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At least 217 records · Page 12

An open-access simulated earthquake ground-motion database for an M7 Hayward Fault earthquake in the San Francisco Bay Region

Comprehensive understanding of earthquake ground motions, particularly in the near-fault region of large-magnitude events, is limited by gaps in strong-motion data. This challenge is prominent in areas with high seismic hazard but infrequent large earthquakes where data is sparse and difficult to interpret. These data limitations lead to uncertainties in the development of site-specific ground motions, which are crucial for engineering risk assessments. To address these challenges, physics-based regional-scale ground-motion simulations have been developed. With the emergence of exaflop-scale computing ecosystems, it is now possible to simulate regional earthquake processes at unprecedented fidelity and generate the large number of fault rupture realizations necessary to characterize both intra- and inter-event ground-motion variability. This article introduces a new database of simulated earthquake ground motions, created for applications in earthquake engineering, earthquake planning, and emergency response. The inaugural version of the database features simulated ground motions for a magnitude 7 Hayward Fault earthquake in the San Francisco Bay Region (SFBR), using the EarthQuake SIMulation (EQSIM) simulation framework and the Graves–Pitarka kinematic rupture model. The aim is to provide high-fidelity, spatially dense, three-component motions generated on the Department of Energy’s (DOE) newest generation of graphics processing unit (GPU)-accelerated supercomputers. These motions are being made openly available to the engineering, scientific, and disaster planning communities. In addition, this work develops protocols for the efficient dissemination of these large data sets and emphasizes community engagement to build confidence in their application. This article discusses the methodology behind the data, underlying software verification and validation, scalable data management, and a user interface for data access. The goal is to facilitate widespread use and elicit expert feedback to maximize the utility and exploitation of simulated motions. While the initial focus is on the San Francisco Region, simulations for additional regions will be added as the DOE program progresses.

Simulated ground-motion database↗

Risk of longer-term endocrine and metabolic conditions in the Deepwater Horizon Oil Spill Coast Guard cohort study – five years of follow-up

Abstract Introduction Long-term endocrine and metabolic health risks associated with oil spill cleanup exposures are largely unknown, despite the endocrine-disrupting potential of crude oil and oil dispersant constituents. We aimed to investigate risks of longer-term endocrine and metabolic conditions among U.S. Coast Guard (USCG) responders to the Deepwater Horizon (DWH) oil spill. Methods Our study population included all active duty DWH Oil Spill Coast Guard Cohort members ( N = 45,224). Self-reported spill exposures were ascertained from post-deployment surveys. Incident endocrine and metabolic outcomes were defined using International Classification of Diseases (9th Revision) diagnostic codes from military health encounter records up to 5.5 years post-DWH. Using Cox proportional hazards regression, we estimated adjusted hazard ratios (aHR) and 95% confidence intervals (CIs) for various incident endocrine and metabolic diagnoses (2010–2015, and separately during 2010–2012 and 2013–2015). Results The mean baseline age was 30 years (~ 77% white, ~ 86% male). Compared to non-responders ( n = 39,260), spill responders ( n = 5,964) had elevated risks for simple and unspecified goiter (aHR = 2.09, 95% CI: 1.29–3.38) and disorders of lipid metabolism (aHR = 1.09, 95% CI: 1.00–1.18), including its subcategory other and unspecified hyperlipidemia (aHR = 1.10, 95% CI: 1.01–1.21). The dysmetabolic syndrome X risk was elevated only during 2010–2012 (aHR = 2.07, 95% CI: 1.22–3.51). Responders reporting ever ( n = 1,068) vs. never ( n = 2,424) crude oil inhalation exposure had elevated risks for disorders of lipid metabolism (aHR = 1.24, 95% CI: 1.00–1.53), including its subcategory pure hypercholesterolemia (aHR = 1.71, 95% CI: 1.08–2.72), the overweight, obesity and other hyperalimentation subcategory of unspecified obesity (aHR = 1.52, 95% CI: 1.09–2.13), and abnormal weight gain (aHR = 2.60, 95% CI: 1.04–6.55). Risk estimates for endocrine/metabolic conditions were generally stronger among responders reporting exposure to both crude oil and dispersants (vs. neither) than among responders reporting only oil exposure (vs. neither). Conclusion In this large cohort of active duty USCG responders to the DWH disaster, oil spill cleanup exposures were associated with elevated risks for longer-term endocrine and metabolic conditions.

