A mathematical simulation of unsteady MHD Casson nanofluid flow subject to the influence of chemical reaction over a stretching surface: Buongiorno's model

In this study, unsteady boundary layer flow with Casson nanofluid within the sight of chemical reaction toward a stretching sheet has been analyzed mathematically. The fundamental motivation behind the present examination is to research the influence of different fluid parameters, in particular, Casson fluid beta (0.2 <= beta <= 0.4), thermophoresis Nt (0.5 <= Nt <= 1.5), magnetohydrodynamic M (3.0 <= M <= 5.0), Brownian movement Nb (0.5 <= Nb <= 2.0), Prandtl numberty, unsteadiness parameter A (0.10 <= A <= 0.25), chemical reaction parameter. (0.1 <= gamma <= 0.8), and Schmidt number Sc (1.0 <= Sc <= 3.0) on nanoparticle concentration, temperature, and velocity distribution. The shooting procedure has been adopted to solve transformed equations with the assistance of Runge-Kutta Fehlberg technique. The impact of different controlling fluid parameters on flow, heat, and mass transportation are depicted in tabular form and are shown graphically. Additionally, values of skin friction coefficient, Nusselt number, and Sherwood number are depicted via tables. Present consequences of the investigation for Nusselt number are related with existing results in writing by taking Nb = 0 and Nt = 0 where results are finding by utilization of MATLAB programming. Findings of current research help in controlling the rate of heat and mass aspects to make the desired quality of final product aiding manufacturing companies and industrial areas.

Automated summary

This study focuses on the mathematical analysis of unsteady boundary layer flow with Casson nanofluid and chemical reaction on a stretching sheet. Various fluid parameters were investigated to understand their influence on nanoparticle concentration, temperature, and velocity distribution, providing insights for controlling heat and mass aspects in manufacturing processes. The results can aid manufacturing companies and industrial areas in optimizing their production processes.