Use the Eigenvalue Solver (
) to find the solution to linear or linearized eigenvalue problems (also called eigenfrequency problems). This solver is automatically used when a
Eigenvalue or
Eigenfrequency study is added to the model.
Use the Defined by study step list to specify if the settings are synchronized with the corresponding study step. Select
User defined to specify the properties below (in addition to the relative tolerance, which is always available).
The settings here are similar to those for the Eigenvalue study step, with the following exceptions:
From the Eigenvalue transformation list, select a transformation method for transforming the eigenvalues into another related quantity. The default is
None, which keeps the original eigenvalues. Depending on the physics in the model, other transformations might also be available.
The number in the Relative tolerance field (default 1.0·10
−6) controls the relative error in the computed eigenvalues.
Select the Enter transformed value check box to enter the value to search around as the transformed value (an eigenfrequency, for example) instead of the corresponding eigenvalue.
The Integration type for eigenvalue solver list and the
Number of integration points for eigenvalue solver list are the same as the
Integration type for estimation list and the
Number of integration points for estimation list described for the Eigenvalue study step. When you choose
Automatic in the
Integration type for eigenvalue solver list, it uses the Gauss type for real symmetric or Hermitian eigenvalue solvers and the trapezoidal method for other types of solver. When you choose
Automatic in
Number of integration points for eigenvalue solver, it is 8 for real symmetric or Hermitian eigenvalue solvers and 16 for other types of solvers.
Select the Distribute linear system solution check box to run the FEAST eigenvalue solver in parallel. See
Running FEAST in a Parallel MPI Mode for more information.
For other settings, see the Eigenvalue or
Eigenfrequency study settings. When the eigenvalue search settings are defined by the study step, these settings, including the ones above except the
Relative tolerance, are not available.
Use the Solution list to specify which solution to use if
Prescribed by is set to
Solution:
Select the Store linearization point and deviation in output check box to store the linearization point and the deviation from that linearization instead of the total solution.
If the eigenvalue itself appears nonlinearly, the solver reduces the problem to a quadratic approximation around an eigenvalue linearization point. Use the settings under Value of eigenvalue linearization point to specify such a scalar. Select the
Transform point check box to transform the linearization point value using the selected eigenvalue transformation. Specify the value of the linearization point in the
Point field (default value: 0).
Select an option from the Scaling of eigenvectors list to specify the scaling method used to normalize the eigenvectors. Select:
The eigenvalue solver is an iterative algorithm. Use the Maximum number of eigenvalue iterations field to limit the number of iterations (default: 300).
When you use the ARPACK solver, you can use the Dimension of Krylov space field to control the algorithm’s memory use. The default value of 0 means that the solver sets the dimension automatically to approximately twice the number specified in the
Desired number of eigenvalues field in the
General section.
Click the Add button (
) to add a constant and then define its name in the
Constant name column and its value (a numerical value or parameter expression) in the
Constant value column. By default, any defined parameters are first added as the constant names, but you can change the names to define other constants. Click
Delete (
) to remove the selected constant from the list.
The Log section contains logs of the eigenvalue solver results and properties of the assembled system, including the solver iterations and the total solution time. This log is stored in the Model MPH-file.