Denic-Roberts, Hristina↗

A deformation-dependent coupled Lagrangian/semi-Lagrangian meshfree hydromechanical formulation for landslide modeling

Abstract The numerical modelling of natural disasters such as landslides presents several challenges for conventional mesh-based methods such as the finite element method (FEM) due to the presence of numerically challenging phenomena such as severe material deformation and fragmentation. In contrast, meshfree methods such as the reproducing kernel particle method (RKPM) possess unique features conducive to modelling extreme events such as the absence of a structured mesh and the ease of adaptive refinement, among others. While the semi-Lagrangian reproducing kernel (SL-RK) shape functions of RKPM defined in the current configuration have proven to be effective in extreme event modelling, the computational cost for the re-evaluation of the shape functions at every time step is costly. In this work, a deformation-dependent coupling of the Lagrangian reproducing kernel (L-RK) and SL-RK approximations is proposed for the solution of a hydro-mechanical formulation for effective simulations of landslides. The ramp function is constructed based on an equivalent plastic strain as a deformation-dependent transition from L-RK shape functions to SL-RK ones as the deformation progresses. The particular focus of the paper will be on modelling seepage-induced landslides with a mixed $$u$$ u – $$p$$ p formulation to couple the solid and fluid phases. Examples are presented to examine the effectiveness of this coupled Lagrangian/semi-Lagrangian reproducing kernel (L–SL RK) formulation and to highlight its performance in landslide modelling.

Baek, Jonghyuk↗

Providing Geospatial Intelligence through a Scalable Imagery Pipeline

This chapter describes ORNL’s (Oak Ridge National Laboratory’s) contributions to imagery preprocessing for geospatial intelligence research and development (R&D) in four sections. First, we discuss challenges involved in building an effective imagery preprocessing workflow and the world-class high-performance computing (HPC) resources at ORNL available to process petabytes of imagery data. Second, we highlight how we developed imagery preprocessing tools over three decades while paving the way for our current cutting-edge machine learning and computer vision algorithms that are impacting humanitarian and disaster response efforts. Third, we discuss how PIPE modules work together to turn raw images into analysis-ready datasets. Fourth, we look toward the future and discuss planned advancements to PIPE and computing trends that will affect geospatial intelligence R&D.

Reith, Andrew↗

Current UAS Capabilities for Geospatial Spectral Solutions

Unmanned aerial systems (UAS) are playing an increasingly pivotal role in advancing the remote collection of data. The various datasets collected by these cutting-edge systems provide near-real-time information and help inform end users on everything from disaster recovery efforts to monitoring atmospheric constituents. This chapter focuses on how the collection of imagery has progressed over time, including the pivotal role UAS play in building large-scale datasets driving data analysis. The authors report the findings of a 2018–2021 survey of the fields that use UAS, the UAS platforms most commonly used, and the sensor components users select to outfit their UAS. The chapter will also discuss the range of platforms currently available, with a specific focus on issues including battery life, data downlinks, data processing times, edge computing, and availability of new sensors. The authors will also discuss the future direction of UAS platforms as well as many of the problems associated with the high spatial and temporal resolution of modern geospatial datasets.

Cotten, David↗

Advancing stem cell technologies for conservation of wildlife biodiversity

ABSTRACT Wildlife biodiversity is essential for healthy, resilient and sustainable ecosystems. For biologists, this diversity also represents a treasure trove of genetic, molecular and developmental mechanisms that deepen our understanding of the origins and rules of life. However, the rapid decline in biodiversity reported recently foreshadows a potentially catastrophic collapse of many important ecosystems and the associated irreversible loss of many forms of life on our planet. Immediate action by conservationists of all stripes is required to avert this disaster. In this Spotlight, we draw together insights and proposals discussed at a recent workshop hosted by Revive & Restore, which gathered experts to discuss how stem cell technologies can support traditional conservation techniques and help protect animal biodiversity. We discuss reprogramming, in vitro gametogenesis, disease modelling and embryo modelling, and we highlight the prospects for leveraging stem cell technologies beyond mammalian species.

