No abstract

The present work is focused on improving the efficiency of a computational fluid dynamics (CFD) – discrete element method (DEM) solver allowing for computations with non-spherical solids. In general, the combination of CFD and DEM allows for simulations of freely moving solid particles within a computational domain containing fluid. The standard approach of CFD-DEM solvers is to approximate solid bodies by spheres, the geometry of which can be fully defined via its radius and center position. Consequently, the standard DEM contact models are based on an overlap depth between particles, which can be easily evaluated for a sphere-sphere contact. However, for a contact between two non-spherical particles, the overlap depth cannot be used and has to be replaced by the more general overlap volume. The precision of the overlap volume computation is (i) crucial for the correct evaluation of contact forces, and (ii) directly dependent on the computational mesh resolution. Still, the contact volume evaluation in DEM for arbitrarily shaped bodies is usually by at least one order of magnitude more demanding on the mesh resolution than the CFD. In order to improve the computational efficiency of our CFD-DEM solver, we introduce the concept of an OCTREEbased virtual mesh, in which the DEM spatial discretization is adaptively refined while the CFD mesh remains unchanged.

Particle-laden flow is prevalent both in nature and in industry. Its appearance ranges from the transport of riverbed sediments towards the magma flow; from the deposition of catalytic material inside particulate matter filters in automotive exhaust gas aftertreatment towards the slurry transport in dredging operations. In this contribution, we focus on the particle-resolved direct numerical simulation (PR-DNS) of the particle-laden flow. Such a simulation combines the standard Eulerian approach to computational fluid dynamics (CFD) with inclusion of particles via a variant of the immersed boundary method (IBM) and tracking of the particles movement using a discrete element method (DEM). Provided the used DEM allows for collisions of arbitrarily shaped particles, PR-DNS is based (almost) entirely on first principles, and as such it is a truly high-fidelity model. The downside of PR-DNS is its immense computational cost. In this work, we focus on three possibilities of alleviating the computational cost of PR-DNS: (i) replacing PR-DNS by PR-LES or PR-RANS, while the latter requires combining IBM with wall functions; (ii) improving efficiency of DEM contact solution via adaptively refined virtual mesh; and (iii) developing a method of model order reduction specifically tailored to PR-DNS of particle-laden flows.