Fatigue life prediction of composite materials using strain distribution images and a deep convolution neural network
- Standort
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Deutsche Nationalbibliothek Frankfurt am Main
- Umfang
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1 Online-Ressource.
- Sprache
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Englisch
- Erschienen in
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Fatigue life prediction of composite materials using strain distribution images and a deep convolution neural network ; volume:14 ; number:1 ; day:25 ; month:10 ; year:2024 ; pages:1-14 ; date:12.2024
Scientific reports ; 14, Heft 1 (25.10.2024), 1-14, 12.2024
- Urheber
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Mizuno, Yuta
Hosoi, Atsushi
Koshita, Hiroyuki
Tsunoda, Dai
Kawada, Hiroyuki
- Beteiligte Personen und Organisationen
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SpringerLink (Online service)
- DOI
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10.1038/s41598-024-75884-2
- URN
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urn:nbn:de:101:1-2501152106531.595154621620
- Rechteinformation
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Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Letzte Aktualisierung
-
15.08.2025, 07:32 MESZ
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Beteiligte
- Mizuno, Yuta
- Hosoi, Atsushi
- Koshita, Hiroyuki
- Tsunoda, Dai
- Kawada, Hiroyuki
- SpringerLink (Online service)
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Filament wound composite fatigue mechanisms investigated with full field DIC strain monitoring
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Fatigue behaviour of composite girders with composite dowels assuming randomly distributed input parameters
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