Narrow Results

The structure of nanoparticles and their thermophysical characteristics potentially affect the performance of nanofluids. The thermal conductivity model termed as Hamilton–Crosser’s model accommodates the influence of nanoparticles shapes for thermal enhancement applications. Hence, this research aims to analyze the thermal transport in ternary nanofluids using Hamilton–Crosser’s model. The problem is formulated for stagnation point flow using the similarity variables in the governing laws. The traditional nanofluid problem is modified for ternary nanofluids with additional physical aspects of heat generation, thermal radiations, thermal slip effects over the convectively heated domain, and dissipation effects. Then, the numerical scheme (shooting method coupled with RK technique) is implemented for the results. The physical outcomes revealed that stronger unsteady effects $({\alpha }_2=0.1,0.8,1.5,2.2)$ increased the movement of the fluid while nanoparticles concentration $({\varphi }_1=0.01,0.02,0.03,0.04)$ abstain the fluid motion. The thermal transport in spherical-type nanoparticles is observed dominant when the Biot number varies $(B_1=0.1,0.2,0.3,0.4)$. However, the increasing transient effects $({\alpha }_2=0.1,0.2,0.4)$ slow down the model efficiency. Addition of platelet nanoparticles is observed as good for cooling of the nanofluidic system followed by the hexahedron and spherical nanomaterial. Moreover, higher dissipation energy, heat generation, and radiation effects are examined as excellent physical parameters to make the fluidic system more efficient.

This paper aims to establish a panoramic foundation for investigating the impact of sunlight on a recently formulated water-based tri-nano hybrid Sutterby liquid (TNHF) under provided magnetic field, directed through photovoltaic solar panels by exploiting the knacks of machine intelligent computing paradigm. The comparative performance of hybrid and tri-nano fluidic system with water as a base fluid is exhaustively analyzed and discussed. This research is unique, as it has a distinguished figurative comparison analysis between two different types of nanofluidic materials, which helps to choose the best one for use in agrivoltaics systems, and replace the materials already in use to enhance the efficiency and performance coefficients. Furthermore, the description of the composition scheme makes this research more feasible and applicable. A numerical dataset of nonlinear mathematical model is generated by employing finite difference scheme in the recently introduced Python bvp-solver algorithm, then it is embedded into artificial intelligence (AI)-based Levenberg Marquardt neural network algorithm (LMNNA). A significant outcome of the research indicates that the integration TNHF results in a notably faster enhancement of heat transfer rate and temperature framework as compared to traditional hybrid fluid. It is observed that introducing three distinct nanomaterials of specific thermophysical characteristics enhances the thermal exchanging profile and faces an obvious flow rate dissipation in solar plate channels. The standard numerical and AI-generated results are documented to portray the stability, accuracy and efficacy of scheme in terms of iterative learning curves on MSE, error analysis, histograms and regression statistics. Additional perquisites of the methodology include cost effectiveness, time-saving ability, robustness, stability and its extendibility.

This work examines the magnetohydrodynamic (MHD) three-dimensional (3D) flow comprising Cu and Al₂O₃ water-based nanofluids. The effects of heat and mass transfer with the effects of nanoparticles are carried out in the existence of thermal radiation and convective heat and mass transfer boundary conditions. By applying the proper similarity transformations the partial differential equations describing velocity, temperature and nanoparticle volume fraction (NVF) are transformed to a system of nonlinear ordinary differential equations (NODE). An optimal homotopy analysis technique is applied to evaluate the analytical solutions. The influences of pertinent parameters on the velocity, temperature and NVF are displayed in graphical and tabular forms. Calculations of Nusselt number, skin friction coefficients and the local Sherwood number are evaluated via tables. An excellent comparison has also been made with the previously-published literature.

