Prediction of Cattaneo–Christov heat flux with thermal slip effects over a lubricated surface using artificial neural network

The lubricated systems containing fluid lubricants have the load-carrying ability. Suitable lubrication permits smooth, incessant operation of machine elements. The significant applications in engineering and industry are drag reduction, cooling of electronic devices and cooling of nuclear reactors,...

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Vydané v:	European physical journal plus Ročník 139; číslo 9; s. 851
Hlavní autori:	Sadiq, M. N., Shahzad, Hasan, Alqahtani, Hassan, Tirth, Vineet, Algahtani, Ali, Irshad, Kashif, Al-Mughanam, Tawfiq
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Berlin/Heidelberg Springer Berlin Heidelberg 24.09.2024 Springer Nature B.V
Predmet:	Accuracy Applied and Technical Physics Artificial neural networks Atomic Back propagation networks Complex Systems Condensed Matter Physics Constitutive relationships Cooling Datasets Differential equations Drag reduction Engineering Error analysis Fluid flow Fluid mechanics Heat conductivity Heat flux Heat transfer Lubricants Lubricants & lubrication Lubrication Mathematical and Computational Physics Molecular Neural networks Nuclear power plants Nuclear reactors Optical and Plasma Physics Optimization techniques Ostwald ripening Partial differential equations Physics Physics and Astronomy Power law Regression models Regular Article Shear stress Temperature Theoretical Thermal analysis Variable thickness Velocity
ISSN:	2190-5444, 2190-5444
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