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dc.contributor.authorKam, TYen_US
dc.contributor.authorChu, KHen_US
dc.contributor.authorChang, ESen_US
dc.date.accessioned2014-12-08T15:46:01Z-
dc.date.available2014-12-08T15:46:01Z-
dc.date.issued1999-12-01en_US
dc.identifier.issn0001-1452en_US
dc.identifier.urihttp://hdl.handle.net/11536/30944-
dc.description.abstractA method is presented for the reliability assessment of transversely loaded laminated composite plates with random strength parameters. The proposed method is constructed on the basis of the first-ply failure method and the series system hypothesis. The first-ply failure analysis of a laminated plate is achieved via the use of a phenomenological failure criterion and the finite element method. In the reliability analysis, the independent (maximum stress) as well as the dependent (Tsai-Hill) failure criteria are used to establish the limit state equation; a direct numerical integration method together with the series system hypothesis are adopted to compute the reliability of the plate. Experimental investigations of lamina strength distributions and first-ply failure of laminated composite plates were performed. It has been found that lamina strengths and first-ply failure load can be well fitted by Weibull distributions. The baseline probability distributions of lamina strength parameters determined from the tests are then used in the reliability analysis of the laminated composite plates. The accuracy of the proposed method in reliability prediction of the laminated composite plates of different sizes is verified against the experimental results.en_US
dc.language.isoen_USen_US
dc.titleReliability assessment of laminated composite plates with random strength parametersen_US
dc.typeArticleen_US
dc.identifier.journalAIAA JOURNALen_US
dc.citation.volume37en_US
dc.citation.issue12en_US
dc.citation.spage1648en_US
dc.citation.epage1655en_US
dc.contributor.department機械工程學系zh_TW
dc.contributor.departmentDepartment of Mechanical Engineeringen_US
dc.identifier.wosnumberWOS:000084120600015-
dc.citation.woscount1-
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