Search Results (119)

Photovoltaic systems deployed on large floating platforms in nearshore waters are strongly influenced by hydroelastic effects, nonlinear shallow-water waves, and variable bathymetry. This study develops a time-domain hydroelastic framework that couples the fully nonlinear non-hydrostatic wave model NHWAVE with a Rankine-source potential-flow solver and a discrete-module Cummins formulation. The wave model provides incident pressures and kinematics over uneven seabeds, while the potential-flow solver evaluates radiation and diffraction effects and transfers the resulting hydrodynamic coefficients into the time domain. Numerical simulations are carried out for a 600 m modular floating structure under regular waves over flat and sloped bathymetries with $tan\alpha =0.0133$, wave periods of 4–6 s, and wave heights of 0.3–1.0 m. The results show that bathymetric variation intensifies shoaling-induced excitation, modifies added-mass and damping distributions, increases the spatial non-uniformity of hydroelastic motions, and amplifies bending-moment RMS responses relative to the flat-bottom case. Additional comparisons between rigid-body and hydroelastic models show clear period-dependent redistribution of motions and bending demand. These results demonstrate that both local bathymetry and structural elasticity must be considered for the reliable analysis and design of nearshore floating photovoltaic systems and other large floating structures. Full article

For AUVs operating under large-rudder-angle yaw maneuvering conditions, linearized hydrodynamic-derivative models often fail to accurately capture strongly nonlinear flow effects, and the applicability of control parameters becomes limited. To address these issues, this paper proposes a CFD-in-the-loop control simulation and parameter optimization framework for large-rudder-angle yaw maneuvers. Based on a coupled hull–propeller–rudder solution method, an unsteady CFD motion simulation model is developed that simultaneously accounts for propeller wake, rudder inflow, and hull-flow interaction, thereby enabling a strongly coupled solution of flow-field evolution and the six-degree-of-freedom motion of the vehicle. On this basis, a CFD-in-the-loop closed-loop control simulation framework is established by integrating the controller, actuator dynamic model, virtual sensors, and CFD motion simulation module into a unified framework, thereby realizing closed-loop computation of control input, flow response, motion update, and state feedback. Furthermore, under the same controller structure and parameter settings, the large-rudder-angle yaw responses predicted by the linearized hydrodynamic-derivative model and the CFD-in-the-loop simulation framework are compared and analyzed. This comparison reveals the dependence of control parameters on the underlying dynamic model and highlights their limited applicability under strongly nonlinear operating conditions. Finally, to address the high computational cost of CFD-in-the-loop simulations, a surrogate-model-based control parameter optimization method is developed to improve parameter tuning efficiency and enhance closed-loop control performance. The results show that the proposed CFD-in-the-loop control simulation framework can effectively characterize the nonlinear hydrodynamic effects arising during large-rudder-angle maneuvers, and provides a more physically consistent basis for control parameter optimization, analysis, and design. Full article

Flood and flash flood events can generate severe hydraulic actions on civil structures, requiring modeling strategies able to link flow features to structural damage. This paper proposes a two-scale numerical framework based on advanced finite element modeling to assess the vulnerability of structures subjected to inundation and flood-driven impact. At the macroscale, the flood propagation and the interaction with the built environment are simulated through the depth-averaged Shallow Water Equations, adopting a time-explicit interface treatment to capture the evolution of the free surface. The macroscale model provides time-dependent water depth and flow velocity along the external surfaces of the structure, which are then used to derive hydrostatic and hydrodynamic actions, also in comparison with code-based formulations. At the mesoscale, these actions are transferred to a detailed structural model to investigate the nonlinear mechanical response of the building. Structural components are described through a coupled damage–plasticity constitutive law, enabling the prediction of stiffness degradation, cracking-driven damage patterns, and the identification of the most critical structural zones under flood loading. The proposed workflow is finally applied to a real structure located in the municipality of Cosenza (Italy), demonstrating the capability of the approach to combine hydraulic intensity measures with physics-based structural damage assessment, supporting scenario analyses and risk mitigation evaluations. Full article

