dc.contributor.author | Amaral, Sergio M. | |
dc.contributor.author | Allaire, Douglas L. | |
dc.contributor.author | Willcox, Karen E. | |
dc.date.accessioned | 2015-06-05T16:40:46Z | |
dc.date.available | 2015-06-05T16:40:46Z | |
dc.date.issued | 2014-10 | |
dc.date.submitted | 2014-07 | |
dc.identifier.issn | 00295981 | |
dc.identifier.issn | 1097-0207 | |
dc.identifier.uri | http://hdl.handle.net/1721.1/97194 | |
dc.description.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. | en_US |
dc.description.sponsorship | SUTD-MIT International Design Centre | en_US |
dc.description.sponsorship | United States. Defense Advanced Research Projects Agency. META Program (United States. Air Force Research Laboratory Contract FA8650-10-C-7083) | en_US |
dc.description.sponsorship | Vanderbilt University (Contract VU-DSR#21807-S7) | en_US |
dc.description.sponsorship | United States. Federal Aviation Administration. Office of Environment and Energy (FAA Award 09-C-NE-MIT, Amendments 028, 033, and 038) | en_US |
dc.language.iso | en_US | |
dc.publisher | Wiley Blackwell | en_US |
dc.relation.isversionof | http://dx.doi.org/10.1002/nme.4779 | en_US |
dc.rights | Creative Commons Attribution-Noncommercial-Share Alike | en_US |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-sa/4.0/ | en_US |
dc.source | MIT web domain | en_US |
dc.title | A decomposition-based approach to uncertainty analysis of feed-forward multicomponent systems | en_US |
dc.type | Article | en_US |
dc.identifier.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. | en_US |
dc.contributor.department | Massachusetts Institute of Technology. Department of Aeronautics and Astronautics | en_US |
dc.contributor.mitauthor | Amaral, Sergio M. | en_US |
dc.contributor.mitauthor | Allaire, Douglas L. | en_US |
dc.contributor.mitauthor | Willcox, Karen E. | en_US |
dc.relation.journal | International Journal for Numerical Methods in Engineering | en_US |
dc.eprint.version | Author's final manuscript | en_US |
dc.type.uri | http://purl.org/eprint/type/JournalArticle | en_US |
eprint.status | http://purl.org/eprint/status/PeerReviewed | en_US |
dspace.orderedauthors | Amaral, Sergio; Allaire, Douglas; Willcox, Karen | en_US |
dc.identifier.orcid | https://orcid.org/0000-0001-8410-6141 | |
dc.identifier.orcid | https://orcid.org/0000-0003-2156-9338 | |
mit.license | OPEN_ACCESS_POLICY | en_US |
mit.metadata.status | Complete | |