Developmental Biology↗

Strategic Survey of Antineutrino-based Nonproliferation Technologies

Antineutrinos carry approximately 3% of the total energy released in fission processes. As a consequence, nuclear energy production provides by far the brightest antineutrino sources on Earth. Antineutrino interactions with ordinary matter are weak and these particles cannot be shielded, making them an ideal signature of fissioning systems. However, the same property makes antineutrinos difficult to detect. Antineutrino detection technologies have matured in recent years, and emerging detection approaches warrant further investment. For near-field applications, the major enabling technological advancement, reported in 2018, is the conclusive detection of the antineutrino spectrum in segmented detectors operating at the surface with minimal shielding. For far-field applications, the highlights are the routine detection of reactor antineutrinos at hundreds of kilometer standoff in the kiloton-scale KamLAND and Borexino liquid scintillator detectors, and in particular the observation of the residual South Korean reactor antineutrino flux in KamLAND following the Fukushima disaster that led to shutdown of reactors in Japan

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Radioactive Plume Avoidance and Aircraft Decontamination – Best Practices

Response to an incident involving the release of radioactive material will most likely involve aircraft for disaster relief and radiological monitoring. Aircraft flying into a radiologically contaminated area risk becoming contaminated, and in the worst cases having to be removed from service. Contamination is avoidable, and decontamination is possible, but both require planning and forethought.

61 RADIATION PROTECTION AND DOSIMETRY↗

Nonproliferation Legacy Technology and Artifact Collection: NASA Space Shuttle Tiles

The NASA Space Shuttle Tiles were used by Sandia in the process of developing the Laser Dynamic Range Imager (LDRI) in support of NASA's Return to Flight following the 2003 Space Shuttle Columbia disaster. The heat shield tiles, provided to Sandia by NASA, are identical to those that were located on the underbelly of the Space Shuttle Columbia's orbiter. Sandia used the tiles to test the efficacy of the LDRI's imaging capabilities. The LDRI was utilized during every space shuttle mission between 2005 and 2011. The tiles are currently located in Building 891 and need to be moved to free up space for operational use. Given their technical significance, Sandia would like to archive them as historically significant items in long-term storage until such time as they can be appropriately displayed or employed as a demonstration artifact. This document provides basic information about the provenance of this artifact.

42 ENGINEERING↗

Resilient U.S. Land Ports of Entry

The continued operation of Land Ports of Entry (LPOE), managed by the Customs and Border Protection (CBP) and General Services Administration% is vital to the U.S. economy and security. Border faculties are included in the Department of Homeland Security (DHS) Government Facilities Sector2, one of the 16 critical infrastructures "whose assets, systems, and networks, whether physical or virtual, are considered so vital to the United States that their incapacitation or destruction would have a debilitating effect on security, national economic security, national public health or safety, or any combination thereof.'" Specifically, disruptions to the flow of border crossing traffic, in the form of closures or increased border crossing wait times, impact the economy and security of all countries involved. This paper describes a process for analyzing and improving the resilience of U.S. Land Ports of Entry. For LPOE, the team believes that energy resilience is the primary objective due to the complete reliance on the e-manifest system and the increasing use of Multi-Energy Portals (MEPs). Emanifests are part of CPB's Automated Commercial Environment (ACE). They document several key pieces of information about cargo vehicles wishing to cross the border into the United States and are submitted before arriving at the port. Vehicles can be flagged for more invasive inspection based on the content of the e-manifest. MEPs are a non-intrusive inspection (NII) technology used to scan the contents of the cargo. Together MEPs and ACE serve an important role in aiding CBP with their mission to protect "the public from dangerous people and materials", and "enabling legitimate trade and travel.'" To analyze resilience of a port, the team would need to understand the port's current energy usage, which systems depend on energy and what backup systems exist, and any emergency operation plans that dictate how systems are operated in the event of a power outage. The team would also need to determine the design basis threats (DBTs) for the LPOE which could include natural disasters, manmade events, and accidents. The magnitudes of the DBTs are calculated and are then translated to expected impacts on the infrastructure and systems at the port. With this information gathered, existing LPOE models developed here at Sandia National Laboratories could be extended to support decisions about resilience. Current models are implemented in FlexSim, a 3rd party discrete event simulator. FlexSim provides 3-D visuals of physical layout that can reveal valuable insights, allows input to be variable (e.g. time it takes to interact with the CBP officer at primary inspection can vary) so that a whole range of possibilities can be captured in the results, and can be used to collect user-defined output metrics. Current LPOE models focus on cargo vehicle traffic, and process changes caused by the installation of new drive-through MEPs. Extending them to address resilience questions would require the addition of key pieces of information learned during the resilience analysis including critical systems, failure rates, and process changes for when failures occur. The primary output metric for current models is border crossing wait time. Additional metrics would also be added to the model to gain a more complete understanding of impacts related to resilience, for example, MEP scan rate. Once complete, the model could be used to analyze the effectiveness of mitigation strategies representing some future state.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Power System Resilience Metrics Augmentation for Critical Load Prioritization

