A Scalable Multiphysics Algorithm for Massively Parallel Direct Numerical Simulations of Electrophoresis
arXiv:1708.08741 · doi:10.1016/j.jocs.2018.05.011
Abstract
In this article we introduce a novel coupled algorithm for massively parallel direct numerical simulations of electrophoresis in microfluidic flows. This multiphysics algorithm employs an Eulerian description of fluid and ions, combined with a Lagrangian representation of moving charged particles. The fixed grid facilitates efficient solvers and the employed lattice Boltzmann method can efficiently handle complex geometries. Validation experiments with more than time steps are presented, together with scaling experiments with over particles and grid cells for both hydrodynamics and electric potential. We achieve excellent performance and scaling on up to cores of a current supercomputer.
Accepted manuscript of publication in Journal of Computational Science (Elsevier)
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