Machine learning approach for 2D abrasion mapping in Sediment Bypass Tunnels: a case study of Koshibu SBT, Japan
Sediment Bypass Tunnels (SBTs) effectively mitigate reservoir sedimentation by diverting flood-laden flows, but they face significant challenges due to hydroabrasive erosion, which compromises their sustainability. Predicting this abrasion is complex due to the intricate interactions between flow hy...
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| Main Authors: | Ahmed Emara, Sameh A. Kantoush, Mohamed Saber, Tetsuya Sumi, Vahid Nourani, Emad Mabrouk |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis Group
2025-12-01
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| Series: | Engineering Applications of Computational Fluid Mechanics |
| Subjects: | |
| Online Access: | https://www.tandfonline.com/doi/10.1080/19942060.2024.2444419 |
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