Mixed convection flow of Magnetohydrodynamic Prandtl nanofluid containing gyrotactic microorganisms: Multi-layer neural network model

Document Type : Article

Authors

1 Center for Computational Modeling, Chennai Institute of Technology, Chennai-600069, India

2 Center for Computational Modeling, Chennai Institute of Technology, Chennai-600069, India.

3 Department of Mathematics, S.A.S., Vellore Institute of Technology, Vellore-632014, India.

4 Division of Mathematics, SAS, Vellore Institute of Technology, Chennai-600127. India.

10.24200/sci.2024.62057.7624

Abstract

This study investigates the impact of activation energy on the flow behaviour of a Prandtl nanofluid that includes gyrotactic microorganisms over a stretching cylinder. This study's uniqueness is in examining Prandtl nanofluid using a non-Fourier heat and mass flow model incorporating thermal radiation. The fluid flow phenomena are defined by nonlinear differential equations incorporating two or more independent variables. The governing equations can be managed using an appropriate numerical technique such as bvp4c with the MATLAB solver. Based on the current investigation, the velocity profile reduces as the magnetic field values increase, while it increases concerning the curvature parameter for $\alpha =0$ and $\alpha ={\pi }/{2}$. The temperature $\theta \left( \eta \right)$increases as radiation values increase but decreases when the thermal relaxation parameter rises. Increased concentration, relaxation, and activation energy values lead to a higher local Sherwood number. The proposed model presents significant advantages with the potential to revolutionize a wide range of applications, including biodiesel production, hydrogen fuel, oil storage techniques, geothermal energy manufacturing, base liquid mechanics, oil emulsification processes, food production, sewage systems, and serving as a substantial source of renewable energy.

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