This study presents a long-term analysis of three different configurations of a spar-type floating wind turbine platform. The probability distributions of long-term motion responses and tower base bending moments for the floating platforms are obtained from wave data in the North Atlantic Ocean. The transfer functions of the platform motions and tower base forces are obtained from aero-servo-hydro-elastic simulations. The long-term distribution is based on transfer functions and theoretical spectra for the sea states that describe the wave data. Responses of the spar-type floating wind turbine platforms are obtained for surge, sway, heave, roll, pitch, and yaw motions. The transfer function for these responses of the floater is obtained using the aero-servo-hydro-elastic simulation. Four design wave-spectrum models that represent the sea states are selected for the present study to evaluate the long-term response spectra. A comparative study of the three spar configurations is performed to support design and safety considerations for floating wind turbines. The study will help to optimize design, reduce costs, implement life-extension strategies, and enable risk-informed decision-making, contributing to the safe and sustainable deployment of floating offshore wind energy systems.
Tsunami bores generate short-duration, highly turbulent flows that impose intense bed shear stress on coastal structures, often leading to toe scour and structural instability. This study experimentally examines the transient evolution of bed shear stress and scour formation at four seawall geometries (box, curve, slope, and step types) using a dam-break wave testing facility and high-resolution Particle Image Velocimetry (PIV). Controlled bores with initial reservoir depths (H = 13, 15, 17 cm) propagated over a movable bed of 1 mm glass beads for scour experiments. PIV measurements on an identical fixed-bed setup from which near-bed shear rate and bed shear stress were derived. Results show scour initiated within the first second after impact and corresponded to brief shear intensifications rather than sustained bed shear stress levels. The box-type seawall produced the deepest scour due to a concentrated downward jet at the toe, even though its peak bed shear stress was lower than that of the other geometries. The curve, slope, and step-type seawalls generated higher instantaneous bed shear stress values but negligible scour because their geometries redirected momentum and shortened the duration of near-bed shear. These results indicate that the bed shear stress magnitude alone is not enough to determine sediment response, but that the duration and direction of transient shear events determine the initiation of motion under tsunami-like bores. Profiles with curved, sloped and stepped form were especially effective in reducing toe scour by dispersing bore momentum and limiting the bed exposure to high shear. This study provides integrated laboratory dataset linking PIV-derived transient bed shear stress with measured scour initiation under wet-bed tsunami bore conditions.
This study introduces the Generalised Admiralty Equation (GAE) to estimate the required calm-water propulsion power using semi-empirical closed-form formulations and a modified Admiralty coefficient ( A_c' ), with limited input data. Additional corrections for protruding appendages, external domes, wind, waves, or other external resistance contributions may subsequently be incorporated using appropriate supplementary methods. The usefulness of the method is particularly relevant for estimating the Energy Efficiency Design Index (EEDI) and optimizing ship configurations at the early design stage. Validation across several hull types shows deviations of approximately 4
Accurate quantification of atmospheric emissions from port service vessels remains challenging in many developing regions because detailed monitoring systems and advanced atmospheric-dispersion models are often unavailable. This study presents a bottom-up framework for estimating emissions and assessing their potential transport toward adjacent terrestrial environments, using the Port of Mohammedia (Morocco) as a case study. Operational data collected from seven service vessels during 2024, including fuel consumption, vessel activity, and engine characteristics, were combined with standard emission factors to estimate annual emissions of carbon dioxide (CO2), nitrogen oxides (NOx), sulfur dioxide (SO2), particulate matter (PM2.5), and particulate matter (PM10). A quality-control procedure was implemented to identify anomalous records and improve inventory reliability. Annual emissions were estimated at 961.24 t CO2, 15.20 t NOx, 0.55 t SO2, 0.26 t PM2.5, and 0.31 t PM10, with substantial temporal variability driven by vessel activity and fuel consumption. Two vessels alone contributed 65.8
The present study investigates wave interaction with two Semi-trapezoidal Porous Breakwaters (STPB) through detailed experimental and soft-computing-based analyses. The hydrodynamic behaviour of the STPB is examined in a wave flume by considering different structural parameters, including variations in porosity and the relative placement of the breakwaters. The influence of these parameters on wave reflection, transmission, and energy dissipation characteristics is systematically analysed under regular wave conditions. The hydrodynamic parameters obtained experimentally are further utilized to develop predictive models for assessing the performance of the porous breakwaters. To enhance prediction capability and reduce the dependency on time-consuming experimental investigations, advanced soft computing techniques such as Artificial Neural Networks (ANN), Support Vector Machines (SVM), and Adaptive Neuro-Fuzzy Inference Systems (ANFIS) are employed. The experimental dataset is divided into training and testing subsets for model development and validation. The predictive performance of the developed models is evaluated using statistical indicators including the coefficient of correlation, root mean square error (RMSE), and scatter index (SI). The importance of the present study lies in the combined experimental and comparative soft-computing-based investigation of STPB, which has received limited attention in previous coastal engineering studies. The study not only develops efficient predictive models for hydrodynamic characteristics of porous breakwaters but also compares the effectiveness of ANN, SVM, and ANFIS approaches in modelling wave-structure interaction problems. The research contributes toward the development of computationally efficient tools for predicting the performance of submerged porous coastal structures in both near-shore and deep-water regions. The findings provide valuable information for the design, optimization, and sustainable application of porous breakwaters for coastal protection and wave energy management.
