Eyring-Powell Nanofluid Research Articles

Mixed convected synchronization of gyrotactic microorganism flow of an Eyring–Powell nanofluid over a riga plate

Mixed convected synchronization of gyrotactic microorganism flow of an Eyring–Powell nanofluid over a riga plate

Powell-Eyring Nanofluid Flow over a Stretching Sheet

This research investigates the flow of a Powell-Eyring Nanofluid flowing over an exponentially stretching sheet. Thermal radiation, Soret, dissipation, and Dufour effects have been put into consideration. The obtained partial differential equations(PDE) have been transformed into ordinary differential equations (ODE) using similarity transformation. Numerical solutions are obtained in MATLAB using bvp4c frame work of fourth order accuracy integration scheme. It has been observed that the boundary layer for momentum increases with the velocity ratio while the boundary layers for thermal and concentration decrease. The velocity diminishes with increasing magnetic parameter while the temperature and concentration increased. The temperature increases with an increase in thermophoresis and Brownian motion. Increasing the fluid parameter resulted in decreased Nusselt number, skin friction, and Sherwood number. Increasing Powell-Eyring fluid parameter decreases the Nusselt number and Sherwood number but increases skin friction. This research may find use in the development of microelectronics, chemical processes, human targeted drug delivery, and heating and cooling system.

Irreversibility analysis of Eyring Powell nanofluid flow in curved porous channel

AbstractThe aim of this study is to minimize entropy in the MHD Eyring‐Powell fluid through a semi‐porous curved channel. The flow phenomena are examined under the consideration of joule heating, viscous heating, thermophoresis, and Brownian motion. The motivation of this research is to minimize entropy production in curved porous channel because thermal systems become more efficient as a result of decreased energy consumption, operational expenses, and experimental costs. This approach is useful in designing industrial equipment that requires efficient thermal management, such as fuel cells, chemical processing, and advanced refrigeration systems. The coupled boundary layer equations of the problem are highly nonlinear PDEs, which are transformed into systems of coupled ODEs by using similarity variables. The solution of a coupled system of ODEs is obtained numerically via Bvp4c. The effect of several physical parameters for entropy analysis, Bejan number, concentration, and velocity/temperature are illustrated and analyzed using graphs. Furthermore, the computational outcomes of physical quantities, for example, heat and mass transfer rate are also presented. Results indicated that the increasing value of the Reynolds number increases the entropy generation rate, while the reverse tendency is noticed for the Eyring‐Powell parameter. The rising values of the Brownian parameter increase the Bejan number after its decrease, while reverse behavior is observed for the thermophoresis parameter.

Applications of neural networking in Eyring-Powell nanofluid dynamics on a rotating surface in a porous medium

One of the fundamental aspects of solving difficult and nonlinear mathematical ideas is the use of Artificial Neural Networks due to their exceptional efficiency in handling such problems. In many complex fields such as computational fluid system, biological computation, and biotechnology, a distinct computing structure is provided by Artificial Neural Networks, which is extremely valuable. The main purpose of this article is to dig out the abilities of the Levenberg-Marquardt technique using back-propagation artificial neural networks regarding the fluid mechanics and the heat transport assessment in nanoparticles. This interdisciplinary field explores heat and mass transfer through objects and fluids, and their impacts on temperature as well as concentration distributions. With the help of mathematical modelling and numerical solution methodologies, researchers can simulate and analyze these processes. The present analysis communicates the Eyring-Powell fluid flow caused by a rotating disk placed in the horizontal direction. The fluid flow over a rotating disk through non-linear partial differential equations is modeled. After converting the partial differential equations to ordinary ones, they are tackled numerically through shooting technique. The Levenberg-Marquardt algorithm using back-propagation artificial neural networks technique is used with reference datasets, having 70 % training, 15 % testing, and 15 % to validation. The method is validated with the help of mean squared error, error histogram and comprehensive regression analysis. These figures show the accuracy of the proposed method for solving nonlinear problems. Flow features such as velocity, temperature as well as the concentration profiles are exemplified quantitatively and have been graphically discussed. Velocity of the fluid decreases for porosity and increases for fluid parameter while temperature increases for thermophoresis and Brownian motion parameters. Consistency is shown by getting a minimum absolute error approaching zero, showing the strength of the proposed approach.

