The effect of slip condition on the three-dimensional flow of Jeffrey fluid along a plane wall with periodic suction

Shoaib, Mohammed; Rana, M. A.; Siddiqui, A. M.

doi:10.1007/s40430-017-0721-0

Cited by 14 publications

(5 citation statements)

References 15 publications

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“…In the future research, the presented BANN-LMT can be used as an effective/accurate stochastic technique for second-grade fluidic system [ 76 ], Casson nanofluid flow model [ 77 ], Jeffrey fluid model [ 78 ], dusty Casson fluid flow model [ 79 ], Darcy–Forchheimer flow model [ 80 ], MHD hybrid fluid flow model [ 81 ] and 2D Sutterby fluid flow model [ 82 ].…”

Section: Discussionmentioning

confidence: 99%

Intelligent Computing with Levenberg–Marquardt Backpropagation Neural Networks for Third-Grade Nanofluid Over a Stretched Sheet with Convective Conditions

Shoaib

Raja²,

Zubair

et al. 2021

Arab J Sci Eng

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This article discussed the influence of activation energy on MHD flow of third-grade nanofluid model (MHD-TGNFM) along with the convective conditions and used the technique of backpropagation in artificial neural network using Levenberg–Marquardt technique (BANN-LMT). The PDEs representing (MHD-TGNFM) transformed into the system of ODEs. The dataset for BANN-LMT is computed for the six scenarios by using the Adam numerical method by varying the local Hartman number (Ha), Prandtl number (Pr), local chemical reaction parameter ( σ ), Schmidt number (Sc), concentration Biot number ( γ 2 ) and thermal Biot number ( γ 1 ). By testing, validation and training process of (BANN-LMT), the estimated solutions are interpreted for (MHD-TGNFM). The validation of the performance of (BANN-LMT) is done through the MSE, error histogram and regression analysis. The concentration profile increases when there is an increase in Biot number and the local Hartmann number; meanwhile, it decreases for the higher values of Schmidt number and the local chemical reaction parameter.

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Section: Discussionmentioning

confidence: 99%

Intelligent Computing with Levenberg–Marquardt Backpropagation Neural Networks for Third-Grade Nanofluid Over a Stretched Sheet with Convective Conditions

Shoaib

Raja²,

Zubair

et al. 2021

Arab J Sci Eng

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“…Amanulla et al 23 obtained the numerical outcomes for the coefficient of skin friction and heat transport analysis of Jeffrey fluid from a vertical inclined plate. Shoaib et al 24 inspected the outcomes of slip condition on Jeffrey fluid along with periodic suction on a plane wall and concluded that the Jeffrey fluid parameters are directing drag force. Reddy et al 25 considered the radiation effect on Jeffrey fluid over an inclined vertical plate.…”

Section: Introductionmentioning

confidence: 99%

Viscoelastic nanofluid motion for Homann stagnation-region with thermal radiation characteristics

Khan

Sarfraz

Ahmad

et al. 2021

Proceedings of the Institution of Mechanical Engineers, Part C:

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The problem of Jeffrey’s nanofluid for a modification of Homann’s exterior potential flow in the stagnation region is modeled over a cylindrical disk. The characteristic of electrically conducting nanofluid flow with a time-independent free stream is noted as well. Due to this, a new family of asymmetric flows is created, which mainly depends on the viscoelastic parameter [Formula: see text] magnetic parameter [Formula: see text] and the stress-to strain rate ratio, i.e., [Formula: see text] By deploying Buongiorno’s model and Rosseland’s approximation, the outcomes of the Brownian diffusion, thermophoresis, and solar radiation on the mass and thermal boundary layer are also scrutinized. The conservation laws are remodeled by a similarity transformation, and the governing equations are solved by a builtin program bvp4c in Matlab. Furthermore, a comparison is made between the numerical outcomes and their large- γ asymptotics for wall stresses and displacement thicknesses. It is discovered that due to the impact of Jeffrey’s material parameters and magnetic field, when [Formula: see text] reaches infinity, along the x-axis the two-dimensional displacement thickness and the coefficient of skin friction are closer to their asymptotic values; however, along the y-axis, they exhibit opposite trend. Moreover, the thermal and mass transport is enhanced due to significant contributions of nanofluid conductivity.

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“…ere are some non-Newtonian models presenting the three-dimensional fluidic problems though a porous wall with variable suction [31][32][33][34][35]. Periodic suction has received very much attention in the field of aerodynamics [36][37][38].…”

Section: Introductionmentioning

confidence: 99%

A Novel Design of Three‐Dimensional MHD Flow of Second‐Grade Fluid past a Porous Plate

Shoaib

Akhtar

Khan

et al. 2019

Mathematical Problems in Engineering

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In this study, a novel theoretical model for three-dimensional (3D) laminar magnetohydrodynamic (MHD) flow of a non-Newtonian second-grade fluid along a plate of semi-infinite length is developed based on slightly sinusoidal transverse suction velocity. The suction velocity involves a steady distribution with a low superimposed perpendicularly varying dispersion. The strength of the uniform magnetic field is incorporated in the normal direction to the wall. The variable suction transforms the fluidic problem into a 3D flow problem because of variable suction velocity in the normal direction to the plane wall. The proposed mathematical modeling and its dynamical analysis are prescribed for the boundary layer flow keeping the magnetic effects without taking into consideration the induced magnetic field. An analytical perturbation technique is employed for the series solutions of the system of ordinary differential equations of velocity profile and pressure. Graphical illustrations are used to analyze the behavior of different proficient parameters of interest. The magnetic parameter is responsible for accelerating the main flow velocity, while controlling the cross flow velocities.

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The effect of slip condition on the three-dimensional flow of Jeffrey fluid along a plane wall with periodic suction

Cited by 14 publications

References 15 publications

Intelligent Computing with Levenberg–Marquardt Backpropagation Neural Networks for Third-Grade Nanofluid Over a Stretched Sheet with Convective Conditions

Intelligent Computing with Levenberg–Marquardt Backpropagation Neural Networks for Third-Grade Nanofluid Over a Stretched Sheet with Convective Conditions

Viscoelastic nanofluid motion for Homann stagnation-region with thermal radiation characteristics

A Novel Design of Three‐Dimensional MHD Flow of Second‐Grade Fluid past a Porous Plate

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