On 01/21/2014 11:15 AM, Jan Blechta wrote:
> On Tue, 21 Jan 2014 11:01:50 -0800
> Nikolaus Rath <[email protected]> wrote:
> 
>> On 01/21/2014 09:43 AM, Simone Pezzuto wrote:
>>> 2014/1/21 Jan Blechta <[email protected]
>>> <mailto:[email protected]>>
>>>
>>>     On Tue, 21 Jan 2014 17:18:54 +0000
>>>     "Garth N. Wells" <[email protected] <mailto:[email protected]>>
>>> wrote:
>>>
>>>     > On 2014-01-21 17:01, Nikolaus Rath wrote:
>>>     > > Hello,
>>>     > >
>>>     > > I noticed that the neumann-poisson demo
>>>     > >
>>>     
>>> (http://fenicsproject.org/documentation/dolfin/1.3.0/python/demo/documented/neumann-poisson/python/documentation.html
>>>     
>>> <https://urldefense.proofpoint.com/v1/url?u=http://fenicsproject.org/documentation/dolfin/1.3.0/python/demo/documented/neumann-poisson/python/documentation.html&k=Izx05CQZXsnLXkTIfmT7FQ%3D%3D%0A&r=1KW6QPJUrZMjRkn7m6Ouj0V90HWobEY8fXrhlFmuc%2Bc%3D%0A&m=v%2F3Ze6UBI9gR2l%2Fu82%2F4Y4fHujXMqW47hgHfmNXSjGw%3D%0A&s=e188e7efbe5d6d1deabbd7fb92be8e35f91642b13aacc34896849ef0c60c62e7>)
>>>     > > fails when using a different solver, e.g. when replacing
>>>     > >
>>>     > > solve(a == L, w)
>>>     > >
>>>     > > with
>>>     > >
>>>     > > solve(a == L, w,
>>>     > >       solver_parameters = {'linear_solver': 'cg',
>>>     > >                            'preconditioner': 'ilu'})
>>>     > >
>>>     >
>>>     > This problem needs very careful treatment when using iterative
>>>     > solvers. Simple block-box preconditioners and solvers will
>>>     > very likely fail.
>>>
>>>     AMG preconditioning based on operator
>>>
>>>       (inner(grad(u), grad(v)) + c*d)*dx
>>>
>>>     could perform well. This operator does not have a dense row
>>> like the original one. This is a strategy similar to
>>> demo_stokes-iterative.
>>>
>>>
>>> In this case the preconditioner is singular (pure neumann), no it
>>> cannot be used.
>>>
>>> As Garth was mentioning, this problem is delicate for iterative
>>> solver, not only because
>>> its indefiniteness, but because the Lagrangian constraint you're
>>> imposing yields
>>> a column (the last one) of the full matrix that belongs to the
>>> kernel of the top-left block.
>>>
>>> Since the nullspace is at hands, I would provide it to the solver
>>> and then use CG+AMG,
>>> with Jacobi relaxation at coarser scale instead Gauss elimination
>>> (at least with petsc boomeramg).
>>
>>
>> Why is there a nullspace? Doesn't the \int u = 0 constraint remove the
>> remaining degree of freedom resulting from the pure Neumann boundary
>> conditions?
> 
> It does not remove any DOF. It adds just one DOF - the Lagrange
> multiplier and an equation which makes the system regular. 

I'm probably just using different terminology, but how can the system be
regular if it has a nullspace? If there is u such that A.u = 0, I would
say that A is singular, not regular.



Best,
Nikolaus

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