Hi Daniel,

thank you very much for your answer!

I also tried a spectral transformation with the Arpack solver with the same
result as without spectral transformation. I am interested in the smallest
real eigenvalues. I know from previous calculations with the Krylov Schur
solver form SLEPc that using or not using a spectral transformation makes a
very big difference here.
I am also solving the mechanical eigenproblem only:
[M*eigenvalue+Kmm]*eigenvector=0

Here I am able to build a preconditioner out of the BlockSparseMatrix Kmm.
The calculations with a preconditioner are really fast.

My situation now is, that I use the same preconditioner for the
mechanical-only system as for the coupled piezosystem (both build only out
of Kmm). I think this should work as long as Kme*(Kee)^-1*Kem is relatively
small with respect to Kmm but I will test this in further computations.

I have also tried another approach using matrices instead of linear
operators. This works better but I think using linear operators is the more
stylish way (this is my first contact with linear operators and I want to
learn to handle them).

I do not want to use SLEPc here because I think handling the PETSc Matrices
and vectors is too uncomfortable for my application. Am I right at this
point? What do you think about using SLEPc here?

Thank you very much in advance, I appreciate every help!
Andreas

Am Fr., 5. Juli 2019 um 20:15 Uhr schrieb Daniel Garcia-Sanchez <
[email protected]>:

> Hi Andreas,
>
> On Thursday, July 4, 2019 at 7:41:31 PM UTC+2, Andreas Hegendörfer wrote:
>>
>>  Hello,
>>
>> 2. Are there better ways to solve this Eigenproblem, maybe with another
>> solver?
>>
>>
> Have you tried an spectral transformation? I'm not familiar with Arpack, I
> use SLEPc. I think that you could use the
> function ArpackSolver::set_shift(). sigma is your guess for the eigenvalue.
>
> Note that if you use an spectral transformation, you can not use an
> iterative solver. You have to use a direct solver, but it considerably
> accelerates the eigenvalue calculation.
>
> If your eigenvalue is from the interior of the spectrum and you don't do
> an spectral transformation, it can take very long.
>
> Best,
> Daniel
>
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