Nanofluid Heat Transfer Research Articles

Cattaneo-christov heat flux theory in tangent hyperbolic hybrid nanofluids with thermal radiation for renewable energy applications

The aim of current paper is to explore the dynamics of Tangent hyperbolic hybrid nanofluid flow and heat transfer over a stretchy surface, combined effect of thermal radiation and Cattaneo-Christov heat flux effects also incorporated in the energy equation. Hybrid nanofluids are advanced class of nanofluid have several engineering applications due to their enhanced thermal, electrical, and rheological properties. Here we developed a mathematical model for two-dimensional hybrid nanofluid containing particles copper (Cu) and alumina oxide (Al2O3) suspended with base fluid H2O. Variable viscosity and viscous dissipation aspect also amalgamated in the present study. After applying the dimensionless variables, the governing PDE's are converted into ODE's. The numerical computations are performed with the help of MATLAB software. The most important outcomes predefined pertinent parameters like magnetic parameter, Weissenberg number, relaxation time, thermal radiation parameter, prosperity parameter, convective parameter, Prandtl number, heat source parameter, Eckert number, on velocity and temperature profile are thoroughly examined graphically and physically. There occur increment in the temperature profile of hybrid nanofluid than regular nanofluid. Also over current outcomes shows close agreement for a particular cases.

Experimental investigation into heat transfer and flow characteristics of magnetic hybrid nanofluid ([formula omitted]/Ti[formula omitted]) in turbulent region

Extensive research and empirical evidence demonstrate the superior thermal performance of nanofluids compared to DIW. Magnetic hybrid nanofluids, such as Fe3O4/TiO2, are currently being explored for their enhanced thermal properties. This study evaluates Fe3O4/TiO2 nanofluids for heat transfer and hydraulic resistance across Reynolds numbers from 3200 to 5300 and volume fractions from 0.00625 % to 0.3 % vol. UV–Vis spectroscopy shows that lower volumetric fractions correlate with decreased sedimentation. Over 30 days, nanofluids with 0.3 % vol, 0.2 % vol, and 0.1 % vol exhibited high sedimentation factors (SF) of 31.79 %, 11.88 %, and 11.44 %, respectively, while 0.00625 % vol, 0.0125 % vol, and 0.025 % vol demonstrated better stability with SFs of 8.89 %, 9.82 %, and 10.24 % respectively. Volume fractions significantly impact heat transfer, with CHT coefficients increasing by 11.42 % at 0.3 % vol, 14.03 % at 0.2 % vol, 18.04 % at 0.1 % vol, and 19.98 % at 0.05 % vol. The greatest enhancements are at lower concentrations: 22.91 % at 0.025 % vol, a peak of 26.33 % at 0.0125 % vol, and 24.30 % at 0.00625 % vol. Pressure drops are highest at 21 % for 0.3 % vol at Re 5018, decreasing with lower concentrations: 13.10 % at Re 5144.4 (0.2 % vol), 11.94 % at Re 5041.6 (0.1 % vol), 9.82 % at Re 5112.2 (0.05 % vol), 7.67 % at Re 5258.7 (0.0125 % vol), and 10.29 % at Re 5094.0 (0.00625 % vol). These results highlight that higher nanoparticle concentrations increase pressure drop, impacting energy efficiency. Lower concentrations (0.0125 % Vol and 0.00625 % Vol) provided better heat transfer with lower pressure losses. Total Efficiency Index (TEI), The optimal nanoparticle concentration for maximum thermal efficiency was approximately 0.0125 % Vol. TEI values were highest at this concentration, indicating enhanced heat transfer with minimal thermal resistance and pressure drop. Higher concentrations (0.2 % Vol and 0.3 % Vol) showed lower TEI values, suggesting reduced thermal efficiency due to increased flow resistance. These findings highlight the importance of selecting an appropriate nanoparticle concentration to optimize thermal performance in heat transfer systems, balancing the benefits of enhanced heat transfer with the drawbacks of higher-pressure losses.

