Levenberg–Marquardt Training Technique Analysis of Thermally Radiative and Chemically Reactive Stagnation Point Flow of Non-Newtonian Fluid with Temperature Dependent Thermal Conductivity

Khalil Ur Rehman (), Wasfi Shatanawi () and Andaç Batur Çolak
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Khalil Ur Rehman: Department of Mathematics and Sciences, College of Humanities and Sciences, Prince Sultan University, Riyadh 11586, Saudi Arabia
Wasfi Shatanawi: Department of Mathematics and Sciences, College of Humanities and Sciences, Prince Sultan University, Riyadh 11586, Saudi Arabia
Andaç Batur Çolak: Information Technologies Application and Research Center, Istanbul Commerce University, 34445 Istanbul, Turkey

Mathematics, 2023, vol. 11, issue 3, 1-27

Abstract: We have examined the magnetized stagnation point flow of non-Newtonian fluid towards an inclined cylindrical surface. The mixed convection, thermal radiation, viscous dissipation, heat generation, first-order chemical reaction, and temperature-dependent thermal conductivity are the physical effects being carried for better novelty. Mathematical equations are constructed for four different flow regimes. The shooting method is used to evaluate the heat transfer coefficient at the cylindrical surface with and without heat generation/thermal radiation effects. For better examination, we have constructed artificial neural networking models with the aid of the Levenberg–Marquardt training technique and Purelin and Tan-Sig transfer functions. The Nusselt number strength is greater for fluctuations in the Casson fluid parameter, Prandtl number, heat generation, curvature, and Eckert number when thermal radiations are present.

Keywords: non-Newtonian fluid; heat transfer; MHD; heat generation; artificial neural networking; Levenberg–Marquardt technique (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2023
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