Nanofluid Heat Transfer Research Articles

Studying the influence of surface roughness with different shapes and quantities on convective heat transfer of fluid within nanochannels using molecular dynamics simulations.

In the past decade, rapid advancements in microtechnology and nanotechnology have propelled modern science and technology into the nanoscale domain, where miniaturization and high integration have found extensive applications across various fields, including industry, biotechnology, and information technology. Mechanisms of nanofluid flow and heat transfer properties have received increasing attention. In the flow and convective heat transfer of fluids at the nanoscale, the shape and dimensions of the surfaces play a crucial role. So, the main purpose of our paper is to investigate the influence of surface roughness with different shapes and quantities on fluid flow and convective heat transfer. In this study, we have chosen argon atoms as the fluid and used copper atoms to simulate the nanochannel walls. In order to investigate the influence of the shape and quantity of roughness on the convective heat transfer of fluids within nanochannels, we computed and analyzed the velocity, temperature, and density distributions of fluids inside channels with triangular, hemispherical, and rectangular roughness. Through simulation results, we found that triangular, hemispherical, and rectangular surface roughness at the same height can result in differences in temperature and velocity of the fluid within nanochannels. With a nanochannel roughness number of 5, the temperature and velocity of the fluid at the middle position of the nano-channel for the triangular roughness increased by 6% and 25% compared to the rectangular roughness, and by 4% and 10% compared to the hemispherical roughness. The fluid temperature and velocity are highest in channels with triangular surface roughness and lowest in those with rectangular roughness. Furthermore, increasing the quantity of surface roughness decreases the temperature and velocity of the fluid within nanochannels. When the quantity of rectangular surface roughness is 5, the fluid temperature within the nanochannel decreases by 12%, and the velocity decreases by 38% compared to a roughness quantity of 1. We also found, through velocity contours, that the presence of roughness increases the local fluid velocity in the rough regions of nanochannels. Roughness also reduces the density fluctuations of the fluid near the walls within the nanochannel. Roughness significantly affects the heat transfer performance of the fluid during its flow, and this influence should not be overlooked. In this study, molecular dynamics theory was employed, and simulations were conducted using the open-source software LAMMPS to investigate the influence of different shapes and quantities of surface roughness on fluid flow within nanochannels. The model in this paper was constructed using the LAMMPS software, and the surface roughness shapes on the walls were implemented as rectangular, hemispherical, and triangular. The wall surfaces were composed of copper atoms, while the fluid consisted of argon atoms. The copper atoms were arranged in a face-centered cubic (FCC) lattice with a lattice constant of 3.615 Å. Similarly, the argon atoms were arranged in a face-centered cubic (FCC) lattice with a lattice constant of 5.62 Å. The interactions between copper atoms were modeled using the EAM (Embedded Atom Method) potential, while the interactions between argon atoms were described using the LJ (Lennard-Jones) potential. The LJ potential was also employed to represent interactions between argon and copper atoms.

Analysis of thermophysical and transport properties of nanofluids using machine learning algorithms

Accurate calculations of thermophysical properties (TPP) and fluid transport properties are crucial for solving and enhancing a myriad of heat and mass transfer issues, particularly in the field of engineering and associated disciplines. This is even more significant in the case of advanced fluids, such as nanofluids, which play a pivotal role in the progression of new technologies. The significance of TPP in heat transfer studies is undeniable, yet there is a notable scarcity of reliable TPP values for nanofluids that can be uniformly applied to numerous problems and complex industrial systems. This shortage poses a unique challenge for nanofluids. The current study introduces NanoFluid Explorer (NanoFEx), a comprehensive MATLAB-based database specifically designed to catalog the TPP of nanofluids. The database is divided into two main parts. The first part employs Gaussian regression, supported by experimental data derived from existing literature, using kernel functions commonly used for this type of analysis. The second part features a neural network, designed for efficiency, that is trained on the aforementioned database and supplemented by an additional database formed from the Gaussian-regression output. This setup allows NanoFEx to recapture TPP values for nanofluids that may be absent in the existing literature. The preliminary findings demonstrate that NanoFEx could prove to be an invaluable resource for both theoretical and experimental researchers studying heat and mass transfer in nanofluids. Moreover, NanoFEx confirms thermodynamically consistent values with any discrepancies attributed to finite-precision computations. Furthermore, NanoFEx achieved over 93% accuracy in predicting key properties. The novelty and relevance of this study stem from the comprehensiveness of the experimental results database. In summary, this research provides an extensive and, to the best of the authors' knowledge, the most reliable dataset currently available for TPP of nanofluids. This significant contribution aims to unify nanofluid TPP research and optimize experimental processes while setting a crucial standard for future nanofluid applications.