Numerical simulation of an unsteady ternary hybrid nanofluid along a convectively heated curved stretching sheet: A Tiwari-Das model

Nanofluids are smart fluids, which are very useful for heat and mass transfer enhancement. They are very much used in industrial, transportation, biomedical, and electronics fields. In the present research, we examine the nanofluid flow across a curved stretching sheet (CSS). Also, this work’s noteworthy originality is its discussion of the impacts of the physical parameters on the ternary hybrid nanofluid flow and heat transfer. Furthermore, the simulation considers nanofluids with water as the base fluid. The Koo–Kleinstreuer–Li (KKL) model examines the viscosity and effective thermal conductivity of fluid flow with suspended nanoparticles. The governing equations of the momentum and the temperature are transformed into ordinary differential equations (ODEs) by similarity transformations. These equations are then solved using a Secant iteration method combined with a Runge–Kutta–Fehlberg (RKF) integration scheme with a shooting technique. Through graphs and tables, the influences of the relevant non-dimensional parameters are presented and analyzed. The findings show that an increase in the curvature parameter and the Biot number is to increase the temperature gradient. The Streamline profiles for various values of the magnetic parameter are also analyzed through figures. We believe that this research has significant implications in biomedical devices and pharmaceutical fluid preparation in biomedical sciences. Some of them are high temperature and cooling processes, paints, space technology, medicines, cosmetics, conductive coatings, bio-sensors, and to name a few.

Heat transfer and entropy generation characteristics of nanofluid flow over bluff bodies under steady and unsteady flow: A two-phase approach

Owing to higher thermal conductivity, nanofluids have the potential to be the coolant for various applications ranging from internal to external flows. A two-phase model is implemented to model the interaction between nanoparticles and base fluid to obtain accurate results. Heat transfer and entropy generation characteristics of nanofluid (Al2O3 and water) flow over bluff bodies such as circular and square cylinders for steady (20 < Re < 100) and unsteady (Re = 150 and 300) flow conditions have been carried out for various volume fractions (0.5–2 %). The same has been expressed in quantitative and qualitative aspects with parameters such as mean Nusselt number, surface Nusselt number, heat transfer enhancement ratio, and entropy generation. Heat transfer rate increases with an increase in flow rate and volume fraction for both steady and unsteady flow. Heat transfer enhancement in steady flow ranges from 1.10 to 1.35. For unsteady flow (Re = 150 & Re = 300), nanofluid's heat transfer enhancement ratio is higher than water in the range of 1.10–1.8. This is attributed to the early separation of flow and the presence of large recirculatory regions. With the increase in Re, the entropy generation decreases for circular and square cylinders. Compared to nanofluid, the entropy generation is higher for water.

A computation analysis with heat and mass transfer for micropolar nanofluid in ciliated microchannel: With application in the ductus efferentes

Inherited heat enhancement capabilities and their significance in the field of medical sciences and industry make nanofluids the focus of research nowadays. Furthermore, due to the remarkable advancements in bionanotechnology and its significance in biomedical fields such as drug delivery systems, cancer tumor therapy, bioimaging, and many others, it has emerged as a key research area. Contribution of cilia for the flow in ductus efferentes of human male reproductive tract is elaborated. A novel mathematical scheme is presented for the heat and mass transfer of MHD micropolar nanofluid transport in an asymmetric channel lined with cilia. The pertinent equations of nanofluid transport are exposed to lubrication approximation theory and solution for the physical problem is examined with efficient bvp4c technique in MATLAB. Fluid rheology is explored with the variations of different transport parameters like Hartmann number, Grashof number, Brownian motion, buoyancy, thermophoresis and Darcy number. It is reported that nanofluid transport is affected with rise in the Lorentz force and show reverse behavior with rising permeability. The temperature of the nanofluid in ciliated microchannel is raised with enhanced value of Hartmann number, Grashof number, Prandtl number, and Darcy number while diffusion phenomenon of nanofluid is slowed down with these parameters. Spinning motion of the nanofluid is enhanced with Grashof number and slow down with nanoparticle Grashof number and different behavior is recorded for Darcy and viscosity parameters in different flow regime. Reported investigation presents crucial findings for ciliary transport of micropolar nanofluid and tackled with appropriate selection of micropolar parameter, Brownian motion parameter, thermophoresis and Grashof number. Moreover, this investigation will be handful for cilia-based actuators which work as micro-mixers in controlling the flow in minute bio-sensors and may prove their worth in micro-pumps employed in various drug-delivery systems.

