changing the nanoparticle compositions. The performance evaluation criteria for 2.0% Al₂O₃, 2.0% Al₂O₃/Cu (50/50%), 2.0% Al₂O₃/Cu (75/25%) and 2.0% Al₂O₃/Cu (25/75%) are evaluated as 1.08, 1.11, 1.10 and 1.12, respectively. Full article

Single and double impinging jets heat transfer of non-Newtonian power law nanofluid on a partly curved surface under the inclined magnetic field effects is analyzed with finite element method. The numerical work is performed for various values of Reynolds number (Re, between 100 and 300), Hartmann number (Ha, between 0 and 10), magnetic field inclination ($\gamma$, between 0 and 90), curved wall aspect ratio ($AR$, between 01. and 1.2), power law index (n, between 0.8 and 1.2), nanoparticle volume fraction ($\varphi$, between 0 and 0.04) and particle size in nm ($dp$, between 20 and 80). The amount of rise in average Nusselt (Nu) number with Re number depends upon the power law index while the discrepancy between the Newtonian fluid case becomes higher with higher values of power law indices. As compared to case with n = 1, discrepancy in the average Nu number are obtained as $-38\%$ and 71.5% for cases with n = 0.8 and n = 1.2. The magnetic field strength and inclination can be used to control the size and number or vortices. As magnetic field is imposed at the higher strength, the average Nu reduces by about 26.6% and 7.5% for single and double jets with n greater than 1 while it increases by about 4.78% and 12.58% with n less than 1. The inclination of magnetic field also plays an important role on the amount of enhancement in the average Nu number for different n values. The aspect ratio of the curved wall affects the flow field slightly while the average Nu variation becomes 5%. Average Nu number increases with higher solid particle volume fraction and with smaller particle size. At the highest particle size, it is increased by about 14%. There is 7% variation in the average Nu number when cases with lowest and highest particle size are compared. Finally, convective heat transfer performance modeling with four inputs and one output is successfully obtained by using Adaptive Neuro-Fuzzy Interface System (ANFIS) which provides fast and accurate prediction results. Full article

This review was focused on expressing the effects of base liquid, temperature, possible surfactant, concentration and characteristics of nanoparticles including size, shape and material on thermal conductivity and viscosity of nanofluids. An increase in nanoparticle concentration can lead to an increase in thermal conductivity and viscosity and an increase in nanoparticle size, can increase or decrease thermal conductivity, while an increase in nanoparticle size decreases the viscosity of the nanofluid. The addition of surfactants at low concentrations can increase thermal conductivity, but at high concentrations, surfactants help to reduce thermal conductivity of the nanofluid. The addition of surfactants can decrease the nanofluid viscosity. Increasing the temperature, increased the thermal conductivity of a nanofluid, while decreasing its viscosity. Additionally, the effects of material of nanoparticles on the thermal conductivity and viscosity of a nanofluid need further investigations. In the case of hybrid nanofluids, it was observed that nanofluids with two different particles have the same trend of behavior as nanofluids with single particles in the regard to changes in temperature and concentration. Additionally, the level of accuracy of existing theoretical models for thermal conductivity and viscosity of nanofluids was examined. Full article

The practical implication of nanofluids is essentially dependent on their accurate modelling, particularly in comparison with the high cost of experimental investigations, yet the accuracy of different computational approaches to simulate nanofluids remains controversial to this day. Therefore, the present study is aimed at analysing the homogenous, multiphase Eulerian–Eulerian (volume of fluid, mixture, Eulerian) and Lagrangian–Eulerian approximation of nanofluids containing nonspherical nanoparticles. The heat transfer and pressure drop characteristics of the multiwalled carbon nanotubes (MWCNT)-based and multiwalled carbon nanotubes/graphene nanoplatelets (MWCNT/GNP)-based nanofluids are computed by incorporating the influence of several physical mechanisms, including interfacial nanolayering. The accuracy of tested computational approaches is evaluated by considering particle concentration and Reynolds number ranges of 0.075–0.25 wt% and 200–470, respectively. The results demonstrate that for all nanofluid combinations and operational conditions, the Lagrangian–Eulerian approximation provides the most accurate convective heat transfer coefficient values with a maximum deviation of 5.34% for 0.25 wt% of MWCNT–water nanofluid at the largest Reynolds number, while single-phase and Eulerian–Eulerian multiphase models accurately estimate the thermal fields of the diluted nanofluids at low Reynolds numbers, but overestimate the results for denser nanofluids at high Reynolds numbers. Full article