GfsAdapt

GfsAdapt is the base class for all the objects used to adapt the resolution dynamically.

The syntax in parameter files is:

[ GfsEvent ] {
  minlevel = 3 maxlevel = 10 
  mincells = 100 maxcells = 100000 
  cmax = 1e-2
  weight = 1
  cfactor = 2
  c = Cost
}

with

minlevel: The minimum number of refinement levels (default is 0).
maxlevel: The maximum number of refinement levels (default is infinity).
mincells: The minimum number of cells in the simulation (default is 0).
maxcells: The maximum number of cells in the simulation. If this number is reached, the algorithm optimizes the distribution of the cells so that the maximum cost over all the cells is minimized (default is infinity).
cmax: The maximum cell cost allowed. If the number of cells is smaller than the maximum allowed and the cost of a cell is larger than this value, the cell will be refined.
weight: When combining several criteria, the algorithm will weight the cost of each by this value in order to compute the total cost (default is 1).
cfactor: Cells will be coarsened only if their cost is smaller than cmax/cfactor (default is 4).

When specifying several different GfsAdapt objects in the same parameter file, the behaviour depends on whether maxcells is specified or not:

If maxcells is specified: A global cost function is constructed by weighing each of the cost functions with their respective weight parameter and is used to perform a global optimisation of the cells distribution respecting the constraint on the total number of cells. A global maximum cost parameter is constructed by taking the minimum of all the cmax parameters. The cfactor parameter is ignored in this case.
else: Cells are refined whenever they violate either of the refinement criteria specified by each GfsAdapt object, and coarsened whenever the verify the coarsening criteria (cost < cmax/cfactor) of all the GfsAdapt objects. The weight parameter is ignored in this case.