Molten salts constitute one kind of PCMs (Phase Change Materials) widely used in concentrating solar power facilities for heat storage and heat transfer. This paper aims to simulate nanofluid PCMs with molecular dynamics method. Concretely, the thermophysical properties of a nanofluid of KNO₃ doped with SiO₂ nanoparticle are investigated by equilibrium and nonequilibrium molecular dynamics simulations. For the first time, these properties of a nanofluid in the family of PCMs are calculated. The density, thermal expansion coefficient, specific heat capacity, thermal conductivity, and viscosity are characterized as functions of the SiO₂ nanoparticle concentration. The effect of the SiO₂ nanoparticle size on the nanofluid’s properties is also investigated. The simulation results present an enhancement of the thermophysical properties, especially for the specific heat capacity, in good agreement with the existing experimental results on a representative nanofluid PCM, and open prospects for the understanding of microscopic mechanism leading to such enhancements.

This paper adopts a theoretical approach to explore the heat and mass transport features for MHD Jeffery–Hamel flow of viscous nanofluids through convergent/divergent channels with stretching or shrinking walls. Recently, this type of flows generated by nonparallel inclined plates with converging or diverging properties has been frequently utilized in various industrial and engineering processes, like, blood flow through arteries, different cavity flows and flow through canals. The current flow model is formulated mathematically in terms of partial differential equations (PDEs) in accordance with conservation laws under an assumption that the flow is symmetric and purely radial. In addition, heat and mass transport mechanisms are being modeled in the presence of Brownian motion and thermophoretic aspects using Buongiorno’s nanofluid model. The dimensionless variables are employed to get the non-dimensional forms of the governing PDEs. The built-in MATLAB routine bvpc4 is implemented to determine the numerical solutions for governing the nonlinear system of ordinary differential equations (ODEs). Numerical results are presented in the form of velocity, temperature and concentration plots to visualize the influence of active flow parameters. The simulated results revealed that the Reynold number has an opposite effect on dimensionless velocity profiles in the case of convergent and divergent channels. Besides, the temperature distributions enhance for higher values of Brownian motion parameter.

In the recent decades, the increasing energy demands and its applications have seen the focus shifting to the hybrid nanofluid flows but so much is still left to be investigated. This analysis is executed to explore the hydro-magnetic flow to investigate the incompressible flow and heat transfer towards a stretching surface with velocity and thermal slips. The scaling similarity transformations are created using Lie group analysis and employing these to convert nonlinear partial differential equations to the nonlinear ordinary differential equations. Here, after converting equations from dimensional to non-dimensional, we will use the BVP4C solver (MATLAB) for plotting the graphs to analyze how distinct non-dimensional parameters affect the skin friction and Nusselt number transfer rate, case 1 graphene + CNT + aluminum oxide with base fluid as water and case 2 magnesium oxide + zirconium oxide + copper oxide with water as base fluid, here taking nanoparticles without different shapes. The hybrid nanofluid temperature profile has mixed behavior, and the velocity profile increases when M rises. The hybrid nanofluid temperature profile curvature has composite behavior when $Pr$ rises. The link between several independent or predictor variables and one dependent or criterion variable has been examined using multilinear regression analysis (MLR). When coefficient values for many variables are subject to change, it can forecast a wide range of outcomes.

The thermal applications of nanofluids are extremely high and researchers have suggested multidisciplinary applications of nanomaterials in heat transfer problems, thermal systems, chemical industries, thermal energy systems, nuclear processes, extrusion mechanism, etc. The aim of this work is to discuss thermal properties of nanofluids for Poiseuille flow with hydrodynamic effects. The magnetohydrodynamic Poiseuille flow of thermo-capillary levels of nanoparticles with apparent viscosity nanofluids is focused. The graphene oxide (GO) nanoparticles are immersed in water-based fluid. The formulated system is solved numerically by using the Chebyshev collocation method. The mathematical technique Qualitat and Zuverlassigkeit (QZ) is applied to find out eigenvalues from comprehensive Orr–Sommerfeld technique. It is noted that the flow of nanofluids becomes stable due to the wave number and magnetic field. The Reynolds and Prandtl numbers have dynamic role on destabilizing the nanofluids transportation. The outcomes of this study are utilized in drug-delivery systems, photodynamic therapy and delivery of antitumor.

