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dc.contributor.authorWang, Pingfeng
dc.contributor.authorWang, Zequn
dc.contributor.authorAlmaktoom, Abdulaziz T.
dc.date.accessioned2014-04-08T14:51:05Z
dc.date.available2014-04-08T14:51:05Z
dc.date.issued2014-06-03
dc.identifier.citationWang, Pingfeng; Wang, Zequn; Almaktoom, Abdulaziz T. 2014. Dynamic reliability-based robust design optimization with time-variant probabilistic constraints. Engineering Optimization, vol. 46:no. 6:ppg. 784-809en_US
dc.identifier.issn0305-215X
dc.identifier.otherWOS:000332146600004
dc.identifier.urihttp://dx.doi.org/10.1080/0305215X.2013.795561
dc.identifier.urihttp://hdl.handle.net/10057/10543
dc.descriptionClick on the DOI link to access the article (may not be free).en_US
dc.description.abstractWith the increasing complexity of engineering systems, ensuring high system reliability and system performance robustness throughout a product life cycle is of vital importance in practical engineering design. Dynamic reliability analysis, which is generally encountered due to time-variant system random inputs, becomes a primary challenge in reliability-based robust design optimization (RBRDO). This article presents a new approach to efficiently carry out dynamic reliability analysis for RBRDO. The key idea of the proposed approach is to convert time-variant probabilistic constraints to time-invariant ones by efficiently constructing a nested extreme response surface (NERS) and then carry out dynamic reliability analysis using NERS in an iterative RBRDO process. The NERS employs an efficient global optimization technique to identify the extreme time responses that correspond to the worst case scenario of system time-variant limit state functions. With these extreme time samples, a kriging-based time prediction model is built and used to estimate extreme responses for any given arbitrary design in the design space. An adaptive response prediction and model maturation mechanism is developed to guarantee the accuracy and efficiency of the proposed NERS approach. The NERS is integrated with RBRDO with time-variant probabilistic constraints to achieve optimum designs of engineered systems with desired reliability and performance robustness. Two case studies are used to demonstrate the efficacy of the proposed approach.en_US
dc.description.sponsorshipNational Science Foundation grant CMMI-1200597.en_US
dc.language.isoen_USen_US
dc.publisherTaylor & Francis LTDen_US
dc.relation.ispartofseriesEngineering Optimization;v.46:no.6
dc.subjectDynamic reliabilityen_US
dc.subjectTime-varianten_US
dc.subjectRobust designen_US
dc.subjectOptimizationen_US
dc.subjectResponse surfaceen_US
dc.titleDynamic reliability-based robust design optimization with time-variant probabilistic constraintsen_US
dc.typeArticleen_US


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    Research works published by faculty and students of the Department of Industrial, Systems, and Manufacturing Engineering

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