A novel reliability evaluation method for large engineering systems
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Univ Arizona, Dept Civil Engn & Engn MechIssue Date
2016-06
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A novel reliability evaluation method for large engineering systems 2016, 7 (2):613 Ain Shams Engineering JournalJournal
Ain Shams Engineering JournalRights
Copyright © 2016 Faculty of Engineering, Ain Shams University. Production and hosting by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).Collection Information
This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at repository@u.library.arizona.edu.Abstract
A novel reliability evaluation method for large nonlinear engineering systems excited by dynamic loading applied in time domain is presented. For this class of problems, the performance functions are expected to be function of time and implicit in nature. Available first-or second-order reliability method (FORM/SORM) will be challenging to estimate reliability of such systems. Because of its inefficiency, the classical Monte Carlo simulation (MCS) method also cannot be used for large nonlinear dynamic systems. In the proposed approach, only tens instead of hundreds or thousands of deterministic evaluations at intelligently selected points are used to extract the reliability information. A hybrid approach, consisting of the stochastic finite element method (SFEM) developed by the author and his research team using FORM, response surface method (RSM), an interpolation scheme, and advanced factorial schemes, is proposed. The method is clarified with the help of several numerical examples. (C) 2016 Faculty of Engineering, Ain Shams University. Production and hosting by Elsevier B.V.ISSN
20904479Version
Final published versionAdditional Links
http://linkinghub.elsevier.com/retrieve/pii/S2090447916000162ae974a485f413a2113503eed53cd6c53
10.1016/j.asej.2016.01.007
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Except where otherwise noted, this item's license is described as Copyright © 2016 Faculty of Engineering, Ain Shams University. Production and hosting by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