Investigation of forced convection of a novel hybrid nanofluid containing NEPCM in a square microchannel: Application of single-phase and Eulerian-Eulerian two-phase models

In the present study, laminar forced convection flow and heat transfer of novel hybrid nanofluid of Al 2 O 3 -n-octadecane/water through a horizontal microchannel under a constant wall heat flux condition are investigated. N-octadecane is regarded as a nano-encapsulated phase change material (NEPCM). Simulations are performed utilizing single-phase and Eulerian-Eulerian two-phase models. Governing equations are discretized by finite volume method and then solved using SIMPLE algorithm. Effects of nanoparticles volume fraction ( φ ), Reynolds number ( Re ), and melting range ( T mr ) on thermal and hydrodynamic parameters of hybrid nanofluid are evaluated. It is shown that predictions by Eulerian-Eulerian approach are more accurate than those by single-phase approach when compared to available experimental data. Addition of Al 2 O 3 and n-octadecane nanoparticles to water-based fluid leads to a reduction in fluid and wall temperatures, which is intensified at higher φ and Re . Also, these nanoparticles do not have a significant effect on hydrodynamic development of flow, while they delay its thermal development. NEPCM with a higher T mr only slightly improves thermal performance of hybrid nanofluid, which is more noticeable in single-phase procedure. Total efficiency of hybrid nanofluid ( η hnf ) is amplified by raising φ for both approaches. This augmentation is more evident in Eulerian-Eulerian model due to better thermal and hydrodynamic performances. Maximum increases in η hnf concerning single-phase and Eulerian-Eulerian models are 27% and 60%, respectively, occurring at φ Al 2 O 3 = 1 % and φ n ‐ octadecane = 10 % . Therefore, this type of hybrid nanofluids, because of its enhanced thermo-physical properties, can be considered as a suitable candidate for thermal energy storage, heat transfer, and renewable energy applications.

Numerical study on mixed convection heat transfer of copper-water nanofluid in a porous cavity with an isothermal solid block in local thermal non-equilibrium

This manuscript reports a numerical study on mixed convection heat transfer of Cu-water nanofluid in a porous cavity with an isothermal solid block in the state of local thermal non equilibrium. The set of governing equations are solved by finite volume method combined with SIMPLE algorithm. Through streamlines and isothermal contour plots as well as the average Nusselt number, the impact of various parameters like the nanoparticle concentration, Richardson number, Darcy number, and inter phase heat transfer coefficient is highlighted. The main findings indicate that the Local thermal non-equilibrium state (H = 1, 10) produces the maximum heat transfer rate than the local thermal equilibrium state (H = 1000).