Exploration of flow irreversibility in electrically magnetized Eyring-Powell nanofluid along an inclined plate with viscous dissipation

Exploration of flow irreversibility in electrically magnetized Eyring-Powell nanofluid along an inclined plate with viscous dissipation

Passive control of bio-convective flow on Eyring–Powell nanofluid over a slippery surface with activation energy and magnetic impact

The current communication deliberates the consequences of the Darcy–Forchheimer flow of Eyring–Powell nanofluid past a slippery surface containing activation energy and motile microorganisms. The flow is influenced by the consequences of Brownian motion, thermal radiation, the Cattaneo–Christov heat-mass flux theory, and thermophoresis. The framed flow models are transformed into ordinary derivative equations by adopting appropriate conversion variables. The transformed equations are numerically tackled by using the bvp4c scheme in MATLAB. The study is remarkable for its comprehensive analysis of the interplay of several flow factors, such as the Forchheimer number, Richardson number, bioconvection Rayleigh number, radiation, thermophoresis, Brownian motion, thermal and mass relaxation time parameters. The outcomes are visualized through tables and diagrams, which provide significant insights into the intricate physical mechanisms involved in this multifaceted subject. Evidently, the velocity profile declines when there is a rise in the buoyancy ratio parameter and the opposite trend is obtained for the Richardson number. The temperature grows when there is a larger magnitude of the thermophoresis parameter and it reduces for greater values of the time relaxation parameter. The activation energy and mass relaxation parameters enhance the concentration profile. The microbe density increases when enhancing the quantity of Peclet number and it declines for bioconvection Lewis number.

Numerical evaluation for the peristaltic flow in the proximity of double-diffusive convection of non-Newtonian nanofluid under the MHD

This article mainly studies the 2-D propagation of a non-compressible Eyring-Powell nanofluid flow through a stretched wedge under the Magneto-hydrodynamic effect. Equations for temperature, concentration, double-diffusive convection and momentum are taken into consideration. Since solving the dimensionless equations associated with our study is an uphill task, we utilize the MATLAB bvp4c solver to illustrate the graphical performance of different parameters. This manuscript may be significant in the projects in the field of industry and medicine. The manuscript's noteworthy features include the magnetic field, heat source-sink parameter, double diffusivity, and solar radiation process. The main finding is that the local fluid parameter k1 and magnetic field parameter M decelerate the velocity of nanofluid. Because different nanoparticles have different effects on fluids, the fluid's temperature exhibits multiple behaviors, therefore by escalating the Prandtl number initially, it increases and then decelerates due to the presence of nanoparticles. The concentration of fluid declines as the Schmidt number rises. The double diffusivity of Eyring-Powell nanofluid improves with magnification in the fluid's Schmidt number Sc and Prandtl number Pr.

Study of gyrotactic motile microorganisms in powell-eyring nanofluid with non-fourier and non-fick’s theories

Study of gyrotactic motile microorganisms in powell-eyring nanofluid with non-fourier and non-fick’s theories

Thermally radiative flow of MHD Powell-Eyring nanofluid over an exponential stretching sheet with swimming microorganisms and viscous dissipation: A numerical computation

This work deals with the study of mass and heat transmission in nanofluid flow in the Powell-Eyring model over a sheet that is exponentially stretched with motile microorganisms. Additionally, viscous dissipation and radiation sources are considered. The governing flow expressions are remodeled into nonlinear ordinary differential equations by implementing the appropriate transformations. The remodeled equations are numerically computed by using the bvp4c technique via MATLAB. The various flow parameters are used to investigate and explain in depth the nanofluid velocity, thermal, nanoparticle volume fraction, and motile microbe density profiles. It is noted that the nanofluid velocity decreases with enlarging the values of the magnetic field parameter. The fluid thermal profile develops for greater quantities of radiation thermophoresis and Brownian motion parameters. The nanoparticle concentration decays when the Prandtl number and Lewis number are increased. The motile microbe density profiles suppress when heightening the values of the Peclet number, bioconvection Lewis number, and bioconvection parameter. The magnetic field parameter leads to a decrease in local skin friction, heat, and mass transfer rates.

