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dc.contributor.authorPeherstorfer, Benjamin
dc.contributor.authorBaptista, Ricardo Miguel
dc.contributor.authorMarzouk, Youssef M
dc.contributor.authorWillcox, Karen E
dc.date.accessioned2018-04-09T13:49:03Z
dc.date.available2018-04-09T13:49:03Z
dc.date.issued2017-01
dc.identifier.isbn978-1-62410-453-4
dc.identifier.urihttp://hdl.handle.net/1721.1/114613
dc.description.abstractDesign of complex engineering systems requires coupled analyses of the multiple disciplines affecting system performance. The coupling among disciplines typically contributes significantly to the computational cost of analyzing the system, and can become particularly burdensome when coupled analyses are embedded within a design or optimization loop. In many cases, disciplines may be weakly coupled, so that some of the coupling or interaction terms can be neglected without significantly impacting the accuracy of the system output. However, typical practice derives such approximations in an ad hoc manner using expert opinion and domain experience. This paper proposes a new approach that formulates an optimization problem to find a model that optimally balances accuracy of the model outputs with the sparsity of the discipline couplings. An adaptive sequential Monte Carlo sampling-based technique is used to efficiently search the combinatorial model space of different discipline couplings. Finally, an algorithm for optimal model selection is presented and applied to identify the important discipline couplings in a fire detection satellite model and a turbine engine cycle analysis model.en_US
dc.description.sponsorshipUnited States. Air Force. Office of Scientific Research. Multidisciplinary University Research Initiative (Award FA9550-15-1-0038)en_US
dc.publisherAmerican Institute of Aeronautics and Astronautics (AIAA)en_US
dc.relation.isversionofhttp://dx.doi.org/10.2514/6.2017-1935en_US
dc.rightsCreative Commons Attribution-Noncommercial-Share Alikeen_US
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/4.0/en_US
dc.sourceOther univ. web domainen_US
dc.titleOptimal Approximations of Coupling in Multidisciplinary Modelsen_US
dc.typeArticleen_US
dc.identifier.citationBaptista, Ricardo, et al. “Optimal Approximations of Coupling in Multidisciplinary Models.” 58th AIAA/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference, 9-13 January 5, 2017, Grapevine, Texas, American Institute of Aeronautics and Astronautics (AIAA), 2017.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Aeronautics and Astronauticsen_US
dc.contributor.mitauthorBaptista, Ricardo Miguel
dc.contributor.mitauthorMarzouk, Youssef M
dc.contributor.mitauthorWillcox, Karen E
dc.relation.journal58th AIAA/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conferenceen_US
dc.eprint.versionAuthor's final manuscripten_US
dc.type.urihttp://purl.org/eprint/type/ConferencePaperen_US
eprint.statushttp://purl.org/eprint/status/NonPeerRevieweden_US
dc.date.updated2018-04-04T15:16:28Z
dspace.orderedauthorsBaptista, Ricardo; Marzouk, Youssef; Willcox, Karen E.; Peherstorfer, Benjaminen_US
dspace.embargo.termsNen_US
dc.identifier.orcidhttps://orcid.org/0000-0002-0421-890X
dc.identifier.orcidhttps://orcid.org/0000-0001-8242-3290
dc.identifier.orcidhttps://orcid.org/0000-0003-2156-9338
mit.licenseOPEN_ACCESS_POLICYen_US


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