Nanoparticle Concentration Profiles Research Articles

Impact of Thermal Energy on Water and Ethylene Glycol (50:50)-Based Rotating Hybrid Nanofluid Past A Riga Surface with Radiation, Homogeneous and Heterogeneous Reactions

Hybrid nanofluid is crucial in improving the efficiency of heat transmission in thermal engineering applications, particularly the cooling of electrical equipment, heat exchangers, fuel cells, printing machines, etc. This study sought to investigate the augmentation of heat and mass transmission by the use of a rotating hybrid nanofluid consisting of a mixture of gold and silver nanoparticles suspended in water and ethylene glycol (50:50) past a heated Riga surface with velocity slip and suction. The energy equation is constructed using nonlinear radiation and heat consumption. The impact of both homogeneous and heterogeneous processes on the hybrid nanofluid is also explored. The governing mathematical model begins with partial differential equations that are converted into ordinary differential equations using a suitable conversion technique. The results of numerical computations are recorded as graphs and tables using the bvp4c scheme in MATLAB. It is noticed that both directional velocities undergo significant negative changes as a result of enhanced values of the rotational parameter. The higher levels of the radiation parameter resulted in significant enhancements in the thermal profile. The falling behavior of the nanoparticle concentration profile is recorded against a greater quantity of both chemical reaction parameters. Based on our analysis, when the Biot number changes from 0.4 to 0.8, the most significant heat transmission gradient occurs.

Computational study with neural networks to double diffusion in Prandtl thermal nanofluid flow adjacent to a stretching surface design with numerical treatment

The study focuses on the implementation of neural networks in analyzing the behavior of Prandtl nanofluid near a extending surface in the existence of dual diffusion. The research investigates the merged consequence of thermal and concentration gradients on the fluid flow and heat transfer characteristics using advanced computational techniques. The investigation delves into the phenomenon of double diffusion in the flow of Prandtl nanofluid near a stretching surface (DD-PNSS), employing the Levenberg-Marquardt scheme with Artificial Neural Networks (LMS-ANNs). The application of similarity variables converts the non-linear partial differential equations into non-linear ordinary differential equations. Through the application of the Lobatto IIIa formula in a three-stage process, various data sets are generated for the LMS-ANNs by varying parameters such as the Prandtl fluid parameter ([Formula: see text]), Prandtl number (Pr), Brownian motion parameter (Nb), thermophoresis parameter (Nt), and Dufour-solutal Lewis number (Ld). The range of parameter α is from 2 to 3.5, parameter β from 0.1 to 0.9, Nb is from 0.1 to 0.4, Nt is from 0.1 to 0.7, Le is from 1 to 3 and Ld is from 0.1 to 0.5. The intrinsic behavior of embedded parameters on dimensionless velocity, temperature, solutal concentration, and nanoparticle concentration profiles is graphically evaluated. The proposed LMS-ANNs model is meticulously tested, validated, and trained using a multi-stage approach, and its performance is compared to established references to ensure its reliability. The effectiveness of the suggested LMS-ANNs model is further affirmed through regression analysis, Mean Squared Error (MSE) evaluation, and histogram studies, showcasing an exceptional accuracy level ranging from 10−08 to 10−10, setting it apart from alternative approaches and reference models.

Exploring concentration-dependent transport properties on an unsteady Riga plate by incorporating thermal radiation with activation energy and gyrotactic microorganisms

Abstract The aim of this study is to examine the entropy generation (EG) associated with the transfer of mass and heat in a concentration-dependent fluid with thermal radiation and activation energy, specifically in the context of an unsteady Riga Plate with gyrotactic microorganism. It is important to solve the ordinary differential equations generated from the controlling partial differential equations using Lie symmetry scaling to verify their quality and reliability. The system’s anticipated physical behavior is compared to Mathematica’s Runge–Kutta–Fehlberg numerical solution. Source parameters are essential for validation since they offer accurate results. Methodically change these values as a percentage to determine how they affect the unsteady fluid’s density, mass, and heat transfer over the Riga plate. Velocity, temperature, nanoparticle concentration and microorganism concentration profiles decrease with varying values of the unsteadiness parameter. EG increases with increasing values of concentration difference, thermal radiation, and Reynold number parameters. The Nusselt number experiences a 26.11% rise as a result of radiation when the unsteadiness parameter is A = − 0.25 A=-0.25 , in comparison with the scenario without radiation. Mass transfer upsurges with increasing values of the Brownian motion parameter and reduces with increasing values of thermophoresis parameter. To verify our conclusions, we compare calculated data, specifically the skin friction factor, to theoretical predictions. Tabular and graphical data can show how physical limits affect flow characteristics.

