| AI Multi-Parameters Bayesian with Genetic Optimization for the Effect of Hall Current on Squeezing Slip Flow |
| Paper ID : 1070-ISCH |
| Authors |
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Mohamed Khaled Abdelhamid *1, Emad M Abo-El Dahab2, Mohamed Abd El-Aziz2, Ahmed M Salem2 1Department of Basic Science, Faculty of Computers and Artificial Intelligence, Cairo University, Giza 12613, Egypt 2Department of Mathematics, Faculty of Science, Helwan University, Helwan-Cairo 11795 Egypt |
| Abstract |
| Traditional parametric studies of thermal-fluid systems often suffer from excessive computational cost and inefficiency due to the need for exhaustive trial-and-error simulations. The novelty is the use of Bayesian Optimization and Genetic Algorithm to identify optimal parameter sets maximizing heat transfer (ππ’upper) while minimizing friction (πΆπ,π₯ πππ€ππ). This study analyzes steady MHD slip flow between two displaceable plates filled with a MoSββSiOβ/EGβwater hybrid nanofluid under the influence of a strong magnetic field, considering Hall current, radiation, and viscous dissipation. The lower plate moves at constant velocity while the upper plate squeezes the fluid under slip conditions in a Darcy porous medium. The transformed governing equations are solved via a finite difference method in Python. Results reveal significant thermal enhancement at the upper plate, especially for hybrid nanofluids. The Eckert number amplifies temperature due to viscous heating, while magnetic and Hall effects raise wall shear at the lower plate. The proposed configuration is especially promising for applications such as directional thermal insulation and energy concentration from the lower to the upper plate, as well as for next-generation power systems where heated working fluids drive turbines for electricity generation. This study offers valuable insights on applications in thermal systems, microfluidics, and energy-efficient designs using smart optimization strategies. |
| Keywords |
| Nanofluids; Parallel plates; Thermal properties; Optimization; MHD |
| Status: Abstract Accepted (Oral Presentation) |