[HTML][HTML] Python framework for hp-adaptive discontinuous Galerkin methods for two-phase flow in porous media
Applied Mathematical Modelling, 2019•Elsevier
In this paper we present a framework for solving two-phase flow problems in porous media.
The discretization is based on a Discontinuous Galerkin method and includes local grid
adaptivity and local choice of polynomial degree. The method is implemented using the new
Python frontend Dune-FemPy to the open source framework Dune. The code used for the
simulations is made available as Jupyter notebook and can be used through a Docker
container. We present a number of time stepping approaches ranging from a classical …
The discretization is based on a Discontinuous Galerkin method and includes local grid
adaptivity and local choice of polynomial degree. The method is implemented using the new
Python frontend Dune-FemPy to the open source framework Dune. The code used for the
simulations is made available as Jupyter notebook and can be used through a Docker
container. We present a number of time stepping approaches ranging from a classical …
Abstract
In this paper we present a framework for solving two-phase flow problems in porous media. The discretization is based on a Discontinuous Galerkin method and includes local grid adaptivity and local choice of polynomial degree. The method is implemented using the new Python frontend Dune-FemPy to the open source framework Dune. The code used for the simulations is made available as Jupyter notebook and can be used through a Docker container. We present a number of time stepping approaches ranging from a classical IMPES method to a fully coupled implicit scheme. The implementation of the discretization is very flexible allowing to test different formulations of the two-phase flow model and adaptation strategies.
Elsevier