Implementing the predictor-corrector approach to examine the thermo-solutal convection for buongiorno eyring-powell nanofluid model with squeezed microcantilivier surface

The Buongiorno nanofluid model serves as a foundational model for theoretical and experimental research in the field of nanofluids, and this model can be applied to various engineering problems, including heat exchangers, biomedical applications, solar collectors, nuclear reactors, and different cooling systems in the automotive and electronics industries. The use of nanofluids in the Eyring-Powell fluid over a squeezed sensing surfaces is a vital area of research for the design and improvement of microfluidic devices and sensors, which find widespread usage in industrial and medical applications. The main purpose of this work is to note the augmentation in thermal conductivity by using the Buongiorno nanofluid model along with the natural convective flow of non-Newtonian Eyring-Powell fluid that is moving on the squeezed sensory surface along with slip velocity. The viscosity of a fluid is assumed to be dependent on temperature. The Cattaneo-Christov heat and mass flux and chemical reaction are assumed to determine the combined effect of heat and mass transport. The governing model of equations is in the form of dimensional partial differential equations, and we have to convert these equations into ordinary differential equations; therefore, a set of similarity transformations is adopted for making the equations into dimensionless form. The numerical results were obtained by adopting the predictor and corrector multistep method, namely the ‘Adams-Bashforth’ technique, in Matlab software. The use of natural convective flow enhances the velocity region. The velocity slip parameter increases the velocity of the fluid, whereas the viscosity parameter drops the velocity profile. The thermophoresis and Brownian motion parameters are the sources of the increment in the temperature region. The thermal relaxation and solutal relaxation parameters are the sources of decline in the temperature region. The squeezing parameter is the source of reduction in the skin friction, whereas the result indicates that the fluid parameter, Grashof number, and viscosity coefficients increase the skin friction.

Thermal conductivity evaluation of radiative entropy optimized cross-flow in Eyring Powell nanofluid past a permeable deformable sheet: the case of solar-powered ship application

Thermal conductivity evaluation of radiative entropy optimized cross-flow in Eyring Powell nanofluid past a permeable deformable sheet: the case of solar-powered ship application

Cattaneo-Christov Heat Flux Model for Bio-Convective Radiative Eyring-Powell Nanofluid with Viscous-Ohmic Dissipation and Magnetic Dipole Impacts

In this work we studied the solutions of the bio-convected Eyring-Powell nanofluid involving gyrotactic micro-organisms in the presence of viscous-ohmic dissipation, double diffusion, and magnetic field over a stretched sheet under the impacts of nonlinear radiation and Arrhenius activation energy. The magneto-nanoparticles suspension in microorganisms are beneficial in nanofluid stability. Also, they have number of applications in nanosciences, biotech, pharmaceuticals, and mechanical development. The nonlinear coupled PDEs are transformed into ODEs by taking a suitable set of similarity transformations and then computationally solved with MATLAB’s bvp4c and RK4-Shooting technique. The skin friction coefficient, Nusselt number, and Sherwood number are represented in tabular form. The mass and heat transmission rate improve in the presence of gyrotactic microorganisms. The temperature as well as concentration of Eyring-Powell Nanofluid get decreased by accelerating the significant mass and thermal stratification. The concentration profile Φ(η) depreciate for higher Chemical reaction rate (σ), Schmidt number (Sc), and temperature difference (δ1) parameters but rises upon increasing values of Activation energy (Ea). Also, the microorganism concentration difference parameter (β1), bioconvection Lewis number Lb and Peclet number Pe are opposing the motile microorganism density profile.

Evolution of heat transfer in MHD nanofluid flow over a porous plate: Insights into the influences of slip and variable viscosity

Temperature-dependent viscosity finds application in various industries such as oil and gas, polymer processing, and food manufacturing. Understanding how viscosity changes with temperature is critical for optimizing processes like drilling operations, polymer molding, and food product consistency. Additionally, it plays a vital role in controlling flow behavior, ensuring efficient heat transfer, and maintaining product quality across different temperature conditions. The exploration of temperature-dependent viscosity in Powell-Eyring nanofluid models represents a novel and unexplored avenue in the field. The study’s novelty is underscored by its comprehensive investigation into a range of factors, such as surface suction, thermal radiation, slip velocity effects, and nanoparticle concentration slip, all integrated within the Powell-Eyring nanofluid model. Moreover, the adoption of bvp4c as a numerical tool further emphasizes the research’s unique contributions. The curves of temperature, concentration, and velocity as a consequence of changes in physical parameters are discussed. Increasing the value of the suction parameter promotes heat transfer but slows the velocity of the nanofluid. The injection of a magnetic field is responsible for compensating for the suction rate. An improvement in the concentration of nanoparticles and temperature is observed as a result of an increase in the slip rate. It is evident that both nanoparticle concentration and temperature rise significantly when Bi, the Biot number, is increased. In the boundary layer, a decrease in velocity is observed as a consequence of an increase in velocity slip, porosity, and magnetic field parameters.

