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• W2023338596 abstract "This work is concerned with the propagation of uncertainty across coupled domain problems with high-dimensional random inputs. A stochastic model reduction approach based on low-rank separated representations is proposed for the partitioned treatment of the uncertainty space. The construction of the coupled domain solution is achieved though a sequence of approximations with respect to the dimensionality of the random inputs associated with each individual sub-domain and not the combined dimensionality, hence drastically reducing the overall computational cost. The coupling between the sub-domain solutions is done via the classical Finite Element Tearing and Interconnecting (FETI) method, thus providing a well suited framework for parallel computing. Two high-dimensional stochastic problems, a 2D elliptic PDE with random diffusion coefficient and a stochastic linear elasticity problem, have been considered to study the performance and accuracy of the proposed stochastic coupling approach." @default.
• W2023338596 created "2016-06-24" @default.
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• W2023338596 date "2014-06-01" @default.
• W2023338596 modified "2023-09-23" @default.
• W2023338596 title "Partitioned treatment of uncertainty in coupled domain problems: A separated representation approach" @default.
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• W2023338596 doi "https://doi.org/10.1016/j.cma.2014.02.004" @default.
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