Intelligent backpropagated neural networks application on Darcy-Forchheimer ferrofluid slip flow system

Ferroliquids are made of small magnetic fragments of iron, nanoscale ferrimagnetic particles suspended on a base liquid (usually organic solvent/water) and are called colloidal liquids, they contain a magnetic suspension. Ferrofluid is used in rotating seals, loudspeakers, computer hard drives and MRI machines. It is hoped that this study will inspire specialists to investigate new applications for this appealing material. As a result, with such efficacy in mind, mathematical modelling for the second order velocity slip flow of Darcy-Forchheimer ferrofluid model (DF-FFM) by employing the intelligent computing paradigm via Artificial Levenberg Marquardt Method with backpropagated neural networks (ALMM-BNN). The PDEs are changed into ODEs by applying appropriate conversions. The reference dataset is obtained by using HAM with the variations of pertinent non-dimensional parameters. Samples of data are collected for training, testing, validation and used to evaluate the approximated solutions of proposed model & comparison with reference results. The performance analysis of DF-FFM is validated through regression analysis, error histogram studies and MSE results. The tabular description for the stability and convergence of the presented fluid flow system based on mean square error is also provided.

Automated summary

Ferroliquids are colloidal liquids made of small magnetic fragments of iron suspended in a base liquid, used in various devices. Research aims to inspire specialists to explore new applications through mathematical modeling and intelligent computing. The performance analysis of DF-FFM is validated through regression analysis, error histogram studies and MSE results.