Nanofluid Model Research Articles

Review on velocity slip with thermal features of irregular heat transport enhancement of hybrid nanofluids

In engineering and industrial processes, hybrid nanofluids, an advanced form of nanofluid, are used to improve thermal efficiency. Hybrid nanofluids have various uses in refrigeration, tumor treatments, power stations, cooling systems, food processing, biomedical devices, and solar thermal systems. Thus, the major purpose of this article is to examine the heat transport features of a hybrid nanofluid on the dynamics of Zn-Ti6Al4V/H2O. The flow phenomenon of such fluid is produced by a shrinking disk when momentum and the thermal phenomenon are maintained. The classical transformation is employed to alter the flow model of a hybrid nanofluid in the form of non-linear ODEs. The produced model is tackled numerically through the MATLAB solver bvp4c function. The aspects of different emerging physical constraints on the flow field, fluid temperature, drag friction, and Nusselt number are exemplified thoroughly. The study finding reveals that the addition of a hybrid nanofluid in a flow system shows a promising increase in thermal transportation rate. The friction drags coefficient and thermal transportation rate show an upsurge in both solution branches for an increment in the suction parameter. Furthermore, higher values of the thermal conductivity parameter show an enhancement in fluid temperature for both branches.

Numerical analysis of bioconvective heat transport through Casson nanofluid over a thin needle.

Bioconvective flows over a thin needle hold significant importance in various fields, particularly in biomedical engineering, microfluidics, and environmental science. This paper examines the bioconvective flow properties of a copper and blood-based Casson nanofluid over a thin needle, accounting for gyrotactic microorganisms in the presence of a magnetic field. The two-phase nanofluid model is applied to formulate the flow problem. The system of non-dimensional ordinary differential equations is obtained by reducing the governing partial differential equations with the help of similarity variables. Further, the ODEs are numerically solved using the 4th-order Runge-Kutta method based Shooting technique. The similar solutions of the non-dimensional ODEs are represented graphically and the blood-based nanofluid's velocity, temperature, concentration, and presence of microorganisms are examined with reference to the accompanying diagrams. A detailed analysis is provided for skin friction, Nusselt number, and microorganism density number. The primary outcomes reveal that the augmentation of the mixed convection parameter and buoyancy ratio parameter enhance the rate of heat transfer.

Thermal Performance Analysis of a Nonlinear Couple Stress Ternary Hybrid Nanofluid in a Channel: A Fractal-Fractional Approach.

Nanofluids have improved thermophysical properties compared to conventional fluids, which makes them promising successors in fluid technology. The use of nanofluids enables optimal thermal efficiency to be achieved by introducing a minimal concentration of nanoparticles that are stably suspended in conventional fluids. The use of nanofluids in technology and industry is steadily increasing due to their effective implementation. The improved thermophysical properties of nanofluids have a significant impact on their effectiveness in convection phenomena. The technology is not yet complete at this point; binary and ternary nanofluids are currently being used to improve the performance of conventional fluids. Therefore, this work aims to theoretically investigate the ternary nanofluid flow of a couple stress fluid in a vertical channel. A homogeneous suspension of alumina, cuprous oxide, and titania nanoparticles is formed by dispersing trihybridized nanoparticles in a base fluid (water). The effects of pressure gradient and viscous dissipation are also considered in the analysis. The classical ternary nanofluid model with couple stress was generalized using the fractal-fractional derivative (FFD) operator. The Crank-Nicolson technique helped to discretize the generalized model, which was then solved using computer tools. To investigate the properties of the fluid flow and the distribution of thermal energy in the fluid, numerical methods were used to calculate the solution, which was then plotted as a function of various physical factors. The graphical results show that at a volume fraction of 0.04 (corresponding to 4% of the base fluid), the heat transfer rate of the ternary nanofluid flow increases significantly compared to the binary and unary nanofluid flows.