Flow and heat transfer of nanofluids in a cylindrical permeable wavy channel embedded in porous medium using Buongiorno’s model

This investigation deals with the flow of Al2O3–water nanofluid in a wavy porous channel embedded in porous rocks. Fluid exchange takes place uniformly between porous rocks and the wavy channel. In this analysis, cylindrical and parallel plate wavy porous channels are considered. Consequences of Brownian motion and thermophoresis on the flow inside a wavy porous channel are elucidated. The modeled equations are made dimensionless by using dimensionless quantities. Impacts of flow parameters on the velocity, temperature, Nusselt number and friction factor are depicted through graphs. The numerical results with respect to parallel plate wavy porous channel are validated by comparing with the published results. The effectiveness of the cylindrical wavy porous channel as a heat transfer enhancement device in comparison to the parallel plate wavy porous channel is confirmed in this study. Designing devices at microlevels and understanding the heat transfer enhancement mechanism in wavy channels using the nanoparticle addition are the major outcomes from the results of this numerical investigation. The heat and mass transfer rate enhancements in the wavy porous channels are due to the higher Brownian motion in the boundary layer region and accelerated thermophoresis through thermal and concentration boundary layer thicknesses.

A comparative study of thermo‐physical properties of different nanofluids for effective heat transfer leading to Li‐ion battery pack cooling

AbstractThe rapid advancement in Lithium‐ion battery technology has significantly boosted the electric vehicle market worldwide. These batteries are highly sought after by automobile manufacturers and researchers due to their exceptional energy storage and power capabilities. However, efficient working temperatures ranges from 15°C to 35°C, making it essential to implement battery cooling and heating methods to maintain optimal performance. This study primarily focuses on battery cooling. The automotive manufactures have focused on ethylene glycol, water and synthetic oils as commonly used coolants for keeping the lithium‐ion battery pack within working temperature limits. However, these fluids have lower heat conduction, leading to reduced heat transfer rates and diminished cooling performance. To address this issue, nano‐enhanced fluids, which are engineered fluids containing suspended nanospheres, have been explored. The heat transfer properties of conventional coolants are increased using nano‐enhanced fluids, thereby improving heat conduction and promoting efficient heat transfer within the battery. The study compares the temperature‐related characteristic of different nano‐enhanced fluids, including oxides of copper (CuO), titanium (TiO2), aluminum (Al2O3), silicon (SiO2), and zinc (ZnO), when added to base fluids such as synthetic oils, water and ethylene glycol. The importance to capacity of specific heat, conductivity of fluid thermally, fluid resistance to flow and fluid volumetric mass which are affected by changes in temperature limits are stressed upon. Depending on the specific application and test conditions, the effectiveness of one nano‐enhanced fluid may outperform the others. In conclusion, the thermo physical properties of nanofluids play a critical role in maintaining the battery pack temperature within operating temperature limits. The selections of nanofluids for particular battery thermal management system depends upon its arrangement along the battery pack and cell geometry. The cooling performance using nanofluids as coolant is 10% to 15% higher than the conventional used fluids. This nano‐enhanced fluid show great promise in enhancing the cooling capabilities of battery cooling systems, contributing to improved Lithium‐ion battery performance in electric vehicles.

Hybrid-nanofluid magneto-convective flow and porous media contribution to entropy generation

PurposeThis paper aims to present a numerical study that investigates the flow of MgO-Al2O3/water hybrid nanofluid inside a porous elliptical-shaped cavity, in which we aim to examine the performance of this thermal system when exposed to a magnetic field via heat transfer features and entropy generation.Design/methodology/approachThe configuration consists of the hybrid nanofluid out layered by a cold ellipse while it surrounds a non-square heated obstacle; the thermal structure is under the influence of a horizontal magnetic field. This problem is implemented in COMSOL multiphysics, which solves the related equations described by the “Darcy-Forchheimer-Brinkman” model through the finite element method.FindingsThe results illustrated as streamlines, isotherms and average Nusselt number, along with the entropy production, are given as functions of: the volume fraction, and shape factor to assess the behaviour of the properties of the nanoparticles. Darcy number and porosity to designate the impact of the porous features of the enclosure, and finally the strength of the magnetic induction described as Hartmann number. The outcomes show the increased pattern of the thermal and dynamical behaviour of the hybrid nanofluid when augmenting the concentration, shape factor, porosity and Darcy number; however, it also engenders increased formations of irreversibilities in the system that were revealed to enhance with the permeability and the great properties of the nanofluid. Nevertheless, this thermal enhanced pattern is shown to degrade with strong Hartmann values, which also reduced both thermal and viscous entropies. Therefore, it is advised to minimize the magnetic influence to promote better heat exchange.Originality/valueThe investigation of irreversibilities in nanofluids heat transfer is an important topic of research with practical implications for the design and optimization of heat transfer systems. The study’s findings can help improve the performance and efficiency of these systems, as well as contribute to the development of sustainable energy technologies. The study also offers an intriguing approach that evaluates entropy growth in this unusual configuration with several parameters, which has the potential to transform our understanding of complicated fluid dynamics and thermodynamic processes, and at the end obtain the best thermal configuration possible.

