Mechanical APDL Basic Analysis Guide - Ansys

With all iterative solvers, be particularly careful to check that the model is appropriately constrained. No
minimum pivot is calculated and the solver will continue to iterate if any rigid body motion is possible.
5.2.4. The Incomplete Cholesky Conjugate Gradient (ICCG) Solver
The ICCG solver operates similarly to the JCG solver with the following exceptions:
• The ICCG solver is more robust than the JCG solver for matrices that are not well-conditioned. Performance
will vary with matrix conditioning, but in general ICCG performance compares to that of the JCG
solver.
• The ICCG solver uses a more sophisticated preconditioner than the JCG solver. Therefore, the ICCG
solver requires approximately twice as much memory as the JCG solver.
The ICCG solver is typically used for unsymmetric thermal analyses and electromagnetic analyses and is
available only for static analyses, full harmonic analyses [HROPT,FULL], or full transient analyses
[TRNOPT,FULL]. (You specify the analysis type using the ANTYPE command.) The ICCG solver is useful for
structural and multiphysics applications, and for symmetric, unsymmetric, complex, definite, and indefinite
matrices. You cannot use this solver for coupled-field applications (SOLID5 or PLANE13).
5.2.5. The Quasi-Minimal Residual (QMR) Solver
The QMR solver is used for electromagnetic analyses and is available only for full harmonic analyses
[HROPT,FULL]. (You specify the analysis type using the ANTYPE command.) You use this solver for symmetric,
complex, definite, and indefinite matrices. The QMR solver is more robust than the ICCG solver.
5.2.6. The Algebraic Multigrid (AMG) Solver
The Algebraic Multigrid (AMG) solver, which is based on the multi-level method, is an iterative solver that
you can use in single- and multiprocessor shared-memory environments. To use more than two processes
with this solver, you must have a license for the ANSYS Mechanical HPC advanced task (add-on) for each
processor beyond the first two.
In a multiprocessor environment, the AMG solver provides better performance than the PCG and ICCG
solvers on shared-memory parallel machines. It also handles indefinite matrix problems for nonlinear analyses.
However, the AMG solver typically uses 50 percent more memory than the PCG solver. The AMG solver is
also intended for problems in which the PCG and ICCG solvers would have difficulty converging (for example,
large, ill-conditioned problems where the ill-conditioning is due to large element aspect ratios within a mesh,
or cases in which shell or beam elements are attached to solid elements). In terms of CPU time when used
in a single-processor environment, the AMG solver performs better than the PCG and ICCG solvers for illconditioned
problems, and it delivers about the same level of performance for ordinary problems.
The AMG solver is available only for static analyses and full transient analyses. (These analyses can be linear
or nonlinear.) In addition, the efficiency of the AMG solver is limited to single-field structural analyses in
which the solution DOFs are combinations of UX, UY, UZ, ROTX, ROTY, and ROTZ. For analyses such as singlefield
thermal analyses in which the solution DOF is TEMP, the AMG solver is less efficient than the PCG or
ICCG.
The AMG solver is accessible from shared-memory parallel ANSYS.
5.3. Solver Memory and Performance
You will get the best performance from ANSYS if you first understand the individual solvers' memory usage
and performance under certain conditions. Each solver uses different methods to obtain memory; under-
Release 13.0 - © SAS IP, Inc. All rights reserved. - Contains proprietary and confidential information
of ANSYS, Inc. and its subsidiaries and affiliates.
5.3. Solver Memory and Performance
103