Heat transfer analysis of Cu-Water nanofluid in a square enclosure using Caputo fractional derivative and machine learning

Fractional-based fluid transport modeling provides a deeper and more comprehensive understanding of the thermophysical properties of small-scale fluids and polymer solutions. Moreover, the fractional-order fluid dynamics framework finds applications in various fields, including renewable energy systems, thermal energy storage, and oil storage tanks. Inspired by these developments, the current study addresses the computational challenges inherent in modeling nanofluid dynamics within a square enclosure by introducing a fractional-order approach to enhance the simulation of buoyant flow and heat transport. Our model integrates the linear interpolation (L1 approach) and finite difference approximation for temporal and spatial derivatives by utilizing the Caputo time-fractional derivative instead of the conventional time derivative. This integration facilitates the use of the Backward Difference Alternating Direction Implicit (BD-ADI) method, which was specifically chosen to reduce the computational burden associated with the non-local characteristics of fractional models. Our results show that by altering the fractional order, significant improvements in heat transfer efficiency are achieved compared to classical models. For instance, compared to the integer order, a lower fractional-order parameter of γ=0.80 with a 4% nanoparticle volume fraction at a Rayleigh number of 103 increases the heat transfer rate by 15.77%. However, at a Rayleigh number of 106, the enhancement reduces to 4.15%, indicating that fractional adjustments’ influence diminishes at higher thermal buoyancy levels. This behavior of the fractional-order nanofluid model, influenced by thermal buoyancy force, has been investigated by using a Multiple Linear Regression(MLR) analysis with 258 numerical samples. Besides, MLR analysis further identifies the nanoparticle volume fraction as a critical factor, influencing the heat transfer rate by 10.48% at lower fractional-order settings.

Influence of Higher Order Chemical Reaction on Rotational and Permeable Radiative Flow with Interruption of Micro-organism

Objective: The concentration on the function of the non-Newtonian radiative Casson Nanofluid model via a permeable and stretchable cone has been investigated. The innovation of the problem is Casson, taken as base fluid, and Manganese Ferrite is dropped in the base fluid under the action of a higher-order chemical reaction. This study examines the convective magneto-hydrodynamic (MHD) flow of a conducting micro-organism fluid confined within a horizontal channel via stimulus of a transverse magnetic field (MHD) and thermal radiation parameter. Methods: The foremost partial differential equations (PDE) are changed into an arrangement of ordinary differential equations by applying adequate corresponding transform. The outputs of these equations are performed numerically employing the RK method and computed by well-established BVP4C MATLAB software Special features such as radiation, heat generation/absorption, Joule heating, and electrically conductive MHD are examined. Skin friction and Nusselt number are incorporated into the flow and results are tabulated and outcomes are discussed graphically. Findings: The system incorporates the effects of micro-organism, pressure gradient and the movement of the moving cone. The generated heat is significant enough to cause radiation from both the fluid and the dust particles. Solutions for velocity and temperature distributions of the fluid, as well as the velocity and energy of the dust particles, are obtained using a perturbation scheme. The analytical impact of numerous geometrical parameters on both fluid and dust particle profiles has been analyzed and illustrated graphically. The impact of nonlinear partial derivative formulations is developed subjected to boundary layer theory. Novelty: As labelled in the results, heterogeneous is the examination of thermal radiation in science and technology such as liquid metal fluids different momentum devices for missiles, and turbines of gas effects on thermal radiation are exhibited and distinguished in various investigations and mathematical applications uses of the view in which radiant production be dependent on temperature are point out as a new value to the prevailing literature. Keywords: Thermal radiation, Brownian motion, Buoyancy flow, Chemical reaction, Heat and Mass transfer, Rotating cone

Cattaneo‐Christov model for cross nanofluid with Soret and Dufour effects under endothermic/exothermic reactions: a modified Buongiorno tetra‐hybrid nanofluid approach

