Rapid spatio-temporal flood modelling via hydraulics-based graph neural networks

Numerical modelling is a reliable tool for flood simulations, but accurate solutions are computationally expensive. In recent years, researchers have explored data-driven methodologies based on neural networks to overcome this limitation. However, most models are only used for a specific case study and disregard the dynamic evolution of the flood wave. This limits their generalizability to topographies that the model was not trained on and in time-dependent applications. In this paper, we introduce shallow water equation–graph neural network (SWE–GNN), a hydraulics-inspired surrogate model based on GNNs that can be used for rapid spatio-temporal flood modelling. The model exploits the analogy between finite-volume methods used to solve SWEs and GNNs. For a computational mesh, we create a graph by considering finite-volume cells as nodes and adjacent cells as being connected by edges. The inputs are determined by the topographical properties of the domain and the initial hydraulic conditions. The GNN then determines how fluxes are exchanged between cells via a learned local function. We overcome the time-step constraints by stacking multiple GNN layers, which expand the considered space instead of increasing the time resolution. We also propose a multi-step-ahead loss function along with a curriculum learning strategy to improve the stability and performance. We validate this approach using a dataset of two-dimensional dike breach flood simulations in randomly generated digital elevation models generated with a high-fidelity numerical solver. The SWE–GNN model predicts the spatio-temporal evolution of the flood for unseen topographies with mean average errors in time of 0.04 m for water depths and 0.004 m2 s−1 for unit discharges. Moreover, it generalizes well to unseen breach locations, bigger domains, and longer periods of time compared to those of the training set, outperforming other deep-learning models. On top of this, SWE–GNN has a computational speed-up of up to 2 orders of magnitude faster than the numerical solver. Our framework opens the doors to a new approach to replace numerical solvers in time-sensitive applications with spatially dependent uncertainties.</p

Anisotropic spin relaxation in graphene

Spin relaxation in graphene is investigated in electrical graphene spin valve devices in the non-local geometry. Ferromagnetic electrodes with in-plane magnetizations inject spins parallel to the graphene layer. They are subject to Hanle spin precession under a magnetic field $B$ applied perpendicular to the graphene layer. Fields above 1.5 T force the magnetization direction of the ferromagnetic contacts to align to the field, allowing injection of spins perpendicular to the graphene plane. A comparison of the spin signals at B = 0 and B = 2 T shows a 20 % decrease in spin relaxation time for spins perpendicular to the graphene layer compared to spins parallel to the layer. We analyze the results in terms of the different strengths of the spin orbit effective fields in the in-plane and out-of-plane directions.Comment: 5 pages, 4 figure

Cost-benefit analysis of flood-zoning policies: A review of current practice

One commonly proposed method to limit flood risk is land-use or zoning policies which regulates construction in high-risk areas, in order to reduce economic exposure and its vulnerability to flood events. Although such zoning regulations can be effective in limiting trends in flood risk, they also have adverse impacts on society, for instance by limiting local development of areas near the water. In order to judge whether proposed land-use or zoning policies are a net benefit to society, they should be accepted or rejected based on a societal cost–benefit analysis (CBA). However, conducting a CBA of zoning regulation is complex and comprehensive guidelines of how to do such an analysis are lacking. We offer guidelines for good practice. In order to assess the costs and benefits of zoning as a climate change adaption strategy, they should be assessed at a societal level in order to account for public good features of flood risk reduction strategies, and because costs in one area can be benefits in another region. We propose a multistep process: first, determine the spatial extent of the zoning policy and how interconnected the zoned area is to other locations; second, conduct a CBA using monetary costs and benefits estimated from an integrated hydro-economic model to investigate if total benefits exceed total costs; third, conduct a sensitivity analysis regarding the main assumptions; fourth, conduct a multicriteria analysis (MCA) of the normative outcomes of a zoning policy. A desirable policy is preferred in both the CBA and MCA

Coupled Dynamic Modeling of Floating Wind Turbine Systems: Preprint

This article presents a collaborative research program that the Massachusetts Institute of Technology (MIT) and the National Renewable Energy Laboratory (NREL) have undertaken to develop innovative and cost-effective floating and mooring systems for offshore wind turbines in water depths of 10-200 m. Methods for the coupled structural, hydrodynamic, and aerodynamic analysis of floating wind turbine systems are presented in the frequency domain. This analysis was conducted by coupling the aerodynamics and structural dynamics code FAST [4] developed at NREL with the wave load and response simulation code WAMIT (Wave Analysis at MIT) [15] developed at MIT. Analysis tools were developed to consider coupled interactions between the wind turbine and the floating system. These include the gyroscopic loads of the wind turbine rotor on the tower and floater, the aerodynamic damping introduced by the wind turbine rotor, the hydrodynamic damping introduced by wave-body interactions, and the hydrodynamic forces caused by wave excitation. Analyses were conducted for two floater concepts coupled with the NREL 5-MW Offshore Baseline wind turbine in water depths of 10-200 m: the MIT/NREL Shallow Drafted Barge (SDB) and the MIT/NREL Tension Leg Platform (TLP). These concepts were chosen to represent two different methods of achieving stability to identify differences in performance and cost of the different stability methods. The static and dynamic analyses of these structures evaluate the systems' responses to wave excitation at a range of frequencies, the systems' natural frequencies, and the standard deviations of the systems' motions in each degree of freedom in various wind and wave environments. This article in various wind and wave environments. This article explores the effects of coupling the wind turbine with the floating platform, the effects of water depth, and the effects of wind speed on the systems' performance. An economic feasibility analysis of the two concepts was also performed. Key cost components included the material and construction costs of the buoy; material and installation costs of the tethers, mooring lines, and anchor technologies; costs of transporting and installing the system at the chosen site; and the cost of mounting the wind turbine to the platform. The two systems were evaluated based on their static and dynamic performance and the total system installed cost. Both systems demonstrated acceptable motions, and have estimated costs of $1.4-$1.8 million, not including the cost of the wind turbine, the power electronics, or the electrical transmission

