Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
509729 | Computers & Structures | 2016 | 9 Pages |
Abstract
•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.
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Science Applications
Authors
R. Haelterman, A.E.J. Bogaers, K. Scheufele, B. Uekermann, M. Mehl,