The rapid rate of improvement in electronic devices has led to an increased demand for effective cooling techniques. The purpose of this study is to investigate the heat transfer characteristics of an aluminum metallic foam for use with an Intel core i7 processor. The metal foams used have a porosity of 0.91 and different permeabilities ranging from 10 pores per inch (PPI) to 40 PPI. The flow rate at the entrance of the porous cavity varied from 0.22 USGPM to 0.1 USGPM. The fluid consists of water with aluminum nanoparticles having a concentration from 0.1% to 0.5%. The heat fluxes applied at the bottom of the porous test cell vary from 13.25 W/cm 2 to 8.34 W/cm 2 . It has been observed that nanofluid and forced convection improves heat extraction. These observations lead to the conclusion that heat enhancement is possible with nanofluid and it is enhanced further in the presence of a high flow rate. However, it was detected experimentally, verified numerically, and agreed upon by different researchers that higher heat extraction is found for a nanofluid concentration of 0.2%. This observation is independent of the porous permeability or applied heat flux. It has also been shown that heat enhancement in the presence of nanofluid is evident, when experimental results were compared to water.

A numerical investigation on the transient free convection flow of the multi-phase nanofluid past a vertical cylinder, which has a power-law variation surface temperature along with the height is presented. The problem has typical engineering applications involving cooling of vertical cylindrical rods in mechanical/manufacturing systems, cooling of nuclear reactors and the design of other advanced cooling technologies. Buongiorno's model is applied in this research, which incorporates thermophoresis and Brownian diffusion effects of nanoparticles. The zero-volume flux condition is implemented for nanoparticle concentration at the boundary to obtain realistic results. A robust second-order accurate finite-difference scheme of Crank-Nicolson type is applied to tackle the system of coupled non-linear partial differential equations numerically. The impacts of time, variable surface temperature power-law exponent, Brownian and thermophoresis parameters are investigated on nanofluid flow and heat transfer aspects. The decisive finding suggests that the effect of the power-law exponent of the variable wall temperature is to reduce the nanoparticle relocation, velocity, and temperature in the nanofluid boundary layer causing the heat transfer enhancement. The skin-friction decreased significantly with the rise of the power-law exponent of the wall temperature. The present numerical scheme is corroborated by comparing the average skin-friction results with the available literature for clear fluid.

In this paper, steady natural convective heat transfer and flow characteristics of Al 2 O 3 -Cu/water hybrid nanofluid filled square enclosure in the presence magnetic field has been investigated numerically. The enclosure is equipped with a wavy circular conductive cylinder. The convection in the cavity is induced by a temperature difference between the vertical left hot wall and the other right cold wall. The steady 2D equations of laminar natural convection problem for Newtonian and incompressible mixture are discretized using the finite volume method. The effective thermal conductivity and viscosity of the hybrid nanofuid are calculated using Corcione correlations taking into consideration Brownian motion of nanoparticles. A numerical parametric investigation is carried out for different values of the nanoparticles volumic concentration, Hartmann number, Rayleigh number, and the ratio of fluid to solid thermal conductivities. According to the results, the corrugated conductive block plays an important role in controlling the convective flow characteristic and the heat transfer rate within the system.

The present discussion concerns some doubtful results included in the above paper.

As conduction, convection, and radiation are fundamental modes of heat emitter and transfer, this paper looks at the influences of temperature-dependent thermal conductivity and thermal radiation on peristaltic flow of pseudoplastic nanofluids in an inclined non-uniform asymmetric channel. Inclined magnetic field is taken into consideration. As the Wiedemann–Franz law in metals, electrical conductivity has identical behavior as that of thermal conductivity; as freely animated evenness, electrons transfer not only electric current but also heat energy. Consequently, electrical conductivity should be depending on the temperature of nanoparticles. The related equations of momentum, mass, and concentration are reformulated using lubrication approximations (i.e., tiny or zero Reynolds number and long wavelength). The resulting system of nonlinear equations is solved semi-numerically with the aid of the parametric ND solve package using mathematica version 11. Results of velocity, temperature, and concentration distributions are obtained in the analytical three-dimensional forms. The streamline graphs are offered in the terminus, which elucidate the trapping bolus phenomenon. As a special case, a comparison is made and signified with the recently published results by Hayat et al. (2016, Soret and Dufour Effects in MHD Peristalsis of Pseudoplastic Nanofluid With Chemical Reaction,” J. Mol. Liq., 220, pp. 693–706). It's found that, the increases in thermal conductivity and electrical conductivity cause an increase in the temperature of nanofluid and the heat transfer rate gets induced so a better absorption of solar energy is gained.