Controlled entropy in tetra-hybrid nono-fluid helmholtz electroosmotic with motile germs via complex peristaltic pumping

Motile microorganisms, such as bacteria, can be engineered to transport medications directly to certain organs, such as cancer, tumors, enhancing drug efficacy and minimizing systemic side effects. These microorganisms can also be programmed to target and eliminate harmful bacteria, offering a novel approach to infection control. In parallel, functionalized nanomaterials show significant promise for precise manipulation of biological fluids. This focused approach improves drug efficacy while reducing systemic negative effects. Also, motile bacteria can be engineered to target and remove dangerous bacteria, providing a fresh approach to infection control. Nanomaterials with various functions show prodigious potential for precise operation of biological fluids. Tetra-hybrid nano-particles exhibit special electrical, optical, and thermal properties. They are composed of gold, silver, alumina, and titania. The streaming flow phenomena that result from the interactions of these nanocomposites with non-Newtonian biofluids, such as blood, can be studied using computational modeling. Considerations are made for forces such as non-Newtonian rheology, localized laser irradiation, and magnetohydrodynamics. Complex cellular trapping patterns are captured by predictions for temperature, velocity, and nanoparticle concentration profiles. Biocompatible multimodal nano-assemblies under magnetic actuation and thermos-plasmonic effects are used to exhibit precision biofluid control. To optimize, engineering parameters are visually analyzed. The unique features of tetra-hybrid nanoparticles, paired with motile microorganisms and non-Newtonian biofluid dynamics, allow for more precise therapeutic techniques, such as targeted medication administration and hyperthermia cancer treatment. By visualizing key engineering parameters, these findings highlight the potential for improved therapeutic strategies, such as targeted drug delivery and hyperthermia-based cancer treatments, enabled by the integration of tetra-hybrid nanoparticles and motile microorganisms in complex biofluid environments.

Numerical Simulation and Neural Network Model for Hydromagnetic Nanofluid Convection in a Porous Wavy Channel with Thermal Non-Equilibrium Model

Abstract The present study aims to analyze the nonfluid MHD convective heat transfer in a porous wavy channel with a local thermal non-equilibrium (LTNE) model. Such a model finds applications related to enhancement in thermal performance, increasing the heat transfer coefficient in the compact design of heat exchangers for the aerospace and automotive industries and elevation in the efficiency of the solar collector. A sinusoidal porous wavy LTNE channel containing nanofluid and subjected to the induced and applied magnetic fields is considered. A uniform magnetic field is applied orthogonal to the channel and the induced magnetic field effects are considered due to the large magnetic Reynolds number. The momentum, continuity, energy, and nanoparticle volume fraction equations constitute the coupled nonlinear system of differential equations and are solved using the Galerkin finite element method. The reliability of the technique is assessed by comparing the proposed procedure with the results from earlier sources. A detailed analysis is presented to determine the effects of different physical parameters arising in the system on temperature, nanoparticle concentration, and velocity profiles. As an illustration, the findings exhibit that increasing the modified diffusivity ratio increases the values of the nanoparticle volume fraction whereas, reducing the modified diffusivity ratio enhances the temperature distribution. A higher value of thermal Rayleigh number presents a significant involvement of buoyancy forces, potentially resulting in the development of convective currents. A higher Nield number indicates more effective heat transport from the solid surface to the nanofluid. Consequently, there is a minimal thermal difference between the solid surface and the bulk nanofluid. Effective heat transmission enhances the nanofluid ability to absorb heat and generates a more consistent dispersion of temperature inside the fluid. The performance of the designed algorithms of the artificial neural network, namely, the Levenberg – Marquardt algorithm, in the problem under consideration is evaluated and the methodology is found reasonably precise with the matching of order around 6 to 7 decimal places of accuracy.

