A novel prediction model for the analysis of Ree-Eyring fluid with Hall current in Darcy-Forchheimer porous media based on machine learning technique
Year: 2025
Type: article
Abstract: Investigating hypothesized phenomena with a Ree-Eyring hybrid fluid over a Von-Karman flow with velocity and thermal slips is the main objective of the present investigation. For the purpose of this phase of study, a mid-rich scheme integrating ANOVA-based ANFIS-PSO is designed in a Darcy-Forchheimer porous medium with a heat source/sink, non-linear thermal radiation and Hall current. To make sure that the appropriate self-similarity variables have been used to convert a non-linear PDE set of equations into an ODE. With a few noteworthy exceptions, the model's study findings are mostly in line with those of earlier studies that were included in the dataset that was used to train the ANOVA-based ANFIS-PSO model. The findings for many profiles are presented in an aesthetically pleasing manner due to the influence of active elements. It demonstrates that the temperature profile compresses and the velocity increases suddenly when the material fluid parameter rises, resulting in a scenario that is in opposition to the increasing slippage condition inputs. When the Darcy-Forchheimer tilts on the azimuthal profile, declination also manifests. Additionally, the most important factors identified by ANOVA were used to examine the approximate solutions based on the training of the constructed model. The ANOVA-based ANFIS-PSO demonstrated extraordinarily high accuracy in terms of skin friction on f (97.61%), skin friction on g (97.01%) and Nusselt number (96.46%). The nanoparticles used in this study are considered suitable for biological applications such as magnetic drug administration, radio-recurrence hyperthermia, biomedical drug delivery, and magnetic reverberation imaging due to their longer lifespan.
Source: Propulsion and Power Research
Language: English
Subfield: Fluid Flow and Transfer Processes
Field: Chemical Engineering
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $1,000
OpenAlex ID: W4414976641