Library Subscription: Guest
Begell Digital Portal Begell Digital Library eBooks Journals References & Proceedings Research Collections
International Journal for Uncertainty Quantification
IF: 4.911 5-Year IF: 3.179 SJR: 1.008 SNIP: 0.983 CiteScore™: 5.2

ISSN Print: 2152-5080
ISSN Online: 2152-5099

Open Access

International Journal for Uncertainty Quantification

DOI: 10.1615/Int.J.UncertaintyQuantification.2016016646
pages 271-286

FAST AND ACCURATE MODEL REDUCTION FOR SPECTRAL METHODS IN UNCERTAINTY QUANTIFICATION

Francisco Damascene Freitas
Department of Electrical Engineering, University of Brasilia, CEP: 70910-900, Brasilia, DF, Brazil
Roland Pulch
Institute for Mathematics and Computer Science, University of Greifswald, Walther-Rathenau-Str. 47, D-17489 Greifswald, Germany
Joost Rommes
Mentor Graphics, 110 rue Blaise Pascal, Montbonnot, France

ABSTRACT

A fast and accurate model order reduction procedure is presented that can successfully be applied to spectral methods for uncertainty quantification problems. The main novelties include (1) the application of model order reduction to uncertainty quantification problems; (2) the improvement of existing model order reduction methods in order to meet the accuracy and performance requirements; and (3) an efficient approach for systems with many outputs. Numerical experiments for large-scale realistic systems illustrate the suitability and performance (50× speedup while preserving accuracy) for uncertainty quantification problems.


Articles with similar content:

DIMENSIONALITY REDUCTION FOR COMPLEX MODELS VIA BAYESIAN COMPRESSIVE SENSING
International Journal for Uncertainty Quantification, Vol.4, 2014, issue 1
Bert J. Debusschere, Habib Najm, Peter Thornton, Cosmin Safta, Khachik Sargsyan, Daniel Ricciuto
A MULTI-FIDELITY STOCHASTIC COLLOCATION METHOD FOR PARABOLIC PARTIAL DIFFERENTIAL EQUATIONS WITH RANDOM INPUT DATA
International Journal for Uncertainty Quantification, Vol.4, 2014, issue 3
Maziar Raissi, Padmanabhan Seshaiyer
DATA ASSIMILATION FOR NAVIER-STOKES USING THE LEAST-SQUARES FINITE-ELEMENT METHOD
International Journal for Uncertainty Quantification, Vol.8, 2018, issue 5
Richard P. Dwight, Alexander Schwarz
A NEW INVERSE METHOD FOR THE UNCERTAINTY QUANTIFICATION OF SPATIALLY VARYING RANDOM MATERIAL PROPERTIES
International Journal for Uncertainty Quantification, Vol.6, 2016, issue 6
Gun Jin Yun, Shen Shang
A LOCALIZED RBF-MQ MESHLESS METHOD FOR SIMULATING COMPRESSIBLE FLOWS
Second Thermal and Fluids Engineering Conference, Vol.2, 2017, issue
Ebrahim Nabizadeh, Darrell W. Pepper