Prediction of wave overtopping discharge on coastal protection structure using SPH-based and neural networks method
- Author
- Bao-Loi Dang (UGent) , Quoc Viet Dang, Magd Abdel Wahab (UGent) and H. Nguyen-Xuan
- Organization
- Abstract
- This paper adopts DualSPHysics, the powerful SPH models, to investigate a large-scale 2-D numerical simulation of wave-structure interactions. As a case study, a non-conventional seawall structure built at Vietnam's coastline is considered. The hydraulic performance of such a structure is assessed using the value of wave overtopping over structure. It is one of the most important considerations when evaluating the efficiency of proposed designs. Due to the geometrical differences, traditional methods such as empirical equations are inconvenient for analyzing such novel structure design with complicated shapes. As a supplement to the experimental study, numerical modeling and machine learning approaches are being studied for assessing such problems. The reliability and effectiveness of two approaches have been proven in several studies in literature. In this work, a large-scale computational model of wave-structure interaction under regular wave conditions is carried out. The simulation results demonstrate good agreement when compared to neural network-based prediction approaches, and analytical solution as well.
- Keywords
- Coastal structure, Wave overtopping, SPH model, Neural networks, SMOOTHED PARTICLE HYDRODYNAMICS, WAVE, BREAKWATER, MODEL
Downloads
-
(...).pdf
- full text (Published version)
- |
- UGent only
- |
- |
- 6.66 MB
Citation
Please use this url to cite or link to this publication: http://hdl.handle.net/1854/LU-8741743
- MLA
- Dang, Bao-Loi, et al. “Prediction of Wave Overtopping Discharge on Coastal Protection Structure Using SPH-Based and Neural Networks Method.” Proceedings of the 4th International Conference on Numerical Modelling in Engineering : Volume 1 : Numerical Modelling in Civil Engineering, NME 2021, edited by Magd Abdel Wahab, vol. 217, Springer, 2022, pp. 71–79, doi:10.1007/978-981-16-8185-1_6.
- APA
- Dang, B.-L., Dang, Q. V., Abdel Wahab, M., & Nguyen-Xuan, H. (2022). Prediction of wave overtopping discharge on coastal protection structure using SPH-based and neural networks method. In M. Abdel Wahab (Ed.), Proceedings of the 4th International Conference on Numerical Modelling in Engineering : volume 1 : Numerical modelling in Civil Engineering, NME 2021 (Vol. 217, pp. 71–79). https://doi.org/10.1007/978-981-16-8185-1_6
- Chicago author-date
- Dang, Bao-Loi, Quoc Viet Dang, Magd Abdel Wahab, and H. Nguyen-Xuan. 2022. “Prediction of Wave Overtopping Discharge on Coastal Protection Structure Using SPH-Based and Neural Networks Method.” In Proceedings of the 4th International Conference on Numerical Modelling in Engineering : Volume 1 : Numerical Modelling in Civil Engineering, NME 2021, edited by Magd Abdel Wahab, 217:71–79. Singapore: Springer. https://doi.org/10.1007/978-981-16-8185-1_6.
- Chicago author-date (all authors)
- Dang, Bao-Loi, Quoc Viet Dang, Magd Abdel Wahab, and H. Nguyen-Xuan. 2022. “Prediction of Wave Overtopping Discharge on Coastal Protection Structure Using SPH-Based and Neural Networks Method.” In Proceedings of the 4th International Conference on Numerical Modelling in Engineering : Volume 1 : Numerical Modelling in Civil Engineering, NME 2021, ed by. Magd Abdel Wahab, 217:71–79. Singapore: Springer. doi:10.1007/978-981-16-8185-1_6.
- Vancouver
- 1.Dang B-L, Dang QV, Abdel Wahab M, Nguyen-Xuan H. Prediction of wave overtopping discharge on coastal protection structure using SPH-based and neural networks method. In: Abdel Wahab M, editor. Proceedings of the 4th International Conference on Numerical Modelling in Engineering : volume 1 : Numerical modelling in Civil Engineering, NME 2021. Singapore: Springer; 2022. p. 71–9.
- IEEE
- [1]B.-L. Dang, Q. V. Dang, M. Abdel Wahab, and H. Nguyen-Xuan, “Prediction of wave overtopping discharge on coastal protection structure using SPH-based and neural networks method,” in Proceedings of the 4th International Conference on Numerical Modelling in Engineering : volume 1 : Numerical modelling in Civil Engineering, NME 2021, Ghent, Belgium, 2022, vol. 217, pp. 71–79.
@inproceedings{8741743,
abstract = {{This paper adopts DualSPHysics, the powerful SPH models, to investigate a large-scale 2-D numerical simulation of wave-structure interactions. As a case study, a non-conventional seawall structure built at Vietnam's coastline is considered. The hydraulic performance of such a structure is assessed using the value of wave overtopping over structure. It is one of the most important considerations when evaluating the efficiency of proposed designs. Due to the geometrical differences, traditional methods such as empirical equations are inconvenient for analyzing such novel structure design with complicated shapes. As a supplement to the experimental study, numerical modeling and machine learning approaches are being studied for assessing such problems. The reliability and effectiveness of two approaches have been proven in several studies in literature. In this work, a large-scale computational model of wave-structure interaction under regular wave conditions is carried out. The simulation results demonstrate good agreement when compared to neural network-based prediction approaches, and analytical solution as well.}},
author = {{Dang, Bao-Loi and Dang, Quoc Viet and Abdel Wahab, Magd and Nguyen-Xuan, H.}},
booktitle = {{Proceedings of the 4th International Conference on Numerical Modelling in Engineering : volume 1 : Numerical modelling in Civil Engineering, NME 2021}},
editor = {{Abdel Wahab, Magd}},
isbn = {{9789811681844}},
issn = {{2366-2557}},
keywords = {{Coastal structure,Wave overtopping,SPH model,Neural networks,SMOOTHED PARTICLE HYDRODYNAMICS,WAVE,BREAKWATER,MODEL}},
language = {{eng}},
location = {{Ghent, Belgium}},
pages = {{71--79}},
publisher = {{Springer}},
title = {{Prediction of wave overtopping discharge on coastal protection structure using SPH-based and neural networks method}},
url = {{http://doi.org/10.1007/978-981-16-8185-1_6}},
volume = {{217}},
year = {{2022}},
}
- Altmetric
- View in Altmetric
- Web of Science
- Times cited: