Abstract Extreme sea states are critical for semi-submersible floating offshore wind turbines (FOWTs) with target locations in intermediate water depths of 70–100 m, where nonlinear motion can significantly impact mooring loads. This study examines the limitations of lumped mass (LM) models under extreme sea conditions using a coupled DualSPHysics-MoorDyn+ model. Crest-focused wave groups are used to simulate extreme sea conditions with a target wave height of 12 m and several peak periods. Phase differences between wave elevation and mooring tension are observed in all test cases, while the 8 s wave period test cases produce cumulative tension peaks, which are suspected to be caused by limited restoring time. Although no distinct snap load is observed, steep, high-frequency focused waves are identified as a critical condition for snap load initiation. The LM formulation exhibits intrinsic limitations in capturing snap loads, further study is needed to clarify its predictive accuracy under extreme conditions.

Maximizing energy absorption is critical for the commercialization of wave energy converters (WECs). Energy-maximizing control algorithms are typically evaluated using linear potential flow solvers, which neglect non-linear hydrodynamic effects, affecting energy capture estimates when WEC motions exceed the linear regime. High-fidelity numerical models can account for these non-linearities, providing more accurate performance predictions. This study presents an integrated framework combining high-fidelity fluid simulations with power take-off (PTO) control. Model Predictive Control (MPC) is implemented directly within the Smoothed Particle Hydrodynamics (SPH) solver DualSPHysics through a novel PTO control modeling methodology: the PTO control module. The approach is validated against experimental data from the WECfarm project under simple damping control. For centralized damping control, the new PTO module shows improved agreement with experiments compared to the Project Chrono implementation. The framework is then applied to the same WECfarm WEC array subject to MPC to demonstrate its functionality, verify the implementation, and quantify the potential increase in absorbed energy relative to damping control. By integrating MPC directly within DualSPHysics, the framework enables realistic, high-fidelity simulations of optimally controlled WEC arrays. The PTO module is adaptable to any control strategy, providing a robust platform for evaluating advanced WEC control in non-linear, high-fidelity simulations.

The application of artificial intelligence (AI) models in maritime and coastal engineering has gained increasing relevance, demonstrating performance comparable to traditional approaches in wave climate analysis and propagation. However, their use in climate change impact and adaptation studies remains limited, particularly for the design and upgrading of coastal protection structures. To address this gap, this study focuses on the development of an AI-based framework to support the adaptation of breakwaters to future climate conditions. A hybrid approach combining artificial neural networks (ANNs) and genetic algorithms (GAs) was implemented, with two feedforward neural networks-based models developed and applied to different sections of the north breakwater of the Port of Valencia, specifically a vertical section and a compound breakwater. The results indicate that, under future climate scenarios (2050), increases of up to 1.2 m in crest elevation, together with reinforcement of the armor layer, are required to ensure adequate structural performance. The analysis also highlights the critical role of extreme events, as approximately 60% of the model errors were concentrated in the upper 90th percentile of wave conditions. Overall, the proposed hybrid ANN-GA framework demonstrated very strong performance, achieving computational efficiencies 30 to 40 times greater than ANN-only models in terms of computational time. These findings underscore the necessity of adapting coastal structures to climate change and confirm the potential of AI-based models as effective tools for climate-resilient coastal engineering, while emphasizing the importance of accurately representing extreme wave conditions.

Fluid-flexible floating structure interaction studies in Computational Fluid Dynamics (CFD) remain predominantly two dimensionals, limiting the exploration of three dimensional effects crucial for the design of Very Flexible Floating Structures (VFFSs). To address this gap, this work extends a previously developed Applied Element Method (AEM) beam formulation into a plate formulation within the coupling of the weakly compressible Smoothed Particle Hydrodynamics (SPH) solver of DualSPHysics and the Multibody Dynamics (MBD) module of Project Chrono. The new structural scheme demonstrates comparable accuracy to established non-linear shell formulations in problems dominated by large displacements. Incorporated into an SPH variable resolution scheme for the fluid phase, the proposed formulation is validated experimentally for flexible floating plates, confirming both the accuracy of the three dimensional AEM framework in fluids and the robustness of the coupling under variable resolution conditions. Thus, the developed fluid-flexible structure interaction model establishes a foundation for advancing the design analysis of VFFSs, including future applications with complex mooring line configurations or large-scale interconnected modular arrays.

