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Sparse Tensor Product Discretization of Stochastic PDE

Project Leader: Prof. Dr. Ch. Schwab
Current Researchers: Claude Gittelson (Seminar for Applied Mathematics, ETH Zurich)
Dr. Andrea Barth (Seminar for Applied Mathematics, ETH Zurich)
Roman Andreev (Seminar for Applied Mathematics, ETH Zurich)
Claude Gittelson (Seminar for Applied Mathematics, ETH Zurich)
Former Researchers Dr. Bastian Pentenrieder
Dr. Marcel Bieri

Description


Parameters in boundary value problems are often incompletely known. Modeling them as random variables or random fields, the solution to a boundary value problem also becomes a random field. In general, it can be interpreted as a parametric element of a function space, with an infinite dimensional parameter domain. Stochastic moments of the solution can be computed directly as functions on higher dimensional domains.

Various sparse tensorization techniques exist to deal with the high dimensionality either of the parameter domain or in the moment equations. We consider multilevel Monte Carlo methods, sparse tensor collocation, and Galerkin methods using generalized polynomial chaos bases. In particular, we develop adaptive techniques for selecting active polynomial chaos modes.

Funding

References

Contacts

Prof. Christoph Schwab
Claude Gittelson
Dr. Andrea Barth

 

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