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Mathematical Models and Computer Simulations

Erschienen in:

01.10.2023

An Artificial Neural Network Solution for the Casson Fluid Flow Past a Radially Stretching Sheet with Magnetic and Radiation Effect

verfasst von: D. Srinivasacharya, R. Shravan Kumar

Erschienen in: Mathematical Models and Computer Simulations | Ausgabe 5/2023

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Abstract

The Casson fluid flow past a radially stretching sheet in the presence of an applied magnetic field and thermal radiation is investigated. Artificial neural networks are used to compute the solution of the flow. A multilayer perceptron neural network with adjustable parameters is used in the trial functions. The Adams optimization (adaptive moment estimation) algorithm is used to determine adjustable parameters of the trial solution. The results of the current method are validated utilizing shooting method in conjunction with the Runge–Kutta fourth-order method. The conclusions demonstrate that the artificial neural network-based method provides significant accuracy and that the effectiveness of the solution improves as the number of neurons in the neural network grows. The impact of relevant parameters on the physical quantities is displayed through graphs. As per the present research, enhancing the radiation parameter causes an increase in skin friction and Nusselt number, while boosting the magnetic parameter causes decrease in skin friction and Nusselt number.

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N. Casson, “A flow equation for pigment-oil suspensions of the printing ink type,” in Rheology of Disperse Systems, Ed. by C. C. Mill (Pergamon, Oxford, 1959), pp. 84–104.

K. Vajravelu, K. V. Prasad, H. Vaidya, N. Z. Basha, and C.-O. Ng, “Mixed convective flow of a Casson fluid over a vertical stretching sheet,” Int. J. Appl. Comput. Math. 3, 1619–1638 (2017). https://doi.org/10.1007/s40819-016-0203-6MathSciNetCrossRefMATH

M. Nawaz, R. Naz, and M. Awais, “Magnetohydrodynamic axisymmetric flow of Casson fluid with variable thermal conductivity and free stream,” Alexandria Eng. J. 57, 2043–2050 (2018). https://doi.org/10.1016/j.aej.2017.05.016CrossRef

M. Sohail, Z. Shah, A. Tassaddiq, P. Kumam, and P. Roy, “Entropy generation in MHD Casson fluid flow with variable heat conductance and thermal conductivity over non-linear bi-directional stretching surface,” Sci. Rep. 10, 12530 (2020). https://doi.org/10.1038/s41598-020-69411-2

A. R. M. Kasim, N. S. Arifin, S. M. Zokri, N. A. N. Ariffin, M. Z. Salleh, and M. I. Anwar, “Mathematical model of simultaneous flow between Casson fluid and dust particle over a vertical stretching sheet,” Int. J. Int. Eng. 12, 253–260 (2020). https://doi.org/10.30880/ijie.2020.12.03.029CrossRef

I. Ullah, S. Shafie, and I. Khan, “Effects of slip condition and Newtonian heating on MHD flow of Casson fluid over a nonlinearly stretching sheet saturated in a porous medium,” J. King Saud Univ.–Sci. 29, 250–259 (2017). https://doi.org/10.1016/j.jksus.2016.05.003CrossRef

M. A. El-Aziz and A. A. Afify, “Influences of slip velocity and induced magnetic field on MHD stagnation-point flow and heat transfer of Casson fluid over a stretching sheet,” Math. Probl. Eng. 2018, 9402836 (2018). https://doi.org/10.1155/2018/9402836CrossRef

A. Hussanan, M. Z. Salleh, H. T. Alkasasbeh, and I. Khan, “MHD flow and heat transfer in a Casson fluid over a nonlinearly stretching sheet with Newtonian heating,” Heat Transfer Res. 49, 1185–1198 (2018). https://doi.org/10.1615/HeatTransRes.2018014771CrossRef

M. Hamid, M. Usman, Z. H. Khan, R. Ahmad, and W. Wang, “Dual solutions and stability analysis of flow and heat transfer of Casson fluid over a stretching sheet,” Phys. Lett. A 383, 2400–2408 (2019). https://doi.org/10.1016/j.physleta.2019.04.050MathSciNetCrossRefMATH

10.

B. J. Gireesha, B. M. Shankaralingappa, B. C. Prasannakumar, and B. Nagaraja, “MHD flow and melting heat transfer of dusty Casson fluid over a stretching sheet with Cattaneo–Christov heat flux model,” Int. J. Ambient Energy 43, 2931–2939 (2020). https://doi.org/10.1080/01430750.2020.1785938CrossRef

11.

R. Devi, V. Poply, and Manimala, “Effect of aligned magnetic field and inclined outer velocity in Casson fluid flow over a stretching sheet with heat source,” J. Therm. Eng. 7, 823–844 (2021). https://doi.org/10.18186/thermal.930347CrossRef

12.

H. T. Alkasasbeh, S. Abu-Ghurra, and H. A. Alzgool, “Similarity solution of heat transfer for the upper-convected Maxwell Casson fluid over a stretching/shrinking sheet with thermal radiation,” JP J. Heat Mass Transfer 16, 1–17 (2019). https://doi.org/10.17654/HM016010001CrossRef

13.

