Mechanical APDL Basic Analysis Guide

(Axel Boer) #1

You can use Table 5.1: Shared Memory Solver Selection Guidelines (p. 112) as a general guideline for
memory usage.


This solver is available only for static or steady-state analyses and transient analyses, or for PCG Lanczos
modal analyses. The PCG solver performs well on most static analyses and certain nonlinear analyses.
It is valid for elements with symmetric, sparse, definite or indefinite matrices. Contact analyses that use
penalty-based or penalty and augmented Lagrangian-based methods work well with the PCG solver as
long as contact does not generat e rigid body motions throughout the nonlinear iterations (for example,
full loss of contact). The Lagrange multiplier method used by MPC184 elements can also be solved by
the PCG solver; see the PCGOPT command for more information. However, for Lagrange-formulation
contact methods, incompressible u-P formulations, and the MPC184 screw joint element, the PCG
solver cannot be used and the sparse solver is required.


Because they take fewer iterations to converge, well-conditioned models perform better than ill-condi-
tioned models when using the PCG solver. Ill-conditioning often occurs in models containing elongated
elements (i.e., elements with high aspect ratios) or contact elements. To determine if your model is ill-
conditioned, view the Jobname.PCS file to see the number of PCG iterations needed to reach a con-
verged solution. Generally, static or full transient solutions that require more than 1500 PCG iterations
are considered to be ill-conditioned for the PCG solver. When the model is very ill-conditioned (e.g.,
over 3000 iterations are needed for convergence) a direct solver may be the best choice unless you
need to use an iterative solver due to memory or disk space limitations.


For ill-conditioned models, the PCGOPT command can sometimes reduce solution times. You can adjust
the level of difficulty (PCGOPT,Lev_Diff) depending on the amount of ill-conditioning in the model.
By default, the program automatically adjusts the level of difficulty for the PCG solver based on the
model. However, sometimes forcing a higher level of difficulty value for ill-conditioned models can reduce
the overall solution time.


The PCG solver primarily solves for displacements/rotations (in structural analysis), temperatures (in
thermal analysis), etc. The accuracy of other derived variables (such as strains, stresses, flux, etc.) is de-
pendent upon accurat e prediction of primary variables. Therefore, the program uses a very conservative
setting for PCG tolerance (defaults to 1.0E-8) The primary solution accuracy is controlled by the PCG.
For most applications, setting the PCG tolerance to 1.0E-6 provides a very accurat e displacement solution
and may save considerable CPU time compared with the default setting. Use the EQSLV command to
change the PCG solver tolerance.


Direct solvers (such as the sparse direct solver) produce very accurat e solutions. Iterative solvers, such
as the PCG solver, require that a PCG convergence tolerance be specified. Therefore, a large relaxation
of the default tolerance may significantly affect the accuracy, especially of derived quantities.


With all iterative solvers you must verify that the model is appropriately constrained. No minimum pivot
is calculated and the solver continues to iterate if any rigid body motion exists.


In a modal analysis using the PCG solver (MODOPT,LANPCG), the number of modes should be limited
to 100 or less for efficiency. PCG Lanczos modal solutions can solve for a few hundred modes, but with
less efficiency than Block Lanczos (MODOPT,LANB).


When the PCG solver encounters an indefinite matrix, the solver invokes an algorithm that handles in-
definite matrices. If the indefinite PCG algorithm also fails (this happens when the equation system is
ill-conditioned; for example, losing contact at a substep or a plastic hinge development), the outer
Newton-Raphson loop is triggered to perform a bisection. Normally, the stiffness matrix is better condi-
tioned after bisection, and the PCG solver can eventually solve all the nonlinear steps.


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