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...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2021-04-01
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| Series: | npj Materials Degradation |
| Online Access: | https://doi.org/10.1038/s41529-021-00166-5 |