AbstractThe previous researchers used a slightly different version of the Buongiorno hybrid nanofluid (BHNF) concept. In the existing research, there is not a single effort that was undertaken to explore the effect that tetra hybrid nanoparticles (tethnf) implanted with the BHNF model have on liquid movement that is then exposed to an elastic sheet. This endeavor focuses on researching the implication of a modified Buongiorno tetra hybrid cross nanofluid concept on magnetized radiative cross nanofluid transport, along with impacts such as Cattaneo–Christov heat flux and Cattaneo–Christov mass flux, variable thermal conductivity, diffusion‐thermo and thermo‐diffusion effects, and endothermic/exothermic type chain reactions. This approach integrates both Buongiorno and tethnf. By inserting similar variables, the controlling model partial differential equations have been transformed into dimensionless Ordinary differential equations. These equations are then treated computationally with the help of the Lobatto III A technique. The MATLAB computer program is used to produce simulation solutions, as well as the findings, which are displayed in the form of graphs and tables. Based on the results that have been gathered, it was discovered that the speed of heat delivery increases when there is an increase in the speed of an endothermic reaction. When the Dufour and thermal relaxation factors are increased, the speed at which heat is transmitted also increases. The fluid viscosity becomes more pronounced as a result of an increase in the viscosity index n, the Weissenberg number We, and the magnetic field M, all of which contribute to a reduction in the velocity distribution. A progressive change in the radiation parameters Rd, Dufour effect, and thermal conductivity which magnifies Nusselt number causes an increase in the heat delivery rate, which in turn amplifies Nusselt number.

Mathematical and Buongiorno nanofluid modelling to predict the thermal and solutal performance of magneto-bioconvective Casson nanofluid flowing in a rotatory disk

Abstract This study aims to improve how heat and mass move in systems that use viscoelastic nanofluids under magnetic fields. These systems are commonly used in industries like biotechnology, energy, and medical devices. The significance of this work lies in exploring the steady flow of magnetohydrodynamic (MHD) Casson nanofluids, incorporating the Buongiorno nanofluid model and swimming microorganisms. This research seeks to deepen the understanding of complex fluid behaviors by examining the effects of thermal radiation and chemical diffusion under thermal and solutal convective boundary conditions. The governing equations, which are inherently nonlinear due to the presence of multiple physical effects, are converted from two-dimensional partial differential equations (PDEs) to ordinary differential equations (ODEs) using a similarity transformation. A semi-analytical solution is derived using the collocation pseudo-spectral method within the MAPLE computational software. The study investigates how factors like Casson and magnetic parameters, Eckert number, Brownian motion, and thermophoresis affect the flow rate, temperature distribution, species concentration, and microorganism motility. These results are validated by comparing them with established benchmarks. The key findings reveal a pronounced oscillatory behavior in the temperature profile at higher Eckert number values, while increased Brownian motion and thermophoresis lead to greater nanoparticle dispersion near the disk surface. Higher Lewis and Peclet numbers lead to increased microorganism concentration, demonstrating stronger convective and advective effects. These insights are vital for optimizing drag force, thermal gradients, and mass transfer in engineering applications that involve rotating disks and magnetic fields.

Simulation of blood flow in a tapered artery with ternary hybrid nanofluid and Jeffrey model

This research simulates flow of blood in a tapered peristaltic artery integrating ternary hybrid nanofluid using the Jeffrey fluid model. The simulation examines the effects of Au, Fe3O4, and Ag nanoparticles on the flow. The artery, modeled as a peristaltic channel, is subjected to nonlinear thermal radiation, magnetic forces, and heat source. The problem is formulated using non-linear Cartesian partial differential equations, which are then transformed into dimensionless form without approximations. Adomian Decomposition Method (ADM) is employed to solve these equations, revealing how normal and shear stress, normal and axial velocities, induced magnetic fields, and temperature profiles vary with changes in relevant parameters. Additionally, biological factors are considered to graph streamlines, providing a comprehensive analysis of the flow dynamics. Some notable results include that adding ternary nanoparticles increases the Nusselt number by 26.03% in Newtonian fluids and 158.69% in Jeffrey fluids, and increasing tapering parameters and wavenumber improves axial and normal velocities, heat transfer, and flow complexity.

