Neural network analysis for prediction of heat transfer of aqueous hybrid nanofluid flow in a variable porous space with varying film thickness over a stretched surface  

作　　者：Abeer S Alnahdi Taza Gul 

机构地区：[1]Department of Mathematics and Statistics,Faculty of Science,Imam Mohammad Ibn Saud Islamic University(IMSIU),Riyadh,Saudi Arabia [2]Mathematics Department,City University of Science and Information Technology,Peshawar,25000,Pakistan [3]DoST-Directorate General of Science and Technology Khyber Pakhtunkhwa,Peshawar,25000,Pakistan

出　　处：《Chinese Physics B》2025年第2期316-326,共11页中国物理B(英文版)

摘　　要：The high thermal conductivity of the nanoparticles in hybrid nanofluids results in enhanced thermal conductivity associated with their base fluids.Enhanced heat transfer is a result of this high thermal conductivity,which has significant applications in heat exchangers and engineering devices.To optimize heat transfer,a liquid film of Cu and TiO_(2)hybrid nanofluid behind a stretching sheet in a variable porous medium is being considered due to its importance.The nature of the fluid is considered time-dependent and the thickness of the liquid film is measured variable adjustable with the variable porous space and favorable for the uniform flow of the liquid film.The solution of the problem is acquired using the homotopy analysis method HAM,and the artificial neural network ANN is applied to obtain detailed information in the form of error estimation and validations using the fitting curve analysis.HAM data is utilized to train the ANN in this study,which uses Cu and TiO_(2)hybrid nanofluids in a variable porous space for unsteady thin film flow,and it is used to train the ANN.The results indicate that Cu and TiO_(2)play a greater role in boosting the rate.

关 键 词：thin film of Cu and TiO_(2)hybrid nanofluids variable porous space unsteady stretching sheet viscous dissipation heat transfer optimization artificial neural network 

分 类 号：O551.3[理学—热学与物质分子运动论] TP183[理学—物理]