The paper presents an entropy generation minimization study for a solar parabolic trough collector (PTC) operating with SiO 2 -water nanofluid using a genetic algorithm (GA), and artificial neural network (ANN). The characteristic variables of nanoparticle volumetric concentration (0.01 ≤ φ ≤ 0.05), mass flow rate (0.1≤ ṁ ≤ 1.1 kg/s), and inlet temperatures (350–550 K) are used to analyze the rate of entropy generated in the PTC. GA is used in optimizing the entropy generation rate for the specified parameters, while ANN is used for predicting and observing the behaviour of these parameters on the rate of entropy generation in the collector. The optimum ANN model is derived with one hidden layer of 18 neurons when training the input variables for the entropy generation predictions. The optimal mean square error used as a performance validation of the model is 0.02288 for training and 0.0282 for testing with an R 2 value of 0.9999. The impact of the defined parameters on the entropy generation rate is presented in the results section. It is concluded that machine learning techniques can be an efficient tool for predicting the rate of entropy generation in a collector within the constraint of the defined parameters.

While a number of liquids are preferred in many heating and cooling applications, their thermal capacity can be a limiting factor in many thermal systems. Therefore, a series of methods such as use of mixtures of two or more fluids, emulsions, phase change materials, and more recently nanoparticle enriched fluids have been proposed. The impact of adding aluminum and copper nanoparticles to water in a closed-loop radiator has been investigated analytically and numerically. Heat transfer performances of different working fluids are studied under the same boundary conditions. The analytical and numerical models including external and internal flow domains of the radiator have been developed, and free convection air cooling has been considered over external surfaces of a radiator. Both plain and nanoparticle added fluid cases are analyzed individually to differentiate the impact over heat transfer. The results indicate that the presence of nanoparticles effectively raised the convective heat transfer coefficient and thus the performance of the radiator system increased by 2.1% and 0.6%, respectively, in comparison to plain water operating condition. Furthermore, the radiator tube length has been shortened by 2.0% and 0.75% for both Al and Cu nanoparticle filled fluid, respectively, to obtain the same thermal performance at a single tube. The total required heat transfer surface area is also reduced by 2.0% and 1.15% for Al and Cu, respectively. Finally, a comparison between analytical and numerical models has been found to be in a good agreement of heat transfer coefficient and Nusselt number.

This article presents the generalization of the unsteady MHD free convection flow of non-Newtonian sodium alginate-ferrimagnetic nanofluid in two infinite vertical parallel plates. The different shape (blade, brick, cylinder, and platelet) ferrimagnetic nanoparticles are dissolved in the non-Newtonian sodium alginate (SA) as base fluid to form non-Newtonian nanofluids. The Jeffrey fluid model together with energy equation is considered to demonstrate the flow. The Atangana–Baleanu fractional operator is utilized for the generalization of mathematical model. The Laplace transform technique and Zakian's numerical algorithm are used to developed general solutions with a fractional order for the proposed model. The obtained results are computed numerically and presented graphically to understand the physics of pertinent flow parameters. It is noticed that the velocity and temperature profiles are significantly increased with the increasing values of the fractional parameter due to the variation in thermal and momentum boundary layers. In the case of the effect of different shapes of nanoparticles, density is a dominant factor as compared to thermal conductivity, which significantly affects the flow of non-Newtonian nanofluid.