This paper describes the fundamental characteristics of cavitation in non-Newtonian liquids and bubble dynamics and then applies them to the domains of bioengineering and biomedicine. The goal of this paper is to examine how Newtonian nanomaterial flows hydromagnetically when subjected to a spinning disc considering such biomedical and bioengineering applications. The vertical axis of the disc rotates with a uniform angular frequency. The fundamental mathematical expressions are governed by the Navier–Stokes equations with the Maxwell equations of magnetism, we obtained ordinary differential equations utilizing Von Kármán’s similarity transformations. Additionally, the effects of the magnetic field and radiation restrictions are considered. The RK-4 technique is used to solve the transmuted nonlinear ODEs. The analysis of MATLAB generated flow profiles has looked for changes in the values of key parameters. It is discovered that an increase in the thermal radiation parameter causes a decrease in the nanofluid temperature while an increase in the volume fraction of magnetite nanoparticles causes an increase. The skin-friction and heat-transfer rate at the disc are highly influenced by its rotational, the porosity of the porous media, thermal radiation and nanoparticle size. The rotational parameter, which regulates the disk’s rotation, is a result of the rotating phenomenon. The research demonstrates that when the disk’s rotation increases, the fluid motion accelerates in both the radial and cross-radial directions. Additionally, increasing the Prandtl number significantly improves heat transport, and a higher value for the rotation parameter shows a lesser concentration phenomenon. Additionally, the Nusselt number shows a decrease curve for a changeable thermal conductivity parameter. Finally, the current research can effectively close a gap in the physique of knowledge.

This work investigates a non-Newtonian MHD Carreau nanofluid over a stretched vertical cylinder of an incompressible boundary layer with mobile microorganisms. The flow exists in permeable media and follows the modified Darcy’s law. An unchanged normal magnetic strength to the walls saturates the system. Ohmic dissipation, heat source, modified chemical reaction with activation energy properties, heat, volumetric nanoparticles fraction as well as microorganism profiles are covered. Thermal conductivity and mass diffusivity are taken as functions of heat and nanoparticle concentration, correspondingly. The fundamental governing system of nonlinear partial differential equations (PDEs) is converted into nonlinear ordinary differential equations (ODEs) by employing appropriate similarity transforms. The latter system is numerically analyzed through fourth-order Runge–Kutta (RK-4) simultaneously with the shooting process. The numerical outcomes showed that the curvature coefficient, magnetism and chemically activated energy perform a significant role in the velocity, heat, nanoparticle and chemical organism distributions. The impacts of several physical restrictions are tested and portrayed in a group of graphs. It is observed that the presence of microbes and nanoparticles, which are described in buoyancy terms, causes the flow to decay and slow down. By lowering the buoyancy and bio-convection characteristics, this infection can be prevented. With the development of all heat-related elements, heat transfer is enhanced, which is a significant feature associated with the current flow. These insights are important and useful in various physical and engineering fields.

An electrically conducting time-dependent flow of water-based nanofluid comprised of Copper and Titanium oxide over a stationary plate embedding with a porous matrix is analyzed in this study. The novelty arises due to the interaction of both the thermal radiation as well as the radiation absorption that affect the heat transport phenomenon. In the single-phase flow, both the variation of particle concentration and the solutal concentration for the inclusion of chemical reaction are taken care of. Also, the influence of the free convection phenomena is explained significantly. The transformed dimensionless system of the governing equations is handled analytically by using the Laplace Transform method. The behavior of the characterizing parameters involved in the governing equations is presented via graphs and the simulation of the numerical results of the rate coefficients like shear rate and rate of heat and solutal transfer is deployed through the table. However, the physical significance of these parameters is deliberated briefly. Finally, the important outcomes are higher heavier species because of lesser solutal diffusivity which attenuates the fluid concentration throughout the domain. Further, radiation absorption causes a significant boost in the nanofluid temperature distribution.

