- Mapdl.bucopt(method='', nmode='', shift='', ldmulte='', rangekey='', **kwargs)¶
Specifies buckling analysis options.
APDL Command: BUCOPT
Mode extraction method to be used for the buckling analysis:
LANB - Block Lanczos
SUBSP - Subspace iteration
Number of buckling modes (i.e., eigenvalues or load multipliers) to extract (defaults to 1).
By default, this value acts as the initial shift point about which the buckling modes are calculated (defaults to 0.0).
Boundary for the load multiplier range of interest (defaults to ).
Key used to control the behavior of the eigenvalue extraction method (defaults to CENTER):
- CENTER - Use the CENTER option control (default); the program computes NMODE buckling
modes centered around SHIFT in the range of (-LDMULTE, +LDMULTE).
- RANGE - Use the RANGE option control; the program computes NMODE buckling modes in the
range of (SHIFT, LDMULTE).
Eigenvalues from a buckling analysis can be negative and/or positive. The program sorts the eigenvalues from the most negative to the most positive values. The minimum buckling load factor may correspond to the smallest eigenvalue in absolute value, or to an eigenvalue within the range, depending on your application (i.e., linear perturbation buckling analysis or purely linear buckling analysis).
It is recommended that you request an additional few buckling modes beyond what is needed in order to enhance the accuracy of the final solution. It is also recommended that you input a non zero SHIFT value and a reasonable LDMULTE value (i.e., a smaller LDMULTE that is closer to the last buckling mode of interest) when numerical problems are encountered.
When using the RANGE option, defining a range that spans zero is not recommended. If you are seeking both negative and positive eigenvalues, it is recommended that you use the CENTER option.
This command is also valid in PREP7. If used in SOLUTION, this command is valid only within the first load step.
Distributed ANSYS Restriction: Both extraction methods (LANB and SUBSP) are supported within Distributed ANSYS. However, the subspace iteration eigensolver (SUBSP) is the only distributed eigensolver that will run a fully distributed solution. The Block Lanczos eigensolver (LANB) is not a distributed eigensolver; therefore, you will not see the full performance improvements with this method that you would with a fully distributed solution.