Stochastic supervised networks for numerical treatment of Eyring–Powell nanofluid model with Darcy Forchheimer slip flow involving bioconvection and nonlinear thermal radiation

The aim of this study is to estimate the solution of Eyring–Powell nanofluid model (EPNFM) with Darcy Forchheimer slip flow involving bioconvection and nonlinear thermal radiation by employing stupendous knacks of neural networks-based Bayesian computational intelligence (NNBCI). A dataset for the designed NNBCI is generated with Adam numerical procedure for sundry variations of EPNFM by use of several variants including slip constant, Schmidt number, mixed convection parameter, Prandtl number, and bioconvection Lewis parameter. Numerical computations of various physical parameters of interest on EPNFM are estimated with artificial intelligence-based NNBCI and compared with reference data values generated with Adam’s numerical procedure. The accuracy, efficacy, and convergence of the proposed NNBCI to successfully solve the EPNFM are endorsed through M.S.E, statistical instance distribution studies of error-histograms, and assessment of regression metric. The proposed dataset exhibits a close alignment with the reference dataset based on error analysis from level E[Formula: see text] to E[Formula: see text] authenticates the precision of the designed procedure NNBCI for solving EPNFMs. The executive and novel physical importance of parameters governing the flow, such as nanofluid velocity, temperature, and concentration profiles, are discussed. The observations imply that the presence of the slip constant, mixed convection parameter and Lewis number influences the velocity of the nanofluid. However, it is observed that temperature of the nanofluid declines for higher values of Prandl number while the concentration of nanofluid improves with increasing values of Schmidt number.

Melting phenomenon of thermally stratified MHD Powell–Eyring nanofluid with variable porosity past a stretching Riga plate

Abstract Recently, experts have become particularly interested in the treatment of disorders caused by magnesium shortage. Hypomagnesemia is produced by a magnesium deficit in the blood, which is an additional stimulation for different diseases such as vomiting, drowsiness, nausea, loss of appetite, and so on. To compensate for this shortage, magnesium is injected as a nanoparticle in the blood (base fluid). The properties of these magnesium nanoparticles specifically their size, dispersion, and surface characteristics are crucial for optimizing their bioavailability and therapeutic efficacy. Advanced material characterization techniques ensure the stability and enhanced performance of these nanoparticles in the physiological environment. Based on these applications, the current research aims to address magnesium deficiency via Powell–Eyring nanofluid flow distorted by the linearly stretchable sheet in the region of the stagnation point. Linear thermal stratification, viscous dissipation, and Joule heating are used to reveal the heat transport features. The magnetic field is applied to the nanofluid at an angle α to further control the fluid dynamics and nanoparticle behavior. Transformations are used to create a set of dimensionless governing equations. Comparative graphs are used to explain the physical behaviors of temperature and velocity fields, demonstrating how material properties impact fluid dynamics. The well-known convergence method (homotopy analysis method) is used to solve the model by comparing graphs.

Intelligent computing approach for the bioconvective peristaltic pumping of Powell–Eyring nanofluid: heat and mass transfer analysis

Intelligent computing approach for the bioconvective peristaltic pumping of Powell–Eyring nanofluid: heat and mass transfer analysis

A computational analysis on two phase Eyring-Powell (non-Newtonian) dust particles flow for heat and mass transfer phenomenon with variable thermal features

In this instigation, the heat and mass transfer pattern on Eyring-Powell nanofluid with suspension of dust particles is focused. For heat transfer phenomenon, the Eyring-Powell nanofluid capturing the variable thermal conductivity. Furthermore, the variable and mass diffusivity assumptions are entertained for summarizing the observations chemical reaction phenomenon. The flow is endorsed to magnetic force impact. The additional impact of Brownian motion and thermophoresis consequences have been adopted. The numerical computations with shooting technique are performed. The physical aspects of parameters have been observed graphically. Based on depicted observations, it is examined that the fluid velocity reduces due to interaction velocity parameter which reverse trend is noted for dust particles velocity. The temperature profile for dusty fluid particles enhanced due to interaction parameter for temperature. Furthermore, the concentration profile reduces due to concentration interaction parameter. Current results present applications in solar energy, thermal processes, heat transform devices cooling systems, plasma, manufacturing processes, energy systems, etc.

