Nusselt Number Of Nanofluids Research Articles

Analysis of heat generation and viscous dissipation with thermal radiation on unsteady hybrid nanofluid flow over a sphere with double-stratification: Case of modified Buongiorno's model

PurposeThis work uses entropy generation analysis to numerically analyze magnetohydrodynamics (MHD) unsteady flow, heat and mass transfer. The study considers changing viscosity, thermal radiation, viscous dissipation, mass suction, heat generation, and stratification processes in a hybrid nanofluid around a spinning sphere. A two-phase nanofluid flow model (Buongiorno model) is used to tackle the current challenge. Both the free stream velocity and the sphere's angular velocity changed over time. Design/methodology/approachThe case study's complicated partial differential equations are transformed into simpler ordinary differential equations utilizing similarity transformation. Implementing the fourth-order Runge-Kutta Fehlberg method with a shooting scheme in MATHEMATICA has allowed us to get numerical solutions for ordinary differential structures. FindingsThe many aspects of these regulated physical characteristics have been elucidated and thoroughly examined via the use of charts and tables. For increasing values of unsteadiness parameter, the velocity profiles in the x-direction grow while they decrease in the z-direction. On the other hand, the temperature profile exhibits a dual pattern, and the concentration profile decreases. As the chemical reaction parameter climbs from 0.25 to 1.0, the Sherwood number for the nanofluid rises by 6721.39% and for the hybrid nanofluid, 3818.9%. When Nr increases from 0.2 to 0.8, nanofluid Nusselt number climbs 22.5% and hybrid nanofluid's Nusselt number rises 21.9%. The Brinkmann number and nanoparticle volume percentage are strongly associated with entropy production. Entropy generation is dual for the temperature difference, magnetic, radiation, and changeable viscosity parameters. The findings are also compared to those from the existing literature and are in excellent agreement with them.

Influence of the twisting and nano fluids on performance of a triangular double tube heat exchanger

Abstract The hydraulic and thermals performance of flow in a double-tube heat exchanger with an inner twisted triangle tube of length L = 1 m has been studied numerically. Equations for energy, turbulence, and Navier–Stokes were used to model the fluid flow and heat transfer in a double-tube heat exchanger with an inner twisted triangle tube. The Reynolds number range was 5000–30,000 for nanofluid (water-Al2O3) as a working fluid under a turbulent flow regime. The considered configuration was examined by varying the volume concentration of nanofluid while keeping the twist ratio constant (Tr = 5). Different cases of volume concentration of nanofluid are triggered (0.05 %, 1 %, 2.5 %, and 4 %, respectively). The numerical outcomes of a double-twisted tube heat exchanger with an inner triangle-twisted tube are validated with the obtainable numerical data. The governing equations were solved with ANSYS Fluent 18.2. The findings reveal that the larger volume concentration of nanofluid (4 %) gives a greater Nusselt number and vice versa due to the increased thermal conductivity of the nanofluid in the double twist tube heat exchanger compared with a plain tube. However, the nanofluid Nusselt number grows with the rise of both the Reynolds number and volume concentration (Ø), and the best value of the Nusselt number is 210 when Reynolds number = 30,000 and Ø = 4 %. The effectiveness of the heat exchanger grows with an increase in the concentration of the nanofluid and a reduction in the torsion ratio compared to the normal tube. The effectiveness of the double-tube heat exchanger with an inner twist triangle tube increases to the highest value of 0.38 at Reynolds 30,000 and Ø = 4 %.

INFLUENCE OF LORENTZ FORCES ON FORCED CONVECTION OF NANOFLUID IN A POROUS ENCLOSURE

The evaluation of the nanofluid heat transfer inside the enclosure is done via a theoretical approach. This study illustrates the change of Nusselt number of nanofluid inside the enclosure with porous media in the existence of a homogeny magnetic field. The change of significant factors of the magnetic field, Rayleigh number, and nanofluid characteristics (m) on thermal characteristics has been fully investigated. Obtained data indicate that increasing the Rayleigh number has changed the impacts of the magnetic field on the heat transfer and nanofluid streamline. Moreover, the heat transfer is improved by the increasing of Ra and m factors at constant Ha = 7.5. Heat transfer enhancement is achieved at a specific m factor by increasing Ra and decreasing the Hartmann number.

