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Digitale Methoden für die Lebensdauerbewertung am Beispiel hochfester Stähle

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Description

Am Fraunhofer IWM werden digitale Konzepte geschaffen, die auf die systematische Nutzung von Werkstoffdaten im Sinne einer beschleunigten Produktentwicklung abzielen. Daten, die in entsprechend strukturierten Datenräumen und Wissensgraphen abgelegt werden, ermöglichen dabei eine interoperable Anbindung verschiedener Analysewerkzeuge, die die verschiedenen Blickwinkel beim Durchlaufen der Prozesskette während der Produktentwicklung abdecken. Ein solcher Datenraum wird für den UseCase »Ermüdung hochfester Stähle« entwickelt. Dabei beeinflusst eine Vielzahl von Parametern das Ermüdungsverhalten, die angefangen bei der metallurgischen Prozessierungsroute über verschiedene Härteverfahren, Belastungsparameter im Bauteileinsatz bis hin zu Bruchflächencharakteristika und verschiedenen Versagensmodi reichen. In einem entsprechenden Wissensgraph soll dazu abgebildet werden, wie sich Werkstoffeigenschaften und -parameter entlang der verschiedenen Prozessschritte entwickeln und verändern. Um Korrelationen für technische Anwendungen sichtbar zu machen und für die Lebensdauervorhersage zu nutzen, wird dabei eine Datenanalyse mittels Machine Learning an den Datenraum angekoppelt. Dazu wurde im Projekt ein umfänglicher Datensatz (ca. 110 Materialien, 1100 Serien und 22000 Ermüdungsexperimente) aufgebaut, der eine Vielzahl von Materialklassen und Einflussgrößen abdeckt und der mittels künstlicher Intelligenz eine Vorhersage der Ermüdungsfestigkeit in Abhängigkeit dieser Einflussgrößen ermöglicht.

Reference: BF-2023-072

Title: Digitale Methoden für die Lebensdauerbewertung am Beispiel hochfester Stähle
Author(s): S. Fliegener, J. M. Dominguez, J. Francisco Morgado, H. U. Kobialka, T. Kraft, M. Luke, J. Rosenberger, J. Tlatlik
DOI: 10.48447/BF-2023-072
Event: DVM-Arbeitskreis Betriebsfestigkeit 49. Tagung 2023
Year of publication: 2023
Publication type: conference paper (PDF)
Language: German
Keywords: lebensdauer stahl digitalisierung ontologie machine-learning

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Author(s): K. Wilde, M. Schlotterbeck, T. Jung, M. Burger

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Author(s): T. Arnold, S. Glane, F. Grober, L. Muth, W. Sextro

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1

German

€25.00

Online only

Author(s): K. Bauer-Troßmann, S. Bucher, S. Laue, S. Schönborn

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1

Werkstoffqualifizierung für die zuverlässige Auslegung druckwasserstoffexponierter Komponenten

Publication type: conference paper (PDF)

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1

German

€25.00

Online only

Author(s): T. Bruder, G. Toplack, G. Jung, S. Chéreau

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1

Einsatz eines virtuellen Modells zur Ermittlung der Prüffähigkeit auf einem Gesamtfahrzeugprüfstand.

Publication type: conference paper (PDF)

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1

German

€25.00

Online only

Author(s): D. Kreuter, T. Westmeier

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1

Virtuelle Vibrationslastableitung: Eine Soft Sensor Anwendung

Publication type: conference paper (PDF)

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1

German

€25.00

Online only

Editor(s): M. Decker

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1

49. Tagung des DVM-Arbeitskreises Betriebsfestigkeit

Publication type: conference proceedings (PDF)

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1

German

€90.00

Online only

Author(s): R. Rennert, T. Schiemann

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1

Ansätze zum rechnerischen Festigkeitsnachweis von additiv gefertigten Bauteilen

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1

German

€25.00

Online only

Author(s): L. Masendorf, A. Esderts

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1

SCHWINGFESTIGKEIT DES SINTERSTAHLS DIESTALOY AE + 0,6 % C BEI BEANSPRUCHUNG MIT VARIABLER AMPLITUDE

Publication type: conference paper (PDF)

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€25.00

Online only

Author(s): W. Kaal, J. Baumgartner, C. Tamm, M. Budnik

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€25.00

Online only