Thanks, Daniel. This is very helpful.
Best Regards,
Syed Ansari S.
On Mon, Aug 22, 2022 at 7:28 PM Daniel Arndt wrote:
> Syed,
>
> Yes, you should be able to use parallel::shared::Triangulation instead.
>
> Best,
> Daniel
>
> On Sat, Aug 20, 2022 at 5:25 AM syed ansari wrote:
>
>> Thanks Danie
On 8/22/22 10:08, Simon Wiesheier wrote:
As stated, what I tried is to use the operator= according to
LAPACKFullMatrix new_matrix = my_system_matrix .
However, there is an error message
"error: conversion from ‘dealii::SparseMatrix’ to non-scalar
type ‘dealii::LAPACKFullMatrix’ requested
L
Thanks for your input.
In the meantime, I replaced the matrix multiplication
res = A^_{-1}*B
by solving 'p' linear systems
A*res[p] = B[p],
where p is the number of columns of the matrix B.
" That's one way to go. FullMatrix::gauss_jordan() also computes the
inverse of a matrix."
As stated, what
On 8/22/22 09:55, Uclus Heis wrote:
Would be also a poddible solution to export my testvec as it is right
now (which contains the global solution) but instead of exporting with
all the preocess, call the print function only for one process?
Yes. But that runs again into the same issue mentione
Dear Wolfgang,
Thank you very much for the suggestion.
Would be also a poddible solution to export my testvec as it is right now
(which contains the global solution) but instead of exporting with all the
preocess, call the print function only for one process?
Thank you
El El lun, 22 ago 2022 a l
On 8/21/22 04:29, Uclus Heis wrote:
//
/testvec.print(outloop,9,true,false);/
It is clear that the problem I have now is that I am exporting the
completely_distributed_solution and that is not what I want.
Could you please informe me how to obtain the locally own solution? I
can not find the w
On 8/20/22 12:56, Raghunandan Pratoori wrote:
for (unsigned int i=0; i
local_history_values_at_qpoints[i][j].reinit(qf_cell.size());
local_history_fe_values[i][j].reinit(history_fe.dofs_per_cell);
history_field_strain[i][j].reinit(history_dof_handler.
On 8/19/22 13:14, Simon Wiesheier wrote:
I also need the system matrix A for a second purpose, namely
to compute a matrix multiplication:
res = A^{-1} * B ,
where B is another matrix.
-To be more precise, I need the inverse of the 19x19 submatrix
corresponding to the unconstrained DoFs only -- n
Hi,
If you search for "block solver" here
https://dealii.org/developer/doxygen/deal.II/Tutorial.html, you will see
all the tutorials that use block solvers. I think that only deal.II's own
solvers support BlockSparseMatrix directly.
Best,
Bruno
On Monday, August 22, 2022 at 9:02:28 AM UTC-4
Syed,
Yes, you should be able to use parallel::shared::Triangulation instead.
Best,
Daniel
On Sat, Aug 20, 2022 at 5:25 AM syed ansari wrote:
> Thanks Daniel for your quick reply. Is it possible to solve the
> same problem with parallel::shared::Triangulation for dim ==1?
>
> On Fri, 19 Aug 20
Dear All,
The following system of equations:
KQ=R
where,
[image: Screenshot from 2022-08-22 13-45-45.png]
were solved using BlockSparseMatrix to form tangent matrix K. It was solved
by:
SparseDirectUMFPACK A_direct;
A_direct.initialize(K);
A_direct.vmult(Q_stp, R);
Now, I'm trying to run my c
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