Optimizing the meso-structural parameters of 2.5D woven composites using the Non-dominated Sorting Genetic Algorithm (NSGA) can effectively improve the retention rate of 45 degrees off-axis performance relative to axial performance. NSGA generally relies on surrogate models to handle the large number of performance evaluations required during optimization. However, commonly used surrogate models such as Artificial Neural Network (ANN) face the challenge of low prediction accuracy when applied to small-sample datasets. To address this issue, a Damage-Guided Neural Network (DGNN) model inspired by Physics-Informed Neural Network (PINN) is proposed in this work. The DGNN incorporates damage images of yarns under ultimate stress states as intermediate prediction outputs, which not only enhances model interpretability but also utilizes this damage information to guide properties predictions and reduce errors. By integrating DGNN with NSGA for multi-objective optimization, the global Pareto front is obtained, from which the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) is subsequently employed to identify a compromise design with superior comprehensive performance. Compared with the baseline design, the proposed approach achieves increases of 3.99% in longitudinal tensile modulus and 2.19% in strength; 11.64% in transverse tensile modulus and 14.56% in strength; and 4.77% and 5.31% in the retention rates of 45 degrees off-axis tensile modulus and strength, respectively.

Floating photovoltaic (FPV) systems face complex multi-physics interactions from wave-induced hydrodynamics and solar variability, yet there is a lack of a digital framework to balance the large amount of data, modelling accuracy, and real-time adaptability. This study addresses this gap by developing an AI-driven digital twin framework that integrates physical experimentation, data integration, and neural network-based modelling. A novel FPV system was experimentally tested under 150 + scenarios in different solar irradiance and water wave conditions, capturing hydrodynamic, thermal, and power performances. A two-tier artificial neural network architecture was implemented, providing a high-fidelity model for detailed analysi and a reduced-order model for real-time applications. The virtual twin can predict key outputs, including heave, surge, pitch, mooring forces, PV temperature, and power output, which potentially reduces the need for sensors on the physical twin and provides more comprehensive information. In summary, the proposed digital twin framework enables remote monitoring, prediction, and intelligent management of FPV systems. Moreover, it holds the potential to support wave-adaptive panel control energy system management, and predictive maintenance. These functions position the digital twin as a core enabler for efficient, reliable, and scalable offshore solar energy deployment.

To address the efficiency limitations of conventional bidirectional turbines in oscillating water column (OWC) wave energy conversion systems, this study proposes a novel dual-chamber OWC configuration coupled with unidirectional impulse turbines. A steady-state Computational Fluid Dynamics (CFD) model based on viscous fluid theory was established and validated against experimental data. Using this model, a comprehensive parametric optimization was performed on rotor blade number, guide vane number, and blade installation angles to enhance aerodynamic performance. The optimized unidirectional turbine achieved a 59.89 % increase in average efficiency and a 67.97 % improvement in peak efficiency compared to a reference bidirectional turbine. Furthermore, the total number of rotor blades and guide vanes was reduced by 26.67 % and 42.31 %, respectively, significantly lowering material requirements and manufacturing costs. Flow field analyses revealed improved pressure distribution, reduced separation zones, and enhanced wake uniformity. This study demonstrates the potential of integrating unidirectional turbines into dual-chamber OWC systems to improve energy conversion performance and reduce structural complexity. The findings provide valuable design insights for wave energy converters. Future work will extend to transient simulations and experimental validation under oscillatory flow conditions.