Entropy generation analysis of oscillatory magnetized darcian flow of mixed thermal convection and mass transfer with joule heat over radiative sheet

Significance of this work is to examine enhanced thermal efficiency of magnetic nanofluid in the presence of Joule heating and radiation in missile technological devices, nuclear energy plants, rockets, solar energy systems and enhancing cyclic processes. Prominent aim of current investigation is to demonstrate the amplitude and oscillating analysis of mixed convective heat rate of Darcian magnetic nanoparticle movements with entropy generation, thermal radiation and Joule heat impact through porous stretching sheet. The magnetic layer along stretching surface plays important role to control thermal performance. Governing mathematical equations are reduced in convenient form by using non-dimensional analysis. The primitive mathematical form of steady and oscillating model is calculated through oscillatory stokes and primitive variables. Using Gaussian elimination and finite differences techniques, the geometrical and numerical outcomes of steady and oscillatory models are obtained by applying FORTRAN lahey-95 programming tool. The novelty of this problem is to study the oscillatory thermal and concentration profiles of Darcian magnetic nanoparticles with Joule heating and radiations. It is examined that momentum and temperature distribution grows as radiant-energy increases but decreases for maximum Joule heating. It is found that temperature and concentration distributions enhances as magnetic force decreases. Prominent enhancing amplitudes in heat and mass transfer are obtained for maximum Schmidt and thermophoresis parameter. Heat and mass transfer decreases as magnetic factor increases due to insulating magnetic nanoparticles.

3D-MHD mixed convection in a darcy-forchheimer maxwell fluid: Thermo diffusion, diffusion-thermo effects, and activation energy influence

In this article, the three-dimensional upper-convected Darcy-Forchheimer Maxwell (UCM) nanofluid flow over a stretching surface is analyzed to investigate the effects of activation energy, thermodiffusion, diffusion thermo, and magnetohydrodynamics (MHD) on heat and mass transfer. The energy equation incorporates a nonlinear radiative heat flux. Using similarity transformation, the nonlinear partial differential equations are reduced to ordinary differential equations, which are then solved using the well-known shooting technique via the fourth-order Runge-Kutta integration method. To validate our results, we also employ MATLAB's built-in function bvp4c. The impact of various parameters, such as activation energy, diffusion thermo, thermodiffusion, Brownian motion parameter, Prandtl number, thermophoresis parameter, and magnetic parameter, on velocity, temperature, and concentration is discussed both graphically and numerically. It is observed that the flow velocity decreases with an increasing magnetic field parameter. Additionally, higher values of the activation energy parameter reduce the nanoparticle concentration profile. The temperature and concentration exhibit opposite behaviors when thermodiffusion and diffusion thermo effects are enhanced.

Fractional dynamics of entropy generation in unsteady mixed convection of a reacting nanofluid over a slippery permeable plate in Darcy–Forchheimer porous medium

AbstractThis paper presents a theoretical investigation of the inherent irreversibility in unsteady fractional time derivative mixed convection of a reacting nanofluid with heat and mass transfer mechanism over a slippery permeable plate embedded in a Darcy–Forchheimer porous medium. The model fractional partial differential equations are obtained based on conservation laws and numerically solved using the implicit finite difference scheme. The study displays and discusses the effects of various emerging parameters on the overall flow structure, such as velocity profiles, temperature distribution, nanoparticles concentration profiles, skin friction, Nusselt number, Sherwood number, entropy generation rate, and Bejan number. It was found that an increase in dimensionless time and fractional parameters leads to a decrease in both the entropy generation rate and the Bejan number. The study revealed that fractional order derivatives can capture intrinsic memory effects, non‐local behaviour, and anomalous diffusion in the nanofluid flow process. This can ultimately lead to better engineering system design and control.

