In our FEA code we perform the rotations at the local level, before
assembly so that it is easy to apply the boundary conditions, then
unrotate locally after solution to get the usual Cartesian components.
Somehow this seems more efficient than doing this globally, but perhaps
I am missing something.
-sanjay
On 5/31/21 9:33 AM, Matthew Knepley wrote:
On Mon, May 31, 2021 at 11:12 AM Stefano Zampini
<[email protected] <mailto:[email protected]>> wrote:
Mike
as long as P is a sparse matrix with compatible rows and cols
(i.e. rows(P)= cols(A) = rows (A)) , MatPtAP will compute the result.
Stefano and Mark are correct. This will work.
I implemented the same thing in my code in a different way. I put this
transformation into the mapping between local and global
vector spaces. The global degrees of
freedom are the ones you want for boundary conditions (normal and
tangential to the boundary), and I eliminate the ones that are
constrained. The local degrees of
freedom are the normal Caresian ones, and these are used for assembly.
The map is used when I execute DMGlobalToLocal() and
DMLocalToGlobal(). There is an
example of me doing this in SNES ex71, Poiseuille flow in a tilted
channel.
Thanks,
Matt
Il giorno lun 31 mag 2021 alle ore 16:52 Mark Adams
<[email protected] <mailto:[email protected]>> ha scritto:
On Mon, May 31, 2021 at 9:20 AM Michael Wick
<[email protected]
<mailto:[email protected]>> wrote:
Hi PETSc team:
I am considering implementing a skew roller boundary
condition for my elasticity problem. The method is based
on this journal paper:
http://inside.mines.edu/~vgriffit/pubs/All_J_Pubs/18.pdf
<http://inside.mines.edu/~vgriffit/pubs/All_J_Pubs/18.pdf>
Or you may find the method in the attached Bathe's slides,
pages 9 -10.
Roughly speaking, a (very) sparse matrix T will be created
which takes the shape [ I, O; O, R], where R is a 3x3
rotation matrix. And the original linear problem K U = F
will be modified into (T^t K T) (T^t U) = T^t F. In doing
so, one can enforce a roller boundary condition on a
slanted surface.
I think it can be an easy option if I can generate the T
matrix and do two matrix multiplications to get T^t K T. I
noticed that there is a MatPtAP function. Yet, after
reading a previous discussion, it seems that this function
is not designed for this purposes
(https://lists.mcs.anl.gov/pipermail/petsc-users/2018-June/035477.html
<https://lists.mcs.anl.gov/pipermail/petsc-users/2018-June/035477.html>).
Yes, and no. It is motivated and optimized for a Galerkin
coarse grid operator for AMG solvers, but it is a projection
and it should be fine. If not, we will fix it.
We try to test our methods of "empty" operators , but I don't
know if MatPtAP has ever been tested for super sparse P. Give
it a shot and see what happens.
Mark
I assume I can only call MatMatMult & MatTransposeMatMult
to do this job, correct? Is there any existingly PETSc
function to do T^t K T in one call?
Thanks,
Mike
--
Stefano
--
What most experimenters take for granted before they begin their
experiments is infinitely more interesting than any results to which
their experiments lead.
-- Norbert Wiener
https://www.cse.buffalo.edu/~knepley/
<http://www.cse.buffalo.edu/~knepley/>