One of the major goals of new grid operation regimes, such as transactive energy systems (TESs), is to make the power grid more resilient to withstand natural or man-made disasters and potential reliability events, and to continue to serve the maximum number of its customers. But it is a well-known fact to system operators that not all customers are the same. This implies that any discussion of TESs’ impacts on the resilience of the power system should consider the needs of its critical customers (such as the power system operation centers, fire and police stations, and hospitals) over those of other customers. When evaluating the resilience of the system, bonus points must be awarded to any system that could maintain its power supply to critical customers during a disturbance that may cause an outage. This report discusses critical infrastructure (CI) as found in the literature and then categorizes it based on the field to which the operations belong (such as human life/safety-related, operations management, necessary city operation, industrial customers, etc.). Each of these CI categories is further divided into types of critical customers (e.g., the human life/safety-related category has different types of customers like hospitals, fire and police stations, etc.). The entire demand of each of the critical customer types is not categorized as critical load (CL); instead, only a portion of the total load of these critical customers is characterized as critical load. This is done based on the categories of equipment, the function of which is crucial in the operation of the overall facility. CL categorization is performed to provide the ratio of the critical load portion to the overall load , so that it can serve as a parameter in the resilience evaluation of the grid through a metrics-based approach. Such categorization is important as it helps to augment the existing quantifiable resilience metrics with CL categorization. The metrics for a power system need to not only consider how well a system performed during a disturbance event, but also how it reduced strain and supplied power to its CLs. The first step in this process is characterize CLs in the system. After CL characterization, the next step is the inclusion of these loads in the resilience metrics. To that end, in this report weight-based augmentation of resilience metrics is proposed, where certain customers (the ones that are categorized as critical) are assigned higher weights than others. Though an overview of assigning weights to customers is discussed, there is no one-size-fits-all approach for every power system. The decisions made about assigning such weights to customers vary greatly from one operator to another, based on their unique systems and the current and predicted states of critical customers. This decision-making can include the type of disturbance event, which might only affect certain parts of the system. In general, analyzing critical customers before an event helps understand system vulnerabilities. It also helps in planning and conducting operations during the event, evaluating system performance after the event, and supporting better planning for future events. An alternative to the current practices of managing the grid for outages is an innovative TES, which has the potential to provide a platform for including distributed energy resources for managing CLs. This report also describes how TES qualities can help (1) to maintain power supply to critical customers for uninterrupted operations and (2) to restore lost power supply to the critical customers rapidly.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Modeling Framework for Bulk Electric Grid Impacts from HEMP E1 and E3 Effects (Tasks 3.1 Final Report)