Artificial neural network (ANN) analysis of non-similar solution of MHD nanofluid flow past a curved stretching surface

The objective of this study is to predict the non-similar solution of Magnetohydrodynamics (MHD) mixed convection transports of viscous nanofluids over a curved stretching surface by using numerical simulation with an artificial neural network (ANN) algorithm, namely the back-propagation Levenberg–Marquardt scheme. In this article, aluminum oxide and iron oxide are used as nanoparticles to enhance the thermal conductivity of the base fluid. Additionally, aluminum oxide and iron oxide nanoparticles are used in certain biomedical applications, including composite materials, photocatalysis, wastewater treatment, and nanofiltration membranes. The radiation, Joule heating, and viscous dissipation effects are studied along with the convective boundary condition. The flow problem is attained in the form of a system of Partial differential equations (PDEs) and converted into dimensionless PDEs via non-similarity transformation. These dimensionless systems of PDEs are converted into a system of Ordinary differential equations (ODEs) via local, non-similar techniques up to second-order truncations. The Bvp4c technique is used to simulate the numerical results. The data sets are collected using the Bv-p4c technique. These data sets are utilized for the validation, training, and testing phases of the developed Back-propagated Levenberg-Marquardt Scheme- Artificial Neural Network (BLMS-ANN) model to determine the solution of the problem for a variety of physical scenarios. The ANN model is utilized to choose data, construct and train a network, and evaluate the performance of the network through the use of mean square error and regression analysis. The ANN models are used to predict the performance of the Nusselt number for both nanofluids and the results demonstrated that ANN is capable of making accurate predictions of the local Nusselt number for both nanofluids. In the entire study, the ANN model predicts the result of the local Nusselt number of nanofluids with higher accuracy as compared to nanofluids.

Natural convection due to lateral uniform heat flux in a slender porous cavity saturated with nanofluid: Departure from LTE state

The present article deals with the influence of the local thermal nonequilibrium (LTNE) state on natural convection in an enclosure filled with nanofluid-saturated porous medium. The flow is induced due to the maintenance of constant heat flux on the vertical walls and insulation of horizontal walls. The Darcy model has been adopted to describe the flow governing equations. These equations are solved numerically by using the alternate direction implicit method and analytically by applying parallel flow assumptions valid for large aspect ratios. Boundary layer analysis is performed to report the boundary layer thickness ( δ x ∼ 2 1 / 2 ( k nf / k f ) 1 / 10 ( R a T ) − 1 / 5 ) as well as the heat transfer rate of nanofluid ( N u nf ∼ ( k nf / k f ) − 1 / 5 R a T 2 / 5 ) . The combined effect of LTNE state parameters (interface heat transfer coefficient (H), porosity scaled thermal conductivity ratio (γ)) and volume fraction of nanoparticle ( ϕ ) is addressed on the flow dynamics and heat transfer mechanism. Rigorous analysis, indicates that the average heat transfer rate of nanofluid and solid porous matrix are increasing function of H and γ, however, the role of γ is accelerated for a relatively high value of H. For increasing the value of γ from 1 to 10, the enhancement in the heat transfer rate of nanofluid is reported to be up to 27% at 10% volume fraction of nanoparticles. The average Nusselt number of nanofluid, as well as solid phase, are reduced when the value of ϕ is increased under the LTNE circumstances. Furthermore, the flow structure is controlled by unicellular structure with rotating anticlockwise direction in the entire study. For the very small value of H the temperature distribution in the solid porous matrix is mainly by conduction mode and distribution is linear, however, for a relatively high value of H the distribution in the same is controlled by both conduction as well as convection, and it will be more pronounced for the higher value of γ.

