Numerical treatment of 2D-Magneto double-diffusive convection flow of a Maxwell nanofluid: Heat transport case study

In this paper, we develop a model of 2D-double diffusive mixed convection boundary layer flow in magnetohydrodynamics Maxwell fluid induced by an inclined shrinking sheet. The suggested model is formulated by the controlling parameters such as mixed convection, suction, Brownian and thermophoretic diffusion. Besides, the variation of Deborah number also affected the present model. The sheet swiftness, wall heat, and concentration are expressed as an exponential function. The mathematical model is initially expressed as partial differential equations (PDEs), which cover the aspects of momentum, energy, and concentration of Maxwell fluid. Subsequently, these partial differential equations will be transformed into ordinary differential equations (ODEs). The numerical technique, developed in MATLAB software and recognized as bvp4c program is implemented to solve the final ODEs. Since the final numerical results are dual, the numerical method to choose the most reliable solution in the real fluid state is implemented and is known as stability analysis in bvp4c program. Finally, the numerical findings are structured in the arrangement of tables and images. These results showed the characteristics of Maxwell fluid for the various distributions, namely velocity, heat, and concentration outlines, joining the skinfrictional coefficient (SFC), local Nusselt, and Sherwood numbers.

Automated summary

This paper presents a model of 2D-double diffusive mixed convection boundary layer flow in magnetohydrodynamics Maxwell fluid induced by an inclined shrinking sheet. The mathematical model is initially expressed as partial differential equations and then transformed into ordinary differential equations to analyze the momentum, energy, and concentration aspects of Maxwell fluid. The numerical findings, obtained using MATLAB software with bvp4c program, show the characteristics of Maxwell fluid for various distributions.