The role of machine learning in analyzing magnetic field localization and vortex generation in tetra-hybrid nanofluid: A numerical study

Modern Physics Letters B, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 3, 2025

This research distinguishes itself by integrating machine learning algorithms to assess the impact of confined magnetic fields on vortex dynamics in hybrid nanofluid flow, through inclusion both vertical and horizontal field strips. Specifically, study focuses a cavity with an aspect ratio 1:5, where bottom lid moves horizontally from left right drive flow. We have applied limited consisting vertical, The authors developed MATLAB codes implement algorithm for solving governing equations flow heat transfer. is based Stream-Vorticity formulation uses finite difference method. can examine how several parameters, such as strength (0–300), nanoparticle volume fraction (0–20%), Reynolds number (Re) (1–50), characteristics nanofluids terms thermal properties. results demonstrate that influence stress distribution pattern temperature distribution. Further, presence also affects Moreover, it has been determined Nusselt (Nu) experiences 60% increase due field, while there remarkable rise attributed Re. Similarly, significant changes are observed skin friction under parameters. These findings carry implications designing operating devices.

Language: Английский

Artificial neural network-based forecasting of air temperature reduction in a tube bank under electric field

Case Studies in Thermal Engineering, Journal Year: 2025, Volume and Issue: 70, P. 106086 - 106086

Published: April 11, 2025

Language: Английский