Bio-convective flow of non-Newtonian Williamson nanofluid model with heat generation and thermal radiation aspects past over a stretched porous sheet via OHAM

Bio-convective flow of non-Newtonian Williamson nanofluid model with heat generation and thermal radiation aspects past over a stretched porous sheet via OHAM

Non-similar investigation of magnetohydrodynamics hybrid nanofluid flow over a porous medium with Joule heating and radiative effects

The aim of present article is to investigate the mixed convective magnetohydrodynamic (MHD) flow through non-similar modeling of hybrid nanofluid over a stretched surface with radiative effects. Nanofluids are considered a cutting-edge medium for energy transmission in the next generation, with outstanding thermodynamic features. The investigation of heat transfer on exponentially expanded sheets hold significant importance for researchers, given its broad range of applications in industries, manufacturing processes, and medical fields. In this study the flow is endorsed with the viscous dissipation, Joule heating and radiation impacts in the energy equation. In order to enhance the heat transfer, hybrid nanoparticles uniformly mixed with the base fluid. The differential equations emerged after the mathematical formulations are made non-dimensional via the non-similarity transformation up to the second order of iteration. To numerically simulate ordinary differential equations (ODEs), the MATLAB function bvp4c is employed. Key factors have been thoroughly mapped out in graphical form for easy comprehension. It is observed that when the strength of the Prandtl and Eckert number increases, the energy profile decreases, meanwhile temperature for expanding surface increases with an expansion in magnetic parameter. It is observed that the greater radiation quantities throughout the entire flux zone increase the thickness of the thermal boundary layer and the hydrodynamic temperature in the stretching situation. The increasing heat for expanding sheet causes fluid temperature to rise heat parameter, but the opposite consequences occur for shrinking sheet. The velocity reduces as the magnetic factor and the porosity parameter rises. The relevant engineering parameters, specifically the coefficient of skin friction and Nusselt number, have been documented in tabular form with respect to the significant factors mentioned earlier. The Nusselt coefficient decreases with an expansion in magnetic and the Ecker number. In accordance with the author's understanding, no previous work on the current model utilizing the local non-similarity method has been published. This discovery could help researchers who are interested in thermal power plants and solar energy storage. In limiting case, excellent agreement is found between present work and published article.

MHD Mixed Convection Boundary Layer Casson Nanofluid Flow over an Exponential Stretching Sheet

This paper investigates the effects of radiation, internal heat source and magnetohydrodynamics (MHD) on the mixed convective boundary layer flow of a Casson nanofluid within a porous medium that is saturated and subject to an exponentially stretching sheet. The nanofluid model incorporates Brownian motion and thermophoresis, and the Darcy model is employed for the porous medium. By applying an appropriate similarity transformation, the nonlinear governing boundary layer equations are converted into a set of nonlinear coupled ordinary differential equations. These equations are then solved numerically using the Hermite wavelet method, with simulations conducted through the MATHEMATICA programming language. The analysis covers various aspects including temperature distribution, velocity, solute concentration and several engineering parameters such as skin friction coefficients, the Nusselt number (rate of heat transfer) and the Sherwood number (rate of mass transfer), all evaluated based on dimensionless physical parameters. The results indicate that elevated radiation intensifies temperatures and leads to thicker thermal boundary layers. As the Casson parameter increases, both the velocity and the momentum boundary layer become narrower. Additionally, a more pronounced chemical reaction rate reduces the thickness of the solutal boundary layer. The accuracy and reliability of the numerical Hermite wavelet method are validated through a comparative analysis with previous studies, demonstrating excellent concordance and confirming the robustness of the computational approach.

