RT Journal Article
T1 Uncertainty quantification in tsunami modeling using multi-level Monte Carlo finite volume method
A1 Sánchez-Linares, Carlos
A1 De-la-Asunción-Hernández, Marc
A1 Castro-Díaz, Manuel Jesús
A1 González-Vida, José Manuel
A1 Macías-Sánchez, Jorge
A1 Mishra, Siddhartha
K1 Maremotos
AB Shallow-water type models are commonly used in tsunami simulations. These models contain uncertain parameters like the ratio of densities of layers, friction coefficient, fault deformation, etc. These parameters are modeled statistically and quantifying the resulting solution uncertainty (UQ) is a crucial task in geophysics. We propose a paradigm for UQ that combines the recently developed path-conservative spatial discretizations efficiently implemented on cluster of GPUs, with the recently developed Multi-Level Monte Carlo (MLMC) statistical sampling method and provides a fast, accurate and computationally efficient framework to compute statistical quantities of interest. Numerical experiments, including realistic simulations in real bathymetries, are presented to illustrate the robustness of the proposed UQ algorithm.
PB SpringerOpen
YR 2016
FD 2016-06-08
LK https://hdl.handle.net/10630/32891
UL https://hdl.handle.net/10630/32891
LA eng
NO Sánchez-Linares, C., de la Asunción, M., Castro, M.J. et al. Uncertainty quantification in tsunami modeling using multi-level Monte Carlo finite volume method. J.Math.Industry 6, 5 (2016). https://doi.org/10.1186/s13362-016-0022-8
DS RIUMA. Repositorio Institucional de la Universidad de Málaga
RD 21 ene 2026