Search Results (240)

In the context of global climate warming, sea surface temperature (SST) rise and sea level (SL) rise are projected to amplify typhoon-related marine dynamic disaster risks. These are idealized sensitivity experiments designed to isolate the individual effects of SST warming and SL rise, not full climate projections. This study investigates Super Typhoon Doksuri (2023) using the WRF-SWAN-ROMS coupled model, with sensitivity experiments designed for SST (+0.8 °C, +2.0 °C, +3.5 °C) and SL rise (+0.4 m, +0.6 m, +0.8 m) scenarios referenced to IPCC AR6 projections. Results indicate that SST rise enhances typhoon intensity by approximately 16% at +3.5 °C, elevates mean wave height by 25.0%, and increases extreme significant wave height by 24.0%, with the extreme wave height sensitivity approximately 2.75 times that of the mean. Storm surge exhibits a nonlinear response, with the extreme surge sensitivity approximately 13.2 times that of the mean. SL rise has relatively minor effects on open sea areas but affects coastal regions notably, expanding the inundation area by approximately 47% under the 0.8 m scenario. The Taiwan Strait channeling effect amplifies wave heights and surges on the right side of the track. Comparative analysis suggests that SST indirectly amplifies disasters by enhancing typhoon intensity, while SL rise directly constrains nearshore dynamics through static water level elevation. These findings offer process-based insights into the contrasting physical mechanisms through which SST rise and SL rise affect coastal hazards in semi-enclosed regions and may inform future ensemble-based climate impact assessments. Full article

Under climate change, the increasing typhoon intensity poses a severe threat to fishery harbor safety through storm surges and extreme waves. Traditional empirical management approaches fail to capture the complex wave-surge coupling inside harbors, leading to risk blind spots in berth allocation. This study enhances the fishery harbor disaster resilience by employing high-resolution coupled wave-storm surge modeling, taking Xinying Central Fishing Harbor (Hainan, China) during Super Typhoon Yagi (September 2024) as a case study. A Holland typhoon model integrated with ERA5 reanalysis data was used to reconstruct the wind field, which subsequently drove a one-way coupled MIKE 21 FM–SW model to simulate regional tides and deep-water waves. A Boussinesq wave model was then applied to resolve nearshore shallow-water wave transformations inside the harbor. Model validation showed strong agreement with observations: correlation coefficients of 0.97 for tides in Xinying station and 0.95, 0.97, 0.93 for significant wave heights in three buoys around Hainan island, with root-mean-square errors of 0.19 m and 0.67, 0.69, 0.31 m, respectively. The Boussinesq wave simulations revealed detailed spatial distributions of wave heights inside the harbor during the typhoon. Based on these simulations, a dynamic berth zoning strategy was developed, mapping safety zones for different vessel sizes according to wave-height tolerance (e.g., ≤0.6 m for medium-sized trawlers). This framework can provide potential support for decision-making regarding fishing vessel refuge during typhoons, maximizing safe capacity while minimizing capsizing risks. Overall, this study demonstrates a feasible pathway from advanced numerical modeling to practical engineering management, supporting a transition from experience-based to data- and model-driven disaster prevention for coastal fishery harbors. Full article

As the development and utilization of underground spaces in coastal cities receive growing emphasis and continue to expand, the secondary disasters of underground flooding triggered by storm surges have become increasingly frequent in recent years. Consequently, the need for emergency evacuation in these spaces has grown more urgent, making the challenge of safe evacuation increasingly critical. However, the classical social force model shows notable limitations in simulating such scenarios, particularly in its lack of characterization of hydrodynamic resistance, heterogeneous pedestrian mobility, and organized guidance mechanisms. Therefore, this paper proposes an improved social force model for more realistically simulating the microscopic dynamics of pedestrians in underground floodwater environments. By extending the classical model, a flood resistance force term is introduced. Furthermore, the model comprehensively considers the varying speeds of pedestrians with heterogeneous attributes—such as age, height, and gender—under different water depths, quantifying the impact of the flood environment on pedestrian mobility. Simultaneously, a leader–follower guidance mechanism is integrated to simulate the influence of organized command behavior on group movement. Simulation experiments in typical underground flood scenarios were conducted to validate the proposed model. Simulation results indicate that flood resistance significantly reduces evacuation efficiency, and heterogeneous pedestrian factors such as age distribution also have a considerable impact. The quantitative findings are as follows: flood resistance increased total evacuation time by 9.3% (from 37.5 to 41.0 s) and decreased the average evacuation rate by 8.6%; similarly, raising the proportion of elderly pedestrians from 20% to 30% prolonged total evacuation time by 9.4% and reduced the average evacuation rate by 8.6%. These outcomes verify the effectiveness of the improved model in characterizing heterogeneous pedestrian behavior in underground flooding scenarios. This study provides a more refined theoretical model and simulation tool to support the development of emergency evacuation plans for underground spaces during floods. Full article

