Scientific Reports (Dec 2022)
Statistical modeling for Ree-Eyring nanofluid flow in a conical gap between porous rotating surfaces with entropy generation and Hall Effect
Abstract
Abstract The attention of the current study is on the flow of a non-Newtonian incompressible Cu-Water nanofluid flow. The water is assumed as base fluid, while copper is used as nanoparticles. The Ree-Eyring prototype describes the performance of non-Newtonian nanofluids. There is a conical gap that nanofluid flow fills among the plane disc and the cone's stationary/rotational porous faces. Additionally taken into account are heat, mass transfer, and entropy production. The given mathematical model is unique due to the effects of a vertically applied Hall Effect, Ohmic dissipation, viscous dissipation, and chemical processes. The Ree-Eyring fluid constitutive equations, as well as the cylindrical coordinates, have been interpreted. The model equations for motion, heat, and concentration can be changed in the collection of non-linear ODEs by employing the applicable similarity transform. This method allocates a couple of nonlinear ODEs relating to velocity, temperature, and concentration distributions. The shooting scheme (bvp4c technique) is used to solve these equations numerically. Statistical analysis like probable error, correlation, and regression are exploited. The probable error is estimated to compute the consistency of the calculated correlation features. The theoretical data is analyzed in both graphical and tabular forms. The modeled parameters like, magnetic number, porosity parameter, Eckert number, chemical reaction parameter, Brownian motion parameter, thermophoretic parameter, Schmidt number, Hall recent parameter, radiation parameter, and volume fraction are discussed in details graphically and theoretically. The outcomes indicate that the velocity components are greater for greater values of nanoparticle volume fraction and Weissenberg number, whereas for enormous values of magnetic and porosity parameters, the velocity components fall.