Journal article
An empirical interpolation and model-variance reduction method for computing statistical outputs of parametrized stochastic partial differential equations
- Abstract:
-
We present an empirical interpolation and model-variance reduction method for the fast and reliable computation of statistical outputs of parametrized stochastic elliptic partial differential equations. Our method consists of three main ingredients: (1) the real-time computation of reduced basis (RB) outputs approximating high-fidelity outputs computed with the hybridizable discontinuous Galerkin (HDG) discretization; (2) the empirical interpolation (EI) for an efficient offline-online decoup...
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- Publication status:
- Published
- Peer review status:
- Peer reviewed
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Authors
Funding
+ Air Force Office of Scientific Research
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Grant:
FA9550-11-1-0141
FA9550-12-0357
Singapore-MIT Alliance
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Bibliographic Details
- Publisher:
- SIAM/ASA Publisher's website
- Journal:
- SIAM / ASA Journal on Uncertainty Quantification Journal website
- Publication date:
- 2016-01-01
- ISSN:
-
2166-2525
Item Description
- Pubs id:
-
pubs:599369
- UUID:
-
uuid:a831c34d-243f-4c1f-803e-93b572685d14
- Local pid:
- pubs:599369
- Source identifiers:
-
599369
- Deposit date:
- 2016-02-06
Terms of use
- Copyright holder:
- SIAM/ASA
- Copyright date:
- 2016
- Notes:
- Copyright © by SIAM and ASA. Copublished by SIAM (Society for Industrial and Applied Mathematics) and ASA (American Statistical Association). This is the accepted manuscript version of the article. The final version will be available online from SIAM/ASA after publication.
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