The design of coastal protection structures requires design parameters that accurately represent the hydrodynamic conditions along the coast. Currently, these input variables are based on univariate probability models, which do not consider the joint probability of water level and statistical wave parameters such as significant wave height. Bivariate probability modeling using copula models offers an alternative. Copulas can be used to describe the dependencies between water level and significant wave height and to compute joint probabilities of occurrence. First, various copulas are fitted to samples of physically consistent combinations of water level and significant wave height extracted from storm surge events along the German Baltic Sea coast of Mecklenburg-Western Pomerania. Next, the most appropriate copula model is used to compute design combinations of water level and significant wave height for selected return periods. The bivariate design parameters are compared with the univariate ones in a simplified design example for wave run-up on a dike. The validation of various models shows that the Frank copula best describes the dependence structure. The bivariate design parameters obtained for the same return periods are lower than those determined using the univariate method. The available data only allow a limited application of the copulas for engineering design in the study area. Nevertheless, copulas have the potential to replace univariate methods for determining design parameters and thus contribute to more reliable and cost-efficient coastal protection structure design. Full article

Submarine landslides pose severe marine geological hazards. Their movement and deposition behaviors can seriously threaten marine engineering stability and coastal safety. The propagation characteristics of landslide-generated tsunamis are therefore critical for hazard assessment. Physical model experiments provide an effective approach for investigating the underlying mechanisms of tsunami generation and propagation. To investigate the complete process from landslide motion to wave generation and propagation, this study developed an underwater soil-movement physical model test system. The system integrates controllable landslide initiation, real-time monitoring of landslide motion, wave height measurements, and full-field image acquisition, enabling synchronous observation of landslide movement and water body response. By controlling the main variables influencing submarine landslide dynamics, a series of physical model experiments were conducted to investigate water surface waves generated under different test conditions. The study examines the complete process from the initial water disturbance caused by submerged landslide motion to tsunami generation and propagation. The effects of landslide volume, particle size, initial submergence depth, and slope angle on tsunami parameters, including wave height, wave velocity, and wave period, were evaluated. Using 21 experimental datasets for each landslide type, namely, cohesionless sandy slides and muddy debris flows, empirical formulas for maximum surge height were established through dimensional analysis, SPSS (v25)-based multiple nonlinear regression, and validation against experimental results. The validation results show strong agreement between the empirical predictions and the physical model test data. Full article

During the global transition toward cleaner energy infrastructure, floating photovoltaic (FPV) systems have emerged as a research focus in renewable energy technologies due to their distinctive spatial utilization advantages. This study examines the hydrodynamic performance of a novel FPV system comprising multiple floating modules connected via flexible connectors to a circular frame. Three distinct connection schemes among the floating modules were designed for comparative analysis. To ensure computational accuracy, a numerical model was established and validated against existing experimental data from a 2 × 3 scaled array. Although the validation setup differs from the novel configurations proposed in this study, the results confirm the reliability of the adopted numerical method. Based on this validated model, time-domain analyses were conducted to evaluate the six-degree-of-freedom (6-DOF) motions of the FPV, as well as the dynamic responses of the flexible connectors and mooring system under various wave periods, heights, and directions. The study shows that the motion differences in FPV under different connection schemes are mainly observed in short wave periods and oblique waves. At a wave direction of 45°, the maximum differences in surge and sway motions among the schemes reach 0.2 m. The disparity in mooring tension and connector tension for different connection schemes increases as the wave period decreases and the wave height increases. Specifically, the maximum difference in connector tension attains 10 kN under a wave period of 9 s and a wave direction of 45°, while the peak difference in mooring chain tension reaches 13 kN at a wave direction of 90°. The dynamic responses of the connectors and mooring chains in the second connection scheme are superior to those of the other two schemes. The numerical simulations identify the optimal connection scheme. The results provide theoretical guidance for the design and practical application of FPV system. Full article

