This package provides methods for solving problems by adaptive FEM.
Observe an estimate of the global error.
Observe entries for the size of the matrix.
Standard observe quantities for stationary finite element strategies.
Estimates the error by testing the difference z-IPz against the residual. Here z is the solution of a dual problem in an enriched finite element space.
Superclasses: <SETUP-ENRICHED-ANSATZ-SPACE> <SOLVE-DUAL-PROBLEM> <LOCAL-TEST-WITH-DUAL> <STANDARD-ERROR-ESTIMATOR>
This class describes iterative finite element appoximation strategies.
This class implements adaptive finite element interpolation of the given coefficient function as a variant of finite element approximation.
Puts the fraction of the cells with the largest error contributions in the refinement table. Note that a fraction of 1.0 yields uniform refinement. Below from-level, global refinement is used. block-p indicates that all children of a parent cell have to be refined at once.
Estimates the error by measuring the difference between the solution and a projected solution in a hierarchical mesh by a certain norm given by local-p and global-p.
Superclasses: <DIFFERENCE-WITH-PROJECTION> <GLOBAL-AND-LOCAL-NORM> <STANDARD-ERROR-ESTIMATOR>
An indicator is used as first argument in the generic functions indicate which works on a blackboard. Based on the quantities computed by an error estimator, i.e. eta, indicate puts a list of elements to be refined on the blackboard. When ensure-mesh-quality is t, the indicator ensures that the difference of mesh widths of neighboring cells does not become larger than a factor of 4.
Marks all cells in a region for refinement.
Rothe strategy for time-dependent problems. The idea of the Rothe method for solving U_t +A U =f is to do an ODE time-stepping scheme in an infinite-dimensional function space. Therefore, in every time-step, the solution has to be approximated sufficiently well in the space variable.
This class describes some iterative finite element solution strategies for continuous, stationary PDE problems.
A strategy is an iteration for solving a problem defined on a blackboard.
Marks all cells for refinement.
Yields both local and global estimate.
Puts a list of elements to be refined on the blackboard.