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Smart proxy modeling : artificial intelligence and machine learning in numerical simulation
\"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.
Book
Urbanization exacerbated the rainfall and flooding caused by hurricane Harvey in Houston
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
, 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.
Journal Article
Machine Learning in Tropical Cyclone Forecast Modeling: A Review
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.
Journal Article
Seismic performance analysis of a wind turbine with a monopile foundation affected by sea ice based on a simple numerical method
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.
Journal Article
Vanadium Redox Flow Batteries: A Review Oriented to Fluid-Dynamic Optimization
Large-scale energy storage systems (ESS) are nowadays growing in popularity due to the increase in the energy production by renewable energy sources, which in general have a random intermittent nature. Currently, several redox flow batteries have been presented as an alternative of the classical ESS; the scalability, design flexibility and long life cycle of the vanadium redox flow battery (VRFB) have made it to stand out. In a VRFB cell, which consists of two electrodes and an ion exchange membrane, the electrolyte flows through the electrodes where the electrochemical reactions take place. Computational Fluid Dynamics (CFD) simulations are a very powerful tool to develop feasible numerical models to enhance the performance and lifetime of VRFBs. This review aims to present and discuss the numerical models developed in this field and, particularly, to analyze different types of flow fields and patterns that can be found in the literature. The numerical studies presented in this review are a helpful tool to evaluate several key parameters important to optimize the energy systems based on redox flow technologies.
Journal Article
Application of 3D-DDA integrated with unmanned aerial vehicle–laser scanner (UAV-LS) photogrammetry for stability analysis of a blocky rock mass slope
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.
Journal Article
Hydrate morphology: Physical properties of sands with patchy hydrate saturation
The physical properties of gas hydrate‐bearing sediments depend on the volume fraction and spatial distribution of the hydrate phase. The host sediment grain size and the state of effective stress determine the hydrate morphology in sediments; this information can be used to significantly constrain estimates of the physical properties of hydrate‐bearing sediments, including the coarse‐grained sands subjected to high effective stress that are of interest as potential energy resources. Reported data and physical analyses suggest hydrate‐bearing sands contain a heterogeneous, patchy hydrate distribution, whereby zones with 100% pore‐space hydrate saturation are embedded in hydrate‐free sand. Accounting for patchy rather than homogeneous hydrate distribution yields more tightly constrained estimates of physical properties in hydrate‐bearing sands and captures observed physical‐property dependencies on hydrate saturation. For example, numerical modeling results of sands with patchy saturation agree with experimental observation, showing a transition in stiffness starting near the series bound at low hydrate saturations but moving toward the parallel bound at high hydrate saturations. The hydrate‐patch size itself impacts the physical properties of hydrate‐bearing sediments; for example, at constant hydrate saturation, we find that conductivity (electrical, hydraulic and thermal) increases as the number of hydrate‐saturated patches increases. This increase reflects the larger number of conductive flow paths that exist in specimens with many small hydrate‐saturated patches in comparison to specimens in which a few large hydrate saturated patches can block flow over a significant cross‐section of the specimen.
Key Points
Controls on hydrate morphology in natural sediments
Accounting for patchy hydrate yields tighter estimates of physical properties
Models to characterize stiffness and conductivities of sands with patchy hydrate
Journal Article
Compressive Strength of Corrugated Paperboard Packages with Low and High Cutout Rates: Numerical Modelling and Experimental Validation
The finite element method is a widely used numerical method to analyze structures in virtual space. This method can be used in the packaging industry to determine the mechanical properties of corrugated boxes. This study aims to create and validate a numerical model to predict the compression force of corrugated cardboard boxes by considering the influence of different cutout configurations of sidewalls. The types of investigated boxes are the following: the width and height of the boxes are 300 mm in each case and the length dimension of the boxes varied from 200 mm to 600 mm with a 100 mm increment. The cutout rates were 0%, 4%, 16%, 36%, and 64% with respect to the total surface area of sidewalls of the boxes. For the finite element analysis, a homogenized linear elastic orthotropic material model with Hill plasticity was used. The results of linear regressions show very good estimations to the numerical and experimental box compression test (BCT) values in each tested box group. Therefore, the numerical model can give a good prediction for the BCT force values from 0% cutout to 64% cutout rates. The accuracy of the numerical model decreases a little when the cutout rates are high. Based on the results, this paper presents a numerical model that can be used in the packaging design to estimate the compression strength of corrugated cardboard boxes.
Journal Article
Compound flood models in coastal areas: a review of methods and uncertainty analysis
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.
Journal Article
Does clinical data quality affect fluid-structure interaction simulations of patient-specific stenotic aortic valve models?
Numerical models are increasingly used in the cardiovascular field to reproduce, study and improve devices and clinical treatments. The recent literature involves a number of patient-specific models replicating the transcatheter aortic valve implantation procedure, a minimally invasive treatment for high-risk patients with aortic diseases. The representation of the actual patient’s condition with truthful anatomy, materials and working conditions is the first step toward the simulation of the clinical procedure.
The aim of this work is to quantify how the quality of routine clinical data, from which the patient-specific models are built, affects the outputs of the numerical models representing the pathological condition of stenotic aortic valve.
Seven fluid–structure interaction (FSI) simulations were performed, completed with a sensitivity analysis on patient-specific reconstructed geometries and boundary conditions. The structural parts of the models consisted of the aortic root, native tri-leaflets valve and calcifications. Ventricular and aortic pressure curves were applied to the fluid domain.
The differences between clinical data and numerical results for the aortic valve area were less than 2% but reached 12% when boundary conditions and geometries were changed. The difference in the aortic stenosis jet velocity between measured and simulated values was less than 11% reaching 27% when the geometry was changed. The CT slice thickness was found to be the most sensitive parameter on the presented FSI numerical model.
In conclusion, the results showed that the segmentation and reconstruction phases need to be carefully performed to obtain a truthful patient-specific domain to be used in FSI analyses.
Journal Article