Multi-Level Monte Carlo Finite Volume methods for uncertainty quantification of acoustic wave propagation in random heterogeneous layered medium


Date

2014-09

Publication Type

Report

ETH Bibliography

yes

Citations

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Data

Abstract

We consider the very challenging problem of efficient uncertainty quantification for acoustic wave propagation in a highly heterogeneous, possibly layered, random medium, characterized by possibly anisotropic, piecewise log-exponentially distributed Gaussian random fields. A multi-level Monte Carlo finite volume method is proposed, along with a novel, bias-free upscaling technique that allows to represent the input random fields, generated using spectral FFT methods, efficiently. Combined together with a novel, dynamic load balancing algorithm that scales to massively parallel computing architectures, the proposed method is able to robustly compute uncertainty for highly realistic random subsurface formations that can contain a very high number (millions) of sources of uncertainty. Numerical experiments, in both two and three space dimensions, illustrating the efficiency of the method are presented.

Publication status

published

Editor

Book title

Volume

2014-22

Pages / Article No.

Publisher

Seminar for Applied Mathematics, ETH Zurich

Event

Edition / version

Methods

Software

Geographic location

Date collected

Date created

Subject

Organisational unit

03435 - Schwab, Christoph / Schwab, Christoph check_circle
03851 - Mishra, Siddhartha / Mishra, Siddhartha check_circle
02501 - Seminar für Angewandte Mathematik / Seminar for Applied Mathematics check_circle

Notes

Funding

247277 - Automated Urban Parking and Driving (EC)

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