Mechanical APDL Basic Analysis Guide

(Axel Boer) #1

Chapter 5: Solution


In the solution phase of an analysis, the computer takes over and solves the simultaneous set of equations
that the finite element method generates. The results of the solution are:



  • Nodal degree of freedom values, which form the primary solution

  • Derived values, which form the element solution.


The element solution is usually calculated at the elements' integration points. The program writes the
results to the database as well as to the results file (.RST,.RTH, or .RMG files).


The following solution topics are available:


5.1. Selecting a Solver


5.2. Types of Solvers
5.3. Solver Memory and Performance
5.4. Using Special Solution Controls for Certain Types of Structural Analyses
5.5. Obtaining the Solution
5.6. Solving Multiple Load Steps
5.7. Terminating a Running Job
5.8. Restarting an Analysis
5.9. Singular Matrices
5.10. Stopping Solution After Matrix Assembly

5.1. Selecting a Solver


Several methods for solving the system of simultaneous equations are available in the program: sparse
direct solution, Preconditioned Conjugate Gradient (PCG) solution, Jacobi Conjugate Gradient (JCG)
solution, Incomplete Cholesky Conjugate Gradient (ICCG) solution, and Quasi-Minimal Residual (QMR)
solution. In addition, distributed versions of the sparse, PCG, and JCG solvers are available for use in
Distributed ANSYS (refer to the Parallel Processing Guide). See the EQSLV command description for details
on each solver, defaults, etc.


You can select a solver using one of the following:
Command(s):EQSLV
GUI: Main Menu> Preprocessor> Loads> Analysis Type> Analysis Options
Main Menu> Solution> Load Step Options> Sol'n Control ( : Sol'n Options Tab)
Main Menu> Solution> Analysis Options
Main Menu> Solution> Unabridged Menu> Analysis Options


The following tables provide general guidelines you may find useful when selecting an appropriate
solver for a given problem. The first table lists solvers that can be run using shared memory parallelism
on shared memory parallel hardware. The second table lists solvers that can be run using distributed


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