Buongiorno's model for fluid flow around a moving thin needle in a flowing nanofluid: A numerical study

Ahmad, Rida; Mustafa, M.; Hina, S.

doi:10.1016/j.cjph.2017.07.004

Cited by 72 publications

(39 citation statements)

References 50 publications

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“…To provide a clear understanding into the present problem, the numerical computations are carried out for several values of the involved parameters which include magnetic, mixed convection, needle size, Brownian motion, thermophoresis and velocity ratio parameter. Validation of the present code has been done by computing the numerical results of f (c) for M = λ = Nr = ε = 0 and Pr = 1 for some values of needle size c. Table 1 shows the data produced by the present code and those of Ahmad et al [21]. As can be seen in Table 1, both pieces of data are found to be in excellent agreement, hence, the present code can be used confidently.…”

Section: Resultsmentioning

confidence: 67%

“…Such situation occurs due to random motion of the particles suspended in the fluid caused by the continuous collision between the nanoparticles and base fluid particles. Conspicuously, the Brownian motion parameter does not change the surface temperature gradient as well as the rate of heat transfer (see [21]). Mathematically, when substituting the condition φ (c) + (Nt/Nb)θ (c) = 0 directly into the energy Equation 3, one may observe that the resulting equation does not contain the parameter Nb, and this is the reason why the graph for the local Nusselt number is not presented here.…”

Section: Resultsmentioning

confidence: 99%

“…Krishna et al [19] and Soid et al [20] investigated the flow and heat transfer past a moving thin needle with the magnetohydrodynamic radiative nanofluid, and stability analysis, respectively. Moreover, Ahmad et al [21] attempted to consider the Buongiorno nanofluid flow past a moving thin needle. However, all the studies mentioned above are restricted to the horizontal surface of the needle.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Magnetohydrodynamics Flow Past a Moving Vertical Thin Needle in a Nanofluid with Stability Analysis

et al. 2018

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In this study, we intend to present the dynamics of a system based on the model of convective heat and mass transfer in magnetohydrodynamics (MHD) flow past a moving vertical thin needle in nanofluid. The problem is formulated in mathematical form by using Buongiorno’s model with the modified boundary condition. The transformed boundary layer ordinary differential equations are solved numerically using the bvp4c function in MATLAB software. The effects of the involved parameters, including, Brownian motion, thermophoresis, magnetic field, mixed convection, needle size and velocity ratio parameter on the flow, heat and mass transfer coefficients are analyzed. The numerical results obtained for the skin friction coefficients, local Nusselt number and local Sherwood number, as well as the velocity, temperature and concentration profiles are graphically presented and have been discussed in detail. The study reveals that the dual solutions appear when the needle and the buoyancy forces oppose the direction of the fluid motion, and the range of the dual solutions existing depends largely on the needle size and magnetic parameter. The presence of the magnetic field in this model reduces the coefficient of the skin friction and heat transfer, while it increases the coefficient of the mass transfer on the needle surface. A stability analysis has been performed to identify which of the solutions obtained are linearly stable and physically relevant. It is noticed that the upper branch solutions are stable, while the lower branch solutions are not.

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Section: Resultsmentioning

confidence: 67%

Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Magnetohydrodynamics Flow Past a Moving Vertical Thin Needle in a Nanofluid with Stability Analysis

et al. 2018

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“…It is observed that heat transfer rate increases for higher values of Sc, whereas Nu x is a diminishing function of K s . [38] and Rida et al [45], but in limiting cases. An outstanding harmony between the results is found.…”

Section: Graphical Analysismentioning

confidence: 93%

“…That also validates the current exploration results. Table 1 depicts the numerically calculated values of f (n) for numerous estimates of n done by Ishak et al [38] and Rida et al [45], but in limiting cases. An outstanding harmony between the results is found.…”

Section: Graphical Analysismentioning

confidence: 99%

Thermally Stratified Darcy Forchheimer Flow on a Moving Thin Needle with Homogeneous Heterogeneous Reactions and Non-Uniform Heat Source/Sink

et al. 2020

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This study discusses the flow of viscous fluid past a moving thin needle in a Darcy–Forchheimer permeable media. The novelty of the envisioned mathematical model is enhanced by adding the effects of a non-uniform source/sink amalgamated with homogeneous–heterogeneous (hh) reactions. The MATLAB bvp4c function is employed to solve the non-linear ordinary differential equations (ODEs), which are obtained via similarity transformations. The outcomes of numerous parameters are explicitly discussed graphically. The drag force coefficient and heat transfer rate are considered and discussed accordingly. It is comprehended that higher estimates of variable source/sink boost the temperature profile.

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Designing artificial neural network of nanoparticle diameter and solid–fluid interfacial layer on single‐walled carbon nanotubes/ethylene glycol nanofluid flow on thin slendering needles

Shafiq

Çolak

Sindhu

2021

Numerical Methods in Fluids

113

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In this study, an artificial neural network (ANN) has been developed to predict the boundary layer flow of a single‐walled carbon nanotubes nanofluid toward three different nonlinear thin isothermal needles of paraboloid, cone, and cylinder shapes with convective boundary conditions. Different effects of particle diameter and solid–fluid interface coating have been taken into account in the thermal conductivity model of nanofluid in which ethylene glycol has been used as the base fluid. Single and dual phase approach is used to establish the management model under the phenomenon of zero heat and mass flux. A dataset has been developed for different scenarios of the fluid model by changing the relevant parameters with the Runge–Kutta based shooting technique. Two different ANN models have been developed to predict Nusselt number and skin friction coefficient (SFC) values. The values obtained from ANN models have been compared with the numerical data, which are the target values. In addition, mean square error and R values have also been examined in order to analyze the prediction performance of ANN models more comprehensively. The calculated R values for Nusselt number and SFC were obtained as 0.9999. The results obtained showed that ANN can predict Nusselt number and SFC values with high accuracy.

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Buongiorno's model for fluid flow around a moving thin needle in a flowing nanofluid: A numerical study

Cited by 72 publications

References 50 publications

Magnetohydrodynamics Flow Past a Moving Vertical Thin Needle in a Nanofluid with Stability Analysis

Magnetohydrodynamics Flow Past a Moving Vertical Thin Needle in a Nanofluid with Stability Analysis

Thermally Stratified Darcy Forchheimer Flow on a Moving Thin Needle with Homogeneous Heterogeneous Reactions and Non-Uniform Heat Source/Sink

Designing artificial neural network of nanoparticle diameter and solid–fluid interfacial layer on single‐walled carbon nanotubes/ethylene glycol nanofluid flow on thin slendering needles

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