Deriving local Nusselt number correlations for heat transfer of nanofluids by genetic programming

The application of nanoparticles in the design of heat exchange systems is anticipated to significantly enhance energy efficiency across the industrial, commercial, and residential sectors. A nanofluid results from mixing a base fluid and nanoparticles. These nanoparticles generally are made from various materials, including metals, metal oxides, and polymers. To design nanofluid-assisted energy systems, it is necessary to estimate the heat transfer achieved by the nanofluids. Most models developed to describe the heat transfer of fluids require estimating the Nusselt number (Nu), representing the ratio of convective heat transfer to conductive heat transfer in a given system. Previous work in nanofluids has focused on modeling equations for the average Nusselt number (Nuavg) in tube systems. However, an equation that allows the local Nusselt number (Nux) to be calculated is more versatile than one which calculates the Nuavg since it can be applied to any length of circular tubes. In this study, we derive equations using Genetic Programming (GP) to estimate the local Nusselt number of nanofluids (Nux,nf) that flow through horizontal circular tubes. The method uses an evolutionary algorithm to generate correlation equations for exploring the interaction of the flow regime, flow properties, system configuration, and nanoparticle properties. It comprises creating a population of candidate equations, selecting the best ones through fitness evaluation, and combining them through genetic operators (Selection, crossover, and mutation) to create a new generation of equations. Acceptable Nux,nf models (R2>0.9) were obtained with GP tree structures larger than three levels (depth 3). Findings from the Nux,nf correlations obtained show that the determinant variables for the model were the Reynolds and Prandtl numbers. This implies that the effect of the nanofluids is driven mainly by alterations made by the nanoparticles to the inertial forces of the flow and the thermal diffusivity. The results of this study highlight the potential of this machine-learning-based approach to provide insight into the physicochemical mass and heat transfer mechanisms.

Thermal Performance of Car Radiator Operated by Al2O3–Ethylene Glycol/Water-Based Nanofluids: A Computational Fluid Dynamics Study

Abstract This study analyzed the heat transfer potential of nanofluids (suspension of Al2O3 nanoparticles in 60:40 mixtures of ethylene glycol and water by volume) compared to the base fluid by modeling the flow in both laminar and turbulent flow regimes in a flat tube of a radiator using both single-phase and Eulerian–Eulerian multiphase approaches of computational fluid dynamics (CFD) simulation. Nusselt number is calculated by varying the Reynolds number for both the models and compared with the theoretical correlations and the experimental data available in the literature. The effect of change in volumetric concentrations, inlet velocities, inlet temperatures, and particle sizes on the heat transfer performance parameters of nanofluids was evaluated. The multiphase approach showed a 5–45% greater increase in Nusselt number than the single-phase approach for the same volume fraction up to 1% and thereafter multiphase approach showed an even higher Nusselt number. The multiphase model revealed that raising the volume fraction up to 2% increases the Nusselt number of nanofluid by approximately thrice that of the base fluid but after that further increase in volume fraction does not show any significant increment. With the increase in Reynolds number, the Nusselt number, as well as surface heat transfer coefficient, increased for both laminar and turbulent flow regimes. Skin friction coefficient, pressure drop across inlet and outlet, and pumping power required increased slightly with the increase in volume fractions. Also, on varying the nanoparticle size, superior performance was observed at the particle size of 25 nm.

Thermal Transfer Study of a Non-Newtonian Nanofluid Behavior in a Microduct

In this study, laminar flow forced convection heat transfer of a non-Newtonian nanofluid flowing inside a Micro conduit that is subjected to a constant wall temperature was investigated. By considering the effect of viscous dissipation. The effects of Brinkman numbers (Br), power low index (n) and nanoparticle concentrations (φ) on the developing temperature fields and the local Nusselt number were examined. The obtained results were validated with available solutions for the special cases of conventional fluids (φ = 0) and non-viscous dissipation effect (Br = 0). Bulk temperature distribution and local Nusselt number are presented graphically for Br = 0, 0.5, 1, -0.5 and 1 for non-Newtonian fluids described by the power-law model with the flow index n = 0.3, 1.0 and 3.0. The Nusselt numbers of nanofluids were obtained for different Al2O3 nanoparticle concentrations as well as various Brinkman numbers.

Computational Assessment of Microrotation and Buoyancy Effects on the Stagnation Point Flow of Carreau-Yasuda Hybrid Nanofluid with Chemical Reaction Past a Convectively Heated Riga Plate.