Experiments and modeling of boiling heat transfer of GNP nanofluids with metallic elements

ABSTRACT This study investigates the boiling characteristics of graphene (GNP) nanofluids, graphene-copper (GNP-Cu) composite nanofluids, and graphene-iron (GNP-Fe) composite nanofluids with mass fractions of 0.001%, 0.002%, and 0.003%. The results indicate that GNP-Cu and GNP-Fe nanofluids can simultaneously enhance the critical heat flux (CHF) and heat transfer coefficient (HTC). Among different mass fractions, GNP-Cu nanofluids with a mass fraction of 0.003% exhibited the highest CHF and HTC. Through the observation of bubbles, the research elucidated that the presence of copper and iron elements is crucial in enhancing heat transfer. Based on the experimental results, this study modified the boiling curve equation of Rohsenow into a linear function. The modified model can predict the boiling curves of GNP-Cu, GNP-Fe, and GNP-Ag nanofluids at various concentrations. Furthermore, the experimental findings indicated a quadratic relationship between the boiling heat transfer coefficient and the heat flux in GNP, GNP-Cu, GNP-Fe, and GNP-Ag nanofluids. As a result, this study investigates the differences in heat transfer and bubble dynamics among GNP nanofluids modified with various metallic elements during boiling. It explores the underlying heat transfer mechanisms and proposes boiling curve equations that are applicable to a range of nanofluids. The findings suggest that acid-mixing treatment and metal-functionalization play a facilitating role in heat transfer of GNP nanofluids. Furthermore, nanofluids loaded with different metallic elements exhibit similar trends in their boiling curve equations.

Comparative analysis of CFD and ANFIS for predicting heat transfer enhancement in water-Fe2O3 nanofluids across various flow regions

Models for enhancement of heat transfer in nanofluids made wide use of adaptive neural fuzzy inference system (ANFIS) and the multi-phase mixture model in recent years. These models originate from two separate but complementary branches of engineering: computational mechanics and machine intelligence. Not only have prior studies used only a small subset of nanofluid and flow parameters in their analyses, but no one has ever compared the two methods to determine which one is more applicable to certain flow regimes to forecast how much heat transfer development nanofluids will exhibit. The purpose of this study was to compare the accuracy of two methods ? CFD and ANFIS in predicting the heat transfer improvement of water-Fe2O3 nanofluid for variety of nanofluid formations and flow characteristics, and recommend the method that would be most useful in predicting this enhancement for each flow regime. While ANFIS consistently outperforms the mixture models in prediction of nanofluid heat transfer enhancement, the latter can sometimes produce results that differ greatly from experimental correlation; however, for nanofluid configurations, the mixture model?s predictions can be dependable (with 1% error).

Nanofluid Heat Transfer in Irregular 3D Surfaces under Magnetohydrodynamics and Multi-Slip Effects

Nanofluid Heat Transfer in Irregular 3D Surfaces under Magnetohydrodynamics and Multi-Slip Effects

Investigation of various hybrid nanofluids to enhance the performance of a shell and tube heat exchanger

