The article describes parallel multiphysics simulations of charged particles in microfluidic flows with the waLBerla framework. To this end, three physical effects are coupled: rigid body dynamics, fluid flow modelled by a lattice Boltzmann algorithm, and electric potentials represented by a finite volume discretisation. For solving the finite volume discretisation for the electrostatic forces, a cell-centered multigrid algorithm is developed that conforms to the lattice Boltzmann meshes and the parallel communication structure of waLBerla. The new functionality is validated with suitable benchmark scenarios. Additionally, the parallel scaling and the numerical efficiency of the algorithms are analysed on an advanced supercomputer.

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a b s t r a c tThe pe physics engine is validated through the simulation of a liquid crystal model system consisting of hard spherocylinders. For this purpose we evaluate several characteristic parameters of this system, namely the nematic order parameter, the pressure, and the Frank elastic constants. We compare these to the values reported in literature and find a very good agreement, which demonstrates that the pe physics engine can accurately treat such densely packed particle systems. Simultaneously we are able to examine the influence of finite size effects, especially on the evaluation of the Frank elastic constants, as we are far less restricted in system size than earlier simulations.

Suspensions with fiber-like particles in the low Reynolds number regime are modeled by two different approaches that both use a Lagrangian representation of individual particles. The first method is the well-established formulation based on Stokes flow that is formulated as integral equations. It uses a slender body approximation for the fibers to represent the interaction between them directly without explicitly computing the flow field. The second is a new technique using the 3D lattice Boltzmann method on parallel supercomputers. Here the flow computation is coupled to a computational model of the dynamics of rigid bodies using fluid-structure interaction techniques. Both methods can be applied to simulate fibers in fluid flow. They are carefully validated and compared against each other, exposing systematically their strengths and weaknesses regarding their accuracy, the computational cost, and possible model extensions.