CEE Seminar: Uncertainty Quantification via a Multi-Fidelity Model Reduction Approach
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April 10, 2018 - 12:00pm to 1:00pm
Alireza Doostan, Associate Professor, Aerospace, University of Colorado at Boulder
Realistic analysis and design of multi-disciplinary engineering systems require not only a fine understanding and modeling of the underlying physics and their interactions but also recognition of intrinsic uncertainties and their influences on the quantities of interest. Uncertainty Quantification (UQ) is an emerging discipline that attempts to address the latter issue: It aims at a meaningful characterization of uncertainties from the available measurements, as well as efficient propagation of these uncertainties through the governing equations for a quantitative validation of model predictions. The use of model reduction has become widespread as a means to reduce computational cost of UQ of complex engineering systems. This talk introduces a model reduction technique that exploits the low-rank structure of the uncertain solution of interest - when exists - for fast propagation of high-dimensional uncertainties. To construct this low-rank approximation, the proposed method utilizes models with lower fidelities (hence cheaper to simulate) than the intended high-fidelity model.....