Hybrid dune-dike structures are innovative developments creating coastal defense systems which are more conveniently integrated with the natural environment. In this study, a numerical study was conducted to investigate the temporal evolution of wave overtopping, with the changing profile of the dune under extreme storm conditions with a constant water level, of two types of hybrid dune-dike structures in Katwijk (dike-in-dune type) and Raversijde (dune-in-front-of-dike type). XBeach 1DH was used to firstly calculate bed profiles for different time steps during a 10-h storm duration using the Surfbeat mode and then, in a second step, mean wave overtopping rates were modelled for each calculated bed profile using the Non-hydrostatic mode. According to the simulation results, most of the dune erosion occurs during the first two hours of the storm, and then continues at a slower rate as the sand deposits in front of the dune. Once the hybrid structure is eroding (so for t > 0), the significant wave height at the dike toe and the mean overtopping discharge increase in time for both Katwijk and Raversijde, although it quickly reaches a plateau for Raversijde. The first simulations with the original non-eroded profiles deviate from this trend. The reason for this deviation needs to be further investigated.

Abstract Wave-seabed interaction around offshore monopile foundations plays an important role in governing seabed response and foundation behaviour. In particular, the development of wave-induced pore pressures under irregular wave loading requires further investigation to assess seabed behaviour under more realistic wave conditions. This paper presents experimental results on wave-induced pore pressures in the seabed surrounding an embedded, scaled monopile subjected to both regular and irregular waves. Tests were conducted under a range of wave heights, wave periods and water depths. Pore pressures were measured at several locations and depths around the monopile. Comparisons between regular and irregular wave tests show that regular waves provide a reasonable approximation of the seabed response when significant pore pressure values are considered. In contrast, the maximum pore pressures induced by irregular waves are substantially larger and can be up to nearly twice those obtained under regular wave loading. The influence of wave period and wave height on both response measures is examined, and differences between the pore pressures under regular and irregular waves are discussed.

This study presents a hydrodynamic assessment of a toroidal wave energy converter (WEC) operating under low-energy conditions of the west coast of Mexico. Performance analysis incorporates the coupling surge, heave, and pitch motions. To investigate mooring-device interaction, two mooring configurations were examined: (A) a single catenary system and (B) a catenary system with a surface-floating buoy. The WEC was evaluated under operational conditions, operational conditions with a constant surface current, and extreme seas. The results show that under operational conditions, the WEC-mooring B configuration achieves higher energy capture than the WEC-mooring A configuration, with performance peaks at 13 s and 11 s, respectively. The presence of a surface current does not significantly influence absorbed power. Under extreme conditions, mooring B reduces mooring-line stresses but causes greater horizontal foundation forces and increased floater drift compared to mooring A. When mooring effects are included, mooring A's performance is advantageous because it shifts peak energy capture toward the dominant sea states at the study site. This maintains better station-keeping capability and achieves a maximum capture width ratio (CWR) of approximately 0.5.

The rising probability of extreme wave and storm surge events poses ever greater risks to coastal structures and populations (Toimil et al., 2020). Central to the assessment of function ability of these coastal structures and cost-effectiveness in their construction is the wave overtopping. In this context, two aspects of wave overtopping are distinguished: the average wave overtopping discharge and the individual wave overtopping volume. Understanding both aspects are essential for a proper safety assessment. Recent studies emphasize the need to delve deeper into these aspects, especially by exploring the overtopping volumes of individual waves and in particular the maximum value, Vmax (Koosheh et al., 2021). Storms are dynamic events, and their effect on the still water level (SWL) can be represented as a time-varying hydrograph. As SWL changes during a storm, it is expected that also the (maximum) individual wave overtopping volumes are variable during storm events. Typically, in laboratory experiments, wave overtopping of coastal defense structures has been investigated for constant water level (CWL) conditions and a predetermined structural exposure time frame. In this approach, any variable water level (VWL) conditions are largely ignored, except in few recent studies (Pepi et al. 2022; Kerpen et al., 2020). The impact of this oversight can be substantial, as (smaller) individual wave volumes in the early stages of a storm, when the SWL rises, can pre-load or saturate the dike, potentially weakening it before the largest overtopping volumes occur during the storm's peak. No research exists yet on the study of individual overtopping volumes for a VWL situation.