Maritime transportation contributes around 3 % of global emissions. As global trade and manufacturing expand, the decarbonization of maritime operations becomes an urgent challenge. Ferry ports in the UK face significant barriers to energy transition, including limited grid capacity, lack of charging infrastructure, and constrained land availability. This study proposes the development of a Floating Photovoltaic (FPV) plant on the sea near the port to independently generate renewable electricity for charging electric vessels operating between UK and France. Four scenarios are analyzed, varying in energy generation targets and ground coverage ratios (GCRs). Energy performance is evaluated using the System Advisor Model (SAM), estimating electricity generation and battery energy storage system (BESS) requirements under limited solar irradiance. A comprehensive economic analysis examines capital expenditure (CAPEX), operational expenditure (OPEX), levelized cost of energy (LCOE), revenue, and payback periods. The study also assesses environmental benefits by quantifying CO2 emissions for FPV lifespan and compares them to diesel-based energy. Moreover, charging technologies are reviewed in relation to current technologies, and a logistics plan for integrating FPV systems and electric vessels is proposed. Results demonstrate that the FPV plant can minimize BESS requirements, and reduce payback periods to as little as 3.62 years, facilitating the pathway of ferry ports to achieve net-zero emissions by 2045, with an estimated reduction of 17million tonnes of CO2 annually. This study is among the first to assess the feasibility of using FPV systems to charge electric vessels at a UK marine port, integrating real-world spatial constraints, phased deployment planning, and life-cycle environmental analysis. It also introduces the conceptual integration of floating wireless charging infrastructure, offering a forward-looking approach to maritime electrification.

Solar energy is one of the fastest-growing contributors to the global energy market. Floating photovoltaic (FPV) systems have emerged as a promising solution to the land-use challenges faced by conventional solar farms. However, the extension of FPV systems to offshore environments is hindered by dynamic wave-structure interactions. Inspired by air-cushion vessels, this study proposes and experimentally validates a novel FPV platform supported by an inflatable air cushion that provides adjustable stiffness and passive damping through air compressibility and wave-induced volumetric deformation. The investigated platform adopts a symmetric structural configuration, which inherently mitigates asymmetric roll and yaw coupling to maintain a balanced hydrodynamic response and stable power generation under wave action. Wave tank experiments were conducted to evaluate the coupled hydro-elastic response, mooring loads, and power generation stability under varying wave heights. The results show that the air-cushion design can significantly reduce peak mooring loads by over 50% compared with the catamaran benchmark. The highest pressure of 20 mbar increases structural stiffness but causes wave-induced losses of up to 30%. Conversely, the lowest pressure of 5 mbar results in excessive compliance that amplifies pitch and heave motion. A moderate pressure of 10 mbar acts as the optimal damping condition within the tested pressure range, suppressing motion resonance while maintaining power output stability. These findings demonstrate the potential of air-cushion integration for offshore FPV adaptability.

Floating photovoltaic (FPV) systems offer a promising pathway for sustainable energy generation by avoiding land occupation, and utilising water cooling to improve energy efficiency. However, their deployment in dynamic aquatic environments introduces significant challenges, including irradiance fluctuations, hydrodynamic loads, and structural fatigue, which complicate reliable performance prediction. These highlight the need for advanced tools that can enable offshore structural monitoring, maintenance decision-making, and power management in a dynamic environment. To address these challenges, this study introduces a real-time digital twin framework for FPV systems, integrating laboratory experimentation, machine learning, and real-time visualisation. A bespoke facility combining a solar simulator, FPV prototype, and wave tank enabled 155 controlled tests under diverse irradiance and wave conditions. The resulting dataset was used to train a Random Forest model, which achieved an overall coefficient of determination of 0.990 and accurately predicted the dynamic responses of heave, surge, and pitch, with minimal discrepancies. The results were visualised through a real-time Unity-based user interface, enabling intuitive interaction and monitoring of the FPV system’s behaviour. These findings demonstrate the potential of AI-enabled digital twins to enhance operational resilience, reduce maintenance costs, and pave the way for intelligent, adaptive control of large-scale offshore FPV deployments.

