Intelligent neural computing to investigate the heat and mass transmission in nanofluidic system between two rotating permeable disks: Supervised learning mechanism

Galal，Ahmed M.1,2; Haider，Qusain3; Arshad，Mubashar4; Hassan，Ali5; Alharbi，Fahad M.6; Alam，Mohammad Mahtab7; Abdeljawad，Thabet8,9,10,11

2024-07-01

10.1016/j.csite.2024.104531

Case Studies in Thermal Engineering   影响因子和分区

2214-157X

The prime objective of the present study is to investigate the effectiveness and accuracy of a single-trained artificial neural network. The Levenberg-Marquardt Backpropagated networks are tested for heat and mass transmission in magnetized hybrid nanofluid flow between the rotating permeable system. The reference data to generate different cases for distinct scenarios has been obtained using the Adams method in Mathematica using the ND-Solver function. Additionally, the system of highly nonlinear PDE's is achieved and transformed into ODE's. The effect of body forces such as thermophoresis particle diffusion and Brownian motion are incorporated in the hybrid nanofluid system. Configuration under observation is permeable and under constant impact of the magnetic field. Rosseland thermal radiation approximation relation is utilized to investigate the linear impact of radiation on velocity and temperature profile. The accuracy and effectiveness of the proposed ANNLMB are depicted with performance demonstrations. Mean square error, histogram error, and regression plots are generated for all the scenarios to discuss the varying impact of different key study parameters on the performance of the proposed ANNLMB. Furthermore, the generated reference data is distributed in the following manner 82 %, 9 %, and 9 % for training, testing, and validation, respectively.

ANN Heat transfer Hybrid nanofluids Levenberg-marquardt intelligent network Rotating disks

SCI ; EI

英语

其他

2-s2.0-85193446622

Scopus

1.Department of Mechanical Engineering,College of Engineering in Wadi Alddawasir,Prince Sattam bin Abdulaziz University,Saudi Arabia
2.Production Engineering and Mechanical Design Department,Faculty of Engineering,Mansoura University,Mansoura,P.O 35516,Egypt
3.Mathematics Area,MathLab,International School for Advanced Studies (SISSA),Trieste,Italy
4.Department of Mathematics,Abbottabad University of Science & Technology,Abbottabad,22500,Pakistan
5.Department of Mechanics and Aerospace Engineering,Southern University of Science and Technology,Shenzhen,Guangdong,China
6.Department of Mathematics,Al-Qunfudah University College,Umm Al-Qura University,Mecca,Saudi Arabia
7.Department of Basic Medical Sciences,College of Applied Medical Science,King Khalid University,Abha,61421,Saudi Arabia
8.Department of Mathematics and Sciences,Prince Sultan University,Riyadh,P.O. Box 66833,11586,Saudi Arabia
9.Department of Medical Research,China Medical University,Taichung,40402,Taiwan
10.Department of Mathematics,Kyung Hee University,Seoul,26 Kyungheedae-ro, Dongdaemun-gu,02447,South Korea
11.Department of Mathematics and Applied Mathematics,School of Science and Technology,Sefako Makgatho Health Sciences University,Ga-Rankuwa,South Africa

Galal，Ahmed M.,Haider，Qusain,Arshad，Mubashar,et al. Intelligent neural computing to investigate the heat and mass transmission in nanofluidic system between two rotating permeable disks: Supervised learning mechanism[J]. Case Studies in Thermal Engineering,2024,59.

Galal，Ahmed M..,Haider，Qusain.,Arshad，Mubashar.,Hassan，Ali.,Alharbi，Fahad M..,...&Abdeljawad，Thabet.(2024).Intelligent neural computing to investigate the heat and mass transmission in nanofluidic system between two rotating permeable disks: Supervised learning mechanism.Case Studies in Thermal Engineering,59.

Galal，Ahmed M.,et al."Intelligent neural computing to investigate the heat and mass transmission in nanofluidic system between two rotating permeable disks: Supervised learning mechanism".Case Studies in Thermal Engineering 59(2024).