This report presents a framework to evaluate the impact of a high-altitude electromagnetic pulse (HEMP) event on a bulk electric power grid. This report limits itself to modeling the impact of EMP E1 and E3 components. The co-simulation of E1 and E3 is presented in detail, and the focus of the paper is on the framework rather than actual results. This approach is highly conservative as E1 and E3 are not maximized with the same event characteristics and may only slightly overlap. The actual results shown in this report are based on a synthetic grid with synthetic data and a limited exemplary EMP model. The framework presented can be leveraged and used to analyze the impact of other threat scenarios, both manmade and natural disasters. This report d escribes a Monte-Carlo based methodology to probabilistically quantify the transient response of the power grid to a HEMP event. The approach uses multiple fundamental steps to characterize the system response to HEMP events, focused on the E1 and E3 components of the event. 1) Obtain component failure data related to HEMP events testing of components and creating component failure models. Use the component failure model to create component failure conditional probability density function (PDF) that is a function of the HEMP induced terminal voltage. 2) Model HEMP scenarios and calculate the E1 coupled voltage profiles seen by all system components. Model the same HEMP scenarios and calculate the transformer reactive power consumption profiles due to E3. 3) Sample each component failure PDF to determine which grid components will fail, due to the E1 voltage spike, for each scenario. 4) Perform dynamic simulations that incorporate the predicted component failures from E1 and reactive power consumption at each transformer affected by E3. These simulations allow for secondary transients to affect the relays/protection remaining in service which can lead to cascading outages. 5) Identify the locations and amount of load lost for each scenario through grid dynamic simulation. This can be an indication of the immediate grid impacts from a HEMP event. In addition, perform more detailed analysis to determine critical nodes and system trends. 6) To help realize the longer-term impacts, a security constrained alternating current optimal power flow (ACOPF) is run to maximize critical load served. This report describes a modeling framework to assess the systemic grid impacts due to a HEMP event. This stochastic simulation framework generates a large amount of data for each Monte Carlo replication, including HEMP location and characteristics, relay and component failures, E3 GIC profiles, cascading dynamics including voltage and frequency over time, and final system state. This data can then be analyzed to identify trends, e.g., unique system behavior modes or critical components whose failure is more likely to cause serious systemic effects. The proposed analysis process is demonstrated on a representative system. In order to draw realistic conclusions of the impact of a HEMP event on the grid, a significant amount of work remains with respect to modeling the impact on various grid components.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Considerations for Distributed Energy Resource Integration in Puerto Rico: DOE Multi-Lab Grid Modeling Support for Puerto Rico; Analytical Support for Interconnection and IEEE Std 1547-2018 National Renewable Energy Laboratory (Task 3.0)

To ensure the sustainable long-term recovery of Puerto Rico's electric power grid from hurricanes María and Irma and to build capacity to manage future potential natural disasters in the most secure and resilient way, the U.S. Department of Energy (DOE) convened experts from multiple national laboratories to develop a comprehensive set of data, models, analytic tools, and studies, considering inputs from a wide variety of stakeholder groups, to support technically sound recommendations for Puerto Rico's energy investment decisions. A resilient electric grid is vital to Puerto Rico's security, economy, and way of life, and it will provide the foundation for essential services that people and businesses on the island rely on every day. This report shows progress for a grid modeling task under the DOE-sponsored project that is a collaboration among the National Renewable Energy Laboratory (NREL) and other national laboratories. In Phase 1 of the multilab effort to support Puerto Rico's recovery, NREL provided the utility company Puerto Rico Electric Power Authority (PREPA) recommendations for a new framework of interconnection standards to accelerate the integration of utility-scale, transmission-connected renewable electrical generation and energy storage that ensure cross-technology compatibility and enable high deployment levels without compromising grid reliably, safety, or security. This Phase 2 report focuses on the interconnection of distributed energy resources (DERs) to the electric distribution system in Puerto Rico. This report is intended to familiarize the reader with Puerto Rico's distribution infrastructure and operational practices and procedures that are relevant to DER interconnection. The report also provides considerations for streamlining the interconnection process given the expected increase in deployments resulting from Puerto Rico's renewable portfolio standard (RPS) goal of 100% renewables by 2050. Accordingly, the report identifies considerations and concerns associated with the increase in intermittent generation, strategies for DER interconnection best practices, and the potential use of the latest technological solutions identified in the latest revision of the Institute of Electrical and Electronics Engineers (IEEE) 1547-2018 interconnection standard.

