Python']Python framework for hp-adaptive discontinuous Galerkin methods for two-phase flow in porous media

被引:9
作者
Dedner, Andreas [1 ]
Kane, Birane [2 ]
Klofkorn, Robert [3 ]
Nolte, Martin [4 ]
机构
[1] Univ Warwick, Math Inst, Zeeman Bldg, Coventry CV4 7AL, W Midlands, England
[2] Univ Stuttgart, Inst Appl Anal & Numer Simulat, Pfaffenwaldring 57, D-70569 Stuttgart, Germany
[3] Int Res Inst Stavanger, POB 8046, N-4068 Stavanger, Norway
[4] Albert Ludwigs Univ Freiburg, Dept Appl Math, Hermann Herder Str 10, D-79104 Freiburg, Germany
关键词
Discontinuous Galerkin; hp-adaptivity; Porous media two-phase flow; IMPES; Dune; !text type='Python']Python[!/text; POSTERIORI ERROR ESTIMATION; LINEARIZATION SCHEME; DISCRETIZATIONS; PARALLEL;
D O I
10.1016/j.apm.2018.10.013
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
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. (C) 2018 Elsevier Inc. All rights reserved.
引用
收藏
页码:179 / 200
页数:22
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