Melting effect on non-Newtonian fluid flow in gyrotactic microorganism saturated non-darcy porous media with variable fluid properties

Nima, Nayema Islam; Salawu, S.O.; Ferdows, M.; Shamshuddin,; Alsenafi, Abdulaziz; Nakayama, A.

doi:10.1007/s13204-020-01491-y

Cited by 37 publications

(13 citation statements)

References 37 publications

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“…The nonmagnetic Nimonic 80a nanoparticle reaches the maximum shear stress, and nonmagnetic SiO 2 nanoparticle generates the smallest shear stress. However, the Nusselt number (wall temperature gradient) decreases with solid volume fraction, as temperature is increased (see earlier figures), and this confirms the effectiveness of nanofluids as superior thermal working fluids 25 . With reduction in the Nusselt number, there is a corresponding transfer of heat to the nanofluid, leading to thicker thermal boundary layers 36–39 .…”

Section: Validation Of Srm Results and Discussionmentioning

confidence: 52%

“…Commonly used heat distribution liquids like ethylene glycol, water, and engine oil have small thermal conductivity when compared with metals. Therefore, dispersing solid metal particles in heat diffusion can meaningfully increase heat conduction 25 . Nanofluids consists of nanoparticles distributed in the base liquids, such as water, ethylene glycol, and so on.…”

Section: Introductionmentioning

confidence: 99%

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Computation of ferromagnetic/nonmagnetic nanofluid flow over a stretching cylinder with induction and curvature effects

et al. 2021

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Motivated by enrobing processes in manufacturing technology with intelligent coatings, this study analyses the flow of an electroconductive incompressible nanofluid with heat distribution in a boundary layer containing metallic nanoparticles or ferroparticles along an extending cylindrical body with magnetic induction effects. The quasilinear boundary conditions for the partial derivative formulations connecting to the far stream and cylinder wall are converted to ordinary nonlinear derivatives by applying appropriate similarity transformations. The emerging system of derivatives is solved by a stable, efficient spectral relaxation method (SRM). The SRM procedure is benchmarked with special limiting cases in the literature and found to corroborate exceptionally well with other studies in the literature. Here, water is taken as the base liquid containing homogenously suspended nonmagnetic (Nimonic 80a, silicon dioxide [SiO2]) or magnetic nanoparticles (ferric oxide [Fe3O4] and manganese franklinite [Mn–ZnFe2O4]). The influence of all key parameters on the velocity and temperature distributions is displayed in graphs and tables with extensive elucidation. The wall local drag force (skin friction) and local temperature gradient (Nusselt number) are also visualized graphically for various parameters. The rate of convergence of the SRM convergence is compared with that of the successive over‐relaxation method, and it is observed to converge faster. Larger magnetohydrodynamic body force parameter and inverse Prandtl magnetic number induce flow deceleration and enhance temperature. Flow acceleration is computed for SiO2 nonmagnetic nanoparticles, and good heat conduction augmentation is produced with magnetic nanoparticle Fe3O4.

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Section: Validation Of Srm Results and Discussionmentioning

confidence: 52%

Section: Introductionmentioning

confidence: 99%

Computation of ferromagnetic/nonmagnetic nanofluid flow over a stretching cylinder with induction and curvature effects

et al. 2021

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“…Kuznetsov et al [21,22] presented the natural convection flow of nanofluid past a vertical sheet. Nima et al [23] reported the behavior of non-Newtonian fluid with variable properties in the presence of the gyrotactic microorganisms. One of the key features was that the density profile is upsurged as the bioconvection Lewis number gets higher.…”

Section: Introductionmentioning

confidence: 99%

Bioconvection Mangnetohydrodynamic Tangent Hyperbolic Nanofluid Flow with Quartic Chemical Reaction Past a Paraboloid Surface

Atif¹,

Khan²,

Abbas³

et al. 2022

Computer Modeling in Engineering &Amp; Sciences

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In this numerical study, the effect of quartic autocatalysis type of chemical reaction, buoyancy force and thermal radiation phenomenon and magnetic effect on tangent hyperbolic nanofluid past an upper horizontal surface of a paraboloid has been studied. By considering the Buongiorno model approach, a diffusion of unequal coefficients in the presence of gyrotactic microorganism is discussed. Implementation of microorganism's idea is used to stabilize the nanoparticles through bioconvection. The modeled PDEs of the problems are converted into nonlinear ODEs with the assistant of the similarity transformations. To tackle nonlinear ODEs, MATLAB package bvp4c is used. In addition, a hallmark of the Matlab code with the reported results in the literature is achieved by benchmarking. The variations in motion, concentration, temperature, and motile density due to sundry parameters have been analyzed in-depth via graphs. Our analysis shows that the density profile of motile of microorganism is hiked with an increment in the bioconvection Rayleigh number but decreases for higher thermal Grashof number.

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“…As a result, the utilization of ultra-fine solid particles in fluids has affected significantly the improvement of heat-transmission execution. According to Nima et al [11], such a variety develops in a more conductive heat-transfer liquid, which has uses in electronics, transportation sectors, pharmaceutical sectors, biomedicine, atomic reactors, and power manufacture, etc. According to Eastman et al [12], the heat-absorption capacity of Nano fluids is significantly higher than that of conventional fluids, with thermal conductivity rising equal to 40% dependent on the size, shape, and thermal properties of solid nanomaterials.…”

Section: Introductionmentioning

confidence: 99%

Heat Transfer Impacts on Maxwell Nanofluid Flow over a Vertical Moving Surface with MHD Using Stochastic Numerical Technique via Artificial Neural Networks

et al. 2021

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The technique of Levenberg–Marquardt back propagation with neural networks (TLMB-NN) was used in this research article to investigate the heat transfer of Maxwell base fluid flow of nanomaterials (HTM-BFN) with MHD over vertical moving surfaces. In this study, the effects of thermal energy, concentration, and Brownian motion are also employed. Moreover, the impacts of a heat-absorbing fluid with viscous dissipation and radiation have been explored. To simplify the governing equations from a stiff to a simple system of non-linear ODEs, we exploited the efficacy of suitable similarity transformation mechanism. Through applicability of state-of-the-art Adams numerical technique, a set of data for suggested (TLMB-NN) is generated for several situations (scenarios) by changing parameters, such as the Thermophoresis factor Nt, Hartmann number M, Eckert number Ec, concentration Grashoff parameter Gc, Prandtl number Pr, Lewis number Le, thermal Grashof number GT, and Brownian motion factor Nb. The estimate solution of different instances has validated using the (TLMB-NN) training, testing, and validation method, and the recommended model was compared for excellence. Following that, regression analysis, mean square error, and histogram explorations are used to validate the suggested (TLMB-NN). The proposed technique is distinguished based on the proximity of the proposed and reference findings, with an accuracy level ranging from 10−9 to 10−10.

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Melting effect on non-Newtonian fluid flow in gyrotactic microorganism saturated non-darcy porous media with variable fluid properties

Cited by 37 publications

References 37 publications

Computation of ferromagnetic/nonmagnetic nanofluid flow over a stretching cylinder with induction and curvature effects

Computation of ferromagnetic/nonmagnetic nanofluid flow over a stretching cylinder with induction and curvature effects

Bioconvection Mangnetohydrodynamic Tangent Hyperbolic Nanofluid Flow with Quartic Chemical Reaction Past a Paraboloid Surface

Heat Transfer Impacts on Maxwell Nanofluid Flow over a Vertical Moving Surface with MHD Using Stochastic Numerical Technique via Artificial Neural Networks

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