ansys.mapdl.core.Mapdl.pred#
- Mapdl.pred(sskey='', lskey='', **kwargs)#
Activates a predictor in a nonlinear analysis.
Mechanical APDL Command: PRED
Command default:
The default command behavior is to use prediction (
Sskey= AUTO). The AUTO option chooses to either use the linear predictor or to turn the predictor OFF. However, prediction does not occur if one or more of these conditions exist:Over prediction occurs due to a large residual force or excessive element distortion.
You are mapping ( mapsolve ) variables to a new mesh during rezoning. (Prediction does not occur for any mapsolve substeps, nor for the first substep afterwards.)
You have steady-state analysis defined ( sstate ), and contact elements exist in the model.
- Parameters:
- sskey
str Substep predictor key:
AUTO- The program uses a predictor but, within certain exceptions, automatically switches prediction off. This behavior is the default; see PRED_default for details.OFF- No prediction occurs.LINEAR (or ON)- Use the linear predictor on all substeps after the first.QUADRATIC- Use the quadratic predictor on all substeps after the second.
- lskey
str Load step predictor:
OFF- No prediction across load steps occurs. This is the default behavior.ON- Use a predictor also on the first substep of the load step. (Sskey= ON is required.)
- sskey
Notes
Activates a predictor in a nonlinear analysis on the degree-of-freedom solution for the first equilibrium iteration of each substep.
When using the arc-length method ( arclen, arctrm ), you cannot issue the DOF solution predictor command ( pred ), the automatic time stepping command ( autots ), or the line search command ( lnsrch ). If you activate the arc-length method after you set pred, autots, or lnsrch, a warning message appears. If you elect to proceed with the arc-length method, the program disables your DOF predictor, automatic time stepping, and line search settings, and the time step size is controlled by the arc-length method internally.
When using step-applied loads, such as tunif, bfunif, etc., or other types of non- monotonic loads, the predictor may adversely affect the convergence. If the solution is discontinuous, the predictor may need to be turned off.
When performing a nonlinear analysis involving large rotations, the predictor may require using smaller substeps. If the model has rotational degrees-of-freedom, the quadratic predictor could work more efficiently than the linear predictor.
This command is also valid in PREP7.