The multigrid in energy preconditioner scales well in the energy dimension and significantly reduces the number of Krylov iterations required for convergence.
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Dec 3, 2016 · The multigrid in energy preconditioner scales well in the energy dimension and significantly reduces the number of Krylov iterations required ...
Multigrid in energy. Preconditioning is important for increasing the robustness of Krylov methods. This is particularly true for the multigroup Krylov solver.
The multigrid in energy preconditioner scales well in the energy dimension and significantly reduces the number of Krylov iterations required for convergence.
Using these methods together, RQI converged in fewer iterations and in less time than all PI calculations for a full pressurized water reactor core, ...
The multigrid in energy preconditioner scales well in the energy dimension and significantly reduces the number of Krylov iterations required for convergence.
A right preconditioner that does multigrid in the energy dimension and is designed to work with the MG Krylov solver was implemented in Denovo [4] . To ...
The objective of this work is to identify a relatively simple and efficient multigrid preconditioner of Krylov methods when solving the neutron noise ...
Application of multigrid preconditioner (V-cycle). ▷ Apply pre-smoother on fine level (any preconditioner). ▷ Restrict residual to coarse level with I ...
We study multigrid preconditioning of matrix-free Newton--Krylov methods as a means of developing more efficient nonlinear iterative methods for large scale ...