Rheolef 6.3: a free and efficient C++ finite element library
 

Rheolef: an efficient FEM C++ finite element library for solving PDE

Version : 6.3
Home: http://ljk.imag.fr/membres/Pierre.Saramito/rheolef
Book: http://cel.archives-ouvertes.fr/docs...DF/rheolef.pdf

News in 6.3:
* minor bugs fixed
* portability improved

Distibution: sources and binaries as debian packages.
The license is GPL.

Keywords: finite element method (FEM), partial derivative equations (PDE), C++

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Summary
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Rheolef is a programming environment that serves as a convenient laboratory for
computations involving finite element methods (FEM) for solving partial
differential equations (PDE). Rheolef is both a C++ library and a set of
commands for unix shell programming, providing algorithms and data structures.

* Algorithms refer to the most up-to-date ones: preconditioned sparse solvers
for linear systems, incompressible elasticity, Stokes and Navier-Stokes flows,
characteristic method for convection dominated heat problems, etc. Also
nonlinear generic algorithms such as fixed point and damped Newton methods.

* Data structures fit the standard variational formulation concept: spaces,
discrete fields, bilinear forms are C++ types for variables, that can be
combined in any expressions, as you write it on the paper.

Combined together, as a Lego game, these bricks allows the user to solve most
complex nonlinear problems. The concision and readability of codes written
with Rheolef is certainly a major keypoint of this environment.

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Main features
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* Poisson problems in dimension d=1,2,3.
* Stokes problems (d=2,3), with Taylor-Hood or stabilized P1 bubble-P1 elements.
* linear elasticity (d=1,2,3), including the incompressible case.
* characteristic method for time-dependent problems:
transport, convection-difusion, and Navier-Stokes equations.
* input and output in various file format for meshes generators and numerical
data visualization systems.

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Advanced features
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* massively distributed memory finite element environment, based on MPI.
* high-order polynomial approximation.
* auto-adaptive mesh algorithms.
* axisymetric problems.
* nonlinear Newton-like PDE solvers
* solve equations on 3d surfaces
* 3d stereo visualization


Pierre Saramito
--
Pierre.Saramito@imag.fr
Directeur de Recherche CNRS
Laboratoire Jean Kuntzmann, Grenoble, France
http://www-ljk.imag.fr/membres/Pierre.Saramito