Investigation of convective heat transport in a Carreau hybrid nanofluid between two stretchable rotatory disks

Abstract Hybrid nanofluids (HNFs) have outstanding energy transfer capabilities that are comparable to mono-nanofluids. Materials had appliances in obvious fields such as heat generation, micropower generation, and solar collectors. The objective of this study is to investigate the new aspects of convective heat transfer in an electrically conducting Carreau HNF situated between two parallel discs. In addition to the presumed stretchability and rotation of the discs, physical phenomena like nonlinear radiation, viscous dissipation, Joule dissipation, and heat generation and absorption are considered. The Cu and TiO2 nanoparticles dispersed in engine oil to understand the intricate phenomenon of hybridization. The Tiwari and Das nanofluid model is employed to model the governing partial differential equations (PDEs) and then simplified using boundary layer approximation. The suitable transformations of similarity variables are defined and implemented to change the set of formulated PDEs into ordinary differential equations. The reduced system is solved semi-analytically by the homotopy analysis method. The influences of involving physical parameters on the velocity and temperature are plotted with the help of graphical figures. This study brings forth a significant contribution by uncovering novel flow features that have previously remained unexplored. By addressing a well-defined problem, our research provides valuable insights into the enhancement of thermal transport, with direct implications for diverse engineering devices such as solar collectors, heat exchangers, and microelectronics.

The significance of magnetized thermal radiation on the magnetohydrodynamic (MHD) behavior of Williamson hybrid ferrofluids over a stretching sheet

The goal of this study is to investigate the fluid dynamics of a pseudoplastic Williamson nanofluid model, explicitly focusing on blood infused with magnetite (Fe2O3) and (Cu) copper nanoparticles, with the aim of enhancing its physiological and industrial applications. This research offers a novel approach by integrating the Williamson fluid model with magnetic nanoparticles, which has not been widely explored in biomedical applications like antitumor therapy and magnetic hyperthermia. The study is mathematically modeled using partial differential equations (PDEs) accounting for the deformation vortices of a stretching surface. These governing equations are transformed into ordinary differential equations (ODEs) via similarity transformations and solved numerically using the Runge-Kutta (R-K) 4th-order method coupled with the shooting technique. The velocity and temperature fields are then analyzed through MATLAB simulations. Results indicate that increasing the Williamson, radiation, and nanoparticle volume fraction parameters elevates the fluid temperature, whereas higher magnetic field strength, Prandtl number, and stretching parameter values reduce it. The novelty of this work lies in its application of the Williamson nanofluid model to real-time medical applications, such as cancer treatment through magnetic hyperthermia, and its potential use in advanced biomedical devices.

Sensitivity study of heat transfer in a Jeffrey ferro-hybrid nanofluid bioconvective squeezing flow with inclined MHD and higher-order chemical reaction: entropy analysis

Abstract The present investigation concentrates on analyzing heat transfer and entropy formation in a time-reliant bioconvective flow of a blood-based Jeffrey hybrid nanofluid via a squeezing channel that is suctioned or injected at the lower plate. Cu nanoparticles and Fe3O4 ferro-nanoparticles are suspended in base-fluid blood. Adding ferro-nanoparticles to a flow process allows for better control of the external magnetic field and improved heat transmission. Noble integration of an aligned magnetic field, Joule's heating, thermal radiation, and higher-order chemical reactions is taken into account in the flow in a porous media. An appropriate choice of similarity variables leads to the non-dimensionalization of the governing equations, that are subsequently solved by the homotopy analysis method (HAM), yielding a semi-analytical solution. An innovative feature of this research is the optimization of heat transfer by the application of the response surface methodology (RSM) technique. Additionally, sensitivity analysis was carried out to identify the most influential parameter. The study's findings indicate that increased suction reduces both velocity and temperature distributions in both the nanofluid and hybrid nanofluid models. In terms of thermal performance, the Blood/Fe3O4 - Cu hybrid nanofluid surpasses the Blood/Fe3O4 nanofluid. The rate of thermal energy transfer is highly sensitive to variations in the Eckert number, while thermal radiation has a relatively lesser impact. Moreover, elevated levels of the magnetic parameter, Eckert number, and nanoparticle concentration lead to augmented entropy formation. This mathematical model is effective for analyzing drug transport mechanisms throughout the human body and presents extensive potential applications in the fields of biology and healthcare.

