Fishbone-shaped dikes are always built on the soft soil submerged in the water, and the soft foundation settlement plays a key role in the stability of these dikes. In this paper, a novel and simple approach was proposed to predict the soft foundation settlement of fishbone dikes by using the extreme learning machine. The extreme learning machine is a single-hidden-layer feedforward network with high regression and classification prediction accuracy. The data-driven settlement prediction models were built based on a small training sample size with a fast learning speed. The simulation results showed that the proposed methods had good prediction performances by facilitating comparisons of the measured data and the predicted data. Furthermore, the final settlement of the dike was predicted by using the models, and the stability of the soft foundation of the fishbone-shaped dikes was assessed based on the simulation results of the proposed model. The findings in this paper suggested that the extreme learning machine method could be an effective tool for the soft foundation settlement prediction and assessment of the fishbone-shaped dikes.

The ship-generated wave causes erosive damage to the slopes of inland waterways and confined waters such as the coastal zone. This critical issue is essentially associated with the navigational safety and sustainable development of coastlines, so it is vital to predicting the maximum wave height of the ship-generated wave (H_m) in the coastline of confined waters. The prediction equations of prior research works are mostly based on measured data and multiple regression analysis; however, this paper aims to propose a novel methodology to predict the maximum wave height of ship-generated waves in confined waters. The maximum wave height caused by a self-propelled ship under various conditions with confined water is measured by employing a water flume. Furthermore, the relationships of functions in the prediction model equation are appropriately derived by dimensional analysis, and the prediction equation model is then solved via the particle swarm optimization algorithm (PSOA). The experimental results reveal that the maximum wave height of the ship-generated wave is seriously affected by the water depth of the channel (h_c), the navigation speed of the ship (V_c), and the distance from the forecast point to the navigation line of the ship (S_c). In addition, the maximum wave height grows and then lessens, which touches its peak point in the region close to Fr_h = 1. The dimensionless analysis indicates that the large wave height of the ship-generated wave can be expressed as a function of the channel depth (h_c), ship speed (V_c), and the distance from the measurement point to the ship’s navigation line (S_c) as; HmSc=1Frh2f(gScVc2). Subsequently, the specific prediction equation is determined by a regression model according to the measured data under various working conditions. By adopting the model expression equation, namely, HmFrh2Sc=k1(gScVc2)k2, the coefficients k₁ and k₂ are evaluated via the PSOA, and the relationship between the water depth of the channel and the coefficients is suitably outlined to obtain the maximum wave height prediction model equations for ship-generated waves.

A sediment suspension model is established to predict the sediment movement beneath asymmetric waves, in which the bottom boundary condition for the sediment concentration equation is specified by means of pickup function parameterized by a modified model of the bottom shear stress. The modified model of the bottom shear stress involves velocity and acceleration processes as well as the phase difference between the near-bed orbital velocity and bottom shear stress. Moreover, the phase difference is not a constant in one wave cycle but different in the durations of positive and negative velocities. And the phase differences are parameterized into a function that is dependent on the degree of wave asymmetry based on plenty of numerical data of the boundary layer obtained by large eddy simulation (LES) of oscillatory boundary layer flows. The bottom shear stress calculated by the modified model is compared with those obtained from both the experiments and the LES model, demonstrating that the modified model can capture the unsteady characteristics of the bottom shear stress beneath asymmetric waves accurately. Then, the proposed sediment suspension model is coupled with a numerical wave flume so as to obtain the progressive wave fields and the suspended sediment movement. The velocity and sediment concentration of both reduced- and large-scale hydrodynamic conditions calculated by the coupled model are compared with experimental data with a good agreement, suggesting reliability of the proposed model to predict sediment transport induced by asymmetric waves.

Huang, W.; Li, S.; Lu, Y., and Zhang, R., 2024. Hydrodynamic characteristics of an ecological revetment cavity structure under the propagation of ship-generated waves in a restricted channel. Journal of Coastal Research, 40(2), 382–394. Charlotte (North Carolina), ISSN 0749-0208. With the rapid development of inland waterway transportation and the rapid increase of ship traffic in restricted channels, the role of ship-generated waves on the restricted channel shore slope becomes increasingly significant. Some river bank protection projects use cavity structures to prevent bank slopes from being scoured and have achieved remarkable results. However, the hydrodynamic characteristics under the action of ship traveling waves inside and outside the cavity are not yet clear. Thus, this paper studies the time and frequency domain characteristics of ship-generated wave fluctuations, flow velocity distribution characteristics, and turbulence distribution characteristics in the cavity, under the action of ship-generated waves, by conducting self-propelled ship model flume tests using a new type of cavity shore protection structure applied to a restricted channel. This study investigates the application of such a structure to shallow water coastal areas with frequent ship traffic. The corresponding results demonstrate that during the ship traveling wave transfer to the cavity, the fluctuation frequency did not change significantly, and fluctuation energy concentrated in the frequency range of 0–1.5 Hz. The high-frequency (0.40–1.5 Hz) energy is concentrated in the secondary wave process, and the low-frequency (0–0.40 Hz) energy is observed throughout the fluctuation process. The cavity structure changes the flow velocity from low-frequency periodic flow to high-frequency oscillatory flow, and the frequency of flow velocity change tends to be uniformly distributed with significantly enhanced turbulence. The cavity's maximum wave height, flow velocity, and turbulence energy positively correlate with the self-propelled velocity of the vessel Vc. Moreover, the characteristic values increase slowly for Vc in the subcritical velocity region (Frh < 0.84), and the characteristic values increase sharply for Vc in the transcritical velocity region (0.84 < Frh < 1.12).