How can machine learning be used for accurate representations and predictions of fracture nucleation in zirconium alloys with hydride populations?
Zirconium alloys are critical material components of systems subjected to harsh environments such as high temperatures, irradiation, and corrosion. When exposed to water in high temperature environments, these alloys can thermo-mechanically degrade by forming hydrides that have a crystalline structu...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
AIP Publishing LLC
2023-07-01
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| Series: | APL Materials |
| Online Access: | http://dx.doi.org/10.1063/5.0155679 |