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 380 articles , 2 standard articles )

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  1. Evcin, Cansu; Uğur, Ömür; Tezer-Sezgin, Münevver: Controlling the power-law fluid flow and heat transfer under the external magnetic field using the flow index and the Hartmann number (2020)
  2. Landet, Tormod; Mardal, Kent-Andre; Mortensen, Mikael: Slope limiting the velocity field in a discontinuous Galerkin divergence-free two-phase flow solver (2020)
  3. Nguyen-Thanh, Vien Minh; Zhuang, Xiaoying; Rabczuk, Timon: A deep energy method for finite deformation hyperelasticity (2020)
  4. Wathen, Michael; Greif, Chen: A scalable approximate inverse block preconditioner for an incompressible magnetohydrodynamics model problem (2020)
  5. Alyaev, Sergey; Keilegavlen, Eirik; Nordbotten, Jan M.: A heterogeneous multiscale MPFA method for single-phase flows in porous media with inertial effects (2019)
  6. Arregui, Iñigo; Cendán, J. Jesús; González, María: A local discontinuous Galerkin method for the compressible Reynolds lubrication equation (2019)
  7. Bartoš, Ondřej; Feistauer, Miloslav; Roskovec, Filip: On the effect of numerical integration in the finite element solution of an elliptic problem with a nonlinear Newton boundary condition. (2019)
  8. Benn, James; Marsland, Stephen; McLachlan, Robert I.; Modin, Klas; Verdier, Olivier: Currents and finite elements as tools for shape space (2019)
  9. Bertoglio, Cristóbal; Conca, Carlos; Nolte, David; Panasenko, Grigory; Pileckas, Konstantinas: Junction of models of different dimension for flows in tube structures by Womersley-type interface conditions (2019)
  10. Bürger, Raimund; Méndez, Paul E.; Ruiz-Baier, Ricardo: On (\boldsymbolH(\operatornamediv))-conforming methods for double-diffusion equations in porous media (2019)
  11. Burman, Erik; He, Cuiyu: Primal dual mixed finite element methods for indefinite advection-diffusion equations (2019)
  12. Chandrashekar, Praveen; Nkonga, Boniface; Bhole, Ashish: A discontinuous Galerkin method for a two dimensional reduced resistive MHD model (2019)
  13. Chen, Robin Ming; Layton, William; McLaughlin, Michael: Analysis of variable-step/non-autonomous artificial compression methods (2019)
  14. Cimrman, Robert; Lukeš, Vladimír; Rohan, Eduard: Multiscale finite element calculations in python using sfepy (2019)
  15. Crestel, Benjamin; Stadler, Georg; Ghattas, Omar: A comparative study of structural similarity and regularization for joint inverse problems governed by PDEs (2019)
  16. Cusseddu, D.; Edelstein-Keshet, L.; Mackenzie, J. A.; Portet, S.; Madzvamuse, A.: A coupled bulk-surface model for cell polarisation (2019)
  17. Dohr, Stefan; Kahle, Christian; Rogovs, Sergejs; Swierczynski, Piotr: A FEM for an optimal control problem subject to the fractional Laplace equation (2019)
  18. Dokken, Jørgen S.; Funke, Simon W.; Johansson, August; Schmidt, Stephan: Shape optimization using the finite element method on multiple meshes with Nitsche coupling (2019)
  19. Dudziuk, Grzegorz; Lachowicz, Mirosław; Leszczyński, Henryk; Szymańska, Zuzanna: A simple model of collagen remodeling (2019)
  20. Eisenmann, Monika; Kovács, Mihály; Kruse, Raphael; Larsson, Stig: On a randomized backward Euler method for nonlinear evolution equations with time-irregular coefficients (2019)

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