Discretization of the convection term in a three-cell compact stencil has been widely used in
Computational Fluid Dynamics (CFD) of engineering because the second-order …

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This work presents a review of the current state of research in data‐driven turbulence
closure modeling. It offers a perspective on the challenges and open issues but also on the …

Over the last years, supervised learning (SL) has established itself as the state-of-the-art for
data-driven turbulence modeling. In the SL paradigm, models are trained based on a …

In this work, we present a novel hybrid Discontinuous Galerkin scheme with hp-adaptivity
capabilities for the compressible Euler equations. In smooth regions, an efficient and …

We present a general family of subcell limiting strategies to construct robust high-order
accurate nodal discontinuous Galerkin (DG) schemes. The main strategy is to construct …

Reinforcement learning (RL) is highly suitable for devising control strategies in the context of
dynamical systems. A prominent instance of such a dynamical system is the system of …

We present Trixi. jl, a Julia package for adaptive high-order numerical simulations of
hyperbolic partial differential equations. Utilizing Julia's strengths, Trixi. jl is extensible, easy …

The stable and accurate approximation of discontinuities such as shocks on a finite
computational mesh is a challenging task. Detection of shocks or strong discontinuities in …

This study proposes a novel method for developing discretization-consistent closure
schemes for implicitly filtered large eddy simulation (LES). Here, the induced filter kernel …