Challenges in Rotor Aerodynamic Modeling for Non-Uniform Inflow Conditions

Within an international collaboration framework, the accuracy of rotor aerodynamic models used for design load calculations of wind turbines is being assessed. Where the use of high-fidelity computation fluid dynamics (CFD) and mid-fidelity free-vortex wake (FVW) models has become commonplace within the wind energy community, these still fail to meet the requirements in terms of execution time and computational cost needed for design load calculations. The fast but engineering fidelity blade-element/momentum (BEM) method can therefore still be considered the industry workhorse for design load simulations. At the same time, upscaling of wind turbine rotors makes inflow non-uniformities (e.g. shear, veer, turbulence) more important. The objective of this work is to assess model accuracy in non-uniform inflow conditions, which violate several BEM assumptions. Thereto a comparison in turbulent inflow has been executed including a wide variety of codes, focusing on the DanAero field measurements, where a 2.3-MW turbine was equipped with, among other sensors, a pressure measurement apparatus. The results indicate that, although average load patterns are in good agreement, this does not hold for the unsteady loads that drive fatigue damage and aeroelastic stability. A simplified comparison round in vertical shear was initiated to investigate the observed differences in a more controlled manner. A consistent offset in load amplitude was observed between CFD and free-vortex codes on the one hand and BEM-type codes on the other hand. To shed more light on the observations, dedicated efforts are ongoing to pinpoint the cause for these differences, in the end leading to guidelines for an improved BEM implementation

A review of ransomware families and detection methods

Ransomware has become a significant problem and its impact is getting worse. It has now become a lucrative business as it is being offered as a service. Unlike other security issues, the effect of ransomware is irreversible and difficult to stop. This research has analysed existing ransomware classifications and its detection and prevention methods. Due to the difficulty in categorizing the steps none of the existing methods can stop ransomware. Ransomware families are identified and classified from the year 1989 to 2017 and surprisingly there are not much difference in the pattern. This paper concludes with a brief discussion about the findings and future work of this research

Causes of death and demographic characteristics of victims of meteorological disasters in Korea from 1990 to 2008

<p>Abstract</p> <p>Background</p> <p>Meteorological disasters are an important component when considering climate change issues that impact morbidity and mortality rates. However, there are few epidemiological studies assessing the causes and characteristics of deaths from meteorological disasters. The present study aimed to analyze the causes of death associated with meteorological disasters in Korea, as well as demographic and geographic vulnerabilities and their changing trends, to establish effective measures for the adaptation to meteorological disasters.</p> <p>Methods</p> <p>Deaths associated with meteorological disasters were examined from 2,045 cases in Victim Survey Reports prepared by 16 local governments from 1990 to 2008. Specific causes of death were categorized as drowning, structural collapse, electrocution, lightning, fall, collision, landslide, avalanche, deterioration of disease by disaster, and others. Death rates were analyzed according to the meteorological type, specific causes of death, and demographic and geographic characteristics.</p> <p>Results</p> <p>Drowning (60.3%) caused the greatest number of deaths in total, followed by landslide (19.7%) and structural collapse (10.1%). However, the causes of deaths differed between disaster types. The meteorological disaster associated with the greatest number of deaths has changed from flood to typhoon. Factors that raised vulnerability included living in coastal provinces (11.3 times higher than inland metropolitan), male gender (1.9 times higher than female), and older age.</p> <p>Conclusions</p> <p>Epidemiological analyses of the causes of death and vulnerability associated with meteorological disasters can provide the necessary information for establishing future adaptation measures against climate change. A more comprehensive system for assessing disaster epidemiology needs to be established.</p

Neural Synchrony during Response Production and Inhibition

Inhibition of irrelevant information (conflict monitoring) and/or of prepotent actions is an essential component of adaptive self-organized behavior. Neural dynamics underlying these functions has been studied in humans using event-related brain potentials (ERPs) elicited in Go/NoGo tasks that require a speeded motor response to the Go stimuli and withholding a prepotent response when a NoGo stimulus is presented. However, averaged ERP waveforms provide only limited information about the neuronal mechanisms underlying stimulus processing, motor preparation, and response production or inhibition. In this study, we examine the cortical representation of conflict monitoring and response inhibition using time-frequency analysis of electroencephalographic (EEG) recordings during continuous performance Go/NoGo task in 50 young adult females. We hypothesized that response inhibition would be associated with a transient boost in both temporal and spatial synchronization of prefrontal cortical activity, consistent with the role of the anterior cingulate and lateral prefrontal cortices in cognitive control. Overall, phase synchronization across trials measured by Phase Locking Index and phase synchronization between electrode sites measured by Phase Coherence were the highest in the Go and NoGo conditions, intermediate in the Warning condition, and the lowest under Neutral condition. The NoGo condition was characterized by significantly higher fronto-central synchronization in the 300–600 ms window, whereas in the Go condition, delta- and theta-band synchronization was higher in centro-parietal regions in the first 300 ms after the stimulus onset. The present findings suggest that response production and inhibition is supported by dynamic functional networks characterized by distinct patterns of temporal and spatial synchronization of brain oscillations