Search results

This paper aims to study numerically the flow, heat transfer, and entropy generation of aqueous copper oxide-silver hybrid nanofluid over a down-pointing rotating vertical cone, with linear surface temperature (LST) and linear surface heat flux (LSHF), in the presence of a cross-magnetic field. In industrial applications, such as oil and gas plants, food industries, steel factories and nuclear packages, the real bodies may contain nonorthogonal walls and variable cross-section three-dimensional forms which this issue can clarify the importance of selective geometry in the present research.

The mass-based scheme is accomplished for the simulation, and the entropy generation and Bejan number will be analyzed in conjunction with the aforementioned model. It has been hypothesized that two types of boundary conditions (LST and LSHF) as well as five nanoparticle shapes (sphere, brick, cylinder, platelet and disk) present a collection of crucial results. The overseeing PDEs are changed over completely to the dimensionless ODEs, and these are solved by Runge–Kutta–Fehlberg approach combined with a shooting methodology for certain values of physical parameters.

Subsequent to the fantastic compromise of the computational outcomes with past reports, the outcomes are introduced to conduct the investigation of the hydrodynamics/thermal boundary layers, the skin friction and the Nusselt number, as well as entropy generation and Bejan number. A state of hybrid nanofluid, which exhibits a remarkable increase in heat transfer in comparison to the states of mono-nanofluid and regular fluid, has been found to have the highest Nusselt number; however, the skin friction values should always be taken into account and managed. The entropy generation improves with the mass of the second nanoparticle (silver), while the opposite pattern is exhibited for the Bejan number. Furthermore, the lowest value of entropy generation number belongs to the cylindrical shape of nanoparticles in the LST case. In final, a significant accomplishment of the current study is the accurate output of the mass-based scheme for an entropy analysis problem.

To the best of the authors’ knowledge, for the first time, in this study, a new development of natural convective flow of a hybrid nanofluid about the warmed (LST and LSHF) and down-pointing rotating vertical cone by the mass-based algorithm has been presented. The applied methodology considers the masses of base fluid (water) and nanoparticles (Ag and CuO) as an alternative to the first and second nanoparticles volume fraction. Indeed, the combination use of the Tiwari–Das nanofluid model and the mass-based hybridity algorithm for the entropy generation analysis can be the main novelty of this work.

This paper aims to simulate the steady laminar mixed convection incompressible viscous and electrically conducting hybrid nanofluid (CuO-Cu/blood) flow near the plane stagnation-point over a horizontal porous stretching sheet along with an external magnetic field and induced magnetic field effects that can be applicable in the biomedical fields like the flow dynamics of the micro-circulatory system and especially in drug delivery.

The basic partial differential equations (PDEs) are altered to a set of dimensionless ordinary differential equations (ODEs) with the help of suitable similarity variables which are then solved numerically using bvp4c scheme from MATLAB. Inasmuch as validation results have shown a good agreement with previous reports, the present novel mass-based algorithm can be used in this problem with great confidence. Governing parameters are both nanoparticle masses, base fluid mass, empirical shape factor of both nanoparticles, suction/injection parameter, magnetic parameter, reciprocal magnetic Prandtl number, Prandtl number, heat source parameter, mixed convection parameter, permeability parameter and frequency ratio. The effect of these parameters on the flow and heat transfer characteristics of the problem is discussed in detail.

It is shown that the use of CuO and Cu hybrid nanoparticles can reduce the hemodynamics effect of the capillary relative to pure blood case. Moreover, as the imposed magnetic field enhances, the velocity of the blood decreases. Besides, when the blade shapes for both nanoparticles are taken into account, the local heat transfer rate is maximum that is also compatible with experimental observations.

An innovative mass-based model of CuO-Cu/blood hybrid nanofluid has been applied. The novel attitude to one-phase hybrid nanofluid model corresponds to considering nanoparticles mass as well as base fluid mass to computing the solid equivalent volume fraction, the solid equivalent density and also solid equivalent specific heat.

The purpose of this paper is to study and analyze the converging/diverging channel flow and heat transfer with the multiple slips effect, which is a development of the Jeffery–Hamel problem using the mass-based hybrid nanofluid algorithm. Whereas transferring biological liquid by arteries is a vital issue, mathematical modeling of hybrid nanofluid flow containing titanium dioxide and silver as nanoparticles and blood as base liquid through a converging/diverging duct, which can be a useful analysis for the fields of drug delivery, has been investigated.

The present approach is based on the Tiwari–Das nanofluid method. In this modeling, the volume fraction of nanoparticles is replaced with nanoparticles masses. The partial differential equations of the mass, momentum and energy conservations are changed to the system of ordinary differential equations through the similarity solution method. The final governing equations are solved by Runge–Kutta–Fehlberg procedure and shooting method.

