Henrik Sönnerlind
COMSOL Employee
Please login with a confirmed email address before reporting spam
Posted:
6 years ago
Aug 6, 2018, 7:47 a.m. EDT
Hi Sarah,
This is used if your eigenvalue problem is nonlinear in the eigenvalue itself. Think about a simple standared eigenvalue problem like
If the matrix A itself depends on the eigenvalue, that is
then the problem is linearized using
where is the value you supply as Value of eigenvalue linearization point.
This means that you can expect accurate eigenvalues only in the vicinity of , and may have to do several analyses with different values of the the linearization point.
Regards,
Henrik
-------------------
Henrik Sönnerlind
COMSOL
Hi Sarah,
This is used if your eigenvalue problem is nonlinear in the eigenvalue itself. Think about a simple standared eigenvalue problem like
( \mathbf A-\lambda \mathbf I) \mathbf x = 0
If the matrix **A** itself depends on the eigenvalue, that is
( \mathbf A(\lambda)-\lambda \mathbf I) \mathbf x = 0
then the problem is linearized using
( \mathbf A(\lambda_0)-\lambda \mathbf I) \mathbf x = 0
where \lambda_0 is the value you supply as _Value of eigenvalue linearization point_.
This means that you can expect accurate eigenvalues only in the vicinity of \lambda_0, and may have to do several analyses with different values of the the linearization point.
Regards,
Henrik