Explicit scheme : By varying the mesh size, we see that for smaller sizes, the computation time for the usual mass matrix (not diagonal) exceeds that of the lumped mass matrix (diagonal). This I understand. But when the mesh size becomes large the computation time for the lumped mass matrix (diagonal) exceeds that of the usual mass matrix (not diagonal). Why ?
A reason can be:
While solving the problem, matrix inversion is required, and the usual mass matrix, if it is sparse, is favored due to its sparsity advantages over the lumped mass matrix.
That's what I said for the first case, but for the second case the explanation it's not that. I think it has to do with stability maybe.
For the first case, Usual non-diagonal matrix can have more non-zero elements, increasing the computation time as compared to the lumped mass diagonal matrix.
No. There are things you didn't consider in my subject, I specified "by varying the mesh". "But when the mesh size becomes large the computation time for the lumped mass matrix (diagonal) exceeds that of the usual mass matrix (not diagonal)." and precisely the calculation time is greater for the lumped mass matrix, which is not usually the case. And there are words you use that are not clear and mean everything and nothing like: if it is sparse, sparsity advantages.
My first answer was for the second case and other for the first case.
Do read it again.
By sparsity advantages, I mean to say that sparse matrix has computational benefits than diagonal matrix for large sizes.
- Badges
- Science topic
- Similar topics
- Biological Science
- Physiology
- Physiological Processes
- Stress