The spectral wave period Tm-1,0 is one of the most widely used characteristic wave periods in coastal engineering for the estimation of wave reflection (Zanuttigh and van der Meer, 2008), wave run-up and overtopping (Altomare et al., 2016; van Gent, 1999), and toe and armour stability (Etemad-Shahidi et al., 2021, 2020), especially in the case of coastal structures on shallow foreshores. These coastal structures are becoming more common due to sea level rise, through adaptation of existing coastal defenses (i.e., hybrid blue-grey nature-based solutions) by e.g., beach and dune nourishments in front of dikes, or through construction of coastal defense structures on existing shallow and very mildly sloped mud-flats and salt marshes, or on reef flats with steeply sloped fore reefs.

Low-lying countries typically have mildly-sloping beaches as part of their coastal defense system. Many countries in north-western Europe have coastal urban areas that rely on this type of defense system, which consists of a low-crested impermeable sea dike with a relatively short promenade, and a long (nourished) beach in front that acts as a very/extremely shallow foreshore as defined by Hofland et al. (2017). Along the cross-section of this hybrid beach-dike coastal defense system, storm waves are forced to undergo many transformation processes before they finally overtop the dike. These hydrodynamic processes include shoaling, sea-swell (SS) wave energy transfer to sub- (also infragravity or IG waves) and superharmonics via nonlinear wave-wave interactions, wave dissipation by breaking and bottom friction, reflection against the dike, wave run-up and overtopping on the dike, bore impact on a wall or building, and finally reflection back towards the sea interacting with incoming bores on the promenade. Due to breaking of the SS waves and growth of the IG waves on the shallow foreshore, the IG waves can become as important or even dominant at the toe of the dike (Hofland et al., 2017; Lashley et al., 2020), which influences the overtopping process (van Gent, 1999).

Wave attenuation under coastal vegetation results from complex hydrodynamics, where energy is removed from the mean flow due to the resistance created by the vegetation. At the scale of an individual plant, this decrease is directly linked to the transformation of energy into turbulent kinetic energy. Numerical models can capture this turbulence shedding when using very high resolutions, but not without a cost. Their applications will be limited to small spatiotemporal scales with regular waves and a single vegetation. This is sufficient for estimating the drag coefficient and investigating flexibility at the blade scale but does not provide a direct computation of wave attenuation over a densely populated vegetation patch. To enhance the scalability of numerical models used to study wave propagation over vegetation meadows, a well-established approach in literature is to implicitly account for energy transfer in the system by introducing an energy sink term into the flow equations. This method is computationally efficient and can overcome the spatiotemporal limitations inherent in direct models. The initial description of wave dissipation was presented by Dalrymple et al. (1984), estimating the energy transfer by integrating the force on a cylinder across its vertical span. An extension of this method to account for varying depths and stochasticity was published by Mendez and Losada (2004). Numerically, these formulations have been widely adapted and implemented in both time and frequency domain models, such as the vegetation model in SWAN and in SWASH by Suzuki et al. (2012) and Suzuki et al. (2019) respectively.

In the past decade, sea dikes were renovated at different locations along the Belgian coast using the concept of a stilling wave basin. Although different in geometrical details, all sea dikes use the same concept: (i) the impact of the incoming waves is reduced by the first seaward wall; (ii) overtopping waves are reflected by the second landward wall, positioned at a certain distance of the first wall on the dike’s crest and (iii) the overtopped volume is flowing back through voids in the seaward wall. In this way, overtopping discharges can be kept to tolerable limits whilst maintaining the crest elevation as low as possible (to minimize visual impact). In general, wave overtopping is calculated using numerical modelling. However, the specific geometry of a dike with stilling wave basin is a complicating factor in a (relatively) fast and accurate modelling approach. For an efficient assessment of the expected average wave overtopping discharge, employing a wave overtopping formula would be preferred.

This review article presents an analysis of Artificial intelligence (AI) applications in ocean and maritime engineering, examining the evolution, current trends, and future directions of AI in the field.A key finding is the transformative impact of Reinforcement Learning (RL), which enables real-time adaptation in dynamic and uncertain marine environments, essential for applications such as autonomous navigation, vessel control, and route optimization. Additionally, the study identifies the promising potential of hybrid AI models, which combine optimization algorithms, fuzzy logic, and deep learning to address the complex, nonlinear challenges inherent in maritime structures and fluid-structure interactions.Looking ahead, the review highlights several promising directions: the expansion of RL into new domains such as coastal erosion modelling and flood prediction; the adoption of transformer architectures for time-series forecasting; and the growing importance of Explainable AI (XAI) and digital twins for transparent and trustworthy deployment in safety-critical systems. As the industry moves towards Artificial General Intelligence (AGI), the article stresses the need for robust regulatory frameworks, ethical safeguards, and the preservation of human oversight to ensure responsible and effective integration of AI technologies in maritime applications.

