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The present study focuses on the assessment of the performance of a Finite Volume Method based, particle-resolved simulation approach to predict the flow through a model packed-bed consisting of 21 layers of spheres arranged in the body centred cubic packing. The unsteady flow developing in the freeboard is also considered. Two highly-resolved large eddy simulation were preformed, for two Reynolds numbers, 300 and 500, based on the particle diameter, employing a polyhedral, boundary-conforming mesh. The geometry and the flow conditions are set to reproduce the flow conditions investigated in the experiment carried out by Velten and Z\"ahringer using Particle Image Velocimetry. The numerical results compare favourably with the measurements both inside and above the bed. The effect of differences arising between the physical and numerical configurations are thoroughly discussed alongside the impact of meshing strategy on the accuracy of the predictions., Comment: 14 pages, 15 figures

Nonlinear entropy stability analysis is used to derive entropy stable no-slip wall boundary conditions for the Eulerian model proposed by Sv\"{a}rd (Physica A: Statistical Mechanics and its Applications, 2018). and its spatial discretization based on entropy stable collocated discontinuous Galerkin operators with the summation-by-parts property for unstructured grids. A set of viscous test cases of increasing complexity are simulated using both the Eulerian and the classic compressible Navier-Stokes models. The numerical results obtained with the two models are compared, and differences and similarities are then highlighted., Comment: The datasets generated during and/or analysed during the current study are available in the Zenodo repository, http://doi.org/10.5281/zenodo.5041436

The framework of inner product norm preserving relaxation Runge-Kutta methods (David I. Ketcheson, \emph{Relaxation Runge-Kutta Methods: Conservation and Stability for Inner-Product Norms}, SIAM Journal on Numerical Analysis, 2019) is extended to general convex quantities. Conservation, dissipation, or other solution properties with respect to any convex functional are enforced by the addition of a {\em relaxation parameter} that multiplies the Runge-Kutta update at each step. Moreover, other desirable stability (such as strong stability preservation) and efficiency (such as low storage requirements) properties are preserved. The technique can be applied to both explicit and implicit Runge-Kutta methods and requires only a small modification to existing implementations. The computational cost at each step is the solution of one additional scalar algebraic equation for which a good initial guess is available. The effectiveness of this approach is proved analytically and demonstrated in several numerical examples, including applications to high-order entropy-conservative and entropy-stable semi-discretizations on unstructured grids for the compressible Euler and Navier-Stokes equations.