Helical gear transmissions in wind turbine gearboxes operate under high torque, variable speed, and complex rolling–sliding contact conditions, where friction-induced wear evolves in a spatially non-uniform manner. However, most existing dynamic models assume uniform or mild wear and therefore fail to capture the nonlinear coupling between localised tooth surface degradation, gear mesh dynamics, and vibration response. In this work, a nonlinear dynamic model of a helical gear pair is formulated by incorporating time-varying mesh stiffness, elasto-hydrodynamic lubrication (EHL)-based friction forces, and wear-dependent contact geometry. The governing equations of motion are derived to explicitly account for the influence of inhomogeneous tooth wear on the contact load distribution and frictional excitation during meshing. Wear evolution is represented as a spatially varying modification of tooth surface topology, enabling the progressive coupling between wear depth, mesh stiffness perturbations, and dynamic transmission error. The model is employed to analyse the effects of non-uniform wear on system stability, vibration spectra, and dynamic response under wind turbine operating conditions. Numerical results reveal that uneven wear introduces nonlinear modulation of gear mesh forces and generates characteristic sidebands and amplitude variations in the vibration signal that are absent in conventional mild-wear formulations. These wear-induced dynamic features provide mathematically traceable indicators for the onset and progression of uneven tooth degradation. The proposed framework establishes a physics-based link between wear evolution and measurable vibration responses, providing a rigorous foundation for advanced vibration-based diagnostics and model-driven condition monitoring of wind turbine gearboxes. Full article

Liquefied natural gas (LNG) sloshing occurs during marine transportation and storage due to vessel motion or external disturbances, leading to complex fluid–structure interactions within the containment system. This study employs OpenFOAM to develop a numerical model of LNG sloshing. The model solves the incompressible multiphase Navier–Stokes equations and utilizes the Volume of Fluid (VOF) method to capture the dynamic behavior of gas–liquid interface. The numerical model was validated against experimental data. Based on this model, the key hydrodynamic characteristics are investigated for LNG sloshing, including nonlinear free surface, transient pressure distribution on the tank walls due to liquid impact, and energy dissipation mechanisms. By varying excitation frequencies, amplitudes, and the configuration of internal components such as baffles or anti-sloshing devices, the study explores the sloshing response and effective control strategies. The results indicate that appropriately designed baffles can significantly mitigate sloshing-induced impact pressures on tank walls and enhance system stability. In the future, this study could extend to multi-layer fluids, multi-degree-of-freedom motions, and simulations under more complex real-world conditions. Full article

The global transition of offshore wind energy into deep-water environments necessitates precise modeling of the complex, nonlinear dynamic responses of floating offshore wind turbines (FOWTs) to stochastic loads. Traditional industry-standard simulation tools often rely on potential flow theory, which neglects critical viscous effects and requires manual, empirical tuning of damping coefficients, reducing model reliability, while CFD modeling demands large computational resources. This paper introduces an application of advanced neural network techniques to model the coupled dynamic response of FOWTs under varied ocean conditions, reducing the simulation time required for training high-fidelity models. The architecture was trained using experimental data from the OC5 semi-submersible platform under the LC4.1 load case and further validated across a matrix of heterogeneous conditions, encompassing steady, turbulent, and irregular wind and wave environments. Results demonstrate exceptional predictive accuracy across coupled degrees of freedom (Heave, Pitch, and Surge), with the model achieving a coefficient of determination (${\mathrm{R}}^2>0.9$) and maintaining superior phase coherence without discernible time lag. Power spectral density analysis confirms the model’s robust ability to capture resonant frequencies and hydrodynamic restoration across varied sea states. This data-driven framework provides a robust, near-instantaneous alternative for simulating FOWTs global dynamics. By successfully capturing complex nonlinear interactions and inertial effects, the methodology enables rapid decision-making in preliminary design, real-time digital twinning, and accelerated long-term fatigue analysis for safety-critical offshore applications. Full article

Docking vessels are used to transport and launch landing crafts, for launching offshore platforms, and in other marine operations. This research develops a new concept for docking vessels, with the aim of optimizing landing operations. Our idea involves separating the functions of transit and landing into two different vessels, where the transporter is the docking vessel of the lander. This generates an efficient concept, as efficient transportation craft and efficient landing craft have different properties to fulfil their functional requirements. The separation enables the design of each vessel with appropriate performance in areas such as cruising speed, range and seakeeping. These functional specifications affect the whole naval architecture of the vessels. This concept is applicable for shores with no harbor facilities, where landing may be necessary for supply or survey. The transporter provides a floating base to the landing craft, with advanced cruising performance, while the lander design has optimal features for shallow water maneuvering and for landing. The docking vessel is of a Semi-SWATH (Small Water-Plane Area Twin Hull) type. A critical aspect of the design concept is the feasibility of launching and docking operations. This research develops this new concept for docking vessels and applies hydrodynamic response analysis to the transporter’s interaction with the lander, for several operational sea states. The method used for the hydrodynamic analysis involves modeling the vessels and solving the wave–body problem for the two interacting vessels, in the frequency domain as well as in the time domain. The time domain analysis enables us to determine the motion of the vessels in real sea spectra, including the representation of the nonlinear response of fenders between the vessels. We apply the AQWA software 2021 developed by ANSYS. The results validate the suitability of this docking application up to a significant wave height of 1.5 m, which present a margin of 0.1 m above the upper limit of sea state 3: 1.4 m. This shows the feasibility of conducting launching and docking operations using this unique design; there is a significant possibility of using this technique to achieve fast and comfortable transportation to a natural shore with no terminal facilities. Full article

