Nonlinear entropy stability analysis is used to derive entropy stable no-slip wall boundary conditions for the Eulerian model proposed by Svärd (Phys A Stat Mech Appl 506:350–375, 2018). The spatial discretization is 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 similarities and differences are then highlighted. However, the differences are very small and probably smaller than what the current experimental technology allows to measure.

Nonlinear (entropy) stability analysis is used to derive entropy–stable no–slip wall boundary conditions at the continuous and semi–discrete levels for the Eulerian model proposed by Svärd in 2018 (Physica A: Statistical Mechanics and its Applications, 2018). The spatial discretization is based on discontinuous Galerkin summation-by-parts operators of any order for unstructured grids. We provide a set of two–dimensional numerical results for laminar and turbulent flows simulated with both the Eulerian and classical Navier–Stokes models. These results are computed with a high-performance hp–entropy–stable solver, that also features explicit and implicit entropy–stable time integration schemes.

The framework of inner product norm preserving relaxation Runge–Kutta methods [D. I. Ketcheson, SIAM J. Numer. Anal., 57 (2019), pp. 2850–2870] 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 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 semidiscretizations on unstructured grids for the compressible Euler and Navier–Stokes equations.