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dc.contributor.advisorWang, Pingfeng
dc.contributor.authorCui, Xiaolong
dc.date.accessioned2016-11-14T21:53:50Z
dc.date.available2016-11-14T21:53:50Z
dc.date.issued2016-05
dc.identifier.othert16005
dc.identifier.urihttp://hdl.handle.net/10057/12650
dc.descriptionThesis (M.S.)--Wichita State University, College of Engineering, Dept. of Industrial and Manufacturing Engineering
dc.description.abstractFailure of practical engineering systems could be induced by several correlated failure modes, and consequently reliability analysis are conducted with multiple disjoint failure regions in the system random input space. Disjoint failure regions create a great challenge for existing reliability analysis approaches due to the discontinuity of the system performance function. This paper presents a new enhanced Monte Carlo simulation (EMCS) approach for reliability analysis and design considering disjoint failure regions. Kriging method is adopted to construct the surrogate model. An adaptive maximum failure potential based sampling scheme is developed to iteratively search failure samples and update the Kriging model. The reliability is assessed by using the updated Kriging model to predict the response of a final set of test data. Three case studies are used to demonstrate the efficacy of the proposed methodology.
dc.format.extentxi, 20 p.
dc.language.isoen_US
dc.publisherWichita State University
dc.rightsCopyright 2016 Xiaolong Cui
dc.subject.lcshElectronic dissertations
dc.titleReliability analysis and design considering disjoint active failure regions
dc.typeThesis


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