Iterative Solvers

Iterative ICCF

This method is recommended for large-scale problems with a small number of right-hand sides.

• Memory use: high.
• Disk use: not used.
• Speed estimation: fast (for well-conditioned problems).
• Quantity of equations:15 000 - 1,000,000 equations and more.
• Supported analyses: linear statics, modal analysis, buckling.
• Available analysis limitations: N/A.
• Other limitations:
  • The correctness of structure restrictions is not checked.
  • Slow convergence if some problems are incorrectly conditioned.

Iterative diagonal

This method is recommended for large-scale problems with a small number of right-hand sides.

• Memory use: minimal
• Disk use: minimal
• Speed estimation: slow
• Quantity of equations:15 000 - 1,000,000 equations and more.
• Supported analyses: linear statics, modal analysis, buckling.
• Available analysis limitations: N/A
• Other limitations:
  • The correctness of structure restrictions is not checked.
  • Slow convergence if some problems are incorrectly conditioned.

Iterative Gauss-Cholesky

This method is recommended for large-scale problems with a small number of right-hand sides, when there's is not enough RAM to use the ICCF method.

The verification of each element matrix is conducted by means of the Vinget regularization procedure ¹².

• Memory use: minimal
• Disk use: minimal
• Speed estimation: slow
• Quantity of equations:15 000 - 1,000,000 equations and more.
• Supported analyses: linear statics, modal analysis, buckling.
• Available analysis limitations: N/A
• Other limitations:
  • The correctness of structure restrictions is not checked.
  • Slow convergence if some problems are incorrectly conditioned.

Iterative multilevel ICCF

This method is recommended for large-scale problems with a small number of right-hand sides. It shows a quicker convergence than the iterative ICCF method.

• Memory use: high
• Disk use: minimal
• Speed estimation: quick for well-conditioned problems
• Quantity of equations:15 000 - 1,000,000 equations and more.
• Supported analyses: linear statics, modal analysis, buckling.
• Available analysis limitations: available structure types: 3D (bar, shell, solid and all special finite elements), 2D frame.
• Other limitations:
  • The correctness of structure restrictions is not checked.
  • Less stable convergence, in a few cases.

Iterative multilevel diagonal

This method is considerably slower than the iterative multilevel ICCF. However, it requires much less RAM memory.

The Smoothing method 2 usually requires fewer iterations compared to the iterative multilevel ICCF method.

The verification of each element matrix is conducted by means of the Vinget regularization procedure ^1,2.

• Memory use: minimal
• Disk use: minimal
• Speed estimation: slow
• Quantity of equations:15 000 - 1,000,000 equations and more.
• Supported analyses: linear statics, modal analysis, buckling.
• Available analysis limitations: available structure types: 3D (bar, shell, solid and all special finite elements), 2D frame.
• Other limitations:
  • The correctness of structure restrictions is not checked.

Iterative multilevel Gauss-Cholesky

This method is considerably slower than the iterative multilevel ICCF. However, it requires much less RAM memory.

The Smoothing method 2 usually requires fewer iterations compared to the iterative multilevel ICCF method.

The verification of each element matrix is conducted by means of the Vinget regularization procedure ^1,2.

• Memory use: minimal
• Disk use: minimal
• Speed estimation: medium (for well-conditioned problems)
• Quantity of equations:15 000 - 1,000,000 equations and more.
• Supported analyses: linear statics, modal analysis, buckling.
• Available analysis limitations: available structure types: 3D (bar, shell, solid and all special finite elements), 2D frame.
• Other limitations:
  • The correctness of structure restrictions is not checked.