What are people saying about cards & stationery in Brea, CA? The solver settings are stored at Study > Solver Configurations > Solution. Ramping the nonlinearities over time is not as strongly motivated, but step changes in nonlinearities should be smoothed out throughout the simulation. We have also introduced meshing considerations for linear static problems, as well as how to identify singularities and what to do about them when meshing. It is sometimes necessary to manually scale the dependent variables. A Global Parameter has to be introduced (in the above screenshot, P) and is ramped from a value nearly zero up to one. Not entering required material parameters. This is relatively expensive to do, but will lead to the most robust convergence. About the Stationary Solver The following background information about the Stationary Solver discusses these topics: Damped Newton Methods, Termination Criterion for the Fully Coupled and Segregated Attribute Nodes, Linear Solvers versus Nonlinear Solvers, and Pseudo Time Stepping. See Knowledge Base 1240: Manually Setting the Scaling of Variables. Check the solver log to see if the continuation method is backtracking. Therefore, it is recommended to use Adaptive Mesh Refinement which will automatically refine the mesh only in regions where it is needed, and coarsen the mesh elsewhere. Have you taken a look at this blog post? This involves a systematic reduction in the model complexity. Reply . This is relatively expensive to do, but will lead to the most robust convergence. In the extreme case, suppose one wants to model an instantaneous change in properties, such as: The memory requirements will always be lower than with the fully coupled approach, and the overall solution time can often be lower as well. Each physics is thus solved as a standalone problem, using the solution from any previously computed steps as initial values and linearization points. Connect and share knowledge within a single location that is structured and easy to search. That is, start by first solving a model with a small, but non-zero, load. The former approach solves for all unknowns in the problem at once, and considers all coupling terms between all unknowns within a single iteration. An example model that combines the techniques of nonlinearity ramping and adaptive mesh refinement with multiple study steps is: Hello guys. For example, if ramping P over values of: 0.2,0.4,0.6,0.8,1.0 the nonlinear solver may fail to converge for a value of 0.8.
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