Consequences of thermal conductivity and thermal density on heat and mass transfer in the nanofluid boundary layer flow toward a stretching sheet in the presence of a magnetic field

The term “thermal conductance” is used to describe a material’s ability to transport or conduct heat. Materials with high thermal conductivity are employed as heating elements, while those with poor thermal conductivity are used for insulation purposes. It is known that the thermal conductivity of pure metals decreases as temperature increases. In this study, the primary focus is on the physical assessment of thermal conductivity, entropy, and the improvement rate of thermal density in a magnetic nanofluid. To achieve this, nonlinear partial differential equations are transformed into ordinary differential equations. These equations are further solved using a computational method known as the Keller box technique. Various flow parameters, such as the Eckert number, density parameter, magnetic-force parameter, thermophoretic number, buoyancy number, and Prandtl parameter, are examined for their impact on velocity, temperature distribution, and concentration distribution. For the asymptotic results, the appropriate range of parameters, such as 1.0 ≤ ξ ≤ 5.0, 0.0 ≤ n ≤ 0.9, 0.1 ≤ Ec ≤ 2.0, 0.7 ≤ Pr ≤ 7.0, 0.1 ≤ Nt ≤ 0.5, and 0.1 ≤ Nb ≤ 0.9, is utilized. The key findings of this study are related to the assessment of heat transfer in a magnetic nanofluid considering thermal conductivity, entropy generation, and temperature density. It is observed that the temperature distribution increases as entropy generation increases. From a physical perspective, thermal conductivity acts as a facilitating factor in enhancing heat transfer. The study concludes by emphasizing the consistency achieved through a comparison of the latest findings with previously reported analyses.

Non-similar approach for enhanced heat and mass transfer in nanofluid using Keller box algorithm

The nanofluids provide various benefits over pure fluids in heat and mass transport applications; hence, their research is crucial. For instance, they can increase heat transfer rate by enhancing the fluid’s thermal conductivity and may enhance mass transfer rate by changing the surface characteristics. Furthermore, nanofluids are being demonstrated to effectively diminish pressure drops in exchangers for heat, which can lower energy consumption and operating expenses. In the existing literature, the majority of the theoretical studies considered self-similar flows. However, there are certain actual flow situations that do not allow for a self-similar solution. The current study considers such of those situations where the non-similarity of the transport phenomena is unavoidable. The non-similarity of the present problem is caused by the consideration of thermophoretic diffusion or the contribution of viscous dissipation when the wall temperature follows a power-law form. For a pure fluid, the same problem admits a self-similar solution in the absence of viscous dissipation effects. In this problem, the non-similarity is caused by the nature of the thermal transport process and not because of the momentum transport. Therefore, the consideration of viscous dissipation in the boundary layer of nanofluid is an interesting aspect to explore the behavior of thermal and mass transport phenomena. Moreover, the current analysis intends to investigate the transport enhancement in a non-similar flow of a nanofluid by utilizing the Buongiorno model. In the current nonsimilar modeling, possibilities for the existence of a self-similar solution are also highlighted. An implicit finite-difference numerical scheme, the Keller-Box method, is utilized. The problem involves several physical parameters of interest, such as the Eckert number, Lewis number, Brownian motion parameter, and thermophoresis parameter, whose potential impact on the non-similar nature of the problem and on thermal enhancement is analyzed and quantified.

Sinusoidal heating on convective heat transfer of nanofluid under differential technique

AbstractSinusoidal convection describes a smooth and repetitive heat transfer oscillation that reasonably calculates the optimal heat transfer for nanoparticle's intermolecular interactions. This study aims to investigate the heat transfer effects of Stokes second problem on the performance of novel fractional differential operators based on rheological characteristics of nanofluid. For the sake of augmentation in thermal characteristics of the nanofluid, the fractionalized governing equations based on the suspension of nanoparticles namely copper and silver in ethylene‐glycol have been developed. The fractional Stokes second problem is simulated with the help of transformation techniques and statistical data analysis. The analytic optimization of mathematical solutions of velocity and temperature have been established in terms of newly defined different Mittag‐Leffler functions. The statistical data for velocity field is generated by varying Hartman number, Prandtl number and Eckert number. The comparative analysis for two types of fractional differential operators of temperature distribution is perceived through bar column label, three‐dimensional color pie chart, three‐dimensional color map surface with projection, three‐dimensional bars and linear fitting of data. The comparative results revealed that temperature distribution has a significant effect and great influence on the stability of nanofluid by the embedded parameters.

