# How to Improve Convergence for the MLFMM

The MLFMM is an iterative solution method, and under certain conditions, the iterative solution may fail to converge. Several model or solution settings are presented that could improve the model's convergence behaviour.

ERROR 4673: Iterative solution of the system of linear equations failed, maybe try another pre-conditioner (solution settings).

WARNING 830: Maximum number of iterations reached without convergence, using in the following the solution with the smallest residuum.

- Activate additional stabilisation for the MLFMM.
- Adjust the mesh.
- Change the preconditioner.
- Change the default box size.
- Use the CFIE for metallic structures.
- Use double precision.

## Activating Additional Stabilisation for the MLFMM

Activating additional stabilisation may help to achieve convergence for the MLFMM.

## Adjusting the Mesh

Slight adjustments to the mesh size (smaller or larger elements) could lead to improved convergence. If a model is discretised too finely or too coarsely, convergence could be negatively affected.

## Changing the Preconditioner

The sparse LU is the default preconditioner. Changing to another preconditioner may help to achieve convergence for the MLFMM. Select one of the following preconditioners:

- Use the sparse approximate inverse (SPAI) preconditioner.
- The default (accelerated SPAI) preconditioner is fast.
- The non-accelerated SPAI preconditioner takes longer than its accelerated counterpart, but often converges better.

- Use the incomplete LU decomposition (ILU) preconditioner.Restriction: The ILU preconditioner is supported only for sequential solutions.

## Changing the Default MLFMM Box Size

The MLFMM uses a boxing algorithm that encloses the entire computational space in a single box at the highest level, dividing this box in three dimensions into a maximum of eight child boxes and repeating the process iteratively until the side length of each child box is approximately a quarter wavelength at the finest level. Using a different box size at the finest level can sometimes facilitate convergence, although memory consumption could increase if the box size is increased.

The default box size is 0.23. A lower value decreases memory consumption while a higher value increases the memory consumption.

## Using the CFIE on MLFMM Metallic Surfaces

- Use the default preconditioner with the CFIE.
- CFIE can only be applied to surfaces bounding closed PEC structures.
- A mixture of CFIE and EFIE surfaces can be used.
- Sharp corners on CFIE surfaces can lead to inaccurate results.

Sharp corners should be meshed finer if CFIE is applied. If there is uncertainty, the EFIE should rather be applied around sharp corners. A rule of thumb is to apply the EFIE up to a few meshed triangles away from the sharp corners.

## Using Double Precision

The Solver uses single precision by default- a single byte is used to store a complex number.

- Double precision requires twice the memory compared to single precision.
- Double precision does not improve convergence for the stabilised MLFMM.