The wire coating method is an engineering development to cover a wire for wadding, motorized forte and ecological protection. In wire coating analysis, moreover, the polymer extruded on the wire is hauled into interior of a die occupied with melted polymer. By considering this significance, the magneto-hydrodynamic flow and heat transmission of Oldroyd-8 constant fluid with suspension of nanoparticles in the wire coating development had been investigated. The fluid with fixed viscosity is considered in porous medium. The flow is conducted with uniform magnetic field. The arising physical governing system is modelled mathematically. The mathematical model is executed by incorporation of thermal radiation and nanoparticles (Embedded in $\mathrm{\text{water}}+\mathrm{\text{hematite}}$ nanoparticles). The wire coating is scrutinized mathematically with four cases ($(\mathrm{\Omega }=0.5,\varnothing =0),\mathrm{\Omega }=0.5,\varnothing =0.05,\mathrm{\Omega }=-0.5,\varnothing =0,\mathrm{\Omega }=-0.5,\varnothing =0.05)$ with constant viscosity and also included in the Reynolds model for constant viscosity. The subsequent flow and heat transmission system were elucidated via the Runge–Kutta technique and the possessions of appropriate governing factors are presented in graphically. The outcome of the current investigation was equated with the previous available outcomes as a specific situation. The results were executed with nanofluid and without nanofluid as well as with positive and negative pressure gradients $(\mathrm{\Omega }=0.5,\varnothing =0),\mathrm{\Omega }=0.5,\varnothing =0.05,\mathrm{\Omega }=-0.5,\varnothing =0,\mathrm{\Omega }=-0.5,\varnothing =0.0$. It is seen that the temperature circulation is augmented due to the upsurge in magnetic parameter M. It is interesting to note that the positive pressure gradient with nanofluid has less momentum distribution compared to rest of the cases. It is also noted that the with negative pressure gradient, the distribution is more compared to positive pressure gradient case.

In this paper, we investigate the analysis of Oldroyd 8-constant fluid flow with nanoparticle suspension via a porous media during the coating of wire is carried out. A constant magnetic field and electrically conducting fluid are considered. The governing equations thus obtained for the present model are converted to nonlinear differential equations using variables in dimensionless form. These equations are analytically solved. The influence of some parameters, like magnetic field parameter, porosity parameter, dilatant constant, pseudo-plastic constant and Brinkman number on velocity and temperature distributions are discussed graphically. For fluctuating viscosity, two models, Reynold’s and Vogel’s are considered. It is observed that the magnetic parameter and the Brinkman number increase, both temperature and velocity profiles show a retarding effect in both Reynold’s and Vogel’s models.

The aim of this work is to present a natural convective and squeezing flow model of two-dimensional couple stress nanofluid which is flowing on the sensory surface with variable fluid viscosity. The fluid flowing on a microcantilever sensory surface and squeezing is happening at free stream. The sensor is also useful to detect the movement of fluid and the variations in thermal and solutal rates. The Cattaneo–Christov model is adopted along with nanoparticle and chemical reaction to explore the transmission of heat and mass rates. The analysis of heat transmission in non-Newtonian couple stress fluid flowing on squeezed sensory surface by using the Cattaneo–Christov heat conduction model has various industrial and scientific applications including the polymer processing, wastewater treatment, chemical reactors, biomedical flows, cooling and heating processes in industries, heat exchangers, microfluidics, oil and gas industries. All the assumptions are applied in the basic governing laws laws and then we get the model of the partial differential equations. The governing model of equations is transmuted into ordinary differential equations form via the transformations and then the numerical results of these ODE’s are examined with a well-defined numerical technique “Shooting Method”. For higher inputs of couple stress, squeezing index and permeability velocity, the fluid’s internal velocity decreases. Because of the Prandtl number and thermal relaxation coefficient, the heat transfer mechanism slows down. Mass transfer increases for greater inputs of the thermal diffusivity coefficient and decreases due to concentration relaxation. Further, the numerical dependency of emerging parameters on the skin friction is illustrated in tabular form. The parametric effects on the model (velocity, temperature and concentration) are introduced using numerical values shown in the table.

