Applied Ocean Research最新文献

The wave glider is an unmanned surface vehicle propelled by wave energy, consisting of three main components: a surface float, a submarine glider, and a tether. The submarine glider serves as the primary propulsion mechanism, converting the wave-induced motions of the float into forward thrust, which is crucial for the wave glider’s energy absorption efficiency. However, predicting the motion performance of the submarine glider presents a significant challenge due to its complex and unique structure. In this study, we establish a kinematic and dynamic model of the submarine glider’s hydrofoils, considering the elastic effects such as spring stiffness, spring preload, and spring attachment positions. To support this model, wind tunnel tests were conducted to determine the lift and drag coefficients of the submarine glider under various motion states. Utilizing the elastic hydrofoil model and the experimentally obtained lift and drag coefficients, we developed a comprehensive kinematic and dynamic simulation model of the submarine glider under heave excitation forces. To validate the accuracy of this model, performance tests for the submarine glider were designed under different vertical excitation forces , with results compared to simulation outcomes. The findings indicate that the deviation between simulated and experimental outcomes is less than 5%, demonstrating the model’s precision. This accurate simulation capability allows for detailed analysis of the effects of various design parameters on the glider’s performance and lays a solid foundation for high-accuracy motion simulation of the entire wave glider.

Large-scale direct shear tests were conducted to investigate the shear behavior of the interface between coral sand and geogrid. Polypropylene biaxial geogrid was embedded in the coral sands with two grain size distributions, which were in-situ coral sand (ISG) and uniformly graded coral sand (UG) from the Paracel Islands in the South China Sea. The results revealed the strain-softening behavior of both coral sands. The peak shear strength of the ISG coral sand was higher than that of the UG coral sand since the relative density of the ISG coral sand was higher. A bilinear relationship of peak shear stress versus normal stress was observed, with a dividing point of 100 kPa normal stress. This is because the shear displacement of the coral sand transferred from shear dilatancy to shear contraction when the normal stress reached 100 kPa, which enhanced the cohesion. The irregular shape of coral sand particles and the strong interaction of the geogrid contribute to a higher interface shear coefficient of coral sand, compared with silicious sand. The relative particle breakage was found to increase as the growth of the normal stress, and breakage was more significant in the ISG coral sand. The particle breakage rate of the reinforced and unreinforced coral sand was very close to each other, indicating that the application of geogrid in coral sand has little effect on the particle breakage rate.

Catastrophic structural failure caused by fatigue damage under cyclic loads can be avoided by identifying critical locations of the damage initiation and the fatigue life during the design stage. Peridynamic (PD) theory defines structure as a collection of material points with non-local bond interactions where the structural discontinuity due to fatigue represented by instantaneous bond breakage is estimated through cumulative decrement of the bond’s life at each load cycle. In this work, we model a reference jacket presented under the Offshore Code Comparison Collaboration Continuation project (OC4) through peridynamic beam formulation. Initially, the static deformations of the beam and deformations of the OC4 jacket under static, harmonic, and irregular point loads are validated with ABAQUS results in all six degrees of freedom. Thereby, the PD fatigue parameters of the jacket’s steel material are calibrated from the experimental data of the corresponding material with a trial simulation for fatigue damage analysis. Later, different load cases from regular waves interacting with the jacket are generated in the PD framework by adopting linear wave theory. Based on the PD cyclic energy release rate model, a comparative study of all load cases to identify critical damage locations with the failure load cycles for damage initiation and fracture is performed for the considered OC4 jacket.

Steel cylindrical shells have significant applications in the field of ocean engineering. However, such shells possess lower actual load-bearing capacity due to their high sensitivity to geometric imperfection. To improve the load-bearing capacity of normal steel cylindrical shells, steel-composite cylindrical shells were proposed in this work, and their buckling behaviours under axial compression were investigated in depth. The theoretical formula of the linear elastic buckling for the steel-composite cylindrical shells was derived. The linear bucking numerical analyses were conducted to verify the correctness of theoretical solution. The imperfection sensitivity of the steel-composite cylindrical shells were also examined by nonlinear buckling numerical analyses. Results show that the maximum average deviation between the theoretical and linear numerical values did not exceed 20 % for all considered models, and most of the average deviations were lower than 10 %. This exhibited a good agreement between the theoretical prediction and numerical simulation. Compared to the normal steel cylindrical shell, the steel-composite cylindrical shell possessed lower imperfection sensitivity and higher load carrying capacity. These findings can provide theoretical guidance for designing and evaluating steel-composite cylindrical shells under axial compression.

The damage state of the crane-wharf structure is difficult to describe quantitatively in earthquake, which brings great challenges to its emergency rescue and post-earthquake repair. At present, the criterion for evaluating the crane-wharf structure damage reflect a certain section or point, such as bending moment, axial force, displacement, stress, strain curvature, etc., which cannot reflect the overall performance and can be easily obtained. In addition, in the current popular performance-based seismic design concepts, the definition of damage degree is an indispensable part, which shows that the extraction and identification of damage characteristics is imminent. Therefore, on the basis of results of centrifuge experiment that have been carried out under different damage conditions, the basic damage law of the crane-wharf structure in liquefiable stratum is analysed first in the study, and it is clear that the existing means cannot distinguish the damage degree in detail. Furthermore, the proven numerical modelling techniques and the Hilbert-Huang transform theory are applied to extract and identify damage characteristics of the crane-wharf structure, Finally, the corresponding damage index is constructed and damage criterion are developed, which provided a reference for damage evaluation of similar structures in liquefiable stratum.

