Computational analysis of the unsteady 3D chemically reacting MHD flow with the properties of temperature dependent transpose suspended Maxwell nanofluid

Ahmad, Shafiq; Çoban, Hasan Hüseyin; Khan, Maleq; Khan, Umair; Shi, Qiu-Hong; Muhammad, Taseer; Chinram, Ronnason; Kadry, Seifedine

doi:10.1016/j.csite.2021.101169

Cited by 27 publications

(11 citation statements)

References 36 publications

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“…Specialists observed that an answer for a particular worth of Reynolds number exists for a 2D stream. Ahmad et al 28 performed the computational investigation of an unstable (3-D) chemically reacting MHD flow of Maxwell fluid. Ahmad et al 29 used the Cattaneo-Christov thermal influx model to probe the hybrid Micropolar nanoliquid stream with triple stratification.…”

Section: Introductionmentioning

confidence: 99%

Insight into the heat transfer of third-grade micropolar fluid over an exponentially stretched surface

Ahammad

Nadeem

Eldin

et al. 2022

Sci Rep

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Due to their unique microstructures, micropolar fluids have attracted enormous attention for their industrial applications, including convective heat and mass transfer polymer production and rigid and random cooling particles of metallic sheets. The thermodynamical demonstration is an integral asset for anticipating the ideal softening of heat transfer. This is because there is a decent connection between mathematical and scientific heat transfers through thermodynamic anticipated outcomes. A model is developed under the micropolar stream of a non-Newtonian (3rd grade) liquid in light of specific presumptions. Such a model is dealt with by summoning likeness answers for administering conditions. The acquired arrangement of nonlinear conditions is mathematically settled using the fourth-fifth order Runge-Kutta-Fehlberg strategy. The outcomes of recognized boundaries on liquid streams are investigated in subtleties through the sketched realistic images. Actual amounts like Nusselt number, Sherwood number, and skin-part coefficient are explored mathematically by tables. It is observed that the velocity distribution boosts for larger values of any of , , and declines for larger and Hartmann numbers. Furthermore, the temperature distribution shows direct behavior with the radiation parameter and Eckert number, while, opposite behavior with Pr , and K . Moreover, the concentration distribution shows diminishing behavior as we put the higher value of the Brownian motion number.

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Section: Introductionmentioning

confidence: 99%

Insight into the heat transfer of third-grade micropolar fluid over an exponentially stretched surface

Ahammad

Nadeem

Eldin

et al. 2022

Sci Rep

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“…here, y j (t) is the reference solution and ŷj (t) is the updated/new solution. Furthermore, the optimization technique, such as a back-propagated Levenberg-Marquardt (BLM) algorithm, is utilized to optimize the connection weights by minimizing the performance function given in Equation (19). For perfect modeling of the approximate solutions, the value of MSE approaches zero.…”

Section: Learning Proceduresmentioning

confidence: 99%

“…Hosseinzadeh [18] studied the effect of magnetic field and radiation on the hybrid fluid in an octagonal porous medium. Chemically reacting MHD 3D Maxwell nanofluid flow subjected to temperature-dependent transposition was investigated by Ahmad [19]. Rashidi [20] investigated the combined effects of nanoparticles and an irresistible field on a micropolar fluid running between two parallel coaxial porous plates under uniform pumping.…”

Section: Introductionmentioning

confidence: 99%

Heat Transfer Analysis of Nanofluid Flow in a Rotating System with Magnetic Field Using an Intelligent Strength Stochastic-Driven Approach

et al. 2022

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This paper investigates the heat transfer of two-phase nanofluid flow between horizontal plates in a rotating system with a magnetic field and external forces. The basic continuity and momentum equations are considered to formulate the governing mathematical model of the problem. Furthermore, certain similarity transformations are used to reduce a governing system of non-linear partial differential equations (PDEs) into a non-linear system of ordinary differential equations. Moreover, an efficient stochastic technique based on feed-forward neural networks (FFNNs) with a back-propagated Levenberg–Marquardt (BLM) algorithm is developed to examine the effect of variations in various parameters on velocity, gravitational acceleration, temperature, and concentration profiles of the nanofluid. To validate the accuracy, efficiency, and computational complexity of the FFNN–BLM algorithm, different performance functions are defined based on mean absolute deviations (MAD), error in Nash–Sutcliffe efficiency (ENSE), and Theil’s inequality coefficient (TIC). The approximate solutions achieved by the proposed technique are validated by comparing with the least square method (LSM), machine learning algorithms such as NARX-LM, and numerical solutions by the Runge–Kutta–Fehlberg method (RKFM). The results demonstrate that the mean percentage error in our solutions and values of ENSE, TIC, and MAD is almost zero, showing the design algorithm’s robustness and correctness.

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“…Due to excessive applicability in engineering and industrial applications, steady flow has gained a lot of concentration of researchers and scholars. However, recently many studies have been conducted on the behavior and characteristics of unsteady fluid flow systems, automobiles, power-generation systems, and aviation industry [16], explored the influence of variable thermal conductivity, viscosity, and Joule heating on the velocity and thermal field in the unsteady flow of 3D Maxwell nanofluid over a stretching surface. An enhancement in the velocity of the fluid has been observed with increased viscosity.…”

Section: Introductionmentioning

confidence: 99%

Heat and Mass Transfer Analysis for Unsteady Three-Dimensional Flow of Hybrid Nanofluid Over a Stretching Surface Using Supervised Neural Networks

et al. 2022

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The application of hybrid nanomaterials for the improvement of thermal efficiency of base fluid has increasingly gained attention during the past few decades. The basic purpose of this study is to investigate the flow characteristics along with heat transfer in an unsteady three-dimensional flow of hybrid nanofluid over a stretchable and rotatory sheet (3D-UHSRS). The flow model in the form of PDEs was reduced to the set of ordinary differential equations utilizing the appropriate transformations of similarity. The influence of the rotation parameter, unsteadiness parameter, stretching parameter, radiation parameter, and Prandtl number on velocities and thermal profile was graphically examined. A reference solution in the form of dataset points for the 3D-UHSRS model are computed with the help of renowned Lobatto IIIA solver, and this solution is exported to MATLAB for the proper implementation of proposed solution methodology based on the Levenberg–Marquardt supervised neural networks. Graphical and numerical results based on the mean square error (MSEs), time series response, error distribution plots, and regression plots endorses the precision, validity, and consistency of the proposed solution methodology. The MSE up to the level of 10–12 confirms the accuracy of the achieved results.

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Computational analysis of the unsteady 3D chemically reacting MHD flow with the properties of temperature dependent transpose suspended Maxwell nanofluid

Cited by 27 publications

References 36 publications

Insight into the heat transfer of third-grade micropolar fluid over an exponentially stretched surface

Insight into the heat transfer of third-grade micropolar fluid over an exponentially stretched surface

Heat Transfer Analysis of Nanofluid Flow in a Rotating System with Magnetic Field Using an Intelligent Strength Stochastic-Driven Approach

Heat and Mass Transfer Analysis for Unsteady Three-Dimensional Flow of Hybrid Nanofluid Over a Stretching Surface Using Supervised Neural Networks

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