Heat transfer and entropy generation analysis in the buoyancy-driven flow of Fe3O4-MWCNT/water hybrid nanofluid within a square enclosure in the presence of fins using machine learning

Abstract

Thermal energy storage systems, heat exchangers, and electronic devices often encounter significant challenges, such as inadequate heat transport and excessive overheating. To mitigate these issues, enhancing convective heat transfer through the use of nanofluids offers a promising solution. Additionally, incorporating fins to augment surface area provides a simple and cost-effective method to significantly improve thermal performance. This study, motivated by the applications of fins and nanofluids, undertakes a theoretical investigation to evaluate heat transfer and entropy generation within a buoyancy-driven hybrid nanofluid inside a partially heated square enclosure. The focus is on the effects of different fin orientations and thermal radiation. The study examines three distinct fin orientations: horizontal, slanted toward the bottom wall, and slanted toward the top wall at the heated wall, with partial heating applied to the left wall. To solve the dimensionless, nonlinear, coupled two-dimensional fluid transport equations, an in-house MATLAB code using the finite difference method is employed. Furthermore, machine learning techniques are used to analyze the parameter variations resulting from different fin orientations to optimize heat transfer. A comprehensive parametric analysis evaluates the impact of key parameters such as thermal radiation, Hartmann number, Rayleigh number, and Darcy number on fluid transport. It is noted that, in case 1, the heat transfer rate rises by 73.07% when the Rayleigh number reaches . Meanwhile, the increases in cases 2 and 3 are 72.99% and 67.55%, respectively. The machine learning analysis indicates that the effect of thermal buoyancy on the heat transfer rate decreases from 43.5 to 38.9% when fin orientations are altered, while the influence of the heat source/sink and thermal radiation increases from 16.5 to 18.8% and from 20.8 to 23.1%, respectively. Horizontal fins demonstrate the highest heat transfer rate, showing increases of 31.98% and 27.19% compared to other fin orientations. However, in terms of minimizing entropy production, the configuration with fins slanted toward the top wall (Case 3) exhibits lower entropy production compared to the horizontal and bottom-slanted fin cases.