Hydromagnetic flow of magnetite-water nanofluid utilizing adapted Buongiorno model

The hydromagnetic flow of magnetite-water nanofluid due to a rotating stretchable disk has been numerically assessed. The nanofluid flow has been modeled utilizing the adapted Buongiorno model that considers the volume fraction-dependent effective nanofluid properties and the major slip mechanisms. In addition, experimentally gleaned functions of effective dynamic viscosity and effective thermal conductivity are deployed. The modeled equations are transformed into a first-order ODEs scheme employing Von Karman's similarity conversions and then resolved via the Runge-Kutta algorithm through the shooting technique. The impact of pertinent terms over the physical quantities, nanoliquid temperature and nanoliquid concentration is explained with the support of graphs. Results show that rising volume fraction of magnetite nanoparticles (NPs) and magnetic field term enhance the drag force. Mass transport rate is demoted with augmenting values of magnetic field parameter whereas is promoted with increase in Schmidt number. Further, it is detected that the changes in stretching strength parameter are directly proportional to Nusselt number and inversely proportional to the thermal field. The findings of this numerical analysis have applications in spin coating, rotating disk reactors, storage devices for computers, food processing, and rotating heat exchangers.

Automated summary

This study numerically evaluates the hydromagnetic flow of a magnetite-water nanofluid induced by a rotating stretchable disk. The Buongiorno model is used to model the nanofluid flow, considering the volume fraction-dependent effective properties and slip mechanisms. Experimentally obtained functions of effective viscosity and thermal conductivity are also employed. The transformed first-order ODEs are solved using the Runge-Kutta algorithm and the shooting technique. The impact of relevant terms on the nanoliquid temperature and concentration is explained using graphs. The findings have important applications in various fields such as spin coating, rotating disk reactors, storage devices, food processing, and heat exchangers.