Uncertainty Quantification by MLMC and Local Time-stepping For Wave Propagation

TL;DR

This paper introduces a novel approach combining Multilevel Monte Carlo with local time-stepping to efficiently perform uncertainty quantification in wave propagation problems with complex geometries, overcoming CFL constraints.

Contribution

It proposes integrating MLMC with local time-stepping to handle complex geometries, maintaining efficiency and explicitness in uncertainty quantification.

Findings

Significant reduction in computational cost with local refinement.

Effective handling of complex geometries without sacrificing explicitness.

Restoration of MLMC efficiency through local time adaptation.

Abstract

Because of their robustness, efficiency and non-intrusiveness, Monte Carlo methods are probably the most popular approach in uncertainty quantification to computing expected values of quantities of interest (QoIs). Multilevel Monte Carlo (MLMC) methods significantly reduce the computational cost by distributing the sampling across a hierarchy of discretizations and allocating most samples to the coarser grids. For time dependent problems, spatial coarsening typically entails an increased time-step. Geometric constraints, however, may impede uniform coarsening thereby forcing some elements to remain small across all levels. If explicit time-stepping is used, the time-step will then be dictated by the smallest element on each level for numerical stability. Hence, the increasingly stringent CFL condition on the time-step on coarser levels significantly reduces the advantages of the multilevel approach. To overcome that bottleneck we propose to combine the multilevel approach of MLMC with local time-stepping (LTS). By adapting the time-step to the locally refined elements on each level, the efficiency of MLMC methods is restored even in the presence of complex geometry without sacrificing the explicitness and inherent parallelism. In a careful cost comparison, we quantify the reduction in computational cost for local refinement either inside a small fixed region or towards a reentrant corner.