Show simple item record

dc.contributor.authorLi, Mingyang
dc.contributor.authorBai, Guangxing
dc.contributor.authorWang, Zequn
dc.identifier.citationLi, Mingyang; Bai, Guangxing; Wang, Zequn. 2018. Time-variant reliability-based design optimization using sequential kriging modeling. Structural and Multidisciplinary Optimization, vol. 58:no. 3:pp 1051-1065en_US
dc.descriptionClick on the DOI link to access the article (may not be free).en_US
dc.description.abstractThis paper presents a sequential Kriging modeling approach (SKM) for time-variant reliability-based design optimization (tRBDO) involving stochastic processes. To handle the temporal uncertainty, time-variant limit state functions are transformed into time-independent domain by converting the stochastic processes and time parameter to random variables. Kriging surrogate models are then built and enhanced by a design-driven adaptive sampling scheme to accurately identify potential instantaneous failure events. By generating random realizations of stochastic processes, the time-variant probability of failure is evaluated by the surrogate models in Monte Carlo simulation (MCS). In tRBDO, the first-order score function is employed to estimate the sensitivity of time-variant reliability with respect to design variables. Three case studies are introduced to demonstrate the efficiency and accuracy of the proposed approach.en_US
dc.publisherSpringer Berlin Heidelbergen_US
dc.relation.ispartofseriesStructural and Multidisciplinary Optimization;v.58:no.3
dc.subjectTime-variant reliability analysisen_US
dc.subjectDesign optimizationen_US
dc.subjectStochastic processesen_US
dc.subjectKriging surrogate modelen_US
dc.titleTime-variant reliability-based design optimization using sequential kriging modelingen_US
dc.rights.holder© 2018, Springer-Verlag GmbH Germany, part of Springer Natureen_US

Files in this item


There are no files associated with this item.

This item appears in the following Collection(s)

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

Show simple item record