Publication Date:
2013-08-10
Description:
In [ Chen et al ., 2013], the fundamental concepts of the modular UQ methodology has been introduced for multi-physics applications in which each physics module can be independently embedded with its internal UQ method (intrusive or non-intrusive). Although the methodology offers the advantage of “plug-and-play” flexibility for general multi-physics systems without losing the global uncertainty propagation property, it is inadequate to quantify uncertainties of reactive transport in heterogeneous porous media. In the current paper, we extend the modular UQ methodology to subsurface flow and reactive transport applications, which are characterized by high dimensionality in the stochastic space due to spatially random velocity field in randomly heterogeneous porous media. Specifically, we develop a scheme to reduce the dimension of the stochastic space. This is achieved via a doubly-nested dimension reduction by applying Karhunen-Loeve expansion [ Karhunen , 1947; Kac and Siegert , 1947] to the logarithmic hydraulic conductivity field and Proper Orthogonal Decomposition [ Pearson , 1901; Hotelling , 1933] to the velocity field. This scheme enables the modular UQ framework to handle spatially random models efficiently while maintaining solution accuracy. When compared against sampling-based non-intrusive UQ methods, the modular UQ method demonstrates a similar accuracy at a fraction of computational cost on designed numerical experiments.
Print ISSN:
0043-1397
Electronic ISSN:
1944-7973
Topics:
Architecture, Civil Engineering, Surveying
,
Geography
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