Machine learning-based fatigue lifetime prediction of structural steels
Fatigue of materials stands as a prevalent cause of mechanical structure failures, which often occur suddenly, unpredictably, and catastrophically. Accurately predicting the fatigue lifespan of materials is crucial, especially given the potential for fatigue failure to occur within a short design li...
Saved in:
| Main Authors: | Konstantinos Arvanitis, Pantelis Nikolakopoulos, Dimitrios Pavlou, Mina Farmanbar |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-06-01
|
| Series: | Alexandria Engineering Journal |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S1110016825004818 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Critical length parameter of HDPE and its use in fatigue lifetime predictions
by: Kamila Kozáková, et al.
Published: (2024-11-01) -
Critical length parameter of HDPE and its use in fatigue lifetime predictions
by: Kamila Kozáková, et al.
Published: (2024-11-01) -
Fatigue lifetime prediction and reliability assessment for fusion blankets under pulsed operational loading
by: Qingzhu Liang, et al.
Published: (2025-01-01) -
Evaluation and Research on Vibration Fatigue Lifetime of On-board IGBT Based on Physical-statistical Model
by: YU Hui, et al.
Published: (2023-06-01) -
Breaking the trade off between corrosion resistance and fatigue lifetime of the coated Mg alloy through cold spraying submicron-grain Al alloy coatings
by: XiaoTao Luo, et al.
Published: (2024-10-01)