Comparative studies on heat transfer and flow resistance of nanofluid in microchannels with different sidewall micro-fins

Comparative studies on heat transfer and flow resistance of nanofluid in microchannels with different sidewall micro-fins

Thermally radiative nanofluid heat transfer analysis inside a closed chamber with gyrotactic microorganisms

PurposeThis paper aims to numerically examine the impact of gyrotactic microorganisms and radiation on heat transport features of magnetic nanoliquid within a closed cavity. Thermophoresis, chemical reaction and Brownian motion are also considered in flow geometry for the moment of nanoparticles.Design/methodology/approachFinite element method (FEM) was depleted to numerically approximate the temperature, momentum, concentration and microorganisms concentration of the nanoliquid. The present simulation was unsteady state, and the resulting transformed equations are simulated by FEM-based Mathematica algorithm.FindingsIt has been found that isotherm patterns get larger with increasing values of the magnetic field parameter. Additionally, numerical codes for rate of heat transport impedance inside the cavity with an increasing Brownian motion parameter values.Originality/valueTo the best of the authors’ knowledge, the research work carried out in this paper is new, and no part is copied from others’ works.

Predicting MHD mixed convection in a semicircular cavity with hybrid nanofluids using AI

This study presents a numerical analysis of magnetohydrodynamic (MHD) mixed convection in a semicircular enclosure containing a rotating inner cylinder and filled with nanofluids and hybrid nanofluids. The investigation explores the effects of Al2O3-TiO2-SWCNT-water hybrid nanofluids with varying nanoparticle compositions, as well as Al2O3-water, TiO2-water, and SWCNT-water nanofluids. The analysis includes the development of an artificial neural network (ANN) model to predict outcomes, achieving 97.34 % accuracy in training and 97.41 % in testing for the average Nusselt number. The study examines the impact of Reynolds number (Re), Richardson number (Ri), Hartmann number (Ha), cylinder rotation speed (Ω), cylinder size, and nanoparticle volume fraction (φ) on heat transfer and fluid flow. Key findings include a 6.98 % increase in heat transfer for SWCNT-water nanofluid from Ri = 1 to Ri = 10, a reduction in heat transfer with higher Hartmann numbers, and a significant 21.12 % enhancement when cylinder speed increases to Ω = 10 compared to a stationary cylinder. Larger cylinder sizes also improve convective heat transfer, with a 66.14 % increase for SWCNT-water nanofluid. Additionally, higher concentrations of SWCNT and Al2O3 in hybrid nanofluids enhance heat transfer performance.

Thermal and velocity slip conditions together with thermal radiative effects on Joule heating mixed convection MHD hybrid nanofluid flow induced by an exponentially shrinking or stretching sheet

ABSTRACT The present study analyzes the mixed convection with magnetohydrodynamic (MHD) flow, Joule heating, and heat transfer in hybrid nanofluids on exponentially stretching or shrinking sheets. The study aims to optimize heat transfer and fluid dynamics properties in engineering and industrial applications. The governing partial differential equations are converted into ordinary differential equations by employing appropriate similarity transformations and then solved using the BVP4C MATLAB tool. In this study, the effects of silver volume fraction, velocity slip, thermal slip, magnetic field, heat generation, Eckert number, and thermal radiation on the skin friction coefficient, Nusselt number, velocity profile, and temperature profile are examined and graphically discussed. The base fluid water contained 2% silver (Ag) and 0.1% titanium oxide (TiO2) nano-particles in this hybrid model. The dual solution was present for a shrinking sheet ( λ < 0 ) when λ ≥ λ c . The skin friction coefficient values decreased by approximately 37%, while the local Nusselt number increased by approximately 3.1% when the velocity slip increased in the first solution. The Nusselt number increased by approximately 0.28% and 12% when the Eckert number and radiative parameter increased, respectively, but decreased by approximately 7.5% and 0.20% when the thermal slip and heat generation increased, respectively.

Integrated neural network based simulation of thermo solutal radiative double-diffusive convection of ternary hybrid nanofluid flow in an inclined annulus with thermophoretic particle deposition

Numerical simulation of magnetohydrodynamic radiative double-diffusive convective heat and mass transfer of a ternary hybrid nanofluid with thermophoretic particle deposition in an inclined annulus is studied. Both sides of cylinders are preserved at uniform temperatures, while the remaining sides are thermally insulated. The coupled nonlinear partial differential equations are solved using a finite difference approach. The detailed computational results of heat and mass transfer rate, temperature, concentration and flow fields are presented and discussed for a distinct range of significant physical parameters. The results demonstrated that increasing the angle of the inclination factor increases fluid flow. In light of buoyancy, when the annular cavity is set downward, the enhanced shear velocity is transported upwards, where it reaches its optimal temperature. The higher temperature difference leads to augmented dynamic fluid motion, particularly in the radial direction, as the system seeks to balance the thermal energy through convective transfer. The Brownian motion parameter has abrupt mobility of nanoparticles in liquid, which promotes particle collisions with liquid molecules, yielding kinetic energy. Increased values of thermophoretic parameters augment the thermophoresis force. Thermophoretic particle deposition increases the concentration of nanoparticles in an annulus due to the migration of particles from hot to cold regions under the influence of temperature gradient. The heat and mass transfer characteristics of ternary hybrid nanofluid are forecasted through an artificial neural network-based Levenberg–Marquardt backpropagated algorithm. The built model shows the heat and mass transfer rate root mean squared values through the Levenberg–Marquardt algorithm as one and mean squared error values as 1e-07 and 1e-08 respectively.