24 POWER TRANSMISSION AND DISTRIBUTION↗

New Jersey Transit Grid Distributed Generation Program. Cybersecurity Design Assurance Assessment

Superstorm Sandy caused a major disruption to passenger-rail and other commuter systems throughout New York and New Jersey. To address this issue, New Jersey Transit (NJT) established the NJ TRANSITGRID project, an effort designed to power bus, ferry, and limited passenger-rail service during natural or man-made disasters. Given the importance of these transportation systems, NJT partnered with Sandia National Laboratories (Sandia) to assess the cyber-resilience of the information systems that monitor and control the electrical systems within the microgrid. The Sandia “tabletop” assessment is based on the most recent 20% design packages. From this assessment, the Sandia team identified several security areas that were undefined or did not implement industry best practices. Finally, the Sandia team presented possible follow-on assessment activities and recommended investigating multiple hardening technologies. Addressing these findings and adding state-of-the-art detection and mitigation technologies will help ensure the NJ TRANSITGRID is built with more comprehensive cyber-resilience features.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Federal Fleet Resilience Planning

Federal fleet operations span the diverse geography of the country as the vehicles provide services in support of equally diverse agency missions. Fleets face the potential for disruption of services from natural disasters, infrastructure failures, and human threats. This report reviews some of the hazards, threats, and disruptions that fleets may face, describes an approach to fleet management that incorporates resilience, and provides an overview of fleet resilience considerations. While this report is not comprehensive, it describes considerations for integrating resilience into fleet management organizational priorities.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Federal Fleet Resilience Planning

Federal fleet operations span the diverse geography of the country as the vehicles provide services in support of equally diverse agency missions. Fleets face the potential for disruption of services from natural disasters, infrastructure failures, and human threats. This report reviews some of the hazards, threats, and disruptions that fleets may face, describes an approach to fleet management that incorporates resilience, and provides an overview of fleet resilience considerations. While this report is not comprehensive, it describes considerations for integrating resilience into fleet management organizational priorities.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

EpiCast: Simulating Epidemics with Extreme Detail

In early 2020, COVID-19 swept the globe. Governments attempted to “flatten the curve” through business shutdowns and stay-at-home orders, but the United States was hit hard. By the end of March, mere months after the virus first emerged in humans 7,000 miles away, the U.S. had recorded 192,300 cases and 5,300 deaths. While this unprecedented disaster sent shockwaves through every level of society and clouded an uncertain future, state and local governments turned to computational and mathematical epidemiology researchers to help formulate intervention strategies to limit the spread of the disease. Traditional forecasting models provided a reasonable understanding of how the near future was likely to look, but local policy makers and public health communities still struggled to understand how potential mitigations ought to be implemented. Decision makers needed a way to measure the impact of their policy choices—they needed better technology. EpiCast answered the call, bringing urgently needed answers to policymakers grappling with how to adjust school and business schedules. EpiCast is modeling software that generates a synthetic, representative population to simulate infectious disease transmission in the United States with extreme detail and granularity. The software models human behavior combined with community-specific information to provide a fine-grained preview of the effect of potential mitigation strategies for decision makers.

60 APPLIED LIFE SCIENCES↗

Global Market Analysis of Microreactors

Microreactors are smaller and simplified versions of nuclear power plants using current generation and advanced nuclear technology designs. The purpose of this report is to assesses the unique capabilities of microreactors and assess potential deployment in specific global markets in the 2030-2050 timeframe, with consideration for regulatory limits. The methods include developing unique microreactor deployment indicators and matching use cases to define future profile markets. Top-down and bottom-up analysis techniques were used to evaluate emerging market trends, derive a range of possible demands, and rank potential markets in 63 countries including current nuclear users and newcomer countries. Deployment is considered from regulatory and planning perspectives. Results indicate significant potential for global deployment of microreactors, but also significant challenges in achieving the technical capacities, meeting regulatory requirements and international accords, achieving competitive costs, and for gaining public acceptance. Profile microreactor markets were identified that include isolated operations, distributed energy, resilient urban applications, marine propulsion, and disaster relief. Market demands could be strong in Western Europe and possibly even the U.S., but particularly strong across Asia and Eastern Europe in isolated operations and distributed energy applications. Build rates in the hundreds of units by 2040 and thousands by 2050 would be needed to attain market penetration at scale.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