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Additiv gefertigter Edelstahl 316L: Charakterisierung des Schädigungs- und Versagensverhalten mittels biaxialer Experimente

Der austenitische Edelstahl 316L (1.4404) findet basierend auf seiner Korrosionsbeständigkeit und seiner hohen Duktilität Anwendung in der Medizintechnik sowie der Luft-, Raumfahrt- und Automobilindustrie. Die Fertigung von Einzelteilen kann durch additive Fertigung, z.B. das pulverbettbasierte Laserstrahlschmelzen (PBF-LB/M), erfolgen, wodurch insbesondere die mechanischen Eigenschaften im Vergleich zu konventionell hergestellten Bauteilen variieren. Insbesondere erfährt das Korngefüge aufgrund der hohen Abkühlrate während der Herstellungsprozesses eine Kornfeinung, wodurch die Streckgrenze bei gleichbleibender Duktilität erhöht wird.

Während der Nutzungsdauer stellen sich eine große Bandbreite von Spannungszuständen ein, wobei es gilt,…

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Während der Nutzungsdauer stellen sich eine große Bandbreite von Spannungszuständen ein, wobei es gilt, Materialschädigung zu kontrollieren und Versagen zu vermeiden. Diese vom Spannungszustand abhängige Phänomene konnten durch biaxiale Versuche und zugehörige numerische Untersuchungen bei aus Blechwerkstoffen spanend gefertigten Bauteilen erfolgreich charakterisiert werden. In der Präsentation werden erste experimentelle Ergebnisse und zugehörige numerische Simulationen mit additiv gefertigten Kreuzproben aus Edelstahl 316L vorgestellt. Die Versuchskörper werden hierbei unter verschiedenen proportionalen Lastpfaden bis zum Bruch belastet und anschließend die Schädigungs- und Versagensmechanismen ausgewertet.

Reference: BR-2024-364

Title: Additiv gefertigter Edelstahl 316L: Charakterisierung des Schädigungs- und Versagensverhalten mittels biaxialer Experimente
Author(s): S. Gerke, J. Diller, J. Blankenhagen, L. D. Pérez Cruz, M. Mensinger, M. Brünig
DOI: 10.48447/BR-2024-364
Event: 56. Tagung des DVM-Arbeitskreises Bruchmechanik und Bauteilsicherheit – Tagung 2024
Year of publication: 2024
Publication type: conference paper (PDF)
Language: German
Keywords: Addive Fertigung,Biaxiale Experimente,Duktile Schädigung

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Author(s): J. Rosenberger, J. Tlatlik, S. Münstermann

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Deep-Learning Basierte Bestimmung Lokaler Mikrostrukturparameter an Duktilem Gusseisen

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Author(s): C. Fällgren, M. Vormwald, H. T. Beier

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