Machine learning approach for 2D abrasion mapping in Sediment Bypass Tunnels: a case study of Koshibu SBT, Japan
- DOI
- 10.1080/19942060.2024.2444419
- Published
- 2024-12-26
- Container
- Engineering Applications of Computational Fluid Mechanics
- Publisher
- Informa UK Limited
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1080/19942060.2024.2444419,
title = {Machine learning approach for 2D abrasion mapping in Sediment Bypass Tunnels: a case study of Koshibu SBT, Japan},
author = {Ahmed Emara and Sameh A. Kantoush and Mohamed Saber and Tetsuya Sumi and Vahid Nourani and Emad Mabrouk},
year = {2024},
journal = {Engineering Applications of Computational Fluid Mechanics},
doi = {10.1080/19942060.2024.2444419},
url = {https://doi.org/10.1080/19942060.2024.2444419}
}RIS
TY - JOUR TI - Machine learning approach for 2D abrasion mapping in Sediment Bypass Tunnels: a case study of Koshibu SBT, Japan AU - Ahmed Emara AU - Sameh A. Kantoush AU - Mohamed Saber AU - Tetsuya Sumi AU - Vahid Nourani AU - Emad Mabrouk PY - 2024 JO - Engineering Applications of Computational Fluid Mechanics DO - 10.1080/19942060.2024.2444419 UR - https://doi.org/10.1080/19942060.2024.2444419 ER -
APA
Emara, A., Kantoush, S. A., Saber, M., Sumi, T., Nourani, V., & Mabrouk, E. (2024). Machine learning approach for 2D abrasion mapping in Sediment Bypass Tunnels: a case study of Koshibu SBT, Japan. Engineering Applications of Computational Fluid Mechanics. https://doi.org/10.1080/19942060.2024.2444419
Source records
- crossref · retrieved 2026-09-27T15:12:10.699Z