Multi-Level Monte Carlo Finite Volume methods for uncertainty quantification of acoustic wave propagation in random heterogeneous layered medium
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Date
2014-09
Publication Type
Report
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yes
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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.
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published
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Volume
2014-22
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Publisher
Seminar for Applied Mathematics, ETH Zurich
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Organisational unit
03435 - Schwab, Christoph / Schwab, Christoph
03851 - Mishra, Siddhartha / Mishra, Siddhartha
02501 - Seminar für Angewandte Mathematik / Seminar for Applied Mathematics
Notes
Funding
247277 - Automated Urban Parking and Driving (EC)
Related publications and datasets
Is previous version of: http://hdl.handle.net/20.500.11850/114607