Radiative effects on 2D unsteady MHD Al₂O₃‐water nanofluid flow between squeezing plates: A comparative study using AGM and HPM in Python

Abstract

This research uses Python programming to explore the influence of magnetic field strength on a two‐dimensional squeezing nanofluid flow confined between two parallel plates. The primary objective is to examine an aluminum oxide nanofluid's velocity and heat transfer characteristics which are governed by dimensionless parameters such as the Prandtl number and friction coefficient. The non‐dimensionalized differential equations are solved employing two analytical techniques: the Akbari‐Ganji Method and the Homotopy Perturbation Method, both implemented through Python programming. Using Python programming to solve these equations represents a novel approach that offers accurate and efficient results. The study's findings reveal that as the Prandtl number increases, the temperature and thermal properties of the nanofluid flow also increase while the concentration decreases. Additionally, the Nusselt number experiences a decline. The implementation of Python programming in this research showcases the versatility of the language in solving complex mathematical problems, particularly in fluid dynamics. Python's ability to provide accurate solutions efficiently enhances its potential for further applications and advancements in this area.