DOLFIN

DOLFIN is a C++/Python library that functions as the main user interface of FEniCS. A large part of the functionality of FEniCS is implemented as part of DOLFIN. It provides a problem solving environment for models based on partial differential equations and implements core parts of the functionality of FEniCS, including data structures and algorithms for computational meshes and finite element assembly. To provide a simple and consistent user interface, DOLFIN wraps the functionality of other FEniCS components and external software, and handles the communication between these components.


References in zbMATH (referenced in 112 articles , 1 standard article )

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  1. Chaudhry, Jehanzeb H.: A posteriori analysis and efficient refinement strategies for the Poisson-Boltzmann equation (2018)
  2. Clason, Christian; Kruse, Florian; Kunisch, Karl: Total variation regularization of multi-material topology optimization (2018)
  3. Creech, Angus C. W.; Jackson, Adrian; Maddison, James R.: Adapting and optimising fluidity for high-fidelity coastal modelling (2018)
  4. Fumagalli, Ivan; Parolini, Nicola; Verani, Marco: On a free-surface problem with moving contact line: from variational principles to stable numerical approximations (2018)
  5. Huber, Markus; Rüde, Ulrich; Waluga, Christian; Wohlmuth, Barbara: Surface couplings for subdomain-wise isoviscous gradient based Stokes finite element discretizations (2018)
  6. Karl, Veronika; Wachsmuth, Daniel: An augmented Lagrange method for elliptic state constrained optimal control problems (2018)
  7. Kulshreshtha, K.; Narayanan, S. H. K.; Bessac, J.; MacIntyre, K.: Efficient computation of derivatives for solving optimization problems in R and Python using SWIG-generated interfaces to ADOL-C (2018)
  8. Lenders, Felix; Kirches, C.; Potschka, A.: trlib: a vector-free implementation of the GLTR method for iterative solution of the trust region problem (2018)
  9. Oh, Duk-Soon; Widlund, Olof B.; Zampini, Stefano; Dohrmann, Clark R.: BDDC algorithms with deluxe scaling and adaptive selection of primal constraints for Raviart-Thomas vector fields (2018)
  10. Oliver Laslett, Jonathon Waters, Hans Fangohr, Ondrej Hovorka: Magpy: A C++ accelerated Python package for simulating magnetic nanoparticle stochastic dynamics (2018) arXiv
  11. Schmidt, Stephan; Schütte, Maria; Walther, Andrea: Efficient numerical solution of geometric inverse problems involving Maxwell’s equations using shape derivatives and automatic code generation (2018)
  12. Walker, Shawn W.: FELICITY: a Matlab/C++ toolbox for developing finite element methods and simulation modeling (2018)
  13. Atroshchenko, Elena; Hale, Jack S.; Videla, Javier A.; Potapenko, Stanislav; Bordas, Stéphane P. A.: Micro-structured materials: inhomogeneities and imperfect interfaces in plane micropolar elasticity, a boundary element approach (2017)
  14. Bakhos, Tania; Kitanidis, Peter K.; Ladenheim, Scott; Saibaba, Arvind K.; Szyld, Daniel B.: Multipreconditioned GMRES for shifted systems (2017)
  15. Březina, Jan; Exner, Pavel: Fast algorithms for intersection of non-matching grids using Plücker coordinates (2017)
  16. Kirby, Robert C.: Fast inversion of the simplicial Bernstein mass matrix (2017)
  17. Kolesov, Alexander E.; Vabishchevich, Petr N.: Splitting schemes with respect to physical processes for double-porosity poroelasticity problems (2017)
  18. Maddison, J. R.; Hiester, H. R.: Optimal constrained interpolation in mesh-adaptive finite element modeling (2017)
  19. Meister, Oliver; Rahnema, Kaveh; Bader, Michael: Parallel memory-efficient adaptive mesh refinement on structured triangular meshes with billions of grid cells (2017)
  20. Rathgeber, Florian; Ham, David A.; Mitchell, Lawrence; Lange, Michael; Luporini, Fabio; Mcrae, Andrew T. T.; Bercea, Gheorghe-Teodor; Markall, Graham R.; Kelly, Paul H. J.: Firedrake, automating the finite element method by composing abstractions (2017)

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