As offshore wind power development advances into deeper waters, tension leg platform (TLP) floating wind turbines stand out for their excellent motion performance, lightweight structure design, and minimal seabed footprint. This paper reviews the advancements in TLP technology, covering structural configurations, dynamic characteristics and control strategies. Particular emphasis is given to analyzing dynamic response under combined environmental loads, including nonlinear motions induced by higher-order wave forces and parametric excitations, as well as the multiphysics coupling mechanisms involving aerodynamics, hydrodynamics, servo control, and structural dynamics. The review concludes by outlining future trends in platform scaling, intelligent operation and maintenance, and multi-energy integration. Overall, this review provides strategic insights for further research and engineering applications of TLP floating wind turbines. Full article

Public health impacts of non-optimal temperatures and air pollution have received insufficient attention in Southeast Europe, one of the most air-polluted regions in Europe, simultaneously pressured by climate change. This study employed a multimodal approach to characterize the microclimate and air quality and conduct a health impact assessment in the three biggest cities in Bulgaria. Simulation of atmospheric thermo-hydrodynamics and assessment of urban microclimate relied on the Weather Research and Forecasting model. Concentrations of fine particulate matter (PM_2.5) and nitrogen dioxide (NO₂) were calculated with a land-use regression model. Ischemic heart disease (IHD) hospital admissions were linked to daily measurements at background air quality stations. The results showed declining trends in PM_2.5 but persistent levels of NO₂, especially in Sofia and Plovdiv. Distributed lag nonlinear models revealed that, in Sofia and Plovdiv, PM_2.5 was associated with IHD hospitalizations, with a fifth of cases in Sofia attributable to PM_2.5. For NO₂, an increased risk was observed only in Sofia. In Sofia, the risk of IHD was increased at cold temperatures, while both high and low temperatures were associated with IHD in Plovdiv and Varna. Short-term effects were observed in response to heat, while the effects of cold weather took up to several weeks to become apparent. These findings highlight the complexity of exposure–health interactions and emphasize the need for integrated policies addressing traffic emissions, urban design, and disease burden. Full article

Understanding particle transport in rough-walled fractures is essential for predicting flow behavior, clogging, and permeability evolution in natural and engineered subsurface systems. This study develops a fully coupled CFD–DEM framework to investigate how self-affine fractal roughness, represented by the Joint Roughness Coefficient (JRC), governs fluid–particle interactions across multiple scales. Nine fracture geometries with controlled roughness were generated using a fractal-based surface model, enabling systematic isolation of roughness effects. The results show that increasing JRC introduces a hierarchy of geometric perturbations that reorganize the flow field, amplify shear and velocity-gradient fluctuations, and enhance particle–wall interactions. Particle migration exhibits a nonlinear response to roughness due to the competing influences of disturbance amplification and the formation of preferential high-velocity pathways. Furthermore, roughness-controlled scaling relations are identified for mean particle velocity, residence time, and energy dissipation, revealing JRC as a fundamental parameter linking geometric complexity to transport efficiency. Based on these findings, a unified mechanistic framework is established that conceptualizes fractal roughness as a multiscale geometric forcing mechanism governing hydrodynamic heterogeneity, particle dynamics, and dissipative processes. This framework provides new physical insight into transport behavior in rough fractures and offers a scientific basis for improved prediction of clogging, proppant placement, and transmissivity evolution in subsurface engineering applications. Full article

Driven by global initiatives to mitigate climate change, the offshore wind power industry is experiencing rapid growth. Personnel transfer between service operation vessels (SOVs) and offshore wind turbines under complex sea conditions remains a critical factor governing the safety and efficiency of operation and maintenance (O&M) activities. This study establishes a fully coupled dynamic response and control simulation framework for an SOV equipped with an active motion-compensated gangway. A numerical model of the SOV is first developed using potential flow theory and frequency-domain multi-body hydrodynamics to predict realistic vessel motions, which serve as excitation inputs to a co-simulation environment (MATLAB/Simulink coupled with MSC Adams) representing the Stewart platform-based gangway. To address system nonlinearity and coupling, a composite control strategy integrating velocity and dynamic feedforward with three-loop PID feedback is proposed. Simulation results demonstrate that the composite strategy achieves an average disturbance isolation degree of 21.81 dB, significantly outperforming traditional PID control. Validation is conducted using a ship motion simulation platform and a combined wind–wave basin with a 1:10 scaled prototype. Experimental results confirm high compensation accuracy, with heave variation maintained within 1.6 cm and a relative error between simulation and experiment of approximately 18.2%. These findings demonstrate the framework’s capability to ensure safe personnel transfer by effectively isolating complex vessel motions and validate the reliability of the coupled dynamic model for offshore operational forecasting. Full article

