Work

Numerical modelling of impact pressure and load characteristics of tidal bores on inclined piles and their rapid prediction using convolutional neural network method

Year: 2025
Type: article
Abstract: Tidal bores are a type of highly nonlinear discontinuous flow that carry tremendous energy. As such, pile structures such as bridge piers located in bore-affected estuarine zones are subjected to significant hydrodynamic impact forces, which may lead to severe structural damage. To safeguard human life and property, it is crucial to assess the impact loads of tidal bores in advance and implement effective protective measures. In this study, a high-resolution numerical tidal bore flume was established based on the open-source solvers OpenFOAM and wave2Foam, enabling the accurate simulation of tidal bore propagation and its interaction with pile structures. The hydrodynamic response and structural behavior of both vertical and obliquely inclined piles under tidal bore impact were systematically investigated, focusing on tidal bore evolution, local flow fields, hydrodynamic loads, and dynamic pressure. The influence of bore type (undular, weak breaking, and breaking), tidal bore height, initial water depth, inclination angle ( α ), and incident direction ( β ) on the hydrodynamic characteristics near pile structures was analyzed in detail. Furthermore, based on numerical simulation results, this study developed empirical formulas for predicting the maximum hydrodynamic load and dynamic pressure exerted on pile structures under different tidal bore conditions, incorporating the effects of inclination and incident angles. In addition, a one-dimensional convolutional neural network (1D-CNN) model was constructed to predict the hydrodynamic evolution of tidal bore impacts. Using a dataset of water level time series collected at multiple monitoring points as input, the model effectively predicted the water run-up on pile surfaces and the corresponding peak hydrodynamic loads. Results show that as the pile inclination angle α increases from −12.5 ° to 12.5 ° , both the maximum load and peak pressure decrease, with larger changes under stronger bores. As the incident direction β shifts from 180 ° to 0 ° , water run-up increases, and piles with β > 90 ° experience higher peak loads. Overall, the load increases as β moves from 0 ° to 180 ° , especially under stronger tidal bores. The proposed 1D-CNN model shows strong predictive capability and robustness, capturing the impact patterns across various angles and directions.
Language: English
Open Access status: hybrid
Estimated APC paid: $4,150
Award: G716258510
OpenAlex ID: W4416388030
FWCI: 0.763
Cites: 24
Cited by: 2
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