Predicting penetration depth in ultra-high-performance concrete targets under ballistic impact: An interpretable machine learning approach augmented by deep generative adversarial network
In recent decades, numerous explosions and ballistic attacks have caused significant global loss of life and property. Ultra-high-performance concrete (UHPC) minimizes blast and impact damage to structures and can be applied to protective walls and bunkers. Many researchers have proposed methods to...
Saved in:
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-03-01
|
| Series: | Results in Engineering |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2590123024021522 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|