Please use this identifier to cite or link to this item: https://olympias.lib.uoi.gr/jspui/handle/123456789/13979
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dc.contributor.authorKostopouios, V.en
dc.contributor.authorLoutas, T.en
dc.contributor.authorDassios, K.en
dc.date.accessioned2015-11-24T17:34:30Z-
dc.date.available2015-11-24T17:34:30Z-
dc.identifier.issn0266-3538-
dc.identifier.urihttps://olympias.lib.uoi.gr/jspui/handle/123456789/13979-
dc.rightsDefault Licence-
dc.subjectlarge scale bridgingen
dc.subjectpull-outen
dc.subjectacoustic emissionen
dc.subjectunsupervised pattern recognition techniqueen
dc.subjectacoustic-emissionen
dc.subjectfailure mechanismsen
dc.titleFracture behavior and damage mechanisms identification of SiC/glass ceramic composites using AE monitoringen
heal.typejournalArticle-
heal.type.enJournal articleen
heal.type.elΆρθρο Περιοδικούel
heal.identifier.primaryDOI 10.1016/j.compscitech.2005.02.002-
heal.identifier.secondary<Go to ISI>://000246253200046-
heal.languageen-
heal.accesscampus-
heal.recordProviderΠανεπιστήμιο Ιωαννίνων. Σχολή Θετικών Επιστημών. Τμήμα Μηχανικών Επιστήμης Υλικώνel
heal.publicationDate2007-
heal.abstractLarge Scale Bridging in SiC/MAS-L (ceramic glass matrix) composites was investigated by using DEN specimens under tensile loading conditions with in situ Acoustic Emission monitoring. The AE data were successfully classified using Unsupervised Pattern Recognition Algorithms and the resulted clusters were correlated to the dominant damage mechanisms of the material. The evolution in time of the different damage mechanisms is feasible after the pattern recognition classification. Microscopic examination was used to correlate the clusters to the damage mechanism they correspond and. thus to provide the failure mode identification based on AE data. (c) 2005 Elsevier Ltd. All rights reserved.en
heal.publisherElsevieren
heal.journalNameComposites Science and Technologyen
heal.journalTypepeer reviewed-
heal.fullTextAvailabilityTRUE-
Appears in Collections:Άρθρα σε επιστημονικά περιοδικά ( Ανοικτά)

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