Solver Settings for Contact Analysis

The following solver settings can help to successfully perform contact simulations:

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In a contact analysis, you almost invariably use an incremental approach. It is possible to solve a problem without friction in a single stationary load step, but such an approach will often fail to converge. In a stationary analysis, you should then use the parametric continuation solver, and gradually increase the load or displacement. Enable it by selecting under in the settings for the Stationary solver.

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Use a direct solver rather than an iterative solver as the linear equation solver if the problem size allows it. Direct solvers are less sensitive and can provide better convergence.

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As a default, the double dogleg nonlinear solver is selected when a stationary study is generated and nodes are present in the model. For the majority of contact problems this solver has more stable convergence properties than the Newton solver, which is the default solver for most other problems. Using otherwise similar settings, the double dogleg solver tends to be somewhat slower than the Newton solver on problems where both solvers converge. It is, however, often possible to take larger parameter steps when using the double dogleg solver. For some problems, the Newton solver can still be the better choice, so if you experience problems using the default settings, try to switch solver.

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It is important to scale the contact degrees of freedom used in the augmented Lagrangian method manually. The convergence check relies on the scaling of the degrees of freedom, but since contact pressures and friction forces often are zero over parts of the simulation, you should not rely on automatic scaling. When the solver sequence is first created, both contact pressure and friction forces are given a manual scaling which is relevant for typical metal-to-metal contact. You should in most cases change this to values appropriate for your application. The variable scaling is accessed under in the solver sequence. Set the scale for each variable to a value that is representative for the expected result. Too large values may give a too early convergence, while too small values may lead to an excessive number of iterations.

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For contact problems, it is often necessary to let the parametric solver use a defensive strategy when going from one parameter step to the next. This can be controlled by setting the value of in the . By default, the parametric solver will use do so by setting the predictor to when contact is present. However, it can sometimes be beneficial to use a more aggressive strategy by setting it to .

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When using the augmented Lagrangian method, one lumped step will be generated in the segregated solver for each node. This split of variables into different lumped steps does not influence the solution as such; you can equally well group the contact variables in a single lumped step. Each lumped step will however generate an individual curve in the convergence plot, making it easier to pinpoint the source of possible convergence problems. You can also increase the granularity even more by changing to in the node in the solver sequence. This will give a separate convergence curve for each dependent variable.

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If the model includes friction, try solving the problem without friction first if possible. When the study works without friction, then enable friction.

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Always solve contact problems that contain friction or decohesion incrementally, using a parametric or time-dependent solver. The evolution of the friction forces is history dependent. For contact problems without friction, an incremental strategy is not necessary but often a good choice.

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The convergence for many contact problem can often be improved by modifying the parameter or time step algorithm. For a stationary study, you can tune the step size in the node, and for a time dependent study, you can modify the time stepping in the .

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For models that include decohesion, see also suggestions under Decohesion.