Influence of activation energy and variable thermal conductivity on magneto-convective nonlinear thermo-radiative Casson nanofluid containing motile microorganisms over a sinusoidal surface

The activation energy of convective-radiative nanoliquids with sinusoidal walls has garnered significant academic interest in recent years. This focus arises due to the pivotal applications of nanoparticles in thermal engineering, industrial processes, and medical sciences. This article investigates the magnetohydrodynamic heat transfer characteristics of Casson nanofluids containing microorganisms influenced by an oscillatory surface. The study incorporates temperature-dependent viscosity and utilizes Buongiorno’s mathematical model to account for nonlinear thermal radiation, Brownian motion, and thermophoretic effects from using nanomaterials in Casson fluids. These effects enhance thermal conductivity, improving the heat transportation phenomenon while considering gyrotactic microorganism density distributions. The boundary layer flow problem is formulated using partial differential equations and associated boundary conditions, subsequently numerically simulated using the bvp4c function. The investigation explores the thermal behavior of nanoparticles in the presence of bioconvection phenomena, Lorentz force, chemical reactions, and activation energy. As a result, this model addresses variable thermal conductivity and bioconvection aspects in Casson nanofluids over a sinusoidal surface. Numerically computed results for the Nusselt number, motile density, and Sherwood number provide insights into several essential features. The findings reveal that an increase in the Casson fluid parameter correlates with a decreased velocity profile. The assumptions of variable thermal conductivity and temperature-dependent viscosity prove more effective in raising the temperature of nanoparticles. The nanoparticle concentration profile rises noticeably for smaller Schmidt number Sc values when the activation energy parameter is higher than larger Sc values. Additionally, the presence of microorganisms in Casson nanofluids leads to increased temperatures due to an elevation in the bioconvection Rayleigh number. Moreover, heightened oscillating frequency parameters decrease nanoparticle concentration and microorganism density. Including activation energy and oscillating frequency parameters further enhances the understanding of nanoparticle concentration and microorganism density dynamics, offering valuable contributions to theoretical research and practical applications across multiple interdisciplinary fields.

INTELLIGENT NUMERICAL METHOD FOR STUDYING MAXWELL WILLIAMSON NANOFLUID FLOW WITH ACTIVATION ENERGY

The use of artificial intelligence and its techniques has become increasingly widespread in recent times. It is being used to solve stiff non-linear equations. Additionally, nanofluids play a pivotal role in studying heat transfer. All of this was the motivation for doing this work. This work investigates a two-dimensional magnetohydrodynamic stretched flow (2D-MHDSF) of Maxwell Williamson nanofluid (MWNF) affected by bioconvection and activation energy numerically through Levenberg-Marquardt backpropagation method (LMBM)-based artificial neural network approach. The mathematical formulation for the problem was obtained through non-linear partial differential equations (PDEs). The leading PDEs were transmitted into non-linear ordinary differential equations by similarity transformation variables. The reference results for the 2D-MHDSF-MWNF model are produced by the Lobatto IIIA method through different scenarios of specific parameters for the flow velocity, fluid temperature, nanoparticle concentration, and motile density profiles. Using obtained results as a dataset to apply the testing, training, and validation steps of the suggested LMBM for the 2D-MHDSF-MWNF model. The mean squared error, analysis of regression, and error histograms are presented to prove the efficiency and precision of the proposed method. The numerical results of LMBM are displayed as a study of the effects of different physical factors on flow dynamics for 2D-MHDSF-MWNF.

An investigation into the impact of thermal radiation and chemical reactions on the flow through porous media of a Casson hybrid nanofluid including unstable mixed convection with stretched sheet in the presence of thermophoresis and Brownian motion

Abstract This article investigates the unsteady mixed convention two-dimensional flow of magnetohydrodynamic Casson hybrid nanofluids (alumina oxide and titanium oxide nanoparticles with base fluid water) flow through porous media over a linearly stretched sheet. We analyzed the heat and mass transfer in mixed convection, thermal radiation, variable thermal conductivity, variable mass diffusivity, and chemical reaction in the presence of thermophoresis and Brownian motion. A system of partial differential equations is reduced to a solvable system of ordinary differential equations by applying a suitable similarity transformation. We used the Runga–Kutta method along with the shooting procedure to solve the flow, heat, and mass transfer equations along with boundary conditions. The results obtained from MATLAB codes are compared with previously published results of the same type in a limiting case. The results of the velocity, temperature, and concentration profile of the hybrid nanofluid for varying different flow parameters are obtained in the form of graphs, while the rate of shear stress, rate of heat, and mass transfer are expressed in tables. We noticed that velocity and temperature diminish as an unsteady parameter increases; however, the reverse trend was observed in the nanoparticle concentration profile. With an increase in the thermal radiation parameter, the resultant velocity and temperature profile improves, while the concentration of nanoparticle profiles decreases. The velocity and temperature increase with higher Brownian motion, while the velocity increases and temperature decreases with higher thermophoresis.

