Numerical study of nanoparticles aggregation on radiative 3D flow of maxwell fluid over a permeable stretching surface with thermal radiation and heat source/sink

The flow of fluid past a stretching sheet under heat and mass transfer analysis is significant because it has numerous applications in engineering and technology, including metal spinning, polymer extrusion, the manufacture of glass fibres, and metal casting etc. The current article investigates the effects of thermal radiation and heat source/sink on 3D nanofluid flow over an elongated surface embedded in a porous medium with nanoparticles aggregation. Further, the significance of variable magnetic field is one of the striking features of the present study. We have considered copper (metallic) and titania (metallic oxide) as nanoparticles and water as base fluid. The effective thermal conductivity of nanofluid is predicted by using a modified Maxwell model. Applying similarity transformations, the governing PDEs are transformed into nonlinear ODEs and solved numerically by MATLAB software using bvp4c and the shooting method. Graphs and tables are plotted to depict the significance of the effective parameters on velocity and temperature profiles as well as skin friction coefficient and Nusselt number. The existence of radiative parameter effects is more advantageous for improving heat transmission. The temperature distribution is enhanced due to presence of nanoparticles aggregation. Thus, the impact of nanoparticles aggregation is supportive theoretical tool in future bioengineering and industrial applications.

Automated summary

This article investigates the effects of thermal radiation and heat source/sink on 3D nanofluid flow over an elongated surface embedded in a porous medium with nanoparticles aggregation. The research findings show that the existence of radiative parameter effects is advantageous for improving heat transmission, and the temperature distribution is enhanced due to the presence of nanoparticles aggregation. These findings provide supportive theoretical tools for future bioengineering and industrial applications.