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To investigate the seismic performance of a wind turbine that is influenced by both the ice load and the seismic load, the research proposes a numerical approach for simulating the seismic behavior of a wind turbine on a monopile foundation. First, the fluid-solid coupled equation for the water-ice-wind turbine is simplified by assigning reasonable boundary conditions and solving the motion equation, and the seismic motion equation of the wind turbine is developed. Then, on this basis, we propose a simplified 3D numerical model that can simulate the interactions among the wind turbine, water and sea ice. By conducting shaking table tests, the results demonstrate that the established numerical model is effective. Finally, we investigate the effect of the boundary range and ice thickness on the seismic performance of a turbine under near-field and far-field seismic actions. Research results illustrate that ice changes the distribution form of the hydrodynamic pressure. Moreover, the thickness of the ice greatly influences the seismic behavior, while the influence of the ice boundary range is only within a certain range. Additionally, the ice load decreases the energy-dissipating capacity of the wind turbine, so the earthquake resilience of the wind turbine is significantly decreased.

Long‐term lake ice evolution under climate change has attracted global attention. However, despite the widespread occurrence of lake shrinkage in endorheic regions worldwide, few studies have explicitly addressed its effects on lake ice regimes. This study fills this research gap by investigating the long‐term evolution of lake ice in Lake Daihai—a large shrinking endorheic lake in China—by integrating six decades (1960–2022) of hydrometeorological data, retrieved Landsat images, and experiments with a three‐dimensional hydrodynamics‐ice numerical model. Our results show that Lake Daihai experienced accelerated shrinkage at an average rate of −2.18 km2 yr−1 from 1960 to 2022, which was primarily driven by intensified anthropogenic activities and increased evaporation. Concurrently, the annual average lake ice thickness exhibited an accelerated decreasing trend at an average rate of −0.39 cm yr−1. This ice‐thinning trend was attributed to the processes of atmospheric warming (air temperature increase: 2.5°C), salinization (increase in salinity: 451.3%), and morphological changes associated with lake shrinkage (water depth reduction: −12 m; surface area reduction: −72.9%). Model experiments reveal3ed that the representative factors (i.e., air temperature, salinity, and average water depth) of these processes were significantly correlated with ice phenology metrics (i.e., ice‐on date, ice‐off date, and ice duration); their relative contributions to ice thinning were 36.1%, 18.9%, and −15.2%, respectively, and the wind speed contributed 3.5%. Ice thinning was driven mainly by atmospheric warming but slowed by lake shrinkage characterized by a decrease in the average water depth. Under ongoing global warming, ice‐thinning is projected to accelerate by 2031 because of the nonlinear increase in the contribution of salinization in this shrinking lake. These findings highlight that traditional climate‐centric models may underestimate or overestimate lake ice dynamics if they fail to account for salinization or morphological changes, underscoring the necessity of developing integrated assessment frameworks tailored to shrinking endorheic lakes.

Tropical cyclones have always been a concern of meteorologists, and there are many studies regarding the axisymmetric structures, dynamic mechanisms, and forecasting techniques from the past 100 years. This research demonstrates the ongoing progress as well as the many remaining problems. Machine learning, as a means of artificial intelligence, has been certified by many researchers as being able to provide a new way to solve the bottlenecks of tropical cyclone forecasts, whether using a pure data-driven model or improving numerical models by incorporating machine learning. Through summarizing and analyzing the challenges of tropical cyclone forecasts in recent years and successful cases of machine learning methods in these aspects, this review introduces progress based on machine learning in genesis forecasts, track forecasts, intensity forecasts, extreme weather forecasts associated with tropical cyclones (such as strong winds and rainstorms, and their disastrous impacts), and storm surge forecasts, as well as in improving numerical forecast models. All of these can be regarded as both an opportunity and a challenge. The opportunity is that at present, the potential of machine learning has not been completely exploited, and a large amount of multi-source data have also not been fully utilized to improve the accuracy of tropical cyclone forecasting. The challenge is that the predictable period and stability of tropical cyclone prediction can be difficult to guarantee, because tropical cyclones are different from normal weather phenomena and oceanographic processes and they have complex dynamic mechanisms and are easily influenced by many factors.

Category 4 landfalling hurricane Harvey poured more than a metre of rainfall across the heavily populated Houston area, leading to unprecedented flooding and damage. Although studies have focused on the contribution of anthropogenic climate change to this extreme rainfall event 1 – 3 , limited attention has been paid to the potential effects of urbanization on the hydrometeorology associated with hurricane Harvey. Here we find that urbanization exacerbated not only the flood response but also the storm total rainfall. Using the Weather Research and Forecast model—a numerical model for simulating weather and climate at regional scales—and statistical models, we quantify the contribution of urbanization to rainfall and flooding. Overall, we find that the probability of such extreme flood events across the studied basins increased on average by about 21 times in the period 25–30 August 2017 because of urbanization. The effect of urbanization on storm-induced extreme precipitation and flooding should be more explicitly included in global climate models, and this study highlights its importance when assessing the future risk of such extreme events in highly urbanized coastal areas. Modelling the contribution of urbanization to the impacts associated with hurricane Harvey in August 2017 shows that urbanization worsens rainfall and flooding.