Heat transfer analysis in a horizontal anisotropic porous channel with Bi-viscous Bingham nanofluid and temperature-dependent Brownian diffusion

PurposeThe purpose of this article is to present a mathematical model for the fully developed flow of Bi-viscous Bingham nanofluid through a uniform-width anisotropic porous channel. The model incorporates a generalized Brinkman-Darcy formulation for the porous layers while considering the motion of nanoparticles influenced by both Brownian diffusion and thermophoresis effects.Design/methodology/approachThe similarity transformations derived through Lie group analysis are used to reduce the system from nonlinear partial differential equations to nonlinear ordinary differential equations. The finite difference method-based numerical routine bvp4c is employed to collect and graphically present the outcomes for velocity, temperature, and nanoparticle concentration profiles. The flow pattern is analyzed through streamlined plots. Furthermore, skin friction, heat, and mass transmission rates are investigated and presented via line plots.FindingsIt is observed that in anisotropic porous media, the temperature profile is stronger than in isotropic porous media. The thermal anisotropic parameter enhances the concentration profile while reducing the temperature.Practical implicationsAnisotropy arises in various industrial and natural systems due to factors such as preferred orientation or asymmetric geometry of fibers or grains. Hence, this study has applications in oil extraction processes, certain fibrous and biological materials, geological formations, and dendritic zones formed during the solidification of binary alloys.Originality/value1. The permeability and thermal conductivity are not constant; instead, they have different values in the x and y directions. 2. This study considers the dependency of thermophoresis on nanoparticle volume fraction and Brownian diffusion on the temperature in both the fluid flow equations and boundary conditions. 3. A novel similarity transformation is derived using Lie group analysis instead of using an existing transformation already available in the literature.

Numerical Investigation of Diffusion thermo and Thermal Diffusion on Mixed Convection flow of Williamson Nanofluid through a vertical cone with porous material in the presence Thermal radiation and Activation Energy

In this paper, analyze the impact of Activation energy, Diffusion thermo and thermal diffusion with heat and mass transfer inherent of over a vertical cone through Thermally Radiant Williamson nanofluid with saturated porous medium under the convective boundary condition in the presence of thermal radiation has been studied. The coefficients of Brownian and thermophoresis diffusions are also taken into consideration. The governing partial differential equations are reduced to a couple of nonlinear ordinary differential equations by using suitable transformation equations; these equations are then solved numerically with the use of the conventional fourth-order Runge Kutta method accompanied by the shooting technique. As a result, the effects of various physical parameters on the velocity, temperature, and nanoparticle concentration profiles as well as on the skin friction coefficient and rate of heat transfer are discussed with the aid of graphs and tables. This study has been directly applied in the pharmaceutical industry, microfluidic technology, microbial improved oil recovery, modelling oil and gas-bearing sedimentary basins, and many other fields. Further, to check the accuracy and validation of the present results, satisfactory concurrence is observed with the existing literature.