<abstract> <p>In this study, we aim to investigate the heat transfer and flow characteristics of diverse hybrid nanofluids (CuO-ZnO-Water, EG-Water, CuO-EG-Water, SiO<sub>2</sub>-EG-Water, and Al<sub>2</sub>O<sub>3</sub>-EG-Water) as coolants across eight discrete inlet velocities in a shell and tube heat exchanger. Various materials (copper, stainless steel, titanium, and carbon steel) have been employed for the tubing to optimize system performance. The impact of Reynolds number concerning hybrid nanofluids on Nusselt number and friction factor was assessed in this research. The results of the numerical simulations are found to agree well with experimental results within an average deviation of 1.8%. The results indicated the superior heat transfer capabilities of the hybrid nanofluid compared to the base fluid across all conditions. The outcomes revealed the superior heat transfer capabilities of the CuO-ZnO-Water hybrid nanofluid under all tested conditions. When employing CuO-ZnO-Water as a coolant, a substantial increase of over 9% in temperature reduction was observed, as opposed to the approximately 6% attained by other hybrid nanofluids at a lower velocity of 0.5 m/s. Notably, higher Reynolds numbers corresponded to increased Nusselt numbers and decreased friction factors. The decline percentage of the friction factor was 43% at Reynolds number ranging between 10,000 to 40,000. We emphasize the imperative need to optimize nanoparticle types for crafting hybrid nanofluids to enhance the performance of industrial heat exchangers and their coolant efficiency. Ultimately, the utilization of hybrid nanofluids in conjunction with shell and tube heat exchanger systems has yielded a notable enhancement in the overall thermal efficiency of these systems.</p> </abstract>

IMPORTANCE OF THERMAL CONDUCTIVITY MODELS IN ANALYZING HEAT TRANSFER OF RADIATIVE HYBRID NANOFLUID ACROSS A STRETCHING SHEET USING DARCY-FORCHHEIMER FLOW

Hybrid nanofluids' enhanced thermal efficiency has important applications in many fields of industry and engineering. The goal of this study is to find out how different thermal conductivity models affect important factors in the Darcy-Forchheimer flow and heat transfer of a hybrid nanofluid made of Al<sub>2</sub>O<sub>3</sub> - Cu and water across a moving surface that can let some fluid pass through it. Magnetohydrodynamics (MHD), thermal radiation, joule heating, and viscous dissipation are all included in the study. Partial differential equations (PDEs) are made more manageable by reducing them to a set of ordinary differential equations (ODEs) via a similarity transformation. After that, Mathematica’s shooting technique and the Runge-Kutta algorithm are used to numerically solve these ODEs. The study analyzes the effects of key factors on the major physical quantities of interest and presents the findings graphically and tabularly. The research also shows that differing thermal conductivity models lead to significantly varied average Nusselt values. The rate of heat transmission improves with the addition of (φ<sub>2</sub> and S. The Xue model in the hybrid nanofluid shows a 0.7% increase in heat transfer rate compared to the nanofluid, while the Maxwell model shows a 0.64% increase and the Yamada-Ota model shows a 1.01% increase. Importantly, for all the considered models of thermal conductivity, the research shows that the average Nusselt number increases linearly with the nanoparticle volume percentage. Finally, the data shows that the Yamada-Ota model consistently produces far higher average Nusselt values than the other models.

Numerical study of flow behavior and heat transfer of ternary waterbased nanofluids in the presence of suction/injection, stretching/ shrinking sheet

Numerical study of flow behavior and heat transfer of ternary waterbased nanofluids in the presence of suction/injection, stretching/ shrinking sheet

Unveiling the magic of localized magnetic field on vortex dynamics and heat transfer of tetra-hybrid nanofluid in lid-driven cavity: an insightful investigation

Unveiling the magic of localized magnetic field on vortex dynamics and heat transfer of tetra-hybrid nanofluid in lid-driven cavity: an insightful investigation

Heat transfer and flow characteristics of cuo-al2o3 hybrid nanofluids in slotted finned channels

This study aimed to investigate the heat transfer coefficient of CuO-Al2O3 hybrid nanofluids within a microchannel heatsink, focusing on the impact of flow rate and volume fraction. The thermal conductivity and viscosity of hybrid nanofluids with different particle ratios were investigated. The results showed that the nanofluids have a more remarkable enhancement in thermal conductivity than water. Employing the hybrid nanofluids enhanced the heat transfer coefficient significantly. Furthermore, a slight growth in the friction factor was observed.