Neural network approach to investigate heat transfer in SWCNTs nanofluid within trapezoidal cavity with varied corrugated rod amplitudes

This article presents Artificial Neural Networks (ANN) for convective heat transfer in a trapezoidal cavity subjected to corrugated heated rod inside it. The LevenbergMarquardt algorithm is utilized to optimize the Neural Networks. The trapezoidal cavity has low-temperature inclined walls and adiabatic upper and lower walls compared to the corrugated heated rod. Single-wall carbon (SWCNTs) nanomaterials are submerged in the base liquid water. The flow of SWCNTs-water is generated due to the temperature gradient in the cavity. The system of dimensional partial differential equations has been formulated for the physical setup under investigation. The dimensional system has been converted into a non-dimensional form using dimensionless variables. Finite element is used for the solutions. The dimensionless functions velocity, temperature, and heat transfer rates are studied against the Rayleigh number (Ra). The outcomes are presented in the form of isotherms, contours, tabular values, and graphs. The data for Artificial Neural Networks (ANN) has been generated by FEM against the Nusselt number. The ANN has been trained for a specific amplitude of the rod and predicted heat transfer against a larger amplitude. The results show good agreement for both training and testing data. The outcomes of analysis reveals that convection caused by temperature gradient is dominant for higher values of the Rayleigh number (Ra). Local Nusselt number has been discussed against different amplitudes, and predicted enhancement for the larger amplitude of the rod.

Statistical and numerical analysis of magnetic field effects on laminar natural convection heat transfer of nanofluid in a hexagonal cavity

This paper presents a statistical and numerical investigation that examines the optimization and sensitivity analysis of the unsteady laminar natural convective heat transfer flow of Fe3O4-water nanofluid in a hexagonal cavity considering the impacts of a sloping magnetic field in one-component nanofluid model. The inclined walls of the cavity are maintained at a constantly low temperature, while the bottom wall is uniformly heated. The upper wall, however, is regarded as adiabatic. The nanofluid thermal conductivity model incorporates the impact of Brownian motion. The Galerkin weighted residual finite element method has been employed to solve the governing dimensionless equations. The results are provided regarding the average Nu, streamlines, and isotherms. The study uses response surface methodology to analyze the sensitivity of parameters such as the Ha, Ra, and nanoparticle volume percentage. Using a response surface policy allows for optimizing the process and identifying the most favorable circumstances to achieve the maximum thermal transfer rate. The flow pattern of the nanofluid is significantly affected by the magnetic field and its alignment. The numerical results indicate a significant rise in the average Nu as the nanoparticle volume percentage, magnetic field inclination angle, nanoparticle type factor, and Ra increase. Conversely, the Hartmann number and the nanoparticle's diameter have contrasting effects. When considering Brownian motion, the average Nu grows by 225.89 % for Ra = 106 with ϕ = 0.03 and 25.28 % for the other case. The optimal condition for heat transfer occurs when Ra = 106, Ha = 4, and ϕ =0.03 while keeping the other parameters constant.

A Mathematical Approach for Stability Analysis of MHD Nanofluid Flow and Heat Transfer over a Stretching Sheet with Thermal Dispersion and Variable Viscosity

A Mathematical Approach for Stability Analysis of MHD Nanofluid Flow and Heat Transfer over a Stretching Sheet with Thermal Dispersion and Variable Viscosity

Experimental and Numerical Study of Heat Transfer and Pressure Drop Non-Newtonian Nanofluid in Corrugated Tube with Twisted Tapes

Experimental and Numerical Study of Heat Transfer and Pressure Drop Non-Newtonian Nanofluid in Corrugated Tube with Twisted Tapes

Numerical investigation of magnetized bioconvection and heat transfer in a cross-ternary hybrid nanofluid over a stretching cylinder

