A decomposition-based approach to uncertainty analysis of feed-forward multicomponent systems
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Willcox_A decomposition.pdf
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Author(s)
Amaral, Sergio M.
Allaire, Douglas L.
Willcox, Karen E.
Date Issued
October 2014
Journal
International Journal for Numerical Methods in Engineering
Publisher
Wiley Blackwell
Citation
Amaral, Sergio, Douglas Allaire, and Karen Willcox. “A Decomposition-Based Approach to Uncertainty Analysis of Feed-Forward Multicomponent Systems.” Int. J. Numer. Meth. Engng 100, no. 13 (October 21, 2014): 982–1005.
Version
Author's final manuscript
Abstract
To support effective decision making, engineers should comprehend and manage various uncertainties throughout the design process. Unfortunately, in today's modern systems, uncertainty analysis can become cumbersome and computationally intractable for one individual or group to manage. This is particularly true for systems comprised of a large number of components. In many cases, these components may be developed by different groups and even run on different computational platforms. This paper proposes an approach for decomposing the uncertainty analysis task among the various components comprising a feed-forward system and synthesizing the local uncertainty analyses into a system uncertainty analysis. Our proposed decomposition-based multicomponent uncertainty analysis approach is shown to be provably convergent in distribution under certain conditions. The proposed method is illustrated on quantification of uncertainty for a multidisciplinary gas turbine system and is compared to a traditional system-level Monte Carlo uncertainty analysis approach.
MIT Department
Massachusetts Institute of Technology. Department of Aeronautics and Astronautics
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Creative Commons Attribution-Noncommercial-Share Alike
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DOI of Published Version
https://doi.org/10.1002/nme.4779