F. Mabood and K. Das, “Outlining the impact of melting on MHD Casson fluid flow past a stretching sheet in a porous medium with radiation,” Heliyon 5, e01216 (2019). https://doi.org/10.1016/j.heliyon.2019.e01216CrossRef

14.

J.-C. Zhou, A. Abidi, Q.-H. Shi, M. R. Khan, A. Rehman, A. Issakhov, and A. M. Galal, “Unsteady radiative slip flow of MHD Casson fluid over a permeable stretched surface subject to a non-uniform heat source,” Case Stud. Therm. Eng. 26, 101141 (2021). https://doi.org/10.1016/j.csite.2021.101141CrossRef

15.

D. T. Pham and X. Liu, Neural Networks for Identification, Prediction and Control (Springer, London, 1995). https://doi.org/10.1007/978-1-4471-3244-8

16.

I. E. Lagaris, A. Likas, and D. I. Fotiadis, “Artificial neural networks for solving ordinary and partial differential equations,” IEEE Trans. Neural Networks 9, 987–1000 (1998). https://doi.org/10.1109/72.712178CrossRef

17.

H. Lee and I. S. Kang, “Neural algorithm for solving differential equations,” J. Comput. Phys. 91, 110–131 (1990). https://doi.org/10.1016/0021-9991(90)90007-NMathSciNetCrossRefMATH

18.

N. Yadav, A. Yadav, and M. Kumar, An Introduction to Neural Network Methods for Differential Equations (Springer, Dordrecht, 2015). https://doi.org/10.1007/978-94-017-9816-7

19.

S. Chakraverty and S. Mall, Artificial Neural Networks for Engineers and Scientists: Solving Ordinary Differential Equations (CRC Press, Boca Raton, FL, 2017). https://doi.org/10.1201/9781315155265

20.

A. J. Meade Jr. and A. A. Fernandez, “Solution of nonlinear ordinary differential equations by feedforward neural networks,” Math. Comput. Modell. 20, 19–44 (1994). https://doi.org/10.1016/0895-7177(94)00160-XMathSciNetCrossRefMATH

21.

M. F. Shahri and A. H. Nezhad, “Estimation of the flow and heat transfer in MHD flow of a power law fluid over a porous plate using artificial neural networks,” Middle East J. Sci. Res. 22 , 1422–1429 (2014).

22.

M. Ziaei-Rad, M. Saeedan, and E. Afshari, “Simulation and prediction of MHD dissipative nanofluid flow on a permeable stretching surface using artificial neural network,” Appl. Therm. Eng. 99, 373–382 (2016). https://doi.org/10.1016/j.applthermaleng.2016.01.063CrossRef

23.

P. B. A. Reddy and R. Das, “Estimation of MHD boundary layer slip flow over a permeable stretching cylinder in the presence of chemical reaction through numerical and artificial neural network modeling,” Eng. Sci. Technol., Int. J. 19, 1108–1116 (2016). https://doi.org/10.1016/j.jestch.2015.12.013CrossRef

24.

M. Elayarani and M. Shanmugapriya, “Artificial neural network modeling of MHD stagnation point flow and heat transfer towards a porous stretching sheet,” AIP Conf. Proc. 2161, 020043 (2019). https://doi.org/10.1063/1.5127634CrossRef

25.

M. A. Behrang, M. Ghalambaz, E. Assareh, and A. R. Noghrehabadi, “A new solution for natural convection of Darcian fluid about a vertical full cone embedded in porous media prescribed wall temperature by using a hybrid neural network-particle swarm optimization method,” WASET Int. J. Mech. Mechatron. Eng. 5, 249–254 (2011).

26.

H. Mutuk, “A neural network study of Blasius equation,” Neural Process. Lett. 51, 2179–2194 (2020). https://doi.org/10.1007/s11063-019-10184-9CrossRef

27.

M. L. Piscopo, M. Spannowsky, and P. Waite, “Solving differential equations with neural networks: Applications to the calculation of cosmological phase transitions,” Phys. Rev. D 100, 016002 (2019). https://doi.org/10.1103/PhysRevD.100.0160029MathSciNetCrossRef

28.

D. P. Kingma and J. Ba, “Adam: A method for stochastic optimization,” arXiv preprint (2014). https://doi.org/10.48550/arXiv.1412.6980

Titel: An Artificial Neural Network Solution for the Casson Fluid Flow Past a Radially Stretching Sheet with Magnetic and Radiation Effect
verfasst von: D. Srinivasacharya
R. Shravan Kumar
Publikationsdatum: 01.10.2023
Verlag: Pleiades Publishing
Erschienen in: Mathematical Models and Computer Simulations / Ausgabe 5/2023
Print ISSN: 2070-0482
Elektronische ISSN: 2070-0490
DOI: https://doi.org/10.1134/S2070048223050101

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