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\"Numerical simulation models are used in all engineering disciplines for modeling physical phenomena to learn how the phenomena work, and to identify problems and optimize behavior. Smart proxy models provide an opportunity to replicate numerical simulations with very high accuracy and can be run on a laptop within a few minutes, thereby simplifying the use of complex numerical simulations which can otherwise take tens of hours. This book focuses on smart proxy modeling and provides readers with all the essential details on how to develop smart proxy models using artificial intelligence and machine learning, as well as how it may be used in real-world cases. Covers replication of highly accurate numerical simulations using artificial intelligence and machine learning. Details application in reservoir simulation and modeling, and computational fluid dynamics. Includes real case studies based on commercially available simulators. Smart Proxy Modeling is ideal for petroleum, chemical, environmental, and mechanical engineers, as well as statisticians and others working with applications of data-driven analytics\"-- Provided by publisher.

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.

In the context of climate change and urbanization, flood becomes one of the most important threats to human life, health, and property. Coastal areas gathering large numbers of population, capital, and industries are vulnerable to suffering from the compound floods caused by hydrological and oceanic processes. The disaster mechanisms of compound floods are more complex, and the consequences are even more serious. Based on the existing research results, this article sorts out the main disaster mechanisms of compound floods in coastal areas and explains the main methods, including using statistical models to study the dependence between flood drivers or joint probability and numerical models to simulate compound flood inundation, and presents the characteristics of different methods. We also discuss the advantages and disadvantages of different models and analyze their uncertainties. Current research seldom considers the rainfall-runoff-storm surge compound flood and the effect of climate change. In addition, there are only a few kinds of literature that integrate statistical models and numerical models to investigate compound flood hazard. Uncertainties in compound flood study methods are also less considered. Future investigation should focus on the characteristics and uncertainties of different models and consider the impact of climate change on compound floods. These will help to fully understand compound floods, research models, and provide effective opinions for flood management in coastal areas.

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

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.

In stability analysis of discontinuity-controlled slopes, the rationality of results is related to the accuracy of three-dimensional (3D) slope morphology and the reliability of the discontinuity survey. With the advent of remote sensing technologies for engineering geological surveys and slope stability analyses, step-change increases have been made in the quality of data available and geometrical characterization of rock slopes. Although these techniques are frequently employed in the characterization of slope geometry and joint surfaces at present, limited research has been undertaken to effectively process the derived data and improve the quality in the reconstruction of slope geometry imported into 3D discontinuous numerical models. In this paper, an integrated system coupling 3D-DDA and UAV-LS photogrammetry is presented as a tool to evaluate the stability of a blocky rock mass slope. The system includes a UAV-LS module, a modeling module, a block-generation module, and a 3D-DDA calculation module. In the UAV-LS module, the use of UAV-LS system integrated with field mapping and site observations allows the acquisition of detailed outputs (point clouds) on both the slope and discontinuity geometry. An effective combination of commercial software Geomagic and Hyperworks is used in the modeling module to process oceans of 3D point cloud data and construct complex 3D geometrical models based on reverse engineering. In the block-generation module, the three-dimensional discontinuous deformation analysis (3D-DDA) method is then carried out in order to simulate the movement of potentially unstable blocks, within which an independent block-cutting algorithm is used to generate the blocks with arbitrary shapes and the finite structural planes similar to the real cases. The 3D-DDA calculation module uses 3D-DDA calculation algorithm to derive the simulation results. The capability of the proposed system for stability analysis of a jointed slope is demonstrated by a practical example.

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.

In order to study the diffusion and sealing mechanism of an innovative grouted material tentatively called “expandable particulate grout material”, the diffusion process was simulated by the numerical method of CFD-DEM coupling. A numerical model was established for a grouting process in an individual fracture based on the basic physical parameters of expandable particles. The numerical model of the expandable particulate slurry flow was established. The interaction between particles and water in different conditions, such as different grouting times, different volume fractions of the particle, and different velocities, was investigated. The differences in the diffusion process and in the running-water sealing mechanism of expandable particles, cement slurry, and cement-sodium silicate slurry in the crack (in a, in b, and in c) were analyzed. The influence of expandable particles on the streamline of the grout and the drag force in the interaction process under the fracture were analyzed. This is summarized The influence of the velocity ratio of grout to water on different physical quantities, such as diffusion opening degree, diffusion velocity, and diffusion distance, was summarized. It is of significant theoretical and practical value to further develop and improve the grouting technology.

Relic coastal landforms (fossil corals, cemented intertidal deposits, or erosive features carved onto rock coasts) serve as sea‐level index points (SLIPs), that are widely used to reconstruct past sea‐level changes. Traditional SLIP‐based sea‐level reconstructions face challenges in capturing continuous sea‐level variability and dating erosional SLIPs, such as tidal notches. Here, we propose a novel approach to such challenges. We use a numerical model of cliff erosion embedded within a Monte Carlo simulation to investigate the most likely sea‐level scenarios responsible for shaping one of the best‐preserved tidal notches of Last Interglacial age in Sardinia, Italy. Results align with Glacial Isostatic Adjustment model predictions, indicating that synchronized or out‐of‐sync ice‐volume shifts in Antarctic and Greenland ice sheets can reproduce the notch morphology, with sea level confidently peaking at 6 m and only under a higher than present erosion regime. This new approach yields insight into sea‐level trends during the Last Interglacial. Plain Language Summary Scientists typically investigate the position of sea level in geological time using the elevation, age, and characteristics of fossil marine organisms living in shallow water (e.g., coral reefs), beach deposits, or erosional features that were formed near the sea level. However, these indicators offer only fragmented, if not only point‐like information in time and not a continuous sea‐level record. To overcome this issue, we use a numerical model that reconstructs the shape of tidal notches (i.e., indentations created close to sea level in carbonate cliffs). We compare model‐generated notch shapes with the real shape of the tidal notch, and we produce a set of continuous sea‐level histories that are more likely to have produced one of the best‐preserved fossil tidal notches in the Orosei Gulf, Sardinia, Italy, carved during the Last Interglacial highstand, 125.000 years ago. Our findings suggest that whether the ice sheets in Antarctica and Greenland melted at the same time or separately, both scenarios could reproduce the actual shape of the tidal notch we observe at present. Our findings indicate that the erosion rate during that period was higher than present and the sea level is very likely to have reached up to 6 m. Key Points Cliff erosion modeling and Monte Carlo analysis indicate tidal notch geometry can offer a continuous record of past sea level variability The geometry of Orosei’s tidal notch, Italy can be replicated through simultaneous or asynchronous Antarctic–Greenland ice melting scenarios The morphology of the Last Interglacial notch is more efficiently replicated using higher‐than‐present erosion rates and a 6 m sea‐level peak