Using genetic algorithms to characterize ferrofluid topographies in externally applied magnetic fields

Both ferrofluidics and genetic algorithms are relatively new fields. Due to complex physical interactions, ferrofluidic topographies and assemblies have only been solved using finite time step, Lattice Boltzmann, and finite-element methods in very simple magnetic field configurations. In this paper, we show that it is possible (and highly advantageous) to employ genetic algorithms to solve for the fluid topographies, which can be extended to include more complex magnetic fields.