Improving approximate matrix factorizations for implicit time integration in air pollution modelling

Share/Save/Bookmark

Botchev, M.A. and Verwer, J.G. (2000) Improving approximate matrix factorizations for implicit time integration in air pollution modelling. [Report]

open access
[img]
Preview
PDF
592kB
Abstract:For a long time operator splitting was the only computationally feasible way of implicit time integration in large scale Air Pollution Models. A recently proposed attractive alternative is Rosenbrock schemes combined with Approximate Matrix Factorization (AMF). With AMF, linear systems arising in implicit time stepping are solved approximately in such a way that the overall computational costs per time step are not higher than those of splitting methods. We propose and discuss two new variants of AMF. The first one is aimed at yet a further reduction of costs as compared with conventional AMF. The second variant of AMF provides in certain circumstances a better approximation to the inverse of the linear system matrix than standard AMF and requires the same computational work.
Item Type:Report
Faculty:
Electrical Engineering, Mathematics and Computer Science (EEMCS)
Research Group:
Link to this item:http://purl.utwente.nl/publications/66898
Official URL:http://db.cwi.nl/rapporten/abstract.php?abstractnr=714
Export this item as:BibTeX
EndNote
HTML Citation
Reference Manager

 

Repository Staff Only: item control page