Machine learning augmented predictive and generative model for rupture life in ferritic and austenitic steels

Abstract The Larson–Miller parameter (LMP) offers an efficient and fast scheme to estimate the creep rupture life of alloy materials for high-temperature applications; however, poor generalizability and dependence on the constant C often result in sub-optimal performance. In this work, we show that...

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Autores principales: Osman Mamun, Madison Wenzlick, Arun Sathanur, Jeffrey Hawk, Ram Devanathan
Formato: article
Lenguaje:EN
Publicado: Nature Portfolio 2021
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Acceso en línea:https://doaj.org/article/e76d63eb1627409782b344abe8ba2147
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