The use of ships and boats as sea-state (SS) measurement platforms has the potential to expand ocean observations while providing actionable information for real-time operational decision-making at sea. Within the framework of the Wave Buoy Analogy (WBA), this work develops an inverse approach in which efficient simulations of wave-induced motions of an advancing vessel are used to train a neural network (NN) to predict SS parameters across a broad range of wave climates. We show that a reduced set of novel motion discriminant variables (MDVs)—computed from short time series of heave, roll, and pitch motions measured by an onboard inertial measurement unit (IMU), together with the vessel’s forward speed—provides sufficient and robust information for accurate, near-real-time SS estimation. The methodology targets small, barge-like tugboats whose operations are SS-limited and whose motions can become large and strongly nonlinear near their upper operating limits. To accurately model such responses and generate training data, an efficient nonlinear time-domain seakeeping model is developed that includes nonlinear hydrostatic and viscous damping terms and explicitly accounts for forward-speed effects. The model is experimentally validated using a scaled physical model in laboratory wave-tank tests, demonstrating the necessity of these nonlinear contributions for this class of vessels. The validated model is then used to generate large, high-fidelity datasets for NN training. When applied to independent numerically simulated motion time series, the trained NN predicts SS parameters with errors typically below 5%, with slightly larger errors for SS directionality under relatively high measurement noise. Application to experimentally measured vessel motions yields similarly small errors, confirming the robustness and practical applicability of the proposed framework. In operational settings, the trained NN can be deployed onboard a tugboat and driven by IMU measurements to provide real-time SS estimates. While results are presented for a specific vessel, the methodology is general and readily transferable to other ship geometries given appropriate hydrodynamic coefficients. Full article

New approaches to the characterization of porous materials must satisfy principles of green analytical chemistry; in addition, they should be reproducible, versatile, and capable of providing relevant information for specific applications. Membrane characterization techniques often fail to meet some of these requirements. Specifically, hydrodynamic porous-based model methods (HPMMs) enable the simulation and evaluation of membrane properties, as well as the monitoring of changes in the response to controlled and uncontrolled modifications. Nevertheless, HPMMs are limited by the multifactorial relationships between their variables and by the generation of only single-value responses. Here, a semi-empirical approach to the characterization of membrane pore structure is proposed and evaluated using simple experimental measurements from pristine and modified membranes. The model enables the determination of the effective pore radius based on two size descriptors related to porosity and permeability, the construction of pore size distributions, and the estimation of structural parameters, such as the number of pores, pore size, and surface porosity. Furthermore, it allows for the simulation of Darcy-type flow behavior in both linear and nonlinear regimes. The model was evaluated on pristine and poly(vinyl alcohol)-modified poly(ethersulfone) ultrafiltration membranes (60–120 mmolL⁻¹) by diafiltration (100–400 kPa). Results demonstrate the usefulness of the model in characterizing membrane pore structure by using simple, fast, and non-destructive methods, thereby enabling advances in analytical diafiltration for membrane characterization. Full article

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. Full article

Floating offshore wind turbines (FOWTs) are crucial for harnessing deep-sea wind energy resources. However, existing studies on FOWTs have predominantly focused on standalone wind turbines, neglecting the wake effects from upstream turbines within the offshore wind farms, thereby leading to inaccurate analyses. This study developed a coupled dynamic analysis method integrating aerodynamics, hydrodynamics, and mooring dynamics, incorporating the upstream wake effects through a three-dimensional (3D) Gaussian wake model and a nonlinear lift line free vortex wake (LLFVW) model. The proposed method was validated through comparisons with experiments in the wave tank and on the equivalent mechanism by the scaled-down models. Dynamic responses in four upstream wake conditions, i.e., no-wake, central wake, lateral offset wake, and multi-wake conditions, were simulated. The results indicated that upstream wake effects exert a significant influence on the dynamic responses of the FOWTs. All the three wake conditions markedly reduced the vibration displacement, fore–aft and side-to-side moments due to velocity deficits. Compared to the central wake, the lateral offset wake exerted a more pronounced effect on the fluctuations in tower-top vibration acceleration, the variations in tower-base moment, and the fluctuations in platform pitch acceleration, thereby posing critical fatigue risks. In contrast, multi-wake effects are less pronounced under the studied configuration. These findings emphasize the necessity of avoiding lateral offset exposures in wind farm layout planning. The proposed framework offers a practical tool for wake-aware design and optimization of FOWTs arrays. Full article