The following article analyzes the effectiveness of directional hydraulic fracturing (DHF) as a method of rock burst prevention, used in black coal mining with a longwall system. In order to define changes in seismic activity due to DHF at the “Rydułtowy” Black Coal Mine (Upper Silesia, Poland), observations were made regarding the seismic activity of the rock mass during coal mining with a longwall system using roof layers collapse. The seismic activity was recorded in the area of the longwall itself, where, on a part of the runway, the rock mass was expanded before the face of the wall by interrupting the continuity of the rock layers using DHF. The following article presents measurements in the form of the number and the shock energy in the area of the observed longwall, which took place before and after the use of DHF. The second part of the article unveils the results of numerical modeling using the discrete element method, allowing to track the formation of goafs for the variant that does not take DHF into consideration, as well as with modeled fractures tracing DHF carried out in accordance with the technology used at “Rydułtowy” coal mine.

Stainless-steel elements are increasingly used in a wide range of load-bearing structures due to their strength, minimal maintenance requirements, and aesthetic appearance. Their response differs from standard steels; therefore, it is necessary to choose a different procedure when creating a correct computational model. Seven groups of numerical models differing in the used formulation of elements integration, mesh density localization, nonlinear material model, and initial geometric imperfection were calibrated. The results of these advanced simulations were validated with published results obtained by an extensive experimental approach on circular hollow sections columns. With regard to the different slenderness of the cross-sections, the influence of the initial imperfection in the form of global and local loss of stability on the response was studied. Responses of all models were validated by comparing the averaged normalized ultimate loads and the averaged normalized deflections with experimentally obtained results.

Despite being exposed to convective stresses for much of the Earth's history, cratonic roots appear capable of resisting mantle shearing. This tectonic stability can be attributed to the neutral density and higher strength of cratons. However, the excess thickness of cratons and their higher viscosity amplify coupling to underlying mantle flow, which could be destabilizing. To investigate the stresses that a convecting mantle exerts on cratons that are both strong and thick, we developed instantaneous global spherical numerical models that incorporate present‐day geoemetry of cratons within active mantle flow. Our results show that mantle flow is diverted downward beneath thick and viscous cratonic roots, giving rise to a ring of elevated and inwardly‐convergent tractions along a craton's periphery. These tractions induce regional compressive stress regimes within cratonic interiors. Such compression could serve to stabilize older continental lithosphere against mantle shearing, thus adding an additional factor that promotes cratonic longevity. Plain Language Summary Cratons are the oldest continental relicts on Earth. Due to plate tectonics and mantle convection, many non‐cratonic rocks get recycled. However, cratons have escaped tectonic recycling, and some have remained stable for more than ∼3 billion years. Previous studies have shown that cratons' high strength and neutral buoyancy provide them with tectonic stability. Here we show that the deep roots of cratons also help to stabilize them. This is because mantle flow is deflected downward beneath thick cratonic roots, and this deflection generates a ring of inwardly‐directed forces around the edges of the craton. These inward forces compress the craton interior. Such self‐induced compressive stresses may further help to stabilize Earth's oldest lithosphere. Key Points Mantle flow leads to inwardly convergent tractions around the edges of cratons, and compressive stress within Convergent tractions result from the downward diversion of mantle flow This convective self‐compression could help stabilize older lithosphere against convective erosion

This paper presents a study of run-up/overtopping over a smooth impermeable dike with promenade using 2D and 3D mesh-based and mesh-free numerical models and results from 2D physical modelling for strong energetic incident waves. These waves induce plunging wave breaking and a complex water/air mixture turbulent flow before overtopped the dike, a challenging configuration for numerical models. The analysis is structured in two phases: (i) evaluates the results of 2D numerical and physical models for run-up and overtopping; (ii) compares qualitatively the results of 3D numerical models for overtopping over a dike with promenade between groins located in front of a slope beach. The results indicate that the main differences obtained in run-up and overtopping are due to differences in wave generation and active absorption systems used in physical and numerical models and in turbulent models used by the numerical models. These differences lead to changes on incident wave height and on wave breaking and, consequently, on reflection, run-up and overtopping over the structure. For 3D simulation, even if larger discrepancies were found on overtopping along the dike, mean wave overtopping discharge and water flow height at the crest of the groin head show a similar order of magnitude.

Hydrogen, as a zero-emission fuel, produces only water when used in fuel cells, making it a vital contributor to reducing greenhouse gas emissions across industries like transportation, energy, and manufacturing. Efficient hydrogen storage requires lightweight, high-strength vessels capable of withstanding high pressures to ensure the safe and reliable delivery of clean energy for various applications. Type V composite pressure vessels (CPVs) have emerged as a preferred solution due to their superior properties, thus this study aims to predict the performance of a Type V CPV by developing its numerical model and calculating numerical burst pressure (NBP). For the validation of the numerical model, a Hydraulic Burst Pressure test is conducted to determine the experimental burst pressure (EBP). The comparative study between NBP and EBP shows that the numerical model provides an accurate prediction of the vessel’s performance under pressure, including the identification of failure locations. These findings highlight the potential of the numerical model to streamline the development process, reduce costs, and accelerate the production of CPVs that are manufactured by prepreg hand layup process (PHLP), using carbon fiber/epoxy resin prepreg material.

Numerical model reduction is exploited for computational homogenization of the model problem of a poroelastic medium under transient conditions. It is assumed that the displacement and pore pressure fields possess macro-scale and sub-scale (fluctuation) parts. A linearly independent reduced basis is constructed for the sub-scale pressure field using POD. The corresponding reduced basis for the displacement field is constructed in the spirit of the NTFA strategy. Evolution equations that define an apparent poro-viscoelastic macro-scale model are obtained from the continuity equation pertinent to the RVE. The present model represents an extension of models available in literature in the sense that the pressure gradient is allowed to have a non-zero macro-scale component in the nested FE 2 setting. The numerical results show excellent agreement between the results from numerical model reduction and direct numerical simulation. It was also shown that even 3D RVEs give tractable solution times for full-fledged FE 2 computations.