The transient mixed convection boundary layer analysis of incompressible flow over an isothermal vertical cylinder is embedded in a saturated porous medium in the vicinity for Gyrotactic microorganism effects. The mathematical model used for the bioconvective nanofluid incorporates the effects of Brownian motion, thermophoresis, and gyrotactic microorganisms. Moreover, the resulting governing nonsimilarity equations are changed into partial differential equations and solved numerically. The results are explained graphically for various physical parameters. It is determined that bioconvection parameter boosts the heat transfer rates and the thickness of the motile microorganism reduces the mass transfer rates. Expanding bioconvection Lewis number leads to decrease in heat transfer rates and the density of the motile microorganism, whereas the mass transfer rates decelerate the flow field. The investigation is pertinent to the nanobiopolymer manufacturing processes.

In this paper, experimental investigation has been performed to characterize the heat transfer behavior of CuO–water and ZnO–water nanofluids. Nanofluids containing different volume percent (vol %) of nanoparticle concentrations flowed over a flat copper plate under a constant heat load. The constant heat flux was maintained using evenly placed cartridge heaters. The heat transfer coefficients of nanofluids were measured and compared with the results obtained from identical experiments performed with de-ionized (DI) water. In order to thoroughly characterize the nanofluids, nanoparticle size was investigated to inspect for possible agglomeration. The particle size was measured by using both a transmission electron microscope (TEM) and a dynamic light scattering system (DLS). Enhancement of convective heat transfer of nanofluids was 2.5–16% depending on the nanoparticle concentrations and Reynolds number. The plausible mechanisms of the enhanced thermal performance of CuO and ZnO nanofluids will be discussed in the following paper.

Stability analysis for the Walters-B model saturated with permeable nanofluid is taken under study including cross diffusion effects. The porous medium is defined using modified Darcy model, and the nanofluid is considered to have the impact of thermophoresis and Brownian motion. The thermal energy equation includes the effects of diffusion and also cross diffusion. For the study of linear theory, normal mode procedure is applied and to understand the nonlinear theory, the method of minimal representation of double Fourier series is utilized. The effects of nondimensional parameters such as concentration Rayleigh number, Lewis number, Soret and Dufour parameters, Solutal Rayleigh number, elastic parameter, Prandtl number, viscosity ratio, and conductivity ratio on the stationary and oscillatory convections are represented graphically. The effect of time on transient Nusselt numbers is also taken under investigation. It is concluded that when time is small, the three Nusselt numbers oscillate for all the governing parameters and approach to steady-state as time increases.

Different-radius of curvature pipes are experimentally investigated using distilled water and Fe 3 O 4 –water nanofluid with two different values of the nanoparticle volume fraction as the working fluids. The mass flow rate is approximately varied from 0.2 to 0.7 kg/min (in the range of laminar flow); the wall heat flux is nearly kept constant. The experimental results reveal that utilizing the nanofluid increases the convection heat transfer coefficient and Nusselt number in comparison to water; these outcomes are also observed when the radius of curvature is decreased and/or the mass flow rate is increased (equivalently, a rise in Dean number). The resultant pressure gradient is, however, intensified by an increase in the volume concentration of nanoparticles and/or by a rise in Dean number. For any particular working fluid, there is an optimum mass flow rate, which maximizes the system efficiency. The overall efficiency can be introduced to include hydrodynamic as well as thermal characteristics of nanofluids in various geometrical conditions. For each radius of curvature, the same overall efficiency may be achieved for two magnitudes of nanofluid volume concentration.

The mixed convective heat transfer of a micropolar nanofluid in a square lid-driven cavity has been numerically studied. The lid is thermally insulated, the side walls are kept cold, and the bottom wall is kept hot with sinusoidally thermal boundary condition. The governing equations were solved by finite volume method using the SIMPLE algorithm. The effect of Grashof number (10 2 –10 5 ), the volume fraction of nanoparticles (0.0–0.1), and micropolarity (0.0–2.0) has been investigated on the heat transfer of Al 2 O 3 –water nanofluid. Also, the variable model was used to calculate fluid viscosity and thermal conductivity coefficient of the nanofluid. The results showed that an increase in Grashof amplifies the buoyancy force and enhances the Nusselt number. Also, an increase in vortex viscosity at low Grashof numbers strengthens the forced convection and increases the Nusselt number over the bottom wall. However, at Gr = 10 5 , the increase in vortex viscosity up to K = 1.0 leads to a decrease in the amount of heat transfer, but its further increase entails the increase in heat transfer. Although the addition of nanoparticles to the fluid improves heat transfer rate, the extent of improvement at nonzero K values is lower than that in the Newtonian fluid. The comparison of the average Nusselt number computed on the hot wall under two different states of temperature-depended thermo-physical properties and constant thermo-physical properties reveals that their difference is more significant for the Newtonian fluid especially at higher volume fraction.