Irreversibility estimation in triply stratified bio-marangoni convection in powell-eyring nanofluid under the influence of external flow

Due to the growing importance of bioconvection phenomena in diverse industrial processes such as oil refining, biotechnology, and food processing, it is essential to examine several effects like a chemical reaction, stratification, Marangoni convection, etc in nanofluid suspensions in the context of transport of microorganisms. The outcome of such studies may provide significant insight into controlling and as well as manipulating the transport of energy, solute, and microorganisms for achieving the requisite target. The aim of our study is to investigate the thermo-solutal Marangoni convection of gyrotactic microorganisms suspended in Powell-Eyring nanofluid in a stratified medium. This analysis also takes into account the effects of external flow and transverse magnetic field. The impact of Arrhenius activation energy, thermal radiation, and binary chemical reactions on bioconvection flow is considered under stratified Marangoni convection. Under appropriate assumptions without violating the physics, the present problem is expressed in terms of nonlinear PDEs. Some capable similarity transformations are employed to convert the PDEs into ODEs and solved numerically by the Runge-Kutta Fehlberg method. The graphical illustrations depict the effects of relevant flow parameters on temperature, nanoparticle volume fraction, and density distributions of motile microorganisms. The study focuses on understanding the variations in significant engineering quantities resulting from changes in crucial effects and analyzing irreversibilities. It is noticed that Marangoni accelerates the mass transfer process while on the other hand delaying the heat transfer and microorganisms density gradient. The dominance of Powell-Eyring nanofluid on the heat and mass transport amplified in accompanying Marangoni convection. The results indicate that the Eyring-Powell fluid significantly reduces entropy generation and the Bejan number. Conversely, an increase in entropy generation is observed for the Marangoni ratio parameter. Hence, this work provides insight into interlinked flow in bioconvective systems, with potential diverse applications in microbiological processes.

Suction impact on Eyring Powell nanofluid flow over an electromagnetic medium with Joule heating

The current study has addressed numerically the importance of blowing and suction outcomes on Eyring-Powell nanofluid flow over an electromagnetic surface with heat generation, activation energy and Joule heating. Through the use of similarity conversions, the governing equations are changed to the level of a collection of nonlinear ODEs. In order to solve the nondimensional ODEs under physically realistic boundary circumstances, the bvp4c variational method has been used. The flow velocity computed numerically compares well to the precise solution presented in the literature. The results of numerical calculations have made this very evident. The graphical patterns were displayed to explore the effects of near-surface tangible parameters and engineering factors on the significant physical flow features. The results indicate that the velocity of the nanofluid decreases as the suction and magnetic parameters rise in value. A comparison is made between the current findings and the results that have been obtained in the past, and it is discovered that there is a good agreement between the results.

Entropy generation and heat transfer analysis of Eyring-Powell nanofluid flow through inclined microchannel subjected to magnetohydrodynamics and heat generation

The current study is inspired to investigate the influences of essential flow dynamics including magnetic field, variable dynamic viscosity, Joule heating, viscous dissipation, porous medium dissipation, heat source, thermal radiation, and convective heating on the mixed convection flow of Eyring-Powell Cu − water nanofluid trough an inclined microchannel in the presence of Darcy-Forchheimer porous medium. The governing mathematical model equations are formulated, converted into dimensionless and thereafter solved numerically in the MATLAB software via Bvp4c-package. The influences of the embedded dimensionless parameters on heat transfer behaviours and entropy generations are displayed trough graphs as well as their physical interpretations are discussed in detail. Consequently, it is revealed that the performance of microchannel thermal system is improved by factors such as injection/suction of fluids, Eyring-Powell fluid, magnetic field, non-Darcy porous medium, Cu − nanoparticles, thermal radiation and convective heating. The drag coefficient and Nusselt number augment with viscous dissipation, variable dynamic viscosity, Darcy porous medium, angle of inclination, Prandtl number and heat source. Moreover, the Nusselt number at around the left and right walls vicinity shows an opposite behaviour with escalating values of the Biot number and thus convective transfer of heat around the microchannel walls is remarkably important. Furthermore, the minimization of net entropy generation rate is achieved with Eyring-Powell fluid, magnetic field, Cu − nanoparticles, thermal radiation and convective heating but it escalates with variable dynamic viscosity, viscous dissipation, angle of inclination, heat source and Prandtl number. Indeed, the irreversibility due to the robust influence of porous medium shows dual behaviours on the net entropy generation rate. Finally, the numerical results are also validated by comparing with the results of already existing literatures and hence, a sounding agreement is attained.