Dear David,
You add a global term, so that the stiffness matrix is no longer
sparse at all. This is why gmm complains. And the linear system
solve will only be possible for a small number of degrees of
freedom. This is avoidable with a specific solve of the system,
writing explicitely the constraint matrix as a rank one matrix. Of
course, a simpler alternative is to prescribe the value of the
unknown at any point of the domain (with a pointwise constraint
brick, this is very easy) and if there is a specific need for
solution to be of zero average, make a post-translation of the
solution.
Yves.
Le 23/02/2017 à 11:17, David Danan a écrit :
Dear Getfem users,
i wanted to solve a simple laplacian with pure Neumann
boundary condition on a cube.
In order to do so, since the problem is ill-posed, i added the
following constraint on the unknown u
int_omega u dx=0
via a Lagrangian multiplier.
In the code, the left-hand side is defined by
Model.add_fem_variable("u", mf_u);
getfem::add_linear_generic_assembly_brick(model, mim,
"(Grad_u.Grad_Test_u)");
model.add_fixed_size_variable("lambda", 1);
getfem::add_linear_generic_assembly_brick(model, mim,
"(lambda*Test_u)");
getfem::add_linear_generic_assembly_brick(model, mim,
"(u*Test_lambda)");
If i am not mistaken, it should correspond to the left hand
side described in
https://fenicsproject.org/olddocs/dolfin/1.3.0/python/demo/documented/neumann-poisson/python/documentation.html
for instance
As a result, the mean value is relatively small in comparison
with u (while not exactly 0).
However, when i run the program, i get the following warning:
Level 2 Warning in ../../src/gmm/gmm_vector.h, line 592:
Inefficient addition of element in rsvector with **** non-zero
entries
Did i do something wrong? If i didn't, is it possible to
disable this warning?
Thanks in advance,
David.
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