Unsteady natural convection flow and heat transfer utilizing magnetic nanoparticles in the presence of a sloping magnetic field inside a square enclosure are simulated numerically following nonhomogeneous dynamic model. Four different thermal boundary conditions: constant, parabolic in space, sinusoidally in space, and time for the bottom hot wall are considered. The top wall of the enclosure is cold while the vertical walls are thermally insulated. Galerkin weighted residual finite element method is used to solve the governing nondimensional partial differential equations. For simulations, 12 types of nanofluids consisting magnetite (Fe 3 O 4 ), cobalt ferrite (CoFe 2 O 4 ), Mn–Zn ferrite (Mn–ZnFe 2 O 4 ), and silicon dioxide (SiO 2 ) nanoparticles along with water, engine oil, and kerosene as base fluids are used. The effects of the important model parameters such as Hartmann number, magnetic field sloping angle, and thermal Rayleigh number on the flow fields are investigated. The results show that the average Nusselt number, shear rate, as well as the nanofluid velocity decreases as the Hartmann number intensifies. Moreover, the rate of heat transfer in nanofluid exaggerates with the increase of the thermal Rayleigh number and the magnetic field sloping angle. Sinusoidally varied in space thermal boundary condition at the bottom wall provides the highest average Nusselt number and the shear rate compared to the other types of thermal boundary conditions studied here. For this case, the highest average Nusselt number is obtained for the Mn–ZnFe 2 O 4 –Ke nanofluid. On the other hand, Fe 3 O 4 –H 2 O nanofluid delivers the highest shear rate compared to the other premeditated nanofluids.

An attempt is made here to characterize thermal conductivity of water-based Al 2 O 3 nanofluid and then use the same in a circular finned thermosyphon (TPCT) to measure its thermal performance. The concentration of Al 2 O 3 nanofluid is varied within 0.05–0.25% by volume. The thermal conductivity of nanofluid is increased with concentration of Al 2 O 3 nanoparticles as well as with temperature. A maximum of 26.7% enhancement of thermal conductivity is observed at 45 °C for 0.25% concentration by volume of nanofluid in comparison to that of de-ionized (DI) water. Variations of surface tension and contact angle of Al 2 O 3 nanofluid are also compared with DI water. One of the smallest TPCT with different heat inputs (4 W, 8 W, and 12 W) and different inclinations (30 deg, 45 deg, 60 deg, and 90 deg) is tested for different concentration of Al 2 O 3 nanofluid, which will find application in smaller electronic units. It is found that use of nanofluid decreases the wall temperature distribution of TPCT. Thermal resistance of TPCT decreases whenever TPCT is filled with nanofluid and a maximum of 36.4% reduction in thermal resistance is noted for 0.25% volume of nanoparticles at 4 W with an inclination of 60 deg. It is also found that performance of TPCT is higher at 60 deg inclination compared to other inclinations, especially for lower heat input.

Two-phase closed thermosyphon (TPCT) is a cost-effective heat transfer device with high thermal efficiency owing to extensive interphase heat and mass transfer. Thus, TPCT has found many industrial applications. Proper selection of the working fluid could further improve efficiency of TPCT, and nanofluids with superior thermal properties are suitable choices. Numerical simulation of boiling and condensation, natural circulation, and hybrid nanofluid modeling in a closed space is a notable challenge and current study is devoted to this subject. In this study, a novel methodology for incorporating the effects of compressibility and thermal expansion into all thermophysical properties of both phases is developed and programmed into a validated computational fluid dynamics (CFD) code. Distilled water, a regular nanofluid, Al 2 O 3 /water, and a hybrid nanofluid, TiSiO 4 /water are selected as the working fluids. Experimental data for wall thermal profile are employed to validate the numerical simulation. Then, overall thermal resistance is evaluated in terms of nanoparticles concentration and input power variations. Results indicate that the numerical methodology developed in this study could evaluate the optimum state of TPCT in an efficient and accurate manner and the optimum state for regular and hybrid nanofluid demonstrates 48% and 54% improvement over distilled water, respectively. Furthermore, a subtle relation between the thermal resistance and the height to which fluid column rises in TPCT has been discerned and quantified, which is used as a supplement to the conventional qualitative method of reasoning to justify the somewhat controversial behaviors of nanofluid application in TPCT.