The effect of emerging parameters on the temperature, the velocity, the Nusselt number and the skin friction have been analyzed by graphical and tabular reports. It is observed that the opposition to hybrid nanofluid flow in the attendance of particles of nonspherical shapes is more enhanced than those in the attendance of particles of spherical shapes. This issue demonstrates that the rheology of a hybrid nanofluid is dependent on the shape of particles. Besides, backflow regimes form in the divergent channel for high values of Reynolds number, m₂ and a. Indeed, this modeling for the hybrid nanofluid can be useful in different technologies and industries such as biological ones. It is worth mentioning that the excellent achievement of the mass-based algorithm for heat transfer and hybrid nanofluid flow is the most important success of this study.

The main originality is related to the development of the Jeffery–Hamel problem using the mass-based hybrid nanofluid algorithm. This new mass-based method is a single-phase hybrid nanofluid approach that the inputs are masses of nanoparticles and base liquid. Besides, considering the multiple slips effect and also pure blood as base fluid in this problem are also new.

The purpose of this study is to model and solve numerically the three-dimensional off-centered stagnation point flow and heat transfer of magnesium oxide–silver/water hybrid nanofluid impinging to a spinning disk.

The applied effective thermophysical properties of hybrid nanofluid including thermal conductivity and dynamics viscosity are according to the reported experimental relations that would be expanded by a mass-based algorithm. The single phase formulations coupled with experimental-based hybrid nanofluid model is implemented to derive the governing partial differential equations which are then transferred to a set of dimensionless ordinary differential equations (ODEs) with the use of the similarity transformation method. Afterward, the reduced ODEs are solved numerically by bvp4c function from MATLAB that is a trustworthy and efficient code according to three-stage Lobatto IIIa formula.

The effect of spinning parameter and nanoparticles masses (m_MgO, m_Ag) on the hydrodynamics and thermal boundary layers behavior and also the quantities of engineering interest are presented in tabular and graphical forms. The recent work demonstrates that the analysis of flow and heat transfer becomes more complicated when there is a non-alignment between the impinging flow and the disk axes. From computational results demonstrate that, the radial and azimuthal velocities are, respectively, the increasing and decreasing functions of the disk spinning parameter. Further, for the greater values of the spinning parameter, an overshoot of the radial velocity owing to the centrifugal forces of the spinning disk is observed. Besides, the quantities of engineering interest gently enhance with first and second nanoparticle masses, while comparing their absolute values illustrates the fact that the effect of second nanoparticle mass (m_Ag) is greater. Further, it is inferred that the second nanoparticle’s mass enhancement results in the amplification of the heat transfer; although, the high skin friction and the relevant shear stress should be controlled.

The combination of experimental thermophysical properties with theoretical modeling of the problem can be the novelty of the present work. It is evident that the experimental relations of effective thermophysical properties can be trustable and flexible in the theoretical/mathematical modeling of hybrid nanofluids flows. Besides, to the best of the authors’ knowledge, no one has ever attempted to study the present problem through a mass-based model for hybrid nanofluid.

The purpose of this paper is to theoretically analysis the steady-state natural convection flow and heat transfer of nanofluids in a square enclosure filled with a porous medium saturated with a nanofluid considering local thermal non-equilibrium (LTNE) effects. Different local temperatures for the solid phase of the nanoparticles, the solid phase of porous matrix and the liquid phase of the base fluid are taken into account.

The Buongiorno’s model, incorporating the Brownian motion and thermophoresis effects, is utilized to take into account the migration of nanoparticles. Using appropriate non-dimensional variables, the governing equations are transformed into the non-dimensional form, and the finite element method is utilized to solve the governing equations.

The results show that the increase of buoyancy ratio parameter (Nr) decreases the magnitude of average Nusselt number. The increase of the nanoparticles-fluid interface heat transfer parameter (Nhp) increases the average Nusselt number for nanoparticles and decreases the average Nusselt number for the base fluid. The nanofluid and porous matrix with large values of modified thermal capacity ratios (γ _p and γ _s ) are of interest for heat transfer applications.

The three phases of nanoparticles, base fluid and the porous matrix are in the LTNE. The effect of mass transfer of nanoparticles due to the Brownian motion and thermophoresis effects are also taken into account.

Sheet processing of magnetic nanomaterials is emerging as a new branch of smart materials’ manufacturing. The efficient production of such materials combines many physical phenomena including magnetohydrodynamics (MHD), nanoscale, thermal and mass diffusion effects. To improve the understanding of complex inter-disciplinary transport phenomena in such systems, mathematical models provide a robust approach. Motivated by this, this study aims to develop a mathematical model for steady, laminar, MHD, incompressible nanofluid flow, heat and mass transfer from a stretching sheet.

