Moving charged particles in lattice Boltzmann-based electrokinetics

The motion of ionic solutes and charged particles under the influence of an electric field and the ensuing hydrodynamic flow of the underlying solvent is ubiquitous in aqueous colloidal suspensions. The physics of such systems is described by a coupled set of differential equations, along with boundary conditions, collectively referred to as the electrokinetic equations. Capuani et al. [J. Chem. Phys. 121, 973 (2004)] introduced a lattice-based method for solving this system of equations, which builds upon the lattice Boltzmann algorithm for the simulation of hydrodynamic flow and exploits computational locality. However, thus far, a description of how to incorporate moving boundary conditions into the Capuani scheme has been lacking. Moving boundary conditions are needed to simulate multiple arbitrarily-moving colloids. In this paper, we detail how to introduce such a particle coupling scheme, based on an analogue to the moving boundary method for the pure LB solver. The key ingredients in our method are mass and charge conservation for the solute species and a partial-volume smoothing of the solute fluxes to minimize discretization artifacts. We demonstrate our algorithm's effectiveness by simulating the electrophoresis of charged spheres in an external field; for a single sphere we compare to the equivalent electro-osmotic (co-moving) problem. Our method's efficiency and ease of implementation should prove beneficial to future simulations of the dynamics in a wide range of complex nanoscopic and colloidal systems that was previously inaccessible to lattice-based continuum algorithms

A scalable and extensible checkpointing scheme for massively parallel simulations

Realistic simulations in engineering or in the materials sciences can consume enormous computing resources and thus require the use of massively parallel supercomputers. The probability of a failure increases both with the runtime and with the number of system components. For future exascale systems, it is therefore considered critical that strategies are developed to make software resilient against failures. In this article, we present a scalable, distributed, diskless, and resilient checkpointing scheme that can create and recover snapshots of a partitioned simulation domain. We demonstrate the efficiency and scalability of the checkpoint strategy for simulations with up to 40 billion computational cells executing on more than 400 billion floating point values. A checkpoint creation is shown to require only a few seconds and the new checkpointing scheme scales almost perfectly up to more than 260, 000 (218) processes. To recover from a diskless checkpoint during runtime, we realize the recovery algorithms using ULFM MPI. The checkpointing mechanism is fully integrated in a state-of-the-art high-performance multi-physics simulation framework. We demonstrate the efficiency and robustness of the method with a realistic phase-field simulation originating in the material sciences and with a lattice Boltzmann method implementation

Numerical simulation of pore fluid flow and fine sediment infiltration into the riverbed

The riverbed embodies an important ecotone for many organisms. It is also an interface between groundwater and surface water, two systems that feature numerous distinctions. The riverbed therefore exhibits many physical and biochemical gradients e.g. flow velocity, temperature, oxygen or nutrient concentration. If the riverbed however becomes clogged through input and deposition of fine sediments, its porosity and permeability decrease leads to reduced interconnectivity between both neighboring systems and eventually reduction of the suitability of the riverbed as a habitat for organisms. Reasons for fine sediment infiltration are high inputs of fine sediments from surface runoff or rainwater retention basins and continuous unnatural low flow velocities typically found in regulated rivers. The objective of our current research is to develop a model for the determination of the factors controlling fine sediment infiltration into the riverbed and their quantitative impact on fine sediment infiltration rates, reduction of riverbed porosity, and permeability. To do so, we use several numerical modeling techniques including the popular lattice Boltzmann method