Floating solar farms have become one of the most promising options for offshore energy infrastructure, yet concerns about wave-induced loading on the structures continue to hold back stakeholders. This study explores the hydrodynamic performance of floating solar arrays using systematic Computational Fluid Dynamics (CFD) simulations, analysing the dynamic behaviour of different floater configurations of catamaran, barge, and the mix of these two. The dynamic responses of 3 × 3 multi-body arrays were evaluated under regular wave conditions with wavelength-to-length ratios (λ/L) ranging from 1.62 to 4.27. The analysis focused on quantifying the Response Amplitude Operators (RAOs) for heave and pitch motions, as well as mooring line forces, to assess stability and energy dissipation characteristics. Results indicate that the barge configuration provides superior wave energy blocking in short wavelengths, with the front row significantly reducing the motion responses of downstream rows, while the catamaran configuration exhibits more similar motion behaviours across the array, as its twin-hull geometry allows greater wave transmission. However, the catamaran configuration outperforms the barge in reducing RAO amplitudes and mooring forces in longer wavelengths, showing peak mooring loads up to 30% lower. A hybrid array combining an upstream row of barge floater with downstream catamarans was envisioned to integrate the wave-blocking effect of the barge with the motion stability of the catamaran units; however, simulation results show limited performance enhancement under the tested wave conditions. Overall, this study provides insights into floater configuration for offshore floating solar farms, informing design choices as the demand for large-array systems grows.

Floating photovoltaic (FPV) systems in coastal and nearshore regions are subjected to complex wave loads that significantly influence their hydrodynamic performance. In the future, industrial scale FPV projects can consist of numerous floating bodies that are too large to be modeled using existing modelling methods such as Computational Fluid Dynamics. Therefore, there is a need to develop data-driven rapid prediction approaches. This study presents a data-driven framework to predict the heave and pitch response amplitude operators (RAOs) of FPV arrays under different wave conditions. A verified simulation model is developed, generating a dataset that incorporates the key influencing factors, including incident wave angle, wavelength-to-floater-dimension ratio, and mooring type. Random Forest (RF) and Multilayer Perceptron (MLP) models are trained and optimized through grid search cross-validation, demonstrating that both models accurately capture the spatial distribution and magnitude of RAOs, with the MLP model showing superior generalization capability. Interpretability analysis further reveals that the wavelength-to-floater-width ratio is the dominant factor driving RAO responses, while appropriate mooring strategies can effectively suppress motions under extreme conditions. Compared with conventional hydrodynamic simulations, the proposed approach significantly reduces computational cost and enables rapid evaluation of FPV dynamic responses, which provides a potentially workable approach to facilitate various purposes of large-scale ocean solar projects, such as design, monitoring, and digital twins.

Floating photovoltaic (FPV) systems offer a promising route for expanding solar generation in coastal and offshore water bodies. However, wave-induced motion, mooring loads, and intermodule forces govern their viability. Excessive motion reduces energy yield, amplifies connector and mooring tensions, and threatens long-term reliability, making accurate hydrodynamic prediction essential for design. Most current CFD studies focus on single-row floaters, typically barge or catamaran-type platforms connected by rigid or hinged connections, leaving the behaviour of multi-row FPVs with compliant inter-module connections largely unexplored. This study develops and validates a high-fidelity CFD framework for rope-mesh FPV arrays, implementing a novel in-memory spring-connector formulation within OpenFOAM's rigidBodyMotion framework to represent compliant, tensioned rope connections. The approach is validated against wave tank experiments for both single-module and 2 & times;2 array configurations. Validation demonstrates excellent accuracy, with heave and pitch RAO errors within 5-13% across wavelengths. The framework successfully captures multi-body interaction effects, including wave-field shielding that reduces aft-row response by upto 10%. Direct comparison demonstrates that conventional rigid joints underpredict pitch by over 20% and overestimate heave by 18%, while the spring connector maintains errors within 5-13%, confirming the necessity of force-based compliant coupling for accurate rope-mesh FPV prediction. Connector force analysis reveals that streamwise connectors experience forces 3-5 times larger than transverse connectors, with peak forces occurring at lambda/L approximate to 2.5-3.5, where phase differences maximise differential motion between rows. These results establish streamwise connections as the critical design drivers for rope-mesh FPV systems under head-sea loading.

