Parametric roll is a nonlinear and intermittent dynamical phenomenon that causes damage to or loss of cargo, and poses significant risks for passenger safety and comfort. The current engineering practice to evaluate susceptibility or likelihood of parametric roll requires hours of nonlinear simulation or model tests in many wave conditions from the long-term operation wave scatter diagram. In this paper a novel generative AI method is proposed to learn the specific conditions that lead to parametric roll without the need to perform exhaustive and time consuming Monte Carlo simulations of all wave conditions. The method uses a low fidelity hydrodynamics model to generate the required large set of training data. A distillation process is employed that produces a series of models that can generate new wave conditions that lead to increasingly severe parametric roll behavior. Then the exceedance probabilities derived from the generated wave conditions are shown to closely match those from Monte Carlo simulations, while requiring significantly fewer computations. Finally, the generated wave conditions are verified by performing simulation with a weakly-nonlinear IRF method, confirming the ability of the method to find conditions that lead to pronounced parametric roll responses at a small fraction of the cost relative to the current practice of using Monte Carlo simulation.

The discontinuous Galerkin method (DGM) has showed appealing performances in addressing underwater explosion (UNDEX) problems with strong discontinuities. However, most of the DGM are limited to the axisymmetric modeling due to the expensive computational cost required in 3D simulations. In this work, we develop a massive MPI parallel framework of 3D local discontinuous Galerkin method (LDGM) for simulating large-scale UNDEX problems with the cavitation effects. The 3D LDGM based on unstructured tetrahedron elements is adopted to solve the wave equation about dynamic pressure excited by the UNDEX and simulate the propagation of the UNDEX shock waves in the fluid domain. To accelerate the calculation of 3D LDGM, the MPI parallel framework scalable on a high-performance computer is designed. In order to improve the parallel efficiency and expand the computational scalability, some optimized techniques are incorporated into the parallel 3D LDGM model. In particular, the information for data communication is stored contiguously in the access-friendly data structures to efficiently implement concurrent non-blocking communications. The real-time memory management strategies with local parallel I/O are developed in terms of reducing latency and restraining memory utilization. Several numerical examples are performed to assess the accuracy, efficiency and scalability of the MPI-based parallel 3D LDGM model. It is demonstrated that the present model can accurately and efficiently simulate the propagation of UNDEX shock waves and well capture the evolution of the cavitation region in 3D spaces. The parallel efficiency can achieve up to 94.1 % even for 155 million tetrahedral elements on 12,000 CPU cores.

Floating offshore wind energy represents a promising frontier in marine renewable energy, enabling deployment in deeper waters. Among the various solutions for floating wind energy, semi-submersible platforms have emerged as the most viable option. The success of this technology depends on their hydrodynamic performance. Current engineering practice for design and operability assessment has primarily focused on short wave excitation, with less attention to long-period waves. Swells carry energy near the natural periods of these structures and are more likely to induce resonant responses in heave, in which scenario the prediction is challenging and less understood. This may lead to over-conservative designs and thus unnecessarily high cost. To address this gap, this study examines resonant responses driven by long-period waves through linear processes. In resonance, viscous effects play a critical role, e.g., in determining response amplitudes. However, estimating viscous effects is challenging as a result of their underlying complex physics and nonlinearity. To better understand the viscous effects and their impact on floating wind turbines, a series of scaled model tests was analysed for a 10-MW floating wind energy platform. To facilitate the interpretation of the experimental results, inviscid flow calculations were also performed. The results indicate that viscous damping is positively correlated with the Keulegan–Carpenter ( KC ) number that characterizes the relative velocity between the floating system and the surrounding water particles. A striking observation is that viscosity can significantly alter the added mass, which is key to the estimation of the natural frequency of the floating system.

• Developed a novel sea level rise forecast model for flooding and erosion control in Australia. • The approach integrating correlation graph, data decomposition, Hilbert feature selection, and adaptive ensemble model (AEM). • The AEM adopted dynamic weights assignment strategy, adjusting to real-time changes in sea level rise by updating the weights. • The proposed model can offer valuable insights for coastal planning and policy making under the recent climate change. Sea level variability is an urgent climate risk, threatening to vanish islands and coastal areas. Forecasting future sea level rise accurately is fundamental to support experts for flooding and erosion control. In this paper, a novel sea level variability forecast model (CG-CEEMDAN HFS-AEM) is proposed integrating correlation graph (CG), a complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN), Hilbert feature selection approach (HFS), adaptive ensemble model (AEM), and oppositional learning sparrow search algorithm (OLSSA). The AEM is a novel ensemble model that combines the strengths of GRU, self-attention LSTM and XGBoost models based on dynamic weights assignment strategy, adjusting to real-time changes in sea level rise by updating the weights according to the error and performance of the models. Firstly, the input data is pre-processed using correlation graph to remove lower correlated variables and fill the missing values in the data. After that the CEEMDAN technique is employed to decompose the data, followed by HFS to select the most efficient features. The selected features are then employed into the AEM model where the OLSSA is adopted to select the optimal hyper-parameters of the proposed model. To verify the efficiency of the proposed CG-CEEMDAN HFS-AEM against comparing models, extensive experiments were conducted to forecast sea level variability for Hillary and Burnie stations in Australia. The results shows that the proposed model obtained the highest accuracy in terms of goodness-of-fit metrics against the state-of-the-art benchmark comparing models. The proposed model can offer a valuable tool for coastal planning and policy making under the recent climate change.

Corrosion-resistant alloy (CRA) liner wrinkling and strain localisation at the triple point present significant challenges to the structural integrity of mechanically lined pipes (MLPs), particularly in girth-welded and weld overlay configurations subjected to bending. This study combines numerical and experimental approaches to evaluate the onset of liner wrinkling and strain localisation at critical weld interfaces. A finite element model (FEM) was developed in ABAQUS and validated against full-scale bending test (FSBT) results. The FEM accurately predicted the mechanical response of MLPs, including wrinkling initiation, deformation patterns, and local axial strains in the triple point region. Strong agreement was achieved between numerical predictions and experimental data, with wrinkling initiation occurring at global tensile strains above the acceptance criteria defined by the Det Norske Veritas (DNV) Joint Industry Project (JIP) guidelines. A parametric study further explored the influence of weld overlay length and internal pressure on wrinkle formation and strain localisation. The results show that while weld overlay length has little effect on wrinkling onset, its local stiffening reduces strain localisation near the triple point. In contrast, internal pressure has a pronounced stabilising effect, substantially delaying liner wrinkling and allowing the pipe to withstand higher bending strains before instability occurs.

Artificial reefs (ARs), as one of the important means for restoring marine habitats, largely depend on their structures for hydrodynamic performance. In this study, we combined particle image velocimetry experiment (PIV) and computational fluid dynamics (CFD) to investigate the influence of a grid guide plate structure on the hydrodynamic performance of the cubic-frame reef. The results reveal that the angles of the front guide plates significantly enhance the upwelling efficiency of the cubic-frame reef, with a maximum increase of 13.06 times. The projected area of the plates also has a significant impact on the upwelling flux. Normalized TKE ( k n ) effectively quantifies wake disturbance intensity and shows a strong correlation with vortex volume. Furthermore, asymmetric plate configurations enhance wake vortex mixing while minimizing energy dissipation. The wake efficiency of the optimized AR structure is 28.31 times greater than that of the cubic-frame reef. These findings demonstrate that optimized guide plate configurations can enhance upwelling efficiency and wake mixing by more than an order of magnitude, providing a practical design basis for constructing artificial reefs that improve water exchange and habitat quality in marine ranching applications.