Python based simulation of heat transfer in stagnation point flow of Maxwell nanofluid over a permeable rotating surface

This study analyzes Maxwell nanofluid stagnation point flow over a rotating permeable surface using Python based Akbari-Ganji’s Method (AGM). The problem is important due to its relevance in rotating thermal devices, nanofluid cooling, biomedical flows, and enhanced oil recovery systems. When steady angular motion occurs about the central line, a circular arc is generated at every point on the disk. Measurements of tangential stress along the boundary separating a spinning plate from the surrounding fluid reveal how much power must be supplied to counter resistive effects and maintain rotation, as well as how changes in the local movement patterns play a role in governing the rate at which energy is conveyed. The novelty lies in applying modified AGM formulation to a rotating disk Maxwell nanofluid configuration. Initially, transform the partial differential equations into ordinary differential equations using an appropriate similarity transformation. Following the transformations, Python was utilized to apply AGM and the Finite Element Method (FEM) for visualization. The primary objective of this study is to develop an efficient framework for analyzing Maxwell nanofluid stagnation point flow over permeable rotating surface using Python based AGM. The obtained solutions show excellent agreement with FEM results while requiring lower computational effort. The results show that higher Deborah numbers weaken radial and azimuthal velocities. Brownian motion and thermophoresis increase temperature but reduce concentration. The results of this research will benefit multiple sectors, such as architectural design frameworks, transportation logistics, medical applications, and enhanced oil recovery techniques involving nanofluids.