Based on Buongiorno's theory and Cauchy equations of motion, a model is developed to examine homogeneous–heterogeneous reactions in boundary layer flow of a nanofluid over a stretching sheet in which a uniform magnetic field is added perpendicular to the flow direction. We apply the shooting method and the fourth-order Runge–Kutta integration to obtain multiple solutions of nonlinear ordinary differential equations with various physical parameters. Results show that nanofluids play significant roles in the procedures of homogeneous and heterogeneous reactions, which may help maintain the stability of chemical reactions. In addition, the terms related to Maxwell fluid either have effect on stability of the system; furthermore, the increasing elastic and magnetic parameters delay the appearance of bifurcation points.

In this study, the thermofluid characteristics of double spirally coiled tube heat exchanger (DSCTHE) were investigated numerically. A three-dimensional (3D) computational fluid dynamic (CFD) model was developed using ansys 14.5 software package. To investigate the heat transfer and pressure drop characteristics of DSCTHE, the Realize k– ε turbulence viscous model had been applied with enhanced wall treatment for simulating the turbulent thermofluid characteristics. The governing equations were solved by a finite volume discretization method. The effect of coil curvature ratio on DSCTHE was investigated with three various curvature ratios of 0.023–0.031 and 0.045 for inner tube side and 0.024–0.032–0.047 for annular side. The effects of addition of Al 2 O 3 nanoparticle on water flows inside inner tube side or annular side with different volume concentrations of 0.5%, 1%, and 2% were also presented. The numerical results were carried out for Reynolds number with a range from 3500 to 21,500 for inner tube side and from 5000 to 24,000 for annular side, respectively. The obtained results showed that with increasing coil curvature ratio, a significant effect was discovered on enhancing heat transfer in DSCTHE at the expense of increasing pressure drop. The results also showed that the heat transfer enhancement was increased with increasing Al 2 O 3 nanofluid concentration, and the penalty of pressure drop was approximately negligible.

This study presents a novel performance evaluation of the commercially available LS-2 collector operating with an oil-based olive leaf-synthesized nanofluid. The nanoparticles were synthesized experimentally from olive leaf extracts (OLEs): OLE-ZVI and OLE-TiO 2 . The thermophysical properties of the nanoparticles were then added to Syltherm-800 thermal oil, and its performance on the parabolic trough solar collector (PTC) was evaluated numerically. The PTC under study was modeled on the engineering equation solver (EES) and validated thermally with results found in the literature. The synthesized nanoparticles were also found to possess anticorrosion properties, nontoxic, and less expensive to produce when compared to commercially available ones. The use of the nanofluids (Syltherm-800/OLE-ZVI and Syltherm-800/OLE-TiO 2 ) was evaluated against the parameters of thermal and exergetic efficiencies, heat transfer coefficient, thermal losses, and pressure drop. The study shows that an enhancement in thermal performance of 0.51% and 0.48% was achieved by using Syltherm-800/OLE-ZVI and Syltherm-800/OLE-TiO 2 nanofluids, respectively. A heat transfer coefficient enhancement of 42.9% and 51.2% was also observed for Syltherm-800/OLE-TiO 2 and Syltherm-800/OLE-ZVI nanofluids, respectively. Also, a mean variation in pressure drop of 11.5% was observed by using the nanofluids at a nanoparticle volumetric concentration of 3%. A comparison of the results of this study with related literature shows that the proposed nanofluids outperform those found in literature.