This study examines the hydrodynamic interaction between two parallel surge-released ships in head regular waves. A hybrid approach combining potential flow theory and functional-decomposition URANS is used for an efficient and accurate simulation. The methodology involves a surge-released module, 4DOF motion equations, multiple coordinate systems, and a dynamic structured grid. Two ship models are used for validation, comparing numerical and experimental results in ship motions and wave loads. The analysis shows good agreement, with differences of less than 5 % in heave and pitch motions, less than 8 % in roll motions, and less than 15 % in total resistance and sway interference forces. Present study also observes consistent trajectories of the wave system between the two ships. The influence of surge motion and wave height on wave-ship-ship interaction is investigated, emphasizing the importance of considering surge motion in seakeeping performance and longitudinal separation. The occurrence of parametric roll in Ship B is accurately resolved by the hybrid method and the parametric roll amplitude is smaller under ship-to-ship interaction conditions. Wave-induced moments play a limited role in this phenomenon, while the dominating roll restoring moment exhibits a hardening effect. Accordingly, roll motion and moments remain relatively unchanged with increasing wave height, indicating the strong nonlinear nature of parametric roll.

This study introduces a framework for designing an optimal multiple rotational inertia double tuned mass damper (MRIDTMD) with multiple tuning frequencies to effectively mitigate vibrations in offshore wind turbines (OWTs) subjected to combined wind, wave, and seismic loads. The framework comprises a coupled numerical model of an OWT with an MRIDTMD, an intelligent optimization algorithm, and parallel computing technology. First, coupled governing equations of motion for an OWT with an MRIDTMD under seismic conditions are derived based on multibody dynamics and fully coupled analysis theories in FAST v8. Subsequently, an MRIDTMD submodule is developed and integrated into FAST v8 to establish a coupled analysis model for an OWT with MRIDTMDs using an updated simulation tool. Furthermore, an intelligent optimization algorithm and parallel computing technology are introduced to establish the framework, and the MRIDTMDs are optimized. Moreover, the efficiency of the optimized MRIDTMD is assessed based on observed reductions in the OWT responses under combined seismic cases. Subsequently, comparisons with an optimized multiple tuned mass damper (MTMD) and a parametric study are conducted. The effectiveness and robustness of the optimized MRIDTMD and the improved mitigation effects of the MRIDTMD compared with the MTMD owing to the additional inerter are proved.

This paper presents a physics informed neural network (PINN) method for constructing a yaw motion hydrodynamic model of the deep-sea mining vehicle during the deployment and recovery processes. Initially, by incorporating the motion equations of the underwater vehicle as part of the loss function, the synchronous construction and optimization of parametric and non-parametric hydrodynamic models are achieved. Subsequently, focusing on the mining vehicle "Lushan", the deployment and recovery processes of deep-sea mining vehicles are simulated using computational fluid dynamics (CFD) methods. The CFD simulation results are utilized as driving data for the mining vehicle hydrodynamic modeling, employing both the novel neural network approach and the conventional neural network (NN) method. A comparison case study reveals that the newly proposed neural network method not only enables synchronous identification of parametric and non-parametric models, but also exhibits resistance to NN overfitting and enhanced generalization capabilities.

Sea surface temperature (SST) is a crucial indicator among the various factors influencing ocean dynamics. It significantly impacts weather patterns, ocean circulation, and marine biodiversity. SST variation is affected by multiple factors such as solar radiation and air-sea heat exchange, which contribute to the complexity of accurately predicting sea surface temperatures. The challenges of SST prediction tasks stem from the difficulty in modeling the coupling relationships between dynamic ocean variables and capturing long-term spatio-temporal dependencies. Existing data-driven methods for SST prediction overlook the physical relationships between ocean variables, and struggle to effectively capture long-term features. In this work, we propose a spatio-temporal-variable transformer model (STVformer) consisting of multi-variable feature representation module and spatio-temporal-variable saliency modeling module for SST prediction. STVformer first models the physical relationship among auxiliary variables including short-wave radiation (SWR), long-wave radiation (LWR), latent heat flux (LHF) and sensible heat flux (SHF) based on the heat budget equation. Then, it leverages the saliency self-attention mechanism and the spatio-temporal attention mechanism to effectively learn the spatio-temporal-variable correlations and long-term dependencies. Extensive experiments are carried out on two datasets to validate the effectiveness of STVformer. The experimental results demonstrate that STVformer surpasses existing methods in SST prediction.

The contradiction between Reynolds similarity and Froude similarity often leads to underperformance in thrust during wind-wave basin physical model tests of floating offshore wind turbine (FOWT), compromising the accuracy of experimental results. This study proposes a novel blade model reconstruction method that combines the third-generation non-dominated sorting genetic algorithm (NSGA-III) and feedforward neural network (FNN), aiming to ensure that the thrust of the model wind turbine matches that of the full-scale model, adhering to Froude similarity principles. The chord and twist angles of the FOWT blades are optimized using NSGA-III, resulting in blade parameters that satisfy thrust similarity. The data derived from the NSGA-III optimization process are utilized for training the FNN, which predicts blade design parameters rapidly based on desired thrust. The data predicted by the FNN are used to remodel the FOWT rotor, and the results are compared with those obtained from NSGA-III. The results demonstrate that the FOWT thrust based on the blade design parameters predicted by the FNN aligns well with the desired thrust of the FOWT model, proving the feasibility of using the FNN for rapid blade reconstruction.