Tangent hyperbolic nanofluid flow through a vertical cone: Unraveling thermal conductivity and Darcy–Forchheimer effects

Purpose: This paper demonstrates the way tangent hyperbolic nanofluid flow through a vertical cone is influenced by varying viscosity and varying thermal conductivity. This study also seeks to illustrate the impact of convective boundary conditions on a fluid. The mathematical modeling also takes the Darcy–Forchheimer effect into account. Methodology: Using the appropriate similarity transformation, the fluid problem is reduced into a set of nonlinear ordinary differential equations. These systems of differential equations are evaluated numerically by applying the Optimal Homotopy Asymptotic Method. Findings: The nature of emergent parameters is examined in relation to the temperature distribution, nanoparticle concentration profile, and velocity profile. An increase in variable viscosity corresponds to a decrease in fluid velocity, while enhanced thermal conductivity results in elevated fluid temperature. The skin friction coefficient, Sherwood, and Nusselt numbers are numerically examined for active concerned parameters. These findings can be put into practice in a variety of fields such as polymer cooling systems and medication. Originality: Existing literature has yet to explore the combination of tangent hyperbolic nanofluids with varying viscosity and thermal conductivity under convective boundary conditions.

Numerical Investigation of Diffusion Thermo and Thermal Diffusion on MHD Convective Flow of Williamson Nanofluid on a Stretching Surface Through a Porous Medium in the Presence Chemical Reaction and Thermal Radiation

In this paper, analyze the impact of Diffusion thermo and thermal diffusion with heat and mass transfer inherent of thermally radiant Williamson nanofluid over a stretyching surface through a porous medium under the convective boundary condition in the presence of thermal radiation and chemical reaction has been studied. The coefficients of Brownian and thermophoresis diffusions are also taken into consideration. The governing partial differential equations are reduced to a couple of nonlinear ordinary differential equations by using suitable transformation equations; these equations are then solved numerically with the use of the conventional fourth-order Runge Kutta method accompanied by the shooting technique. As a result, the effects of various physical parameters on the velocity, temperature, and nanoparticle concentration profiles as well as on the skin friction coefficient and rate of heat transfer are discussed with the aid of graphs and tables. This study has been directly applied in the pharmaceutical industry, microfluidic technology, microbial improved oil recovery, modelling oil and gas-bearing sedimentary basins, and many other fields. Further, to check the accuracy and validation of the present results, satisfactory concurrence is observed with the existing literature.

Entropy analysis for two-dimensional double-diffusive mixed convective flow of a Williamson nanofluid through a porous medium

The problem of double-diffusive convection is investigated by considering the MHD effect on non-Newtonian Williamson fluid flowing over a porous medium. The nature of fluid flow and the amount of heat and mass transfer are studied by the variation of MHD and porous parameters. The flow equations are coupled having more than one independent variable which can be transformed into a single independent variable by introducing similarity variables and solved numerically with the utilization of builtin MATLAB bvp4c package. The Brownian motion and thermophoresis effects on flow equations are studied graphically and the irreversibility of flow is considered. The presence of the Prandtl number in the momentum equation and its effect on physical parameters are taken into account. The variation of Williamson parameter on velocity, temperature, nanoparticle concentration, and concentration profiles are analyzed. The primary innovation of our research is shown in tables that contrast the acquired outcomes with the earlier conclusions found in the literature. The behavior of energy and concentration profiles are shown through graphs by differing numerical values of physical parameters.

Magnetohydrodynamic thermo-bioconvective flow of 3D rotating Williamson nanofluid with Arrhenius activation energy in a Darcy–Forchheimer medium over an exponentially stretching Surface

This paper aims to analyze the heat and mass transfer characteristics of the 3D thermo-bioconvective flow of rotating Williamson nanofluid over an exponentially stretching vertical sheet. The flow distribution considers the influence of nonlinear thermal radiation, Hall and ion-slip currents, joule heating, coupled effects of Dufour and Soret diffusion, internal heat generation, Arrhenius activation energy, Brownian, and thermophoresis diffusion in a Darcy–Forchheimer porous medium. The modeled partial differential equations (PDE) in terms of continuity, momentum, energy, concentration, and density of motile microorganisms are reformed into ordinary differential equations (ODE) forms employing similarity variables. The resulting equations are solved numerically using the spectral local linearization method (SLLM). The successive over-relaxation technique is applied to accelerate and enhance the convergence of the method. The obtained results are graphically and tabularly represented and numerically explored for the effects of pertinent parameters on the velocity, temperature, nanoparticle concentration, and motile microorganism concentration profiles. The rotation and mixed convection parameters dropped the primary velocity curve, while the Williamson and heat source parameters uplifted the microbes density distributions. The temperature field rises with an increase in radiation and microbes Brownian motion and declines with an increase in Hall and ion-slip numbers. Furthermore, with the increase in activation energy from 0.5 to 2 and the mixed convection parameter from 0.6 to 1.3, we observe a respective 3.93% rise and 8.30% fall in mass transfer rates. The current investigation has broad applications, including MHD accelerators, biotechnology, the formation of elastic sheets, the production of polymer solutions, and the synthesis of nanoparticles through microbial processes.

