A computational tool for the estimation of the optimum gradient magnetic field for the magnetic driving of the spherical particles in the process of cleaning water

Abstract

The use of magnetic nanoparticles for cleaning potable water from heavy metals is a novel technique. Suitable magnetic fields are imposed in order to separate magnetic nanoparticles from the water main stream. A numerical methodology that combines computational fluid dynamics and evolution strategy techniques for the optimum magnetic navigation of particles in water is presented here. The method is based on an iterative algorithm that aims to minimize the deviation of particles from a desired trajectory by continuously adjusting a gradient magnetic field in an appropriate way. For the evaluation of the performance of this computational method, several series of simulations are performed with different number of adjustments of the magnetic field gradient. Using the above-mentioned method, it is found that the increase of the number of adjustments of the magnetic field gradient results in the decrease of the particles’ deviation from the desired trajectory. Finally, the percentage of particles that are following the desired trajectory increases as the concentration of the simulated particles increases.