The lie group analysis method for heat transfer in steady boundary layer flow field of nanofluid

In order to reveal the mechanism of the abnormal movement (Brownian motion enhances thermal scattering) of nanoparticles on the fluid enhanced heat transfer, the two-phase model was used to study the abnormal convection and diffusion of viscous nanofluids in the flat boundary layer of porous medium. Firstly, for the two-dimensional steady boundary layer stagnation point flow of incompressible Newtonian-nanofluids, the nonlinear governing equations of the flow field and temperature field of nanofluids are established from the Oberbeck-Boussinesq approximate equations. Secondly, the modern Lie group analysis method is introduced, we give the Lie symmetry determining equation of the flow field partial differential equations and the characteristics of the solutions. Further, using the relationship between the Lie symmetries and the conserved quantities, the conservation vector form of the flow field and the group invariant solution are derived in detail, and the reduced order model of the nanofluid flat boundary layer is obtained. Finally, the correctness of the analytical results obtained by the Lie group method was verified for different values of the flow parameter Prandtl. Research has shown that the Lie group method can be used to analytically solve the velocity and temperature distribution functions of abnormal motion of nanoparticles. The fluid temperature increases with the increase of the volume fraction parameter of nanoparticles, but decreases with the increase of the Prandtl value of the base fluid, and decreases with the increase of the plate stretching speed. The Lie group analysis method in this paper provides reference value for numerical simulation solutions of various heat and mass transfer in nanofluids.

Impact of Convection and Rotation on Advanced Thermal Energy Storage Using Nanoencapsulated Phase Change Materials in Wavy Enclosures

Free convection heat transfer in hybrid nanofluids in a differentially heated wavy enclosure is studied. The wavy enclosure moves at a constant counterclockwise rotational speed along its longitudinal axis. The enclosure is filled with a hybrid nanofluids consisting of water (H2O) and nanoencapsulated phase change materials (NEPCMs). These NEPCMs consist of a polyurethane coating and a core of N‐nonadecane, which undergoes a phase transition and has the capacity to retain or emit a significant quantity of latent heat. The dimensionless forms of the governing equations have been solved using finite element method. The validity of the present code is demonstrated by comparing its predictions with published results. The governing parameters under consideration are the corrugated number, 0 ≤ N ≤ 3, the volume fraction of hybrid nanoparticles, 0.0 ≤ ϕ ≤ 0.05, the Taylor number, 8 × 102 ≤ TaH2O ≤ 2 × 104. Changing the rotation speed is found to alter the melting and solidification zones in terms of pathways and size zones. The melting zone has a large size at moderate wave number, and its size shrinks and shifts downward as the wave number increases. An increase in the heat transfer rate values up to 38% is obtained when the concentration is adjusted from 1% to 5% for N = 1.

Effects of Nanoparticle Size on Natural Convection Pattrns of Nanofluids with the Lattice Boltzmann Method

