Low-cycle fatigue life prediction method for stud connectors based on interpretable machine learning
Abstract Low-cycle fatigue is a common failure mode of stud connectors in bridges. Accurate prediction of their life is crucial for material design and engineering applications. However, traditional theoretical formulas and experimental methods suffer from limitations such as low accuracy and indivi...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
SpringerOpen
2025-08-01
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| Series: | Journal of Materials Science: Materials in Engineering |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s40712-025-00316-6 |
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