CFC2023

HORSES3D: a high order discontinuous Galerkin solver for flow simulations, including new developments using machine learning

  • Ferrer, Esteban (Universidad Politécnica de Madrid)

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We present the latest developments of our high order discontinuous Galerkin solver HORSES3D, an open source high-order discontinuous Galerkin framework, capable of solving a variety of flow applications, including compressible flows (with or without shocks), incompressible flows, various RANS and LES turbulence models, particle dynamics, multiphase flows, and aeroacoustics. Recent developments allow us to simulate challenging multiphysics including turbulent flows, multiphase and moving bodies, using local p-adaption and fast multigrid time advancement. In addition, we also present recent work that couples Machine Learning techniques and high order simulations.