Field measurements of ship motions at berth are often sparse, heterogeneous, and collected across multiple vessels and locations, limiting the applicability of conventional response-modelling approaches. This study presents a statistical framework for analysing sea-state-conditioned motion responses using long-term monitoring data with incomplete overlap between degrees of freedom (DoF). Each DoF is analysed independently and conditioned on significant wave height ($H_s$) and peak wave period ($T_p$), with directional values retained across the full angular range (0–360°) and examined separately. A two-stage quality-control procedure combining plausibility checks and robust regression removes inconsistent response–sea-state pairs while preserving dominant behaviour. Motion response envelopes are derived by binning observations in sea-state space and computing median and upper-percentile statistics. To quantify sampling uncertainty, bootstrap resampling provides 95% confidence intervals for envelopes and derived metrics, ensuring robust comparative conclusions. Results show systematic growth in motion variability with increasing $H_s$, with surge exhibiting the strongest translational sensitivity and roll the largest amplification. Synthetic sea surfaces generated using a spectral random-phase approach reproduce prescribed sea-state characteristics, supporting physical interpretation. The study contributes a data-driven framework for heterogeneous berth datasets, robust quality control, uncertainty-aware response envelopes, and statistically consistent synthetic seas, aligning field-based monitoring with practical port operability assessment. Full article

This study investigates long-term wildfire emissions and smoke-plume geospatial characteristics in Greece by analyzing a multi-pollutant dataset spanning January 2003 to August 2025. Details of emissions of carbon monoxide (CO), carbon dioxide (CO₂), methane (CH₄), particulate matter (PM_2.5), organic carbon (OC), and black carbon (BC) were derived from the Global Fire Assimilation System (GFAS), which converts MODIS fire radiative power into trace gas and aerosol fluxes at 0.1° resolution, and also accounts for the land type. Burned-area statistics from the European Forest Fire Information System (EFFIS) were used for cross-validation. Data were processed into daily, monthly, annual, and cumulative time series, with spatial mapping at the municipality scale and information regarding long-term trends. The analysis shows that while there are several sizeable wildfire events in the country every year, the bulk of the total of Greek wildfire emissions for the last 23 years is attributable to a few extreme fire seasons (2007, 2021, and 2023) that produced abrupt emission surges and accounted for a disproportionate share of national totals. Analysis of spatial data identifies the areas of Evia, East Attica, Messinia, and Evros as persistent emission hotspots. Although wildfire CO₂ emissions are generally a minor fraction of Greece’s anthropogenic totals (<5%), they reached 15–17% during peak fire years. Plume-injection height analysis reveals that most smoke remains below ~1 km but can reach 3–6 km during extreme events, facilitating long-range transport. Overall, the dataset demonstrates a shift toward more intense and concentrated wildfire events in recent years, highlighting both their growing climatic relevance and their acute impacts on regional air quality. Full article

The Yanshangou landslide, located in the Baihetan Reservoir area, poses severe potential threats to the normal operation of the reservoir due to its distinct deformation characteristics and high sensitivity to reservoir water level fluctuations. This study systematically investigates the geological background, deformation characteristics, stability evolution, and landslide-induced surge hazards of the Yanshangou landslide in the Baihetan Reservoir area. This work only considers the influence of reservoir water level fluctuations, which is the dominant factor controlling the current progressive deformation of the landslide. Field surveys and GNSS/deep displacement monitoring results revealed that the Yanshangou landslide exhibits obvious staged deformation characteristics, and the landslide deformation rate was closely coupled with the dynamic changes in reservoir water level. A slope stability evaluation method integrating the Morgenstern–Price limit equilibrium method and Richard’s equation was established, and the results indicated that the Yanshangou landslide has low saturated permeability. Therefore, its factor of safety (FOS) presents a clear four-stage variation trend in response to reservoir water level fluctuations. A Smoothed Particle Hydrodynamics (SPH)-based numerical model was further developed to simulate the landslide-induced surges under two typical reservoir water level scenarios (815 m and 765 m). The simulation results demonstrated that a high reservoir water level led to more intense surges with greater height and higher velocity, while a low reservoir water level resulted in surges with a wider propagation range along the reservoir bank. The research findings of this study provide a comprehensive theoretical basis and detailed data support for the prevention and mitigation of geological hazards in the Baihetan Reservoir area, and also offer a reference for the hazard management of similar reservoir landslides worldwide. Full article

