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dc.contributor.authorChen, Zhenzhong
dc.contributor.authorMu, Haoxun
dc.contributor.authorLi, Xiaoke
dc.date.accessioned2024-12-24T18:46:52Z
dc.date.available2024-12-24T18:46:52Z
dc.date.copyright8/2/2024 12:00:00 AM
dc.date.issued2024
dc.identifier.issn2377-2158
dc.identifier.othervvuq_009_02_021006.pdf
dc.identifier.urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4302731
dc.description.abstractIn the study of reliability of systems with multiple failure modes, approximations can be obtained by calculating the probability of failure for each state function. The first-order reliability method and the second-order reliability method are effective, but they may introduce significant errors when dealing with certain nonlinear situations. Simulation methods such as line sampling method and response surface method can solve implicit function problems, but the large amount of calculation results in low efficiency. The curved surface integral method (CSI) has good accuracy in dealing with nonlinear problems. Therefore, a system reliability analysis method (CSIMMS) is proposed on the basis of CSI for solving multiple failure modes system reliability problems with nonoverlapping failure domains. The order of magnitude of the failure probability is evaluated based on the reliability index and the degree of nonlinearity, ignoring the influence of low order of magnitude failure modes, and reducing the calculation of the system failure probability. Finally, CSIMMS and other methods are compared with three numerical examples, and the results show the stability and accuracy of the proposed method.
dc.publisherThe American Society of Mechanical Engineers (ASME)
dc.titleA Curved Surface Integral Method for Reliability Analysis of Multiple Failure Modes System With Nonoverlapping Failure Domains
dc.typeJournal Paper
dc.journal.volume9
dc.journal.issue2
dc.journal.titleJournal of Verification, Validation and Uncertainty Quantification
dc.identifier.doi10.1115/1.4065857
dc.journal.fristpage21006-1
dc.journal.lastpage21006-9
dc.page9
dc.treeJournal of Verification, Validation and Uncertainty Quantification:;2024:;volume( 009 ):;issue: 002
dc.contenttypeFulltext


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