Implicit Solvers

Implicit Solvers with Parallel Version Compatibility Table

  Option Radioss SMP Radioss MPP SPMD
Implicit Resolution /IMPL/SOLVER/1 PCG PCG
Buckling Modes /IMPL/BUCKL/1 N/A MUMPS
Eigen Modes /EIG (Starter) N/A MUMPS
Iterative Preconditioned Conjugate Gradient
Massively Parallel Multi-Frontal Solver

Linear Solvers

Direct, Iterative and Mixed

Linear solver will be used in both Linear and Nonlinear Analyses, so it is very important to choose an appropriate solver for your application.

The PCG (Preconditioned Conjugate Gradient) iterative solver has been available from the first version of Radioss Implicit followed by MUMPS solvers (default solver).

If you are not sure as to which solver to use for a particular application, it is recommended to try a MUMPS solver first. For large simulations, such as Full-Vehicle Analysis, where memory might be an issue, the PCG method with higher quality preconditioner (this is set using /IMPL/PREPAT/n, for example: n=2) could be used instead.

For a Nonlinear Analysis, it is worth comparing the two methods on your model by running a simple Linear Analysis before launching the actual analysis.

Nonlinear Solvers

Modified Newton and Quasi-Newton Methods

Once again, the choice of solver depends on the type of analysis. Generally, the Quasi-Newton method is more suitable for an analysis with a high degree of nonlinearity, but it requires more memory and costs more per iteration.