The Zhuanghe coast in the northern part of the Yellow Sea is one of China’s important fishing and ocean engineering areas. Frequent storm surge events pose a significant threat to residents’ safety and properties. This study used the coupled Finite Volume Coastal Ocean Model (FVCOM) and the Surface Wave Model (FVCOM-SWAVE) to investigate storm surges and wave heights during Typhoons Muifa (1109) and Lekima (1909) in the northern parts of the Yellow Sea and analyze the impact of the typhoon parameters on flood inundation on the Zhuanghe coast. The wind stress comparison in the coupled wave–current model uses synthetic wind field data formed by superimposing ERA5 wind fields with a parameterized typhoon model. The results showed that the simulated and measured tide levels, wave heights, and storm surges were in good agreement, indicating that the coupled model accurately reproduced the dynamics of the storm surges and wave heights during the two typhoons. The maximum significant wave height (H_s) exhibited a right-skewed distribution in the two typhoons’ paths, with extreme values consistently located to the right of the typhoon’s center. The decrease in atmospheric pressure at the center of Typhoon Muifa was significantly, nonlinearly, and positively correlated with the severity of storm surge disasters. A significant correlation was observed between the path of Typhoon Muifa and the disaster intensity. Full article

In estuarine environments, machine learning (ML) methods have been widely applied to predict water-level variations prone to flooding. However, most studies have focused on low-frequency components driven by tides and surges, neglecting high-frequency oscillations such as seiches. This study addresses this gap by assessing the ability of ML methods to predict seiche-influenced water levels. The application was conducted in the upper Elorn estuary (France), where seiches exceeded 0.6 m in height, with first-mode periods of 45–70 min. The ML procedure relied on a series of recurrent neural networks (RNNs, LSTM, and GRUs) and was implemented in a two-step framework to separately predict (i) low-frequency water-level variations and (ii) high-frequency seiche oscillations. The model accurately reproduced low-frequency dynamics (with a coefficient of determination of 0.98) and captured a substantial portion of seiches-related variability during major events. The integration of seiches improved peak total water-level predictions, reducing the mean absolute error by 30% during tidal cycles characterized by strong seiches (amplitude exceeding 0.1 m). Furthermore, the inclusion of seiches enhanced the estimation of the highest 10% peak water levels while reducing the tendency to underestimate measurements. These findings emphasize the importance of integrating seiche-generating physical processes into ML-based forecasting frameworks. Full article

Offshore wind power currently shows the trend of a larger wind turbine capacity and deep-sea wind farm sites. Traditional wind farms with single-type wind turbines can hardly accommodate the dual requirements of high-efficiency power generation and wake effect mitigation of wind farms. Moreover, the wind shear of fixed wind turbines and the platform motion of floating wind turbines result in insufficient adaptability to a hybrid wind farm with multi-type wind turbines. To address that issue, this paper takes offshore wind farms with a multi-type hybrid layout for wake optimization. Firstly, based on the wind shear model, the influence of hub height difference for fixed wind turbines is analyzed, and the platform motion of semi-submersible floating wind turbines is evaluated through MoorDyn. On this basis, the wake optimization strategy for maximizing the total power generation of a wind farm is proposed based on the Gaussian Curl Hybrid model, which realizes three-dimensional wake control by considering the hub height difference and floating platform motion of multi-type wind turbines. The case study demonstrates that the multi-type hybrid layout itself has inherent wake suppression and optimization potential. The fixed wind farm with a row–column hybrid layout achieves an average power generation efficiency of 65.25%, which is superior to the single-type layout. For the floating wind farm with an inner–outer hybrid layout, the displacement misalignment effect is significant, with a maximum offset of 21.66 m in surge and 10.32 m in sway, and the total power is increased by 6.87 MW. And a hierarchical wake control mode matching multi-type wind turbines is formed. It provides a novel wake regulation mechanism for the design and operation of hybrid offshore wind farms. Full article

Underwater rock plug blasting involves a highly complex, transient gas–liquid–solid multiphase flow that is difficult to simulate accurately with conventional single-phase models. To address this gap, a novel three-phase three-layer mathematical model is presented in this study. This model represents the stratified flow behavior by decomposing the conduit into an upper gas layer, a middle gas–liquid–solid mixture layer, and a lower consolidated bed layer. Governing equations for mass, momentum, and energy conservation are derived and solved using the finite volume method. The model is validated against physical model tests, showing a maximum gate shaft surge deviation of only 0.27%, a Pearson correlation coefficient of 0.965, and a relative RMSE of 4.2%. A sensitivity analysis is performed to quantify the influence of key operational water levels, including the reservoir, gate shaft, and slag pit, on critical transient loads. The results demonstrate that a decrease in the reservoir water level from 106 m to 86 m concurrently reduces both surge height and impact pressure. A smaller reservoir–shaft water level difference (5–15 m) increases the initial cushion pressure and amplifies the surge. In contrast, a larger level difference (20–30 m) suppresses surge but increases impact pressure. Furthermore, an excessively high water level in the slag pit (exceeding 47.8 m) weakens the cushioning effect, thereby lowering the impact pressure. The proposed multiphase model provides an improved approach for predicting hydraulic transients during underwater rock plug blasting. Full article

