Skip to article

 

Tracking the Process of Solving a Nonlinear Problem Based on Convergence.log

Let us consider the process of solving equations for nonlinear processes using the example static setting.

After standard finite element discretization of the equilibrium equation the task boils down to the following: find the vector of nodal displacements u n+1, satisfying the equation: nonlinear processes using the example static setting.

where f int , f ext - vectors of internal and external forces at the nodes, respectively.

This equation is nonlinear. In CAE Fidesys it is solved using the Newton-Raphson iterative method. Each iteration of this method represents solution of linearized problem (1).

Let the approximation be known . Then iteration ( k ) of the Newton-Raphson method is reduced to a linear system of equations:

where r (k-1) , δu (k) - absolute force increments and displacements, respectively (in CAE Fidesys absolute residuals | r (k-1)  | , | δu (k) | designated as ABS. FORCE RESIDUAL, ABS. VARIABLE RESIDUAL).

Having solved system (2), we update the nodal movements in the form:

The solution process by the Newton-Raphson method is illustrated using the figure:

The criteria for stopping the iterative process depend on the characteristics of the model.

Let's look at them in more detail.

Let us introduce the concept of relative residuals of forces and displacements, respectively:.

Their equivalents in CAE Fidesys are denoted as REL. FORCE RESIDUAL and REL. VARIABLE RESIDUAL.

Then the rationale for the conclusion about solution (2) and stopping the iterative process follows from the standard sentences:

This criterion is used for cases not presented in 1 and 2. In fact, we are talking about calculations with finite deformations, possibly going in conjunction with other nonlinearities.

Nonlinear calculation may end for the following reasons:

In cases 2 and 3, a possible solution would be to increase the minimum number steps or maximum number of iterations. However, if the number of iterations more than 20, this means the convergence is very slow and it is advisable to check statement of the problem. You can also pay attention to cases where the residuals increase during iterations, usually this is a sign that the problem will not converge.

Substeps

Let us introduce the concept of substeps for a nonlinear problem. The convergence of the problem depends from the initial approximation, the further it is from the solution, the worse the convergence. To fix this you need to apply a smaller fraction of the load (column RATIO), to reduce displacement increments. To control data Several parameters are entered in substeps:

If a substep converges, then the length of the next step will increase, until until it reaches 1/(number of minimum substeps).

If a substep diverges, it will be restarted with a zero initial approximation. Then, in case of failure, the length of the substep will be halved and decrease until it reaches the value 1/(number of maximum substeps). In this case, the calculation will fail.

Additionally, the length of the substep can be reduced in plastic problems, if plastic deformations exceed a certain threshold.

In static tasks, the LOAD TIME column indicates the current time. This time is conditional and equal to 1 for one static step. Column RATIO shows the proportion of applied loads of this static step.

For dynamic nonlinear problems, the algorithm for splitting steps is described above is also applicable, however in this type of calculation there are dynamic time steps replace the minimum number of steps, and setting the number of initial steps are ignored.

The LOAD TIME column indicates the current time, and the RATIO column shows the proportion of applied loads for a given step.

NOTES:

The figure below shows an example of the contents of the Convergence.log file (for tasks with settings: 2 - static steps, minimum number of substeps - 2, maximum number of substeps - 8, maximum number of iterations - 10):