Study of Radiative Heat Transfer of Third-Grade Nanofluid Flow with Variable Viscosity in PostTreatment Analysis of the Wire Coating Process

Wire coating technology plays a pivotal role in ensuring the efficiency, safety, and sustainability of mining operations. Its contributions go beyond the surface, impacting various aspects of mining activities, from safety compliance to energy efficiency and environmental responsibility. To attain maximum efficiency in the wire/cable coating process, the foremost concern of any scientists, experts and technologists is to consider the concept of wall shear stress, heat, and mass transfer phenomenon in the interior of dyes. The fundamental requirement of the coating process is to improve the rate of heat transfer. Therefore, the purpose of the current work is to ascertain how suspended nanoparticles influence the phenomenon of heat and mass transfer rate during the post-treatment of the coating process in the presence of third-grade liquid. The Buongiorno model is employed to examine the thermophoresis and Brownian features of nano-liquid. The governing equations are formulated and simplified using suitable non-dimensional parameters. Solutions for the non-linear differential equations are obtained numerically. The outcome of various pertinent parameters on momentum, thermal, and nanoparticle concentration profiles are delineated graphically. Further, regression analysis has been carried out to understand the importance of the correlation between heat transfer rate and flow control parameters.

Three-dimensional Analysis of Electromagnetic Nanomaterial Flow and Thermal Variations for Forced Convection

This paper investigates the three-dimensional motion of electromagnetic nanofluid under the influence of heat source/sink, nonlinear heat radiation, magnetic field, and altered Arrhenius equation. Nonlinear stretching in the velocity is considered in the x-direction. Thermophoresis (Nt) and Brownian motion (Nb) are also considered in nanoparticle concentration profiles and temperature analysis. The boundary layer equations are transformed into nonlinear ODEs using suitable similarity transformations. The coupled nonlinear homogeneous system of ordinary differential equations is tackled by the MAPLE software. Non-dimensional system of the equation contains fourteen physical parameters Fr, Nb, M, γ, λ, Rd, δ, Pr, Nt, S, E, Sc, Bi and power index, which are governed by the physical model. Graphs are presented to show the impact of the abovementioned parameters on temperature, concentration and velocity profile. The present study contributes by observing how the aforementioned parameters influence the heat dissipation rate of nanofluids. This study has broad applications in the field of nanofluids like oil production, metal extrusion, heat exchangers, catalytic reactors etc. Also, results for a particular case found good concurrence with earlier work.

Computational analysis of cilia-mediated flow dynamics of Jeffrey nanofluid in physiologically realistic geometries

Cilia play important roles in fluid transport and development by propagating metachronal waves along cell surfaces. This study numerically investigates the biomechanics of cilia-driven flow of Jeffrey nanofluid in a wavy curved channel. The orthogonal curvilinear coordinates are used for the mathematical formulation of the problem in a set of partial differential equations. The governing equations are simplified using the dimensionless numbers and stream functions and then reduced using the long wavelength and low Reynolds number assumptions. Shooting method is applied to determine velocity, temperature, and nanoparticle concentration profiles. The resultant velocity, temperature profiles, nanoparticle concentration profiles, and streamlines are interpreted and elucidated graphically. The parametric analyses systematically examine the impacts of channel curvature, thermal buoyancy forces, nanoparticle concentrations, Jeffrey fluid rheology, and cilia motion kinematics on transport phenomena. Key findings show temperature and concentration gradients strongly influenced by cilia beating. The study provides deeper insight into the influence of these parameters on the cilia-driven flow in a complex wavy curved channel, bearing potential applications in heat transfer systems, nanotechnology, and biotechnology, among other fields.