The upscaling of turbines in the offshore wind industry has been unprecedented, as compared to 5–6 MW rated turbines 10 years ago. A typical 20–26 MW rated turbine in modern commercial applications (MingYang MySE 18.X-20 MW installed in 2025 and 26 MW prototype by Dongfang Electric tested in 2025) has been demonstrated. This scaling has been made possible by increasing rotor diameters (>250 m) and hub heights (>150–180 m) to achieve capacity factors of up to 55–65%, annual energy generation of more than 80 GWh/turbine, and significant decreases in levelised cost of energy (LCOE) to current values of up to 63–65 USD 2023/MWh globally averaged in 2023 (with minor variability in 2024 due to market changes and new regional areas). The paper analyses turbine upscaling over three levels of hierarchy, including turbine scale—rated capacity and physical aspect, project scale—multi-gigawatts of farms, and market scale—the global pipeline > 1500 GW level, and combines techno-economic evaluation, structural evaluation of loads, and infrastructure needs assessment. The upscaling has the advantage of reducing the number of turbines dramatically (e.g., 500 to 67 turbines in a 1 GW farm, as turbine size is increased to 15 MW) and balancing-of-plant (BoP) CAPEX (turbine-to-turbine foundations and cables) by some 20 to 30 percent per unit of capacity, and serial production learning rates of between 15 and 18% per doubling of capacity. But the problems that come with the increase in ultra-large designs are nonlinear increments in mass and load (i.e., blade-root and tower-bending moments), logistical constraints (blades > 120 m, nacelle up to 800–1000 tonnes demanding special vessels and ports), supply-chain issues (rare-earth materials, vessel shortages increase day rates by 30–50%), and technology limitations (aeroelastic compounded by numerical differences between reference 5 MW, 10 MW, and 15 MW models), it becomes evident that there is a significant increase in deflections of the tower and blades and platform surge/pitch responses with continued increases in power levels, but without a correspondingly mature infrastructure. The regional differences (mature ports of Europe vs. U.S. Jones Act restrictions vs. scale-up of vessels/manufacturing in China) lead to the necessity of optimisation depending on the context. The analysis concludes that, to the extent of mature markets with adapted logistics, continuous upscaling is an effective business strategy and can result in 5 to 12 percent further reductions in LCOE, but beyond that point, gains become marginal or even negative, as risks and costs increase. The competitiveness of the future depends on multi-scale/multi-market-based approaches—modular-based families of turbines, programmatic standardisation, vibration control innovations, and industry coordination towards supply-chain alignment and standards. Its major strength is that it transcends mere size–cost relationships and shows how nonlinear structural processes, aero-hydro-servo-elastic interactions, and bottlenecks in logistical systems are becoming more determinant of the efficiency of ultra-large turbines. The study demonstrates that upscaling turbines has LCOE benefits through the support of associated improvements in installation facility, supply-chain preparedness, and structural vibration control potential, based on the comparisons of quantitative loads, techno-economic scaling trends, and regional market differentiation. Full article

For deep-draft cylindrical platforms with a large annular column boot, the influence of the column boot diameter-to-height ratio (d/h) on motion performance remains unclear. This study investigates the effect of d/h on platform hydrodynamics while keeping the main body geometry, displacement, and draft unchanged. A hybrid numerical model validated against tests is adopted: STAR-CCM+ free-decay simulations identify equivalent linear damping, and ANSYS AQWA predicts hydrodynamic coefficients, response amplitude operators, and coupled time-domain responses under a 100-year survival sea state in the western South China Sea. Increasing d/h substantially increases heave added mass and added pitch moment of inertia, leading to longer natural periods and higher damping in heave and pitch. However, its effect on motion responses is non-monotonic and strongly response-dependent. As d/h increases, the responses are initially reduced markedly. The minimum surge and heave responses occur at d/h = 2.39 and 4.67, with reductions of about 34.0% and 87.2%, respectively, while the pitch response is already reduced by about 67.3% at d/h = 7.22. Further increases in d/h may weaken surge and heave mitigation while providing limited additional benefit for pitch. These findings provide qualitative understanding and quantitative guidance for response-oriented column boot design and optimization of similar platforms. Full article