DUNE, the Distributed and Unified Numerics Environment is a modular toolbox for solving partial differential equations (PDEs) with grid-based methods. It supports the easy implementation of methods like Finite Elements (FE), Finite Volumes (FV), and also Finite Differences (FD). DUNE is free software licensed under the GPL (version 2) with a so called ”runtime exception” (see license). This licence is similar to the one under which the libstdc++ libraries are distributed. Thus it is possible to use DUNE even in proprietary software. The underlying idea of DUNE is to create slim interfaces allowing an efficient use of legacy and/or new libraries. Modern C++ programming techniques enable very different implementations of the same concept (i.e. grids, solvers, ...) using a common interface at a very low overhead. Thus DUNE ensures efficiency in scientific computations and supports high-performance computing applications.

References in zbMATH (referenced in 129 articles , 2 standard articles )

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  1. Bach, Annika; Sommer, Liesel: A (\Gamma)-convergence result for fluid-filled fracture propagation (2020)
  2. Chamakuri, Nagaiah; Kügler, Philipp: A coupled monodomain solver with optimal memory usage for the simulation of cardiac wave propagation (2020)
  3. Dahmen, Wolfgang; Gruber, Felix; Mula, Olga: An adaptive nested source term iteration for radiative transfer equations (2020)
  4. Moxey, David; Amici, Roman; Kirby, Mike: Efficient matrix-free high-order finite element evaluation for simplicial elements (2020)
  5. Ohlberger, Mario; Schweizer, Ben; Urban, Maik; Verfürth, Barbara: Mathematical analysis of transmission properties of electromagnetic meta-materials (2020)
  6. Varma, V. Dhanya; Chamakuri, Nagaiah; Nadupuri, Suresh Kumar: Discontinuous Galerkin solution of the convection-diffusion-reaction equations in fluidized beds (2020)
  7. Andreas Nüßing, Maria Carla Piastra, Sophie Schrader, Tuuli Miinalainen, Heinrich Brinck, Carsten H. Wolters, Christian Engwer: duneuro - A software toolbox for forward modeling in neuroscience (2019) arXiv
  8. Chamakuri, Nagaiah: Parallel and space-time adaptivity for the numerical simulation of cardiac action potentials (2019)
  9. Detommaso, Gianluca; Dodwell, Tim; Scheichl, Rob: Continuous level Monte Carlo and sample-adaptive model hierarchies (2019)
  10. Engwer, Christian; Henning, Patrick; Målqvist, Axel; Peterseim, Daniel: Efficient implementation of the localized orthogonal decomposition method (2019)
  11. Grohs, Philipp; Hardering, Hanne; Sander, Oliver; Sprecher, Markus: Projection-based finite elements for nonlinear function spaces (2019)
  12. Schmidt, Patrick; Steeb, Holger: Numerical aspects of hydro-mechanical coupling of fluid-filled fractures using hybrid-dimensional element formulations and non-conformal meshes (2019)
  13. Teixeira Parente, Mario; Mattis, Steven; Gupta, Shubhangi; Deusner, Christian; Wohlmuth, Barbara: Efficient parameter estimation for a methane hydrate model with active subspaces (2019)
  14. Verfürth, Barbara: Heterogeneous multiscale method for the Maxwell equations with high contrast (2019)
  15. Youett, Jonathan; Sander, Oliver; Kornhuber, Ralf: A globally convergent filter-trust-region method for large deformation contact problems (2019)
  16. Cicuttin, M.; Di Pietro, D. A.; Ern, A.: Implementation of discontinuous skeletal methods on arbitrary-dimensional, polytopal meshes using generic programming (2018)
  17. Djurdjevac, Ana; Elliott, Charles M.; Kornhuber, Ralf; Ranner, Thomas: Evolving surface finite element methods for random advection-diffusion equations (2018)
  18. Hanowski, Katja K.; Sander, Oliver: The hydromechanical equilibrium state of poroelastic media with a static fracture: A dimension-reduced model with existence results in weighted Sobolev spaces and simulations with an XFEM discretization (2018)
  19. Huber, Markus; Rüde, Ulrich; Waluga, Christian; Wohlmuth, Barbara: Surface couplings for subdomain-wise isoviscous gradient based Stokes finite element discretizations (2018)
  20. Kröner, Axel; Kröner, Eva; Kröner, Heiko: Finite element approximation of level set motion by powers of the mean curvature (2018)

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