On the onset of stationary convection on Jeffrey nanofluid layer saturated with a porous medium: Brinkman model

In this paper, we investigate the onset of convection in a Jeffrey nanofluid layer saturated with the porous medium using Darcy-Brinkmann model. Normal mode analysis and Galerkin type weighted residual method (GWRM) are used to analyse conservation equations. Effects of Brownian motion and thermophoresis are taken into account in the Jeffrey nanofluid model. The Buongiorno model deployed for nanoparticles incorporates the influences of thermophoresis and Brownian motion. Three cases of free-free, rigid-rigid and rigid-free boundaries are considered. For stationary convection, the effects of Darcy number, Jeffrey parameter, Lewis number, nanoparticle Rayleigh number, porosity and modified diffusivity ratio for all the above mentioned boundary conditions are investigated analytically and graphically. The numerical computed values of stationary thermal Rayleigh number are presented graphically for three distinct combinations of boundary conditions. The study is of great significance in many different areas such as automotive, pharmaceutical, geophysics, soil sciences, food processing, oceanography, limnology, etc., and excellent coincidence is found regarding the present paper and earlier published work.

Multilayer deep-learning intelligent computing for the numerical analysis of unsteady heat and mass transfer in MHD carreau nanofluid model

The objective of this article is to investigate the mechanism of unsteady heat and mass transfer (HMT) in a magnetohydrodynamics Carreau nanofluid flow (MHD-CNFF). To accomplish this, we utilized a novel artificial intelligence-based (AI) method, deep learning predictive technique combined with Levenberg-Marquardt scheme (DLPT-LMS). The similarity transformation is applied to convert the partial differential equations (PDEs) into a set of non-linear ordinary differential equations (ODEs). We numerically solved these resulting ODEs using the Adam numerical approach in sophisticated “Mathematica” software. The influence of Brownian motion parameter, thermophoresis parameters, Prandtl number, Lewis number, and mass transfer parameters on the temperature, velocity, and concentration profile is analyzed using a synthetic dataset. This evaluation is conducted across different variation of MHD-CNFF by leveraging DLPT-LMS. The absolute error (AE) across various iteration of MHD-CNFF demonstrated a progressive drop, indicating the accuracy of DLPT-LMS. The outcomes of this investigation revealed that the AE ranged from 10−3 to 10−8 which shows a minimum error between actual and predicted value. Additionally, the MSE confirmed the accuracy of proposed DLPT-LMS in predicting the behavior of velocity, temperature, and concentration profiles, with lower values showing better predictions. The model accuracy was reinforced by performance results, including regression analysis and error histograms. Error values gradually decreased during training, validation, and testing phases, exhibiting a robust convergence and indicating the highly reliability of AI-based algorithm for investigating intricate fluid dynamics in MHD-CNFF systems.

Heat transportation phenomena subject to Ellis fluid over a spinning body: A dynamics of trihybrid nanoparticles

AbstractThe boosting of base fluid thermal transport is a remarkable significance in the current research era, and numerous types of techniques are being utilized to achieve this goal. The mixture of nanoparticles inside the host fluid is responsible to improve base fluid thermal performance. The modified Buongiorno's nanofluid model is explored in the current study along with the significant trihybrid nanoparticle effect. The fundamental equations of the chosen flow model are transformed using a similarity transformation, and the succeeding equations are then resolved numerically using the discretization of Keller‐Box in MATLAB. The primary velocity profile is directly raised with large values of the Hartman number, unsteady, and Ellis's fluid parameters, while an inverse curves trend is reported in secondary velocity. The primary speed of fluid is significantly greater compared to di and mono‐hybrid cases, and this study reveals that optimal thermal transport is achieved against tri‐hybrid cases. The tri‐hybrid model has 9% improvement in Nusselt number when compared to single and two‐type nanoparticle fluid models.