This study developed a mathematical model for steady, laminar, MHD, incompressible nanofluid flow, heat and mass transfer from a stretching sheet. A uniform constant-strength magnetic field is applied transversely to the stretching flow plane. The Buongiorno nanofluid model is used to represent thermophoretic and Brownian motion effects. A non-Fourier (Cattaneo–Christov) model is used to simulate thermal conduction effects, of which the Fourier model is a special case when thermal relaxation effects are neglected.

The governing conservation equations are rendered dimensionless with suitable scaling transformations. The emerging nonlinear boundary value problem is solved with a fourth-order Runge–Kutta algorithm and also shooting quadrature. Validation is achieved with earlier non-magnetic and forced convection flow studies. The influence of key thermophysical parameters, e.g. Hartmann magnetic number, thermal Grashof number, thermal relaxation time parameter, Schmidt number, thermophoresis parameter, Prandtl number and Brownian motion number on velocity, skin friction, temperature, Nusselt number, Sherwood number and nanoparticle concentration distributions, is investigated.

A strong elevation in temperature accompanies an increase in Brownian motion parameter, whereas increasing magnetic parameter is found to reduce heat transfer rate at the wall (Nusselt number). Nanoparticle volume fraction is observed to be strongly suppressed with greater thermal Grashof number, Schmidt number and thermophoresis parameter, whereas it is elevated significantly with greater Brownian motion parameter. Higher temperatures are achieved with greater thermal relaxation time values, i.e. the non-Fourier model predicts greater values for temperature than the classical Fourier model.

The problems of simulation of the formation and development of nanosystems with time were considered at different structural levels. Main theoretical concepts were systematized, which allowed successive modelling of a nanosystem with the use of the molecular dynamics, mesodynamics and continuum mechanics methods. Practical problems such as the calculation of dependence of the elasticity modulus of a nanoparticle on its size, the investigation of the formation and movement of nanoparticles in gas phase were discussed.

This study aims to numerically analyse the impact of an inclined magnetic field and Joule heating on the conjugate heat transfer because of the mixed convection of an Al₂O₃–water nanofluid in a thick wall enclosure.

A horizontal temperature gradient together with the shear-driven Flow creates the mixed convection inside the enclosure. The nonhomogeneous model, in which the nanoparticles have a slip velocity because of thermophoresis and Brownian diffusion, is adopted in the present study. The thermal performance is evaluated by determining the entropy generation, which includes the contribution because of magnetic field. A control volume method over a staggered grid arrangement is adopted to compute the governing equations.

The Lorentz force created by the applied magnetic field has an adverse effect on the flow and thermal field, and consequently, the heat transfer and entropy generation attenuate because of the presence of magnetic force. The Joule heating enhances the fluid temperature but attenuates the heat transfer. The impact of the magnetic field diminishes as the angle of inclination of the magnetic field is increased, and it manifests as the volume fraction of nanoparticles is increased. Addition of nanoparticles enhances both the heat transfer and entropy generation compared to the clear fluid with enhancement in entropy generation higher than the rate by which the heat transfer augments. The average Bejan number and mixing-cup temperature are evaluated to analyse the thermodynamic characteristics of the nanofluid.

This literature survey suggests that the impact of an inclined magnetic field and Joule heating on conjugate heat transfer based on a two-phase model has not been addressed before. The impact of the relative slip velocity of nanoparticles diminishes as the magnetic field becomes stronger.

This paper aims to present a black-box fuzzy system identification method coupled with genetic algorithm optimization approach to predict the mixture thermal conductivity at dissimilar temperatures and nanoparticle concentrations, in the examined domains.

WO3 nanoparticles are dispersed in the deionized water to produce a homogeneous mixture at various nanoparticles mass fractions of 0.1, 0.5, 1.0 and 5.0 Wt.%.

The results depicted that the models not only have satisfactory precision, but also have acceptable accuracy in dealing with non-trained input values.

The transmission electron microscopy is applied to measure the mean diameters, shape and morphology of the dry nanoparticles. Moreover, the stability of nanoparticles inside the water is evaluated by using zeta potential and dynamic light scattering (DLS) tests. Then, the prepared nanofluid thermal conductivity is presented at different values of temperatures and concentrations.

This study aims to investigate the use of CdO nanoparticles with recycled aggregates (RAs) and its effect on the structural behavior of reinforced concrete (RC) slab elements.

The study has been conducted through three phases: in the first phase, the structure of lab-synthesized CdO nanoparticles was investigated and then cement was partially replaced by CdO nanoparticles to estimate the optimum dose. The second phase focused on the properties of the RA collected from demolition wastes. In the third phase, RC slabs with different concrete mixes using RA and CdO nanoparticles were experimentally tested.

The results indicated good effect of using CdO nanoparticles with RA to improve the RC slab specimens’ behavior compared with the control specimen.

In present times, nanoparticles have a promising importance in the construction field. The influence of nanoparticles on the compressive strength of the concrete has been investigated by many researchers, but using it with RA is considered a new topic.