Significant wave height forecasting plays a crucial role in marine engineering, navigation safety, coastal protection, and climate research. However, traditional physics-based numerical simulation methods and purely data-driven models each have inherent limitations. The former require significant computational resources for high-resolution, large-scale simulations and demand stringent initial and boundary conditions, while the latter often fail to accurately capture the underlying physical dynamics of wave processes under sparse observational data or extreme sea conditions. To address these challenges, this study proposes an innovative hybrid forecasting framework that integrates physics-based numerical modeling with data-driven approaches, thereby achieving both physical plausibility and high prediction accuracy in wave height forecasting. The framework first employs numerical models such as WAVEWATCH III – which solves the wave action balance equation – to generate preliminary predictions based on fundamental wave dynamics. These predictions are then refined by a data-driven correction module comprising three submodules: the Edge-Enhanced Wind-Wave Fusion (EWF) module, which enhances the input wave height data by incorporating edge information via the Sobel operator and fuses it with the corresponding wind field information to capture critical wind-wave interactions; the Bidirectional Temporal Feature Fusion (BTFF) module, which integrates geographical spatial information and wave activity weights while employing bidirectional temporal propagation to effectively capture both short-term and long-term nonlinear temporal dependencies; and the Wave-Adaptive Filter (WAF) module, which employs adaptive kernel estimation and spatial displacement prediction to extract and enhance multi-scale local wave features. Finally, a contrastive learning-based feature fusion mechanism projects the physics-based and data-driven predictions into a shared latent space, achieving deep integration of complementary information. Experimental results demonstrate that our model has achieved state-of-the-art performance on the ERA5 dataset.

Wave energy has the potential to play a crucial role in the ongoing energy transition towards the exploitation of renewable energy sources. Among the wave energy converters, Oscillating Water Column (OWC) is recognized to be one of the most promising technologies. Despite the amount of research conducted on those devices, there is no consensus on the optimal OWC configuration. In this context, circular OWCs emerged as an attractive option as it is a configuration unaffected by the direction of the incoming waves. Recently, research focused on devices equipped with multiple chambers in order to increase the overall device efficiency via the introduction of concentric chambers. This paper studies a multi-chamber concept arising from the partition of a cylindrical single chamber OWC into multiple chambers spanning a reduced inner angular width. Within the linearized potential flow theory, throughout the eigenfunction expansion matching method, and considering a linear power take off, a semi-analytical solution is obtained. Next, numerical results pertaining to the cases of a circular OWC comprising two and three chambers, spanning the whole inner sector, are discussed. The numerical analysis shows that the use of multiple chambers having a reduced angular width increases the overall energy-wise performance of the system with respect to the case of a single chamber OWC.

Optimisation and control co-design, for wave energy systems, is receiving increased focus, in the drive to design commercially viable wave energy systems. A consistent bottleneck in wave energy converter (WEC) system optimisation is the need to iteratively calculate hydrodynamic forces, which is computationally time-consuming. One solution, to improve the computational efficiency of WEC optimisation loops, is through the use of surrogate models, which are computationally efficient approximations of the fundamental calculations provided by linear potential-flow boundary-element solvers. Surrogate models offer a computationally efficient framework for conducting iterative design optimisation provided sampling of the search space, when collating training data at the pre-computation stage, is well designed. Surrogate models can be used both to evaluate hydrodynamic response parameters and to calculate objective function values (e.g., captured energy or cost of energy), within design optimisation loops. This study explores both options and examines the computational time/fidelity trade-off involved in the use of surrogate models for WEC geometry optimisation. • Surrogate models emulate hydrodynamics for efficient WEC geometry control co-design. • A single surrogate linear hydrodynamics model is applied to three WEC CCD scenarios. • Careful design space sampling for training data reduces BEM pre-computation times. • Artificial neural network interpolation accuracy is similar to cubic polynomials.

We carry out a laboratory study of weakly nonlinear waves atop a following, vertically sheared current, relevant for a wide range of coastal and ocean locations. The experimental observations are compared with existing theories for the shear-current modified dispersion relation and amplitudes of second-harmonic waves, where a good agreement has been shown. Both the experiments and theoretical calculations show that the findings for wave groups and regular waves are consistently affected by the presence of the following current. For regular (carrier) waves with a fixed absolute frequency, the additional presence of the following current is found to decrease the amplitude of the second-harmonic waves when the linear amplitude is fixed, yet increase the second-harmonic waves when the steepness is fixed owing to the additional shear-current modified effects on the dispersion relation of linear waves. These nuanced and apparently contrasting findings address the significance of resolving the combined wave–current field effectively to ensure a correct interpretation of wave properties in field measurements.

Automatic berthing is one of the key functions for autonomous navigation of unmanned ships, and it is an important technology that assists and ensures ships complete their voyage tasks. To enhance the robustness, scenario universality, and disturbance resistance of automatic berthing technology, an automatic berthing method based on weight optimal loop shaping is proposed in this paper. Firstly, to enhance the robust stability margins of the berthing controller, the concept of weight optimization is introduced to transform the frequency-domain dependent weight optimization into an optimization problem with a finite number of frequency-domain independent constraints. Secondly, to improve the continuity and scenario universality of the algorithm, a transformation model between berth and earth coordinates is constructed using Bézier curves, and a forward Euler signal tracking method is introduced to provide a differentiable reference trajectory for the control system. Finally, the proposed method is validated through the construction of various berthing scenarios. The validation results indicate that the proposed method can achieve automatic berthing in different scenarios with better stability and disturbance resistance, and a theoretical reference is provided for the development of autonomous berthing technology for unmanned ships.

• Investigation of cyclic loading sequence on a monopile in an overconsolidated clay. • An advanced constitutive model used to predict the cyclic response of clay. • Cyclic amplitude and order of loading sequence governs strain and pore water pressure accumulation. • Strain and pore water pressure accumulation influences monopile stiffness and damping under single amplitude and multi-staged cyclic loading. • Ordering of cyclic load sequence matters under the premise of undrained cyclic loading in clays. Wind and wave actions that vary in amplitude, frequency and direction cause irregular cyclic loading on monopiles supporting offshore wind turbines (OWTs), resulting in cumulative deformation. Current design practice apply widely accepted classification methods to decompose a storm history into an idealised series of cyclic load parcels with uniform amplitude, ordered in magnitude. This approach is based on Miner’s rule, which assumes that the final accumulated deformation in the soil is independent of the sequence in which load cycles are applied. Research has shown this approach to be reasonable under drained conditions in sand. This study investigates the validity of this assumption under fully undrained conditions in clay through a series of three dimensional (3D) finite element analyses incorporating an advanced soil constitutive model. A large diameter monopile installed in an overconsolidated clay deposit is subjected to cyclic loading sequences arranged in ascending, descending, and mixed-sorted order. The effect of the load ordering sequence is demonstrated by comparing local soil behaviour in terms of cyclic ratcheting, strain accumulation, clay-structure degradation and excess pore-water pressure buildup and linking these to the global pile response in terms of pile rotation, stiffness, and damping. Findings show that under fully undrained conditions, the ordering of cyclic load sequence notably affects the performance of monopiles in overconsolidated clay deposits. These results suggest that experimental investigations are needed to further explore cyclic loading sequences on monopiles in clay, which could inform the development of improved numerical and design procedures for offshore monopiles.