My BoundaryValues-function looks like
template <int dim>
class BoundaryValues : public Function<dim>
{
public:
BoundaryValues () : Function<dim>() {}
virtual double value (const Point<dim> &p,
const unsigned int component = 0) const;
};
template <int dim>
double BoundaryValues<dim>::value (const Point<dim> &p,
const unsigned int /*component*/)
const
{
return std::sin(2 * numbers::PI * (p[0]+p[1])) + OFFSET;
}
Thus I do not think that that is the problem. Assembly of the matrix and
the residual is done using a second constraint matrix called
"newton_constraints", defined as
newton_constraints.clear();
newton_constraints.reinit(solution_relevant_partitioning);
DoFTools::make_hanging_node_constraints(dof_handler,
newton_constraints);
VectorTools::interpolate_boundary_values(dof_handler, 0,
ZeroFunction<dim>(), newton_constraints);
newton_constraints.close();
in the following way:
newton_constraints.distribute_local_to_global(cell_residual,
local_dof_indices, local_residual);
or
newton_constraints.distribute_local_to_global(cell_matrix, cell_rhs,
local_dof_indices, system_matrix, system_rhs);
in order to keep the zero boundary conditions for the newton update.
Am Dienstag, 26. September 2017 03:15:47 UTC+2 schrieb Wolfgang Bangerth:
>
> On 09/25/2017 01:25 PM, 'Maxi Miller' via deal.II User Group wrote:
> >
> > I do not understand the reason why that happens. Is it a mathematical
> > problem? Or rather a problem in my code? Afaik the gradients should not
> > depend on the offset, thus I do not know where to look for the problem
> here.
>
> Did you adjust the boundary values in the same way as the initial
> values? Because if you don't, your initial guess will have a sharp
> boundary layer where it drops from OFFSET to zero, and that leads to a
> very large non-linearity.
>
> Best
> W.
>
> --
> ------------------------------------------------------------------------
> Wolfgang Bangerth email: [email protected]
> <javascript:>
> www: http://www.math.colostate.edu/~bangerth/
>
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