Abstract
In this paper two types of local sparse preconditioners are generalized to solve three-dimensional Helmholtz problems iteratively. The iterative solvers considered are the conjugate gradient normal method (CGN) and the generalized minimal residual method (GMRES).
Both types of preconditioners can ensure a better eigenvalue clustering for the normal equation matrix and thus a faster convergence of CGN. Clustering of the eigenvalues of the preconditioned matrix is also observed. We consider a general surface configuration approximated by piecewise quadratic elements defined over unstructured triangular partitions. We present some promising numerical results.
| Original language | English |
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| Pages (from-to) | 475-489 |
| Number of pages | 15 |
| Journal | Applied Numerical Mathematics |
| Volume | 36 |
| Issue number | 4 |
| Publication status | Published - Mar 2001 |