This paper presents a novel single-step method for preparation copper nanofluids by electrical explosion of wire in liquid. Three types of fluids were used as a medium of the wire explosion process: deionised water, cetyl trimethyl ammonium bromide (CTAB) solution 0.001 M and ethylene glycol. The X-ray diffraction (XRD), field emission scanning electron microscope (FE-SEM), energy dispersive spectroscopy (EDS) and UV-vis spectroscopy were used to investigate the properties of the nanofluids. Pure copper phase was detected in the nanofluids using ethylene glycol and mixture of copper and oxide phase was observed in the nanofluids using water and CTAB solution. FE-SEM analysis showed that size of particles formed in ethylene glycol was about 90 nm, the smallest in three samples.

In this study, an investigation has been carried out to examine the effects of thermal radiation, heat generation/absorption, viscous dissipation and suction parameter on MHD flow of water-base nanofluid (Ag, Cu, Al₂O₃, CuO and TiO₂). This study also focused on the mixed convective flow of water-base nanofluid due to a vertical permeable plate in the presence of convective boundary condition. Further, heat transfer has been inspected for water-base fluid influenced by heat generation/absorption and viscous dissipation. Moreover, the governing equations are reduced to nonlinear ordinary differential equations via Sparrow–Quack–Boerner local non-similarity method. These nonlinear ODEs are simulated numerically by means of Runge–Kutta–Fehlberg method (RKF-45). The impact of pertinent parameters on the dimensionless velocity, nanofluid temperature, skin friction and local Nusselt number are discussed and displayed. The results match with a special case of formerly available work. The present exploration exhibits that nanoparticle volume fraction increases the velocity and temperature of Cu-water nanofluid. It is also shown that magnetic parameter reduces the heat transfer rate.

Modern biomedical and tribological systems are increasingly deploying combinations of nanofluids and bioconvecting microorganisms which enable improved control of thermal management. Motivated by these developments, in this study, a new mathematical model is developed for the combined nanofluid bioconvection axisymmetric squeezing flow between rotating circular plates (an important configuration in, for example, rotating bioreactors and lubrication systems). The Buongiorno two-component nanoscale model is deployed, and swimming gyrotactic microorganisms are considered which do not interact with the nanoparticles. Thermal radiation is also included, and a Rosseland diffusion flux approximation is utilized. Appropriate similarity transformations are implemented to transform the nonlinear, coupled partial differential conservation equations for mass, momentum, energy, nanoparticle species and motile microorganism species under suitable boundary conditions from a cylindrical coordinate system into a dimensionless nonlinear ordinary differential boundary value problem. An efficient scheme known as differential transform method (DTM) combined with Padé-approximations is then applied to solve the emerging nonlinear similarity equations. The impact of different non-dimensional parameters i.e. squeezing Reynolds number, rotational Reynolds number, Prandtl number, thermophoresis parameter, Brownian dynamics parameter, thermal radiation parameter, Schmidt number, bioconvection number and Péclet number on velocity, temperature, nanoparticle concentration and motile gyrotactic microorganism density number distributions is computed and visualized graphically. The torque effects on both plates, i.e. the lower and the upper plate, are also determined. From the graphical results, it is seen that momentum in the squeezing regime is suppressed clearly as the upper disk approaches the lower disk. This inhibits the axial flow and produces axial flow retardation. Similarly, by enhancing the value of squeezing Reynolds number, the tangential velocity distribution also decreases. More rigorous squeezing clearly therefore also inhibits tangential momentum development in the regime and leads to tangential flow deceleration. Tables are also provided for multiple values of flow parameters. The numerical values obtained by DTM-Padé computation show very good agreement with shooting quadrature. DTM-Padé is shown to be a precise and stable semi-numerical methodology for studying rotating multi-physical flow problems. Radiative heat transfer has an important influence on the transport characteristics. When radiation is neglected, different results are obtained. It is important therefore to include radiative flux in models of rotating bioreactors and squeezing lubrication dual disk damper technologies since high temperatures associated with radiative flux can impact significantly on combined nanofluid bioconvection which enables more accurate prediction of actual thermofluidic characteristics. Corrosion and surface degradation effects may therefore be mitigated in designs.