Very Flexible Floating Structures (VFFS), deployed into offshore environments by the renewable energy sector, have set the ground for new marine applications. Characterized by very thin and elongated structural layouts, while composed of highly flexible materials, they exhibit non-linear structural behaviour when subjected to wave-induced loads. To numerically predict their hydro-viscoelastic response, the Applied Element Method (AEM), commonly used in non-linear structural dynamics, is introduced into the existing coupling scheme of the Smoothed Particle Hydrodynamics (SPH) solver, DualSPHysics, and the Multibody Dynamics (MBD) module of Project Chrono. In this paper, the coupling scheme is modified to implicitly define the timestep of Project Chrono, facilitating the development of AEM formulated structures. The structural response accuracy of the proposed framework is validated against analytical and experimental data in both dry and wet conditions, covering linear and non-linear deformations, as well as elastic and viscous material properties. Fluid response is also verified through wave reflection and wave dissipation, demonstrating the suitability of the developed numerical framework for modelling non-linear fluid-flexible structure interaction applications.

In this paper, a generic computational framework, based on the generalized-mode approach, is developed for the fully coupled time-domain aero-hydro-servo-elastic analysis of Hybrid Offshore Wind and Wave Energy Systems (HOWiWaESs), consisting of a Floating Offshore Wind Turbine (FOWT) and several wave energy converters (WECs) mechanically connected to it. The FOWT’s platform and the WECs of the HOWiWaES are modeled as a single floating body with conventional rigid-body modes, while the motions of the WECs relative to the FOWT are described as additional generalized modes of motion. A numerical tool is established by appropriately modifying/extending the OpenFAST source code. The frequency-dependent exciting forces and hydrodynamic coefficients, as well as hydrostatic stiffness terms, are obtained using the traditional boundary integral equation method, whilst the generalized-mode shapes are determined by developing appropriate 3D vector shape functions. The tool is applied for a 5 MW FOWT with a spar-type floating platform and a conic WEC buoy hinged on it via a mechanical arm, and results are compared with those of other investigators utilizing the multi-body approach. Two distinctive cases of a pitching and a heaving WEC are considered. A quite good agreement is established, indicating the potential of the developed tool to model floating HOWiWaESs efficiently.

Climate change is impacting atmospheric patterns and therefore wave conditions, with ports being among the most affected infrastructures, making it crucial to ensure their operability under changing climatic conditions. Most scientific studies on climate change focus on coastal erosion and flooding, whereas research on its impact on port operability remains relatively scarce. This challenge could be tackled with the emergence of Artificial Intelligence (AI), where alternative modeling approaches can be developed. Thus, a novel AI-based model specifically designed for studying port agitation is introduced herein. By integrating a hybrid deep learning approach, combining Feedforward Neural Networks (FFNNs) to model wave climate and Convolutional Neural Networks (CNNs) for port image analysis, port agitation has been successfully predicted compared to linear wave propagation models. This marks the first instance of utilizing image processing tools to analyze port agitation, resulting in a model with a remarkably low error rate, while offering a significant reduction in computational time compared to traditional wave propagation models, reducing computational time by a factor of four to ten. The accuracy of the proposed model has been investigated and validated for the Port of Valencia, located in the Spanish section of the Mediterranean Sea.

The European coasts are among the most densely populated of the world, with natural sand dune barriers urbanised and replaced by traditional hard coastal protection structures. Without the needed measures to adapt, the number of people exposed to floods is anticipated to increase 187 million worldwide by the end of the 21st century. In Europe, the coasts of The North Sea, the Baltic Sea, and the Atlantic are anticipated to experience substantial flood risks from sea-level rise, and climate extremes are also expected to impact southern Europe Mediterranean coasts (Vousdoukas et al., 2017). Future coastal management surpasses the current fixed and non-adaptive flood coastal protection setup: Hybrid Nature-based-Solutions (abbreviated as NbS) that can efficiently integrate static hard infrastructure with dynamic aeolian, and vegetated sediments are currently developed along urbanized areas of most of the European sandy coasts, yet still at small scales.

