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A Python Framework for Solving Advection-Diffusion Problems

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Finite Volumes for Complex Applications IX - Methods, Theoretical Aspects, Examples (FVCA 2020)

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Abstract

This paper discusses a Python interface for the recently published Dune-Fem-DG module which provides highly efficient implementations of the Discontinuous Galerkin (DG) method for solving a wide range of non linear partial differential equations (PDE). Although the C++ interfaces of Dune-Fem-DG are highly flexible and customizable, a solid knowledge of C++ is necessary to make use of this powerful tool. With this work easier user interfaces based on Python and the Unified Form Language are provided to open Dune-Fem-DG for a broader audience. The Python interfaces are demonstrated for both parabolic and first order hyperbolic PDEs.

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Notes

  1. 1.

    https://gitlab.dune-project.org/dune-fem/dune-fem-dg.git.

References

  1. Alnæs, M.S., Logg, A., Ølgaard, K.B., Rognes, M.E., Wells, G.N.: Unified Form Language: A domain-specific language for weak formulations of partial differential equations. CoRR abs/1211.4047 (2012). http://arxiv.org/abs/1211.4047

  2. Bangerth, W., Hartmann, R., Kanschat, G.: deal.II—a general purpose object oriented finite element library. ACM Trans. Math. Softw. 33(4), 24/1–24/27 (2007). http://dealii.org/

  3. Bastian, P., Blatt, M., Dedner, A., Engwer, C., Klöfkorn, R., Kornhuber, R., Ohlberger, M., Sander, O.: A generic grid interface for parallel and adaptive scientific computing. Part II: implementation and tests in DUNE. Computing 82(2–3), 121–138 (2008)

    Google Scholar 

  4. Brdar, S., Baldauf, M., Dedner, A., Klöfkorn, R.: Comparison of dynamical cores for NWP models: comparison of COSMO and DUNE. Theor. Comput. Fluid Dyn. 27(3–4), 453–472 (2013). https://doi.org/10.1007/s00162-012-0264-z

  5. Brdar, S., Dedner, A., Klöfkorn, R.: Compact and stable discontinuous Galerkin methods for convection-diffusion problems. SIAM J. Sci. Comput. 34(1), 263–282 (2012)

    Article  MathSciNet  Google Scholar 

  6. Dedner, A., Girke, S., Klöfkorn, R., Malkmus, T.: The DUNE-FEM-DG module. ANS 5(1), 21–62 (2017). https://doi.org/10.11588/ans.2017.1.28602

  7. Dedner, A., Kane, B., Klöfkorn, R., Nolte, M.: Python framework for hp-adaptive discontinuous Galerkin methods for two-phase flow in porous media. AMM 67, 179–200 (2019)

    MathSciNet  MATH  Google Scholar 

  8. Dedner, A., Klöfkorn, R.: A generic stabilization approach for higher order discontinuous Galerkin methods for convection dominated problems. J. Sci. Comput. 47(3), 365–388 (2011)

    Google Scholar 

  9. Dedner, A., Klöfkorn, R.: The Dune-Fempy module (2019). https://dune-project.org/sphinx/content/sphinx/dune-fem/

  10. Dedner, A., Klöfkorn, R., Nolte, M., Ohlberger, M.: A generic interface for parallel and adaptive scientific computing: abstraction principles and the DUNE-FEM module. Computing 90(3–4), 165–196 (2010)

    Article  MathSciNet  Google Scholar 

  11. Dedner, A., Nolte, M.: The Dune-Python module. CoRR abs/1807.05252 (2018). http://arxiv.org/abs/1807.05252

  12. Karniadakis, G., Sherwin, S.: Spectral/HP Element Methods for Computational Fluid Dynamics. Oxford University Press, Oxford (2005). http://www.nektar.info/

  13. The Feel++ Consortium: The Feel++ book (2015). https://www.gitbook.com/book/feelpp/feelpp-book

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Acknowledgements

Robert Klöfkorn acknowledges the support of the Research Council of Norway through the INTPART project INSPIRE (274883).

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Correspondence to Andreas Dedner .

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Dedner, A., Klöfkorn, R. (2020). A Python Framework for Solving Advection-Diffusion Problems. In: Klöfkorn, R., Keilegavlen, E., Radu, F.A., Fuhrmann, J. (eds) Finite Volumes for Complex Applications IX - Methods, Theoretical Aspects, Examples. FVCA 2020. Springer Proceedings in Mathematics & Statistics, vol 323. Springer, Cham. https://doi.org/10.1007/978-3-030-43651-3_66

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