The single-moored light buoys employed in the lower reaches of the Yangtze River play an important role in indicating ship navigation and ensuring safety. To clarify the interaction between waves and floating buoys moored to the riverbed, this paper applies a numerical approach to investigate the wave-induced motion performance of a light buoy and reveal the effects of different mooring configurations to extend its service life. An open-source smoothed particle hydrodynamics (SPH)-based numerical model named dualsphysics coupled with MoorDyn is implemented. This coupled model is validated by simulating the motion of a moored rectangle buoy in regular waves, and compared with experimental data and the numerical results of reef3d code, a mesh-based computational fluid dynamics (CFD) model. The validation results show that the coupled model reproduces experimental data well and has a smaller deviation in comparison with reef3d. Then, the coupling model is applied to simulate the hydrodynamic performance of the real-size light buoy employed in Yangtze River and investigate the effects of encounter angle between wave propagation direction and mooring chain. The results demonstrate the capability of this coupled mooring model to simulate the motion of a moored buoy in regular waves, and this numerical approach will be extended to simulate the light buoy in more complex environments such as irregular waves, flow or extreme weather in further work.

Sensors are widely used in inland waterway buoys to monitor their position, but the collected data are often affected by noise, outliers, and irregular sampling intervals. To address these challenges, a standardized data processing framework is proposed. Outliers are identified using a hybrid approach combining interquartile range filtering and Isolation Forest algorithm. Interpolation methods are adaptively selected based on time intervals. For short-term gaps, cubic spline interpolation is applied, otherwise, a method that combines dominant periodicity estimation with physical constraints based on power spectral density (PSD) is proposed. An adaptive unscented Kalman filter (AUKF), integrated with the Singer motion model, are applied for denoising, dynamically adjusting to local noise statistics and capturing acceleration dynamics. Afterwards, a set of time-frequency features are extracted, including centrality, directional dispersion, and wavelet transform-based features. Taking the lower Yangtze River as a case study, representative buoys are selected based on dynamic time warping similarity. The features analysis result show that the movement of buoys is closely related to the dynamics dominated by the semi-diurnal tide, and is also affected by runoff and accidents. The method improves the quality and interpretability of buoy motion data, facilitating more robust monitoring and hydrodynamic analysis.

Ship waves could alter the hydrodynamic field and play an important role for sediment movement and morphological changes, especially in shallow water regions of inland waterways. However, the response of riverbed morphology to ship waves is still unclear. In this paper, the impacts of ship waves on the bed profile in inland waterways are investigated by means of laboratory experiments. Observations of ship waves and bed profile changes exposed to different ship wave conditions are conducted. There exists a power exponential relationship between the corresponding polygon area and perimeter of the cross-sectional bed profile after the action of ship waves, which indicates that the bed profile is only adjusted in the geometric direction. Moreover, the dimensionless local scour depth is well predicted through the dimensionless expression of ship-induced near-bed velocity, ship draft, and offshore distance, which describes the impacts of ship waves on the bed morphology in inland waterways.

The ship waves and related hydrodynamics over a sloping bed are investigated numerically in this paper, and we aim to clarify the characteristics of ship wave deformation and its hydrodynamic effects. Laboratory experiments are performed with a self-propelled ship model to produce various wave conditions over a sloping bed in the water flume, providing the datasets for validation works of numerical simulations. With the implementation of model sensitivity analysis, numerical calculations of ship-induced waves and flow velocities are completed using the non-hydrostatic model in XBeach and compared against experimental measurements. The results show that the model is not only able to calculate primary and secondary waves well, but also the ship-induced near-bed velocity when ship waves are prominent in the water flume. Further numerical investigations of ship wave transformation and associated hydrodynamic effects are conducted over a sloping bed under different ship speed conditions. The ship wave height and run-up variations along the cross-shore transect clearly indicate the wave energy dissipation due to breaking and bottom friction. The ship-induced flow velocities are found to be mainly contributed by the low-frequency primary waves in our numerical experiments.

This paper addresses the bidirectional multi-chamber lock scheduling problem by formulating a multi-objective mixed-integer linear programming (MILP) model that simultaneously minimizes average ship waiting time and maximizes chamber utilization. A tailored adaptive large neighborhood search (ALNS) algorithm is developed specifically based on the principle of the destruction and reconstruction of solutions. The algorithm efficacy is validated using the real-word data from Huai’an Lock of the Subei canal. The scheduling rules and parameters are defined from practical operation records. Simulation results demonstrate that the ALNS-based optimization significantly improves lock performance with average chamber utilization increasing by 12.98% and waiting time decreasing by 44.40%. Sensitivity analyses on objective weights further confirm the robustness of the proposed method. Benchmark comparisons with a greedy heuristic, genetic algorithm (GA), and particle swarm optimization (PSO) highlight the effectiveness and computational efficiency of ALNS. This study further explores a threshold-based directional control strategy, showing that relaxing strict alternating-direction rules under asymmetric traffic demand can improve efficiency. The findings provide practical insights for lock scheduling, offering decision support for lock authorities in designing adaptive scheduling and directional control policies.