Aplication of Genetic Algorithms to an Inverse Field Problem in Magnetic Fluid Dynamics

Abstract

The purpose of the present work is to study whether genetic algorithms can solve an inverse field problem in magnetic fluid dynamics (MFD) efficiently.
We have investigated how the interface between two fluids of different conductivity in a highly simplified model of an aluminum electrolysis cell can be reconstructed by means of external magnetic field measurements. The knowledge of the interface deformation can be used to prevent undesired instabilities in aluminum reduction cells [1].