A variety of Offshore Floating Photovoltaics (OFPVs) applications rely on the capacity of their floating support structures displacing in the shape of surface waves to reduce extreme wave-induced loads exerted on their floating-mooring system. This wave-adaptive displacement behaviour is typically realized through two principal design approaches, either by employing slender and continuously deformable structures composed of highly elastic materials or by decomposing the structure into multiple floating rigid pontoons interconnected via flexible connectors. The hydrodynamic behaviour of these structures is commonly analyzed in the literature using potential flow theory, to characterize wave loading, whereas in order to deploy such OFPV prototypes in realistic marine environments, a high-fidelity numerical fluid–structure interaction model is required. Thus, a versatile three-dimensional numerical scheme is herein presented that is capable of handling non-linear fluid-flexible structure interactions for Very Flexible Floating Structures (VFFSs): Multibody Dynamics (MBD) for modularized floating structures and floating-mooring line interactions. In the present study, this is achieved by employing the Smoothed Particles Hydrodynamics (SPH) fluid model of DualSPHysics, coupled both with the MBD module of Project Chrono and the MoorDyn+ lumped-mass mooring model. The SPH-MBD coupling enables modelling of large and geometrically non-linear displacements of VFFS within an Applied Element Method (AEM) plate formulation, as well as rigid body dynamics of modularized configurations. Meanwhile, the SPH-MoorDyn+ captures the fully coupled three-dimensional response of floating-mooring and floating-floating dynamics, as it is employed to model both moorings and flexible interconnectors between bodies. The coupled SPH-based numerical scheme is herein validated against physical experiments, capturing the hydroelastic response of VFFS, rigid body hydrodynamics, mooring line dynamics, and flexible connector behaviour under wave loading. The demonstrated numerical methodology represents the first validated Computational Fluid Dynamics (CFD) application of moored VFFS in three-dimensional domains, while its robustness is further confirmed using modular floating systems, enabling OFPV engineers to comparatively assess these two types of wave-adaptive designs in a unified numerical framework.

To increase the total installed capacity, multiple wave energy converters (WECs) will be installed in an array configuration. Within these WEC arrays, hydrodynamic interactions occur and the sea state is modified accordingly. These WECs are equipped with a Power Take-Off (PTO) which converts the kinetic energy of the waves to mechanical energy. An optimal PTO can be obtained by setting the PTO control impedance equal to the complex conjugate of the intrinsic impedance of the WEC. Within a WEC array constituting of n closely spaced WECs, where hydrodynamic interactions between the WECs occur through radiation and diffraction of waves, then x n PTO control impedance matrix should be equal to the complex conjugate of then x n intrinsic impedance matrix. This paper discusses the incremental experimental modelling of five 'WECfarm' WECs: Modelling of the five isolated WECs, a two-WEC array, a three-WEC array, a four-WEC array, and a five-WEC array. System identification (SID) tests are performed to obtain an accurate dynamic model of the isolated WECs and the WEC arrays. Based on this model, causal impedance matching Proportional (P) controllers are designed, and tested fora selection of irregular long- and short-crested waves. This paper presents the dataset and results of the experimental campaign performed at the Coastal & Ocean Basin Ostend (COB), Belgium. With high measurement accuracy and repeatability, the presented dataset is reliable, while by considering controlled WECs, and operational and extreme wave conditions, it is realistic.

The wave energy sector aims to reduce the costs and maximize the Wave Energy Converter (WEC) power absorption to reach parity with other renewable energies. Likewise, the continuous change in the local metocean conditions due to several mid and long-term atmospheric and ocean events, and the reduction in air pollution from the extraction of non-renewable energies have prompted a meticulous examination regarding the WEC performance (Lavidas, 2019). Specifically, for the Belgian Continental Shelf (BCS) a performance assessment of several WECs at different locations has been developed. The eleven locations for evaluating the WECs are shown. The wave information at those locations has been estimated through numerical wave modeling by using the Simulation Wave Nearshore (SWAN) model (Booij, et. al., 1996). The numerical model setup consists of three nested meshes with resolutions of 5 x 5 km, 1 x 1 km, and 200 x 200 m. The bathymetry is based on ETOPO-1 (Eakins, et. al., 2010) and Agency for Maritime and Coastal Services (MDK). The model setup was forced with the ERA5-reanalysis (Hersbach, et. al. ,2023) wind database for 11 years (2010 – 2021). Then, the spectral parameters were validated for 2015 with the BVH buoy data (Meetnet Vlaamse Banken, 2023).