A novel tetra hybrid bio-nanofluid model with stenosed artery

Abstract For treating and diagnosing cardiovascular diseases, the field of biomedical engineering is significant because it develops new ways and techniques. Stenosis is the narrowing of an artery, and it leads reduction in the flow rate of blood. This study investigates the blood flow mechanism in an artery using a mathematical model of Carreau nanofluid with four distinct nanoparticles. Tetra nanofluid model produces significant advancement in the simulation of blood flow through the stenosed arteries. The model is capable of predicting the pressure drop and velocity distribution for diagnosing and treating stenosis. The spectral relaxation approach is used to present the model's efficiency and effectiveness, which makes it a suitable method for solving the governing equations of this study. The findings of this study have important implications for the development of new treatments and diagnostic techniques for stenosis and other cardiovascular diseases.

Intelligent neuron based interpretation of carreau trihybrid nanofluid model with streamline analysis: Configuration of distinct geometries

This current attempt develops a more efficient predictive model that can accurately simulate the behavior of Carreau trihybrid nanofluids in non-trivial configurations. This study interprets thermal behavior of Carreau trihybrid nanofluid model with streamline analysis considering the two geometries wedge and cone. Three nanoparticles are involved in base fluid (water) with physical effects of non-uniform heat sink source and nonlinear thermal radiation are assumed for heat transport and Lorentz forces are considered for velocity inspection. Furthermore, this study employs intelligent neural networks to interpret data for streamline and thermal transport analysis, focusing on the specific cases of wedge and cone geometries. Initial data fetched through bvp4c and further, obtained data trained through supervised neural scheme, Levenberg marquardt neural network (LM-NN) is applied and required predictions are made. Higher “Gc” indicates stronger solutal buoyancy forces, which promote upward fluid movement, thereby increasing the velocity gradient. With increasing (M), the velocity profile decreases. Fluid exhibits enhancing the velocity gradient with higher (n). Higher particle concentration enhances the fluid's viscosity and resistance.

Entropy analysis of mixed convective electro-magnetohydrodynamic couple-stress hybrid nanofluid flow with variable electrical conductivity in a porous channel

The paper presents a novel study to examine the irreversibility of quadratically mixed convective electro-magnetohydrodynamic (EMHD) flow of a couple-stress hybrid nanofluid (CSHNF) with variable properties in a vertical porous channel. The channel walls are exposed to an applied electric field effect and a uniform transverse magnetic field. The hybrid nanofluid considered is an ethylene glycol (C 2 H 6 O 2) base mixed with multi-walled carbon nanotubes (MWCNT) and silver (Ag) nanoparticles (NPs), assuming the base fluid and nanoparticles to be in a state of thermal equilibrium following the Tiwari-Das nanofluid model. The potential applications of the study can be in microfluidics to nanofluidics, particularly in developing cooling technologies, EMHD pumps, high-end microelectromechanical systems (MEMS), and lab-on-a-chip (LOC) devices used in bioengineering. A constant pressure gradient acting in the flow direction and the buoyancy effect under the quadratic Boussinesq approximation drive the flow. The governing momentum and energy equations are nondimensionalized using pertinent dimensionless parameters and solved by the semi-analytical homotopy analysis method (HAM). The entropy generation and the Bejan numbers are derived to examine the irreversibilities in the system. To investigate the rate of shear stresses and heat transfer, skin friction coefficients and Nusselt numbers on the channel walls are determined. The analysis emphasizes the influence of nanoparticle concentration and electromagnetic field on the flow dynamics, temperature distribution, and system irreversibilities in the presence of porous media. It reveals the enhancement of fluid velocity and temperature degradation for higher concentrations. In contrast, both reduce for higher magnetic and electrical strength. With the enhancement of electrical joule heating and quadratic convection, a higher entropy generation rate is attained with a low rate of heat transfer irreversibility. However, it reduces with higher nanoparticle concentration, electrical strength, porosity, and variable electrical conductivity parameters under the dominance of heat transfer irreversibility.