The aim of this study is to investigate the effects of thermal radiation and chemical reactions on magnetohydrodynamic hyperbolic tangent liquid, which includes nanoparticles on a stretched surface while taking into account Brownian motion and thermophoresis. The nonlinear partial differential equations governing the system are converted into nonlinear ordinary differential equations through suitable similarity transformations. The focus of the study is to elucidate important engineering concepts such as skin friction, Sherwood number, and heat transfer, as well as to understand the effects of various expressions on the different profiles. The Keller-box approach, a sophisticated numerical tool, is used to get the numerical answers to the current enquiry. The generated findings are extensively tested for correctness and dependability. The findings of this study might have far-reaching ramifications for a variety of technical applications, including heat exchangers, chemical reactors, and thermal management systems.The results show that the rate of mass transfer rises with the increment in the factors of chemical reaction, thermal radiation, nanoparticles volume, and Brownian motion.

Nanofluids with peristaltic flows are being studied in depth because they can be used in so many different ways, such as to diagnose and treat diseases. In this paper, the peristaltic flow of a nanofluid with viscosity and electric conductivity that change with temperature is used. There are different base fluids and nanoparticles that are being thought about. First, the governing equations are modeled, and then they are made easier to understand by assuming that the wavelength is long and the Reynolds number is small. To make a dimensionless differential system, the right dimensionless numbers are added. Mathematica’s built-on function NDSolve is used to figure out the numerical solution of the resulting system. To figure out how fast heat moves, researchers compare different combinations of base fluids and nanoparticles.

The miniaturization of electronic devices without compromising their heat dissipation capacities is the main concern due to the rapid evolution in power industries and engineering fields. The conventional methods of cooling or heating the devices are changed and old tactics of using conventional fluids for heat dissipation are replaced with nanofluids of strong thermal efficiency. In the present context, the experimental as well as theoretical studies of nanofluids (Cu–H₂O/Al₂O₃–H₂O) flow inside the wavy and microchannels are elucidated and discussed for different physical conditions. It is found that the use of Cu–H₂O/Al₂O₃–H₂O nanofluid improves the thermal efficiency of heat exchangers. The complex shapes and sizes of heat exchangers such as multilayer heat exchangers, heat exchangers with twisted and square shapes and multijet heat exchangers are considered effective coolants as compared with straight microchannel heat exchangers. The use of Cu–H₂O/Al₂O₃–H₂O nanofluids improves the overall heat transfer efficacy of electronic devices, and it is considered a promising coolant for various applications including aerospace (spacecraft and satellites), automobile (cooling the engines and power management in electric vehicles), renewable energy (solar plants), microelectronic devices (heat dissipation through the microprocessor and cooling the other components of devices) and modern heat exchangers of engineering domains.

Nanofluids, characterized by the dispersion of nanoparticles in a base liquid, have attracted significant attention in recent years due to their exceptional thermal properties. Specifically, the specific heat capacity of nanofluids plays a crucial role in the design and optimization of heat transfer systems. Traditional experimental methods for determining the specific heat capacity of nanofluids are often limited in terms of cost, time, and operating condition ranges. To address these limitations, this research focuses on the development of a novel predictive model for estimating the specific heat capacity of nanofluids. This study aims to develop a machine learning regression model called Gradient Boost Regression (GBR) with Grid Search optimization (GSO) for accurately predicting the specific heat capacity of aluminum nitride (Al₂N₃) nanoparticles that are suspended in both water and an ethylene glycol (EG) solution. The GBR-GSO model capitalizes on the strengths of GBR, which can effectively capture complex relationships, and GSO, a metaheuristic optimization technique inspired by the law of gravity. By integrating these two approaches, we aim to create a robust and accurate predictive model for specific heat capacity in nanofluids. To develop and validate the GBR-GSO model, a diverse dataset based on experimental-specific heat capacity collected from the literature has been designed. The performance of the model has been evaluated by comparing its predictions with experimental data. The GBR-GSO model achieved 99.99% accuracy with the experimental data of specific heat capacity. This research contributes to the advancement of nanofluid-based heat transfer systems by providing an effective tool for predicting the specific heat capacity of nanofluids. The developed model can facilitate the design and optimization of various engineering applications, leading to the development of energy-efficient and sustainable technologies.