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- W3019258177 abstract "Monte Carlo methods are probably the most popular approach in uncertainty quantification to compute expected values of quantities of interest (QoIs). Multilevel Monte Carlo (MLMC) methods significantly reduce the computational cost by distributing the sampling across a mesh hierarchy and restricting most samples to the coarser grids. Geometric constraints, however, may impede uniform coarsening thereby forcing some elements to remain small across all levels. Then, the increasingly stringent CFL stability condition on the time-step on coarser levels effectively nullifies the advantages of the multilevel approach. By adapting the time-step to the locally refined elements on each level, local time-stepping (LTS) methods permit to restore the efficiency of MLMC methods even in the presence of complex geometry without sacrificing the explicitness and inherent parallelism." @default.
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- W3019258177 date "2019-01-01" @default.
- W3019258177 modified "2023-09-28" @default.
- W3019258177 title "Efficient Uncertainty Quantification for Wave Propagation in Complex Geometry" @default.
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