Most current analytical research on the hydroelastic interaction between water waves and submerged horizontal elastic plates remains within the scope of linear theory due to the underdevelopment of mathematical methods for solving nonlinear problems. To address this gap, this work employs an approach that combines computational fluid dynamics (CFD) with computational solid mechanics (CSM) to dynamically simulate the fully coupled nonlinear hydroelastic interactions between ocean waves and a submerged horizontal plate. This research highlights the significance of nonlinear point responses of a submerged horizontal plate under focused wave conditions. A phase-based harmonic separation method (i.e., phase-decomposition method) is used to isolate wave amplitude and force harmonic components in complex wave scenarios. This approach allows for the clean delineation of individual harmonics from the total wave force by controlling the phase of incident focused waves and is for the first time applied to the response analysis of elastic structures. This paper successfully used the phase-decomposition method to separate the individual harmonics of the point displacement of a horizontal elastic plate, directly demonstrating the significance of nonlinear responses. Additionally, the impact of plate rigidity, which relates to natural frequency, on nonlinear responses is investigated. The results indicate that plates with a certain dimensionless plate rigidity will exhibit more significant nonlinear responses. By cleanly separating each individual harmonic response, this study provides new insights into the nonlinear hydroelastic responses of a horizontal plate interacting with water waves and offers a new perspective on fatigue analysis, underscoring the importance of nonlinearity for future engineering designs.

This study investigates the hydrodynamic and energy conversion performance of a cylindrical oscillating water column (OWC) device integrated with a breather valve for bidirectional pneumatic regulation. The primary objective is to suppress peak power output under high wave conditions and reduce the required generator rated capacity, thereby improving the load factor and operational efficiency during normal wave conditions. A threedimensional computational fluid dynamics (CFD) is developed to simulate steady-state and transient flow characteristics, incorporating the nonlinear behavior of the breather valve. Parametric analyses are conducted to evaluate the effects of valve threshold pressure (3-12 kPa) and opening ratio (1 %-6 %) under regular wave conditions. Results reveal that the valve's pressure and flow regulation capabilities increase with the opening ratio, though this effect gradually saturates. Moreover, for a given threshold, a minimum opening ratio is required to achieve stable pressure relief, which decreases with increasing threshold pressure. The optimal configuration (3 kPa threshold with 5 % opening ratio) achieves substantial performance improvements compared to a conventional OWC without a breather valve. Specifically, the rated generator capacity is reduced by 87 % (from 740 kW to 100 kW), average generator efficiency increases by 50 % (from 60.8 % to 90.9 %), and average wave-to-electricity conversion efficiency improves by 46 % (from 10.3 % to 15 %). Additionally, annual energy production increases by 43 %, from 83,000 kWh to 119,000 kWh. These findings highlight the breather valve's effectiveness in stabilizing pneumatic power output and enhancing the overall efficiency of OWC systems.

Floating Photovoltaic (FPV) systems are a promising solution for offshore renewable energy, with modular FPV arrays offering significant potential for large-scale deployment. However, the development of FPV systems is hindered by insufficient understanding of their hydrodynamic performance, which affects stability and energy efficiency. This study proposes a dual-module FPV array combining box-type and semi-submersible modules to improve hydrodynamic stability under mild wave conditions in the South China Sea. The effects of array layout and PTO damping are examined under various wave conditions. The system is optimized to balance energy harvesting and motion control, and its performance is further evaluated under irregular waves at selected operational sites. Results indicate that the dual-module design effectively leverages the hydrodynamic characteristics of both module types, reducing motion responses and dynamic loads. The incorporation of optimal PTO damping further enhances system stability and energy efficiency by effectively suppressing pitch and heave motions, with maximum reductions of 31.43 % and 41.56 %, respectively, under the selected operational wave conditions. While damping remains effective under head-on waves, its performance slightly decreases under oblique waves, underscoring the importance of aligning the array with the predominant wave direction. Additionally, integrating a wave energy PTO system into the FPV array enables wave power to supplement solar energy, contributing 17.04 % of the total energy output at the selected operational sites. The proposed FPV system offers a practical solution for stabilizing floater motion, enhancing solar power generation, and capturing wave energy, advancing the feasibility of FPV technology for large-scale offshore applications.

