A rheological analysis of nanofluid subjected to melting heat transport characteristics

Numerical simulation of the nanofluid flow consists of gyrotactic microorganism and subject to activation energy across an inclined stretching cylinder

The current study examines the numerical simulation of the nanoliquid boundary layer flow comprising gyrotactic microbes with mass and energy transmission across a stretching inclined cylinder. The consequences of chemical reaction, heat generation/absorption, buoyancy force and Arrhenius activation energy is also considered on the nanofluid flow. The flow mechanism has been modeled in the form of system of nonlinear partial differential equations (PDEs). That system of PDEs is further transform into the dimensionless set of ordinary differential equations (ODEs) through the similarity substitutions. The obtained set of differential equations are numerically computed through the parametric continuation method (PCM). The effects of the distinct physical constraints on the energy, velocity, mass and the motile microbe profiles are discoursed and evaluated through Tables and Figures. It has been noticed that the velocity curve drops with the influence of inclination angle and Richardson number, while enhances against the variation of curvature factor. Furthermore, the energy field boosts with the upshot of inclination angle and heat source term, while declines with the influence of Prandtl number and Richardson number.

Numerical exploration of forced convection hydromagnetic hyperbolic tangent nanofluid flow over a permeable wedge with melting heat transfer

In this communication, the joint impacts of the process of melting as well as wedge angle entity on hydromagnetic hyperbolic tangent nanofluid flow owing to permeable wedge-shaped surface in the incidence of suspended nanoparticles along with radiation, Soret and Dufour numbers are scrutinized. The mathematical model which represents the system consists of a system of highly non-linear coupled partial differential equations. These equations are solved using a finite-difference-based MATLAB solver which implements the Lobatto IIIa collocation formula and is fourth-order accurate. Further, the comparison of computed results is carried out with the previously reported articles and outstanding conformity is recorded. Emerged physical entities affecting the bearings of tangent hyperbolic MHD nanofluid velocity, distribution of temperature, and concentration of nanoparticles are visualized in graphs. In another line, shearing stress, the surface gradient of heat transfer, and volumetric rate of concentration are recorded in tabular form. Most interestingly, momentum boundary layer thickness and thicknesses of thermal as well as solutal boundary layers enhance with an increment of Weissenberg number. Moreover, an increment on tangent hyperbolic nanofluid velocity and decrement on the thickness of momentum boundary layer is visualized for the increment of numerical values of power-law index entity, which can determine the behavior of shear-thinning fluids.This study has applications for coating materials used in chemical engineering, such as strong paints, aerosol manufacturing, and thermal treatment of water-soluble solutions.

Application of Levenberg-Marquardt technique for electrical conducting fluid subjected to variable viscosity

In the present study, design of intelligent numerical computing through backpropagated neural networks (BNNs) is presented for numerical treatment of the fluid mechanics problems governing the dynamics of magnetohydrodynamic fluidic model (MHD-NFM) past a stretching surface embedded in porous medium along with imposed heat source/sink and variable viscosity. The original system model MHD-NFM in terms of PDEs is converted to nonlinear ODEs by introducing the similarity transformations. A reference dataset for BNNs approach is generated with Adams numerical solver for different scenarios of MHD-NFM by variation of parameter of viscosity, parameter of heat source and sink, parameter of permeability, magnetic field parameter, and Prandtl number. To calculate the approximate solution for MHD-NFM for different scenarios, the training, testing, and validation processes are conducted in parallel to adapt neural networks by reducing the mean square error (MSE) function through Levenberg-Marquardt backpropagation. The comparative studies and performance analyses through outcomes of MSE, error histograms, correlation and regression demonstrate the effectiveness of proposed BNNs methodology.

Computational optimization for the deposition of bioconvection thin Oldroyd-B nanofluid with entropy generation

The behavior of an Oldroyd-B nanoliquid film sprayed on a stretching cylinder is investigated. The system also contains gyrotactic microorganisms with heat and mass transfer flow. Similarity transformations are used to make the governing equations non-dimensional ordinary differential equations and subsequently are solved through an efficient and powerful analytic technique namely homotopy analysis method (HAM). The roles of all dimensionless profiles and spray rate have been investigated. Velocity decreases with the magnetic field strength and Oldroyd-B nanofluid parameter. Temperature is increased with increasing the Brownian motion parameter while it is decreased with the increasing values of Prandtl and Reynolds numbers. Nanoparticle's concentration is enhanced with the higher values of Reynolds number and activation energy parameter. Gyrotactic microorganism density increases with bioconvection Rayleigh number while it decreases with Peclet number. The film size naturally increases with the spray rate in a nonlinear way. A close agreement is achieved by comparing the present results with the published results.

A shear-rate-dependent flow generated via magnetically controlled metachronal motion of artificial cilia

Cilia beating is a naturally occurring phenomenon that can be utilized in fluid transport in designing several biomechanical devices. Inspired by the ubiquity of bio-fluids (which are non-Newtonian), we report the characteristics of shear-rate-dependent viscosities on fluid flow generated by the wavy propulsion of magnetic cilia. We assume that the metachronal waves of these cilia form a two-dimensional wavy channel, which is filled with generalized Newtonian Carreau liquid. Galilean transformation is employed to relate fixed and moving frames. The constitutive equations are reduced under the classical lubrication assumption. The resulting fourth-order nonlinear differential equations are solved via a perturbation approach using the stream function. The effects of four dominant fluid parameters (shear thinning/thickening, power-law index, and zero- and infinite-shear-rate viscosity), magnetic parameter (Hartmann number), and metachronal wave parameters on fluid velocity, pressure rise per wavelength, and trapping phenomenon are shown in graphical results and explained thoroughly. This study could play an advisory role in designing a magnetic micro-bot useful in the biomedical industry.