The present framework deliberated the mixed convection stagnation point flow of a micropolar Carreau–Yasuda hybrid nanoliquid through the influence of the Darcy-Forchheimer parameter in porous media toward a convectively heated Riga plate. In this investigation, blood is used as a base liquid and gold (Au) and copper (Cu) are the nanoparticles. The main novelty of the present investigation is to discuss the transmission of heat through the application of thermal radiation, viscous dissipation, and the heat source/sink on the flow of a micropolar Carreau–Yasuda hybrid nanoliquid. Further, the results of the chemical reaction are utilized for the computation of mass transport. Brownian motion and thermophoretic phenomena are discussed in the current investigation. The current problem is evaluated by using the connective and partial slip conditions and is formulated on the basis of the higher-order nonlinear PDEs which are converted into highly nonlinear ODEs by exploiting the similarity replacement. In the methodology section, the homotopic analysis scheme is employed on these resulting ODEs for the analytical solution. In the discussion section, the results of the different flow parameters on the velocity, microrotation, energy, and mass of the hybrid nanofluid are computed against various flow parameters in a graphical form. Some of the main conclusions related to the present investigation are that the velocity profile is lowered but the temperature is augmented for both nanoparticles volume fractions. It is notable that the skin friction coefficient is reduced due to the higher values of the Darcy-Forchheimer parameter. Further, the rising performance of the hybrid nanofluid Nusselt number is determined by the radiation parameter.

Numerical study of hydrodynamic and thermal behavior of Al2O3/Water nanofluid and Al2O3-Cu/Water hybrid nanofluid in a confined impinging slot jet using two-phase mixed model

This study utilizes the two-phase mixture model to conduct a numeric study of Al2O3/Water and Al2O3-Cu/Water (hybrid) nanofluid's hydrodynamic and thermal behavior in a laminar confined impinging slot jet in 50 ≤ Re ≤ 300 and nanoparticles volume fractions (NVF) ranging from 0 - 2%. This study considers various aspect ratios (H/W), including 2, 4, and 6, to investiate the confining effects. This paper gives a comparative analysis of nanofluids and hybrid nanofluids in terms of the parameters concerning the flow: Reynolds and local Nusselt number (Nux), average Nusselt number (Nuavg), flow lines' contour, and temperature distribution under similar geometric conditions and Reynolds number. In comparison with nanofluids, the hybrid nanofluids have higher local Nusselt number on the entire target surface, this advantage of hybrid nanofluid attribute to higher thermal conductivity of them. The average Nusselt numbers of nanofluids and hybrid nanofluids plotted at different Refor various aspect ratios(H/W=2,4), and the effect of aspect ratio and momentum are explained. Furthermore, pumping power of both fluid analysed for all nanoparticles volume fraction (0 - 2%) at different Reynolds number. The result shows that pumping power of hybrid nanofluid is higher than base fluid and nanofluid, because the dynamic viscosity of hybrid nanofluid is higher than base fluid (water) and nanofluid. Besides; the study identified some correlations in the hybrid nanofluids regarding the stagnation point and the average Nusselt numbers. Presumably, these correlations are valid under certain conditions: 50≤ Re ≤ 300, 2 ≤ H/W≤ 6, and volume fracture (0 - 2%).

Comprehensive comparative analysis of Metal-Oxide nanoadditives impacts on Oil-Filled Finemet and Vitroperm alloy core transformers HST concerning nanofluid thermophysical properties accurate estimation

In this paper, a precious analysis is dedicated to thermal properties of three metal oxide-based nanofluid samples as well as their overall effects on a 630 kVA oil natural-air natural three-phase transformer thermal performance. The studied nanofluids comprise a typical mineral oil as the transformer base fluid in which Magnetite, Copper Oxide and Alumina nanoparticles are individually dispersed assuming different solid volume fractions. The suspensions are assessed in terms of density, specific heat capacity, thermal conductivity and viscosity. Furthermore, volume fraction- and temperature-dependent formulas, well-matched with the existing experimental data, are proposed to demonstrate excellent correlation coefficients. Subsequently, the derived formulas are utilized as initial functions for transformer thermal modeling. Actually, to pursue the mentioned approach, performing electromagnetic analyses are indispensable. In this regard, making use of two nanocrystalline alloys, namely, Finemet FT-3 M and Vitroperm 500F as core materials can significantly reduce the transformer resultant losses once compared to the case in which conventional electrical steels are utilized. In this study, to represent the enhancements found in the nanofluid filled transformer perfectly, in addition to analysis of the simulation results against those gained using pure mineral oil, one type of natural ester, Midel 1204, is designated as another option for comparison purposes. It is worth mentioning that by increasing the level of nanoparticles volume concentration, a notable decrease can be observed not only in the oil average temperature, but also in the winding hot spot temperature. The investigations are performed for the transformer under different load rates considering the influence of ambient temperature, and the results accuracy are authenticated through making qualitative comparison against the thermal image of a prototype magnetic nanofluid-immersed transformer. Moreover, the system resultant temperatures are verified to exhibit the finest magnitudes in presence of the studied nanofluids, even lower than that of the ester oil with an extremely high thermal conductivity. Finally, the studied fluids and nanofluids Nusselt numbers versus Rayleigh numbers are attained to demonstrate the results fine agreement with the experimental values, as well as presenting satisfactory enhancement in CuO nanofluid Nusselt number compared to mineral oil-based Alumina/Magnetite/Titania nanofluids results.