PurposeIn this study, we investigate the effects of an extended ternary hybrid Tiwari and Das nanofluid model on ethylene glycol flow, with a focus on heat transfer. Using the Cross non-Newtonian fluid model, we explore the heat transfer characteristics of this unique fluid in various applications such as pharmaceutical solvents, vaccine preservatives, and medical imaging techniques.Design/methodology/approachOur investigation reveals that the flow of this ternary hybrid nanofluid follows a laminar Cross model flow pattern, influenced by heat radiation and occurring around a stretched cylinder in a porous medium. We apply a non-similarity transformation to the nonlinear partial differential equations, converting them into non-dimensional PDEs. These equations are subsequently solved as ordinary differential equations (ODEs) using MATLAB’s bvp4c tools. In addition, the magnetic number in this study spans from 0 to 5, volume fraction of nanoparticles varies from 5% to 10%, and Prandtl number for EG as 204. This approach allows us to examine the impact of temperature on heat transfer and distribution within the fluid.FindingsGraphical depictions illustrate the effects of parameters such as the Weissenberg number, porous parameter, Schmidt number, thermal conductivity parameter, Soret number, magnetic parameter, Eckert number, Lewis number, and Peclet number on velocity, temperature, concentration, and microorganism profiles. Our results highlight the significant influence of thermal radiation and ohmic heating on heat transmission, particularly in relation to magnetic and Darcy parameters. A higher Lewis number corresponds to faster heat diffusion compared to mass diffusion, while increases in the Soret number are associated with higher concentration profiles. Additionally, rapid temperature dissipation inhibits microbial development, reducing the microbial profile.Originality/valueThe numerical analysis of skin friction coefficients and Nusselt numbers in tabular form further validates our approach. Overall, our findings demonstrate the effectiveness of our numerical technique in providing a comprehensive understanding of flow and heat transfer processes in ternary hybrid nanofluids, offering valuable insights for various practical applications.

Mixed convective nanofluid flow and heat transfer induced by a stretchable rotating disk in porous medium

AbstractEnhancement of “heat transfer” using “nanofluid” has diverse potential applications in heat exchangers, thermal management of electric devices, cooling of tractors, solar thermal systems, manufacturing of paper, and many others. Hence, the aim of the current investigation is to explore the impacts of “mixed convection” on “nanofluid flow” over a permeable rotating disk, which is stretched radially in a porous medium. Variable wall “temperature” and “convective boundary conditions” are also considered here. This makes the present investigation different from others. The suitable “similarity transformations” are imposed to alter the governing partial differential equations into a set of coupled ordinary differential equations (ODEs). Then, these ODEs are solved numerically by the “4th order Runge‐Kutta method” using the “shooting technique” with the help of the bvp4c package in MATLAB software. The effects of fluid controlling “parameters” on “flow and thermal fields” as well as “skin friction coefficient” and “Nusselt number” are presented graphically and explained physically. Due to enhanced rotation of the disk, the radial and azimuthal velocity of the fluid increase and the temperature of the fluid decreases. Most importantly, it is observed that when the disk rotates faster than the stretching rate, the temperature of the nanofluid decreases rapidly, which has wider applications for cooling purposes. It is also noted that when the suction parameter increases its value from −1 to 1, for Ag–water nanofluid, the “skin friction coefficient” decreases by 73.56%, and the Nusselt number also decreases by 24.11%, and for Fe3O4–water nanofluids, the “skin friction coefficient” decreases by 71.25% and the Nusselt number decreases by 24.47%.

Two-Phase Lattice Boltzmann Study on Heat Transfer and Flow Characteristics of Nanofluids in Solar Cell Cooling

During solar cell operation, most light energy converts to heat, raising the battery temperature and reducing photoelectric conversion efficiency. Thus, lowering the temperature of solar cells is essential. Nanofluids, with their superior heat transfer capabilities, present a potential solution to this issue. This study investigates the mechanism of enhanced heat transfer by nanofluids in two-dimensional rectangular microchannels using the two-phase lattice Boltzmann method. The results indicate a 3.53% to 22.40% increase in nanofluid heat transfer, with 0.67% to 6.24% attributed to nanoparticle–fluid interactions. As volume fraction (φ) increases and particle radius (R) decreases, the heat transfer capability of the nanofluid improves, while the frictional resistance is almost unaffected. Therefore, the performance evaluation criterion (PEC) of the nanofluid increases, reaching a maximum value of 1.225 at φ = 3% and R = 10 nm. This paper quantitatively analyzes the interaction forces and thermal physical parameters of nanofluids, providing insights into their heat transfer mechanisms. Additionally, the economic feasibility of nanofluids is examined, facilitating their practical application, particularly in solar cell cooling.