FEniCS

The FEniCS Project is a collaborative project for the development of innovative concepts and tools for automated scientific computing, with a particular focus on automated solution of differential equations by finite element methods. FEniCS has an extensive list of features for automated, efficient solution of differential equations, including automated solution of variational problems, automated error control and adaptivity, a comprehensive library of finite elements, high performance linear algebra and many more.


References in zbMATH (referenced in 217 articles , 2 standard articles )

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  1. Bal, Guillaume; Hoffmann, Kristoffer; Knudsen, Kim: Propagation of singularities for linearised hybrid data impedance tomography (2018)
  2. de Hoop, Maarten V.; Kepley, Paul; Oksanen, Lauri: An exact redatuming procedure for the inverse boundary value problem for the wave equation (2018)
  3. Froese, Brittany D.: Meshfree finite difference approximations for functions of the eigenvalues of the Hessian (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. Maljaars, Jakob M.; Labeur, Robert Jan; Möller, Matthias: A hybridized discontinuous Galerkin framework for high-order particle-mesh operator splitting of the incompressible Navier-Stokes equations (2018)
  6. Morgan, Hannah; Scott, L.Ridgway: Towards a unified finite element method for the Stokes equations (2018)
  7. Schmidt, Stephan: Weak and strong form shape hessians and their automatic generation (2018)
  8. 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)
  9. Vabishchevich, Petr N.: Numerical solution of time-dependent problems with fractional power elliptic operator (2018)
  10. Walker, Shawn W.: FELICITY: a Matlab/C++ toolbox for developing finite element methods and simulation modeling (2018)
  11. Abali, Bilen Emek: Computational reality. Solving nonlinear and coupled problems in continuum mechanics (2017)
  12. Ahlkrona, Josefin; Shcherbakov, Victor: A meshfree approach to non-Newtonian free surface ice flow: application to the Haut Glacier d’Arolla (2017)
  13. Alger, Nick; Villa, Umberto; Bui-Thanh, Tan; Ghattas, Omar: A data scalable augmented Lagrangian KKT preconditioner for large-scale inverse problems (2017)
  14. Allen, Jeffery; Leibs, Chris; Manteuffel, Tom; Rajaram, Harihar: A fluidity-based first-order system least-squares method for ice sheets (2017)
  15. Ambartsumyan, I.; Khattatov, E.; Yotov, I.: Mixed finite volume methods for linear elasticity (2017)
  16. Ambrosi, D.; Pezzuto, S.; Riccobelli, D.; Stylianopoulos, T.; Ciarletta, P.: Solid tumors are poroelastic solids with a chemo-mechanical feedback on growth (2017)
  17. Anker, Felix; Bayer, Christian; Eigel, Martin; Ladkau, Marcel; Neumann, Johannes; Schoenmakers, John: SDE based regression for linear random PDEs (2017)
  18. Antonov, M.Yu.; Grigorev, A.V.; Kolesov, A.E.: Numerical modeling of fluid flow in liver lobule using double porosity model (2017)
  19. Arnold, Douglas N.; Chen, Hongtao: Finite element exterior calculus for parabolic problems (2017)
  20. Avvakumov, A.V.; Strizhov, V.F.; Vabishchevich, P.N.; Vasilev, A.O.: Algorithms for numerical simulation of non-stationary neutron diffusion problems (2017)

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Further publications can be found at: http://fenicsproject.org/citing/