Impacts of two-phase nanofluid approach toward forced convection heat transfer within a 3D wavy horizontal channel

Combined approach of geometrical variations to increase heat transfer surface with the application of high thermal conductive nanofluids can influence heat transfer enhancement in new thermal systems. This study numerically investigates the thermophoresis and Brownian diffusion as convective heat transfer enhancement mechanisms with two-phase Al2O3-water nanofluid in a 3D wavy horizontal channel having upper and lower wavy surfaces imposed with a uniform temperature and adiabatic conditions, respectively. Empirical correlations are used to model the thermal conductivity and viscosity as the most influential thermophysical properties of nanofluid. A commercial CFD code based on the Finite element Method (FEM) is employed to solve the governing equations in curvilinear coordinates for the computational domain. The employed dimensionless parameters include Reynolds number (Re), nanoparticle concentration (ϕ), channel’s number of oscillations (N) and amplitude (A). The current results correlate reasonably with similar experimental results in the literature. The results show that nanofluid flow in the wavy-channel augmented heat transfer, especially at increasing nanoparticle volume fraction and Reynolds number. Also, higher convective heat transfer is attained with increasing flow mixing due to increase in oscillation frequency. Local Nusselt number of nanofluid significantly rises when the Re varied from 200 to 1000 by about 75% at ϕ=0.02, N=4 and A=0.1.

Numerical Analysis of Mixed Convective Heat Transfer from a Square Cylinder Utilizing Nanofluids with Multi-Phase Modelling Approach

The present study deals with the numerical simulation of mixed convective heat transfer from an unconfined heated square cylinder using nanofluids (Al2O3-water) for Reynolds number (Re) 10–150, Richardson number (Ri) 0–1, and nanoparticles volume fractions (φ) 0–5%. Two-phase modelling approach (i.e., Eulerian-mixture model) is adopted to analyze the flow and heat transfer characteristics of nanofluids. A square cylinder with a constant temperature higher than that of the ambient is exposed to a uniform flow. The governing equations are discretized and solved by using a finite volume method employing the SIMPLE algorithm for pressure–velocity coupling. The thermo-physical properties of nanofluids are calculated from the theoretical models using a single-phase approach. The flow and heat transfer characteristics of nanofluids are studied for considered parameters and compared with those of the base fluid. The temperature field and flow structure around the square cylinder are visualized and compared for single and multi-phase approaches. The thermal performance under thermal buoyancy conditions for both steady and unsteady flow regimes is presented. Minor variations in flow and thermal characteristics are observed between the two approaches for the range of nanoparticle volume fractions considered. Variation in φ affects CD when Reynolds number is varied from 10 to 50. Beyond Reynolds number 50, no significant change in CD is observed with change in φ. The local and mean Nusselt numbers increase with Reynolds number, Richardson number, and nanoparticle volume fraction. For instance, the mean Nusselt number of nanofluids at Re = 100, φ = 5%, and Ri = 1 is approximately 12.4% higher than that of the base fluid. Overall, the thermal enhancement ratio increases with φ and decreases with Re regardless of Ri variation.