Flexible Fluid-Structure Interaction (FFSI) has emerged as an important, but challenging research direction in modern ocean engineering. This line of research gradually evolved in response to the pressing need to model the dynamic responses of ships and marine structures to sea loads; to predict the performance of flexible marine propellers, energy converters, and coastal protection systems; and to understand the mutual interactions between sea ice, marine vegetation, and mud with oceanic and coastal processes occurring near the surface and seabed. This review presents the state of knowledge and art of modelling of FFSI in the maritime environment, tracing research progress from early physical tests to high-fidelity computational ones emerged recently. Flexible wave-structure interaction, global ship hydroelasticity, hydroelastic slamming, flexible marine propellers, vegetation dynamics, and wave-mud interactions are covered. Limitations and strengths of existing models, and the challenges that remain are discussed in-depth, and it is concluded that FFSI-based research in ocean engineering has very well grown, though some gaps are still open. In specific, hydroelastic effects are still overlooked in the design practices and classification rules do not fully incorporate them, and there are still concerns regarding uncertainties related to FFSI modelling of flexible slamming, dynamic of flexible marine vegetation, and wave-mud interactions. Hence, future research must bridge computational modelling with real-world applications, expand benchmarking coverage for marine engineering problem, and incorporate AI-based methods for modelling FFSI problems, predicting related dynamic responses, or accelerating simulations.

The transition towards Net Zero Emissions (NZEs) is being accelerated by hybrid renewable technologies such as Floating Photovoltaic (FPV) systems and marine current turbines, which combine solar panels and cross-flow marine turbines mounted on floating structures for near-shore applications. Despite their innovative potential, these renewable technologies face significant challenges in stability and durability due to the effects of wind, waves, and ocean currents. Therefore, a flexible mooring system is essential to address these challenges. This research examines the influence of variations in the number of mooring lines and wave direction on the hydrodynamic response of FPV systems. Utilizing a catenary mooring system consisting of anchors, mooring lines, floats, and connectors, the study evaluates various configurations to determine the optimal solution for enhanced motion stability. Computational Fluid Dynamics (CFD) simulations are employed to analyze the dynamic response of FPV systems under different environmental conditions, represented on a sea-state scale, with a focus on pure oscillatory motions: heave, roll, and pitch. The findings aim to provide valuable insights for the design and operation of more stable and efficient FPV systems in marine environments, thereby supporting the advancement of sustainable renewable energy.

Land availability constraints limit the installation of conventional ground-mounted solar installations. As a result, Floating Photovoltaic (FPV) systems are gaining popularity as an alternative to renewable energy generation. FPV consist of individual solar panels that are commonly symmetrical and modular. However, the hydrodynamic behaviour of FPVs in water surface waves is understudied to ensure their stability and optimal performance under varying environmental conditions. This literature review examines various modelling techniques applied in studying FPV hydrodynamics. Specifically, the application of Computational Fluid Dynamics (CFD) solvers and potential flow theory solvers is investigated for their effectiveness in capturing the behaviour of FPVs and mooring dynamics under the impact of wind and waves. The review highlights the advantages and limitations of each approach. Findings suggest that a combined CFD-potential flow approach offers a perfect balance between accuracy and computational efficiency, offering valuable insights into the performance of FPVs. However, extensive research is notably absent in hydrodynamic modelling for large-scale FPVs. This lack of research represents a significant gap in our current study on multiscale FPV systems.