Improving the performance of the partitioned QN-ILS procedure for fluid–structure interaction problems: Filtering

• Performance of QN-ILS can be improved with data from previous time steps.
• When this is done, filtering might be necessary.
• Filtering is a compromise, as discarding data might impair the convergence speed.
• We introduce two new ways of filtering. Better results are obtained.

The Quasi-Newton Inverse Least Squares method has become a popular method to solve partitioned interaction problems. Its performance can be enhanced by using information from previous time-steps if care is taken of the possible ill-conditioning that results. To enhance the stability, filtering has been used. In this paper we show that a relatively minor modification to the filtering technique can substantially reduce the required number of iterations.