Numerical investigation and ANN modeling of the effect of single-phase and two-phase analysis of convective heat transfer of nanofluid in a cavity

The goal of this numerical investigation is to explore and compare the hydrothermal characteristics of free, mixed, and forced convection of water-copper nanofluid in a cavity using single-phase (SPM) and two-phase (TPM) methods. The top and bottom walls of the cavity are insulated, and the left and right walls are kept at a constant temperature so that the temperature of the left wall is higher than that of the right wall. The impact of volume fraction of nanoparticles ( $$\varphi$$ ), Rayleigh number (Ra), Richardson number (Ri) and Reynolds number (Re) on the performance features is assessed. In addition, the artificial neural network (ANN) is employed to develop a predictive model of average Nusselt number of nanofluid. The results showed that the TPM was more accurate than the SPM. Additionally, it was observed that increasing the $$\varphi$$ , Ra, Ri and Re leads to increasing the average Nusselt number of nanofluid. The maximum heat transfer improvement for the mixed convection and forced convection modes was 28% and 32%, respectively. Furthermore, the ANN modeling revealed the nanoparticle concentration has a negligible role on the results of free convection, while the opposite is true of forced convection.

Numerical Analysis of Heat Transfer Improvement in Flat Tube Car Radiator by Using TiO2/Water Nanofluids

This research investigated two-phase heat transfer numerically using TiO2/water nanofluids to enhance the thermal performance in a flat tube car radiator. Nanofluid is a colloid dispersion in a nano-sized which is a breakthrough in terms of the thermal devices. The radiator is widely used in the automotive industry as a heat exchanger. The enhancement of thermal accomplishment was studied numerically by analyzing in thermohydraulic characterizations. A numerical study was conducted by TiO2/Water nanofluids using five concentrations consisting, that is, 0.05%, 0.5%, 1.0%, 3.0% and 5.0% and six Reynolds number variations. Nanofluids with volume concentrations of 0.05%, 0.5%, and 1.0% volume concentration indicated that the values of Nusselt number were lower compared to water. Meanwhile, the values of Nusselt number for nanofluids with volume concentration of 3.0% and 5.0% were higher than water. This occurs because the transfer coefficient enhancement was higher when compared to the increase of thermal conductivity.

Numerical study on the thermo-hydraulic performance analysis of fly ash nanofluid

The heat transfer and flow characteristics of water-based fly ash nanofluid for concentrations of 0.1–1.5 vol.% that flow through a copper tube at an inlet fluid temperature of 303 K with constant heat flux boundary conditions are estimated numerically. Stability, viscosity, and thermal conductivity of fly ash nanofluid have been determined experimentally and compared with correlations available in the literature. STAR CCM + software was used to solve the governing equations using the finite volume method (FVM). Water and stable fly ash nanofluid were used as working fluids for the Reynolds number range of 4500–16,000. The Nusselt number and friction factor at 1.5% volume concentration are greater than the base fluid by 36% and 9.4%, respectively. The fly ash nanofluid showed a performance index ( $$\eta$$ ) value of more than 1 at all concentrations undertaken, indicating that the use of fly ash nanofluid in heat transfer applications is beneficial. The highest $$\eta$$ value is determined to be 1.5 approximately for a nanofluid concentration of 1.5 vol.%. The fly ash nanofluid exhibits enhanced heat transfer performance contrasted to SiO2 nanofluid. The utilization of fly ash particles for heat transfer enhancement can aid in the reduction of environmental pollution to a certain extent. Novel correlations are suggested for the estimation of fly ash nanofluid Nusselt number and friction factor.

Study of Convective Heat Transfer Enhancement of Nanofluid Inside Tube (Dept.M)

Nanofluids are suspensions of metallic or nonmetallic nano-powders in base liquid and can be employed to increase heat transfer rate in various applications. In this work laminar flow forced convection heat transfer of (Al2O3 or CuO)/water nanofluid inside a circular tube with constant wall heat flux is investigated experimentally. The Nusselt numbers of nanofluids are obtained for different nano particle concentrations as well as various Reynolds number. Experimental results emphasize the enhancement of heat transfer due to the nano-particles presence in the fluid. Heat transfer coefficient increases by increasing the concentration of nano-particles in nanofluid. The increase in heat transfer coefficient due to presence of nano-particles is much higher than the prediction of single phase heat transfer correlation used with nanofluid properties. Considering the factors affecting the convective heat transfer coefficient of the nanofluid, a new convective heat transfer correlation for nanofluid under single-phase flows in tube is established. Comparison between the experimental data and the calculated results indicate that the correlation describes correctly the energy transport of the nanofluid. The range of operating parameter is Reynolds number from 500 to 2500 and particle volume concentrations up to 2.0%. Comparison between present and pervious results is carried out.

