Multi-level Monte Carlo finite volume methods for uncertainty quantification of acoustic wave propagation in random heterogeneous layered medium

JOURNAL OF COMPUTATIONAL PHYSICS

卷:312

Article

Mishra, S.²  Schwab, Ch.¹  Sukys, J.³ 

[1] ETH, HG, Seminar Appl Math, G57-1,Ramistr 101, Zurich, Switzerland

[2] ETH, Seminar Appl Math, HG G57-2,Ramistr 101, Zurich, Switzerland

[3] ETH, Computat Sci & Engn Lab, CLT E 13,Clausiusstr 33, Zurich, Switzerland

关键词: Uncertainty quantification;    Acoustic wave equation;    Multi-level Monte Carlo;    Finite volume method;    Linear scaling;    Log-normal random layered media;    Bias-free upscaling;    High performance computing;   

DOI  :  10.1016/j.jcp.2016.02.014

来源: Elsevier

【 摘 要 】

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 recently developed 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. (C) 2016 Elsevier Inc. Allrightsreserved.

【 授权许可】

Free