Bödewadt and von Kármán slip ows involving non-Newtonian nano uids: Validation using machine learning

Abstract

Bödewadt and von Kármán ows are of paramount importance in uid dynamics of rotating sys tems such as turbomachinery and geophysical ows. Moreover, nano uid's enhanced heat transfer properties can improve cooling e ciency in applications involving turbines and electronic systems. The focus of this thesis is twofold. Firstly, to investigate the Bödewadt boundary layer ow of a Reiner-Rivlin uid containing nanoparticles over a stationary porous disk under slip conditions. Secondly, it deals with von Kármán ow of Je rey nano uid over a rotating permeable disk with partial-slip conditions. Understanding the behavior of non-Newtonian uids under slip conditions is essential for various practical applications, including polymer processing, biomedical engineering and geological uid dynamics. The two-phase Buongiorno model is employed in both the stud ies, incorporating temperature-dependent di usion coe cients for enhanced accuracy which leads to non-linear Robin-type condition. To facilitate numerical simulations, the transport equations are converted into an ordinary di erential system comprising four unknowns. In the present work, a highly reliable Keller-Box methodology is adopted which agrees very well with the MATLAB built in program bvp4c. The computed 2-D and 3-D streamlines vividly capture the ow scenario with non-Newtonian nano uid. The principal aim is investigating the impact of non-Newtonian behavior and slip on the ow pattern, while also examining the behavior of temperature/concentration eld for nanoparticle working uids. Furthermore, we develop linear and quadratic regression models designed to precisely predict both the surface drag and disk cooling rate of the skin friction coe cients and Nusselt number from the numerical simulations, e ectively illustrating the contributions of Brownian di usion and thermophoresis to the proposed model. Present ndings reveal that the slip condition contributes to boost the surface cooling rate, which holds signi cant implications for engineering applications. Least Absolute Shrinkage and Selection Operator (LASSO) is employed to validate the computational results of skin friction coe cients and Nusselt number.