Time scale analysis for prediction of Nusselt number of nanofluids flowing through straight tubes: An experimental study.

In view of anomalous heat transport behavior in nanofluids, a number of possible mechanisms suggested by various authors to explain the thermal conductivity and heat transfer coefficient enhancement lacks unanimity. Hence, the aim of this research article is to explore convective heat transfer enhancement mechanisms by correlating it with observed experimental data of nanofluids. The analysis is carried out by comparing the order of magnitude of different diffusion mechanisms for different types of nanofluid systems. Four different types of nanofluids, Al2O3/EG-W (0.6, 0.9, 1.2 and 1.5 vol.%.), Al2O3/PG-W (1, 1.5, 2 and 2.5 vol.%.), CuO/PG-W (0.25, 0.5, 0.75 and 1 vol.%) and MgO/PG-W (0.3 and 0.66 vol.%) have been studied in this research. A generalized mechanism based correlation have been proposed to predict the Nusselt number for these nanofluids, for a flow through straight tube under laminar conditions. Results showed that the Brownian motion is very slow in comparison to nano convection diffusion and heat diffusion. The proposed model predicted the combined data for all the nanofluids studied well within a range of ±5%. Statistical error of proposed model were also calculated. Data of other authors was also validated using the proposed correlation, and parity plot showed that the correlation predicted the data well within a range of ±15%.

An experimental investigation on the thermo-hydraulic properties of CuO and Fe3O4 oil-based nanofluids in inclined U-tubes: A comparative study

U-tubes are nowadays widely used in large industries, especially in heat exchangers, as well as solar absorbers. Optimizing and increasing the thermal efficiency of heat exchangers reduces fossil fuel consumption and costs savings. A comparative experimental study was conducted on friction factor, and heat transfer of oil-based nanofluids flow (CuO and Fe3O4 with 0.5%, 1%, and 2% mass concentrations) inside inclined U-tube at 0°, 30°, 60°, and 90° inclination angles under constant heat flux. The nanofluids prepared in two steps method by dispersing nanoparticles in SN-500 base oil. The tests were performed in five different flow rates. The results showed that compared to the base fluid, using nanoparticles increased the friction factor and convective heat transfer coefficient. According to the results, it was found that the highest heat transfer rate belonged to 0.5% CuO and 1% Fe3O4, and the maximum increase in Nusselt number for nanofluids happened at 30° inclination angles. Finally, it was found that the Fe3O4 nanofluid with 1% concentration had the highest value among all the test nanofluids samples in horizontal and inclined modes.

Heat transfer of nanofluid through helical minichannels with secondary branches

Heat transfer, fluid flow characteristics and entropy generation of water-Al2O3 nanofluid for cylindrical heat sinks with helical minichannels that have secondary branches are investigated experimentally. The minichannels helix angles are 45, 60 and 90 degrees; the volume fraction of nanoparticles variation is 0.05% – 0.1%; the Reynolds number range is between 113 to 478. The effects of the helix angle of minichannels, Reynolds number and nanoparticle volume fraction are studied. The heat transfer enhances with increasing Reynolds number, decreasing helix angle and increasing volume fraction of nanoparticles. However, with increasing Reynolds number, increasing helix angle and decreasing nanoparticles volume fraction, the friction factor decreases. The experimental results show that the secondary branches decreased the friction factor and Nusselt number. The maximum enhancement of Nusselt number in helix angle 60 and 45 for pure water are 31.1% and 51.3% greater in comparing with the straight minichannel, respectively; moreover, maximum enhancement of the Nusselt number of nanofluid compared with the pure water was about 14.3% for 0.1% vol. The thermal entropy generation rate decreases and, the frictional entropy generation rate increases with increasing the nanoparticles volume fraction and decreasing the helix angle. Furthermore, two new correlations are obtained for the Nusselt number and friction factor.