Mechanical APDL Structural Analysis Guide

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Eigensolver Application

To find many modes (about 40+) of large models. This Medium High

solver is more robust when the mass matrix is partially zero,

Subspace

or when there are u-P formulation elements in the model.

It is recommended when using Distributed ANSYS.

The PCG Lanczos, Subspace, unsymmetric, and damped methods are the only eigenvalue solvers that
will run a fully distributed solution in Distributed ANSYS.

3.8.1. Block Lanczos Method

The Block Lanczos eigenvalue solver uses the Lanczos algorithm where the Lanczos recursion is performed
with a block of vectors. The Block Lanczos method uses the sparse matrix solver, overriding any solver
specified via the EQSLV command.

The Block Lanczos method is especially powerful when searching for eigenfrequencies in a given part
of the eigenvalue spectrum of a given system. The convergence rat e of the eigenfrequencies will be
about the same when extracting modes in the midrange and higher end of the spectrum as when ex-
tracting the lowest modes. Therefore, when you use a shift frequency (FREQB on MODOPT) to extract
n modes beyond the starting value of FREQB, the algorithm extracts the n modes beyond FREQB at
about the same speed as it extracts the lowest n modes.

While the Block Lanczos eigensolver is typically very robust for a wide range of applications, some element
types may cause the eigensolver difficulty in achieving a final solution.These include MPC184 elements
that use the Lagrange multiplier method and FLUID30,FLUID220, and FLUID221 elements that use the
symmetric element matrix formulation for modal analyses (KEYOPT(2) = 2).

3.8.2. PCG Lanczos Method

The PCG Lanczos method internally uses the Lanczos algorithm, combined with the PCG iterative solver.
This method will be significantly faster than the Block Lanczos method for the following cases:

• Large models that are dominated by 3-D solid elements and do not have ill-conditioned matrices due, for
  example, to poorly shaped elements


• Only a few of the lowest modes are requested

Having ill-conditioned matrices or asking for many modes (e.g., more than 100 modes) can lead to an
inefficient solution time with this method.

The PCG Lanczos method finds only the lowest eigenvalues. If a range of eigenfrequencies is requested
on the MODOPT command, the PCG Lanczos method will find all of the eigenfrequencies below the
lower value of the eigenfrequency range as well as the number of requested eigenfrequencies in the
given eigenfrequency range. Thus the PCG Lanczos method is not recommended for problems when
the lower value of the input eigenfrequency range is far from zero.

When to Choose PCG Lanczos over Block Lanczos

The Block Lanczos eigensolver is currently the recommended eigensolver for most applications. However,
the PCG Lanczos eigensolver can be more efficient than the Block Lanczos eigensolver for certain cases.
Follow these guidelines when deciding whether to use the Block Lanczos or PCG Lanczos eigensolver.

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Modal Analysis