In this work, numerical simulation of natural convection of nanofluids within a square enclosure were investigated by using the non-dimensional lattice Boltzmann method (NDLBM). The effects of key governing parameters Knudsen number ($10^{-6} \le Kn_{f,s} \le 10^4$), Rayleigh number ($10^3 \le Ra_{f,L} \le 10^6$), and nanoparticle volume fraction ($10^{-2} \le \phi_s \le 10^{-1}$) on the heat and mass transfer of nanofluids were discussed. The results show that in the low $Ra_{f,L}$ conductive domited regime, the nanoparticle size has little effect on heat transfer, whereas in the high $Ra_{f,L}$ convective dominated regime, larger nanoparticle sizes significantly enhance flow intensity and heat transfer efficiency. As fixed $Ra_{f,L}$ and $\phi_s$, the heat transfer patterns change from conduction to convection dominated regimes with increasing $Kn_{f,s}$. The influence of nanoparticle volume fraction was also investigated, and in convection dominated regime, the maximum heat transfer efficiency was achieved when $\phi_s = 8 \%$, balancing both thermal conduction and drag fore of nanofluids. Additionally, by analyzing the full maps of mean Nusselt number ($\overline {Nu}_{f,L}$) and the enhancement ratio related to the base fluid ($Re_{n,f}$), the maximum values of $\overline {Nu}_{f,L}$ and $Re_{n,f}$ occur when the nanoparticle size is $Kn_{f,s} = 10^{-1}$ for both conductive and convective dominated regimes. To capture the effects of all key governing parameters on $\overline {Nu}_{f,L}$, a new empirical correlation has been derived from the numerical results, providing deeper insights into how these parameters influence heat transfer performance.

Numerical simulation of the oscillating thin plate impact on nanofluids flow in channel

The present numerical study aims to present the effect of a titled oscillating thin plate with different inclination angles on the Al2O3-water nanofluid flow and heat transfer performance. The subsequent work establishes methods for forming fluid-structure interactions by the impact of Al2O3-water nanofluid at 0.1-1.0 vol. % volume fraction upon the thin plate using COMSOL Multiphysics 5.4. The turbulent model is solved using the (k-?) model, and the flow assembly around the thin plate obstacle has been confirmed at the Reynolds number of Re=4?104. It exemplifies how Nanofluid flow interaction can distort structures. The turbulent, two-dimensional, stationary, and incompressible flow around an oscillating thin plate with inclined angles with upstream and downstream mounted inside a horizontal channel was studied. The numerical study includes an investigation of the effect of five inclination angles of the thin plate (30, 60, 90, 120, and 150?) on the pressure, velocity, and temperature contours of the Al2O3-water nanofluid. Also, the study presented the drag profile and left a force on the thin plate caused by the fluid flow. The results showed that a titled oscillating thin plate inside the flow direction increases pressure drop, von Mises deformation stress, x-displacement and drag force fields, and the Nusselt number. Where the pressure increased from 2.61?103 to 6.21?103 pa, the von Mises stress increased from 4.43?106 to 1.78?107 N/m, and the X-displacement increased from 1.6 to 5.5 mm when increasing the plate angle from 30 to 90?.

Numerical analysis of mixed convection and Thomson-Troian slip effects on ternary nanofluid flow and heat transfer over a stretching sheet with porous media: Darcy-Forchheimer model

The present study unveils research that examines the laminar motion of water-infused nanofluid comprised of nanoparticles of TiO2 (titanium dioxide), Ag (silver), and Cu (copper) over a stretching sheet. The flow undergoes a novel slip condition based on Thomson and Troian to model complex fluid behavior near solid walls and incorporate the Darcy-Forchheimer model to comprehensively analyze the influence of a porous medium on flow behavior. Moreover, a heat source/sink and radiation are included to ensure the outcome of the energy equation will resemble most actual-world applications. Partial differential equations (PDEs) of higher order, originally used to describe the system are then reformulated into higher-order non-linear ordinary differential equations (ODEs) by taking symmetry variables that are chosen thoughtfully. The resulting boundary layer equations are then turned into a set of ODEs by implementing relevant similarity transformations, which can be solved using the M ATLAB function bvp4c. Through graphs, the variations in the velocity, Nusselt number, temperature, and skin friction coefficient were displayed. The outcome showed that the incorporation of silver nanoparticles (0.01–0.03) enhanced the skin friction coefficient by ≈ 1.68 % and the Nusselt number reduced up to ≈ 5 %. The Forchheimer number also reported a 6.5% enhancement and 1.5% reduction in the skin friction coefficient and the Nusselt number, respectively. The velocity slip parameter γ1 correlates with an upswing in temperature and skin friction coefficient for the ternary nanofluid while observing a decline in the velocity and Nusselt number.