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2021-11-23
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Structure Stability

The Structure Stability is an add-on that can be activated in the Base Data. This add-on allows you to perform a nonlinear stability analysis using the incremental method to obtain the results close to reality also for nonlinear structures. The critical load factor is determined in such a way that the loads of the underlying load case are gradually increased until the instability is reached. This load increment takes into account nonlinearities, such as failing members, supports, and foundations, as well as material nonlinearities. After the load increment, you can optionally perform a linear stability analysis on the last stable state in order to determine the stability mode. These can be displayed in the Results navigator.

The Structure Stability add-on in the new program generations RFEM 6 and RSTAB 9 adopts the function of the add-on modules RF‑STABILITY (RFEM 5) or RSBUCK (RSTAB 8), but it includes some new features.

  • Activation as a property of a load case or a load combination
  • Automated activation of the stability calculation via combination wizards for several load situations in one step
  • Incremental load increase with user-defined termination criteria
  • Modification of the mode shape normalization without recalculation
  • Result tables with filter option

Usage in Program

The program provides various methods for the eigenvalue analysis:

Direct Methods
The direct methods are useful for the models of small and medium size. These fast methods for equation solvers benefit from a lot of the computer memory (RAM). The following direct methods are available:

  • Lanczos (RFEM)
  • Roots of Characteristic Polynomial (RFEM)
  • Subspace Iteration Method (RFEM/RSTAB)
  • Shifted Inverse Iteration (RSTAB)

ICG Iteration Method (Incomplete Conjugate Gradient [RFEM])
Using this method, the eigenvalues are determined one after the other, so this method requires only little working memory and can therefore be used, for example, for the calculation of very complex structures with few eigenvalues.