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At least 559 records · Page 31
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Bridge Seismic Screening Tool (BSST), Version 2.0

The Regional Resiliency Assessment Program (RRAP) is a cooperative assessment of specific critical infrastructure within a designated geographic area and a regional analysis of the surrounding infrastructure that addresses a range of infrastructure resilience issues that could have regionally and nationally significant consequences. In 2018, DHS’s Cybersecurity and Infrastructure Security Agency (CISA) sponsored the Oregon Transportation Systems RRAP project in coordination with the Office of the Governor (under the oversight of the state resilience officer), the Oregon Office of Emergency Management (OEM), the Oregon Department of Transportation (ODOT), and other regional stakeholders (CISA 2021). This project focuses on assessing the impacts of a Cascadia Subduction Zone (CSZ) earthquake on state transportation systems and, in particular, how those impacts may affect the ability of emergency response efforts to move supplies into the region. The intended outcome of this analysis is the prioritization of transportation routes and modes for additional planning, investment, hardening, or other activities to enhance their resilience—and therefore, to enhance their ability to support response and recovery efforts following a CSZ earthquake. An important part of this transportation system-level assessment has been to assess the seismic vulnerability of the state highway system. In doing so, the RRAP project team used the Bridge Seismic Screening Tool (BSST) to assess, at a system-level, the potential impacts that a CSZ earthquake could have on state highway bridges (Bergerson et al. 2019).1 Argonne National Laboratory (Argonne), in collaboration with the Washington State Department of Transportation (WSDOT), originally developed the BSST as part of the 2017 Washington State Transportation Systems RRAP project, a sister project to the 2018 Oregon Transportation Systems RRAP project. Argonne updated the BSST during this more recent project in Oregon based on feedback from stakeholders and subject matter experts (SMEs) on the original version of the tool. The first step in the BSST is to assess the seismic vulnerability of roadway bridges following a CSZ earthquake to determine a projected or potential damage state. Damage states then help determine approximate reopening times for bridge crossings.2 This document provides details on the BSST methodology, the implementation of that tool to analyze the projected damage incurred in a CSZ earthquake scenario, and the determination of corresponding reopening times of interstate, state highway, and local bridges following such an event.

58 GEOSCIENCES↗
DOE OSTI2021

Assessing the Accuracy of a Borehole-Controlled Velocity Model of Yucca Flat, Nevada, Using Large-N Seismic Data

The Source Physics Experiment (SPE) aims to improve nuclear test monitoring capabilities through a series of chemical explosions in Yucca Flat within the Nevada National Security Site (NNSS) (Snelson et al., 2013). With geologic data from over 950 boreholes, Yucca Flat has excellent borehole control on stratigraphy. These data were used to create a Geologic Framework Model (GFM) of the basin to aid in the study of seismic wave propagation through the Earth. However, the seismic velocities of the geologic units in the GFM are less well-defined. With the acquisition of five new active source Large-N datasets, we can now quantitatively assess the accuracy of the seismic model previously controlled by borehole data alone.

58 GEOSCIENCES↗
DOE OSTI2025

Tactical Analysis for Calculating Contextual Risk at Boundaries: Summary of Laboratory Directed Research & Development Effort

The Tactical Analysis for Calculating Contextual Risk at Boundaries (TACCRAB) tool is an innovative digital twin (DT) platform and automated risk algorithm designed to transform operational decision-making in structured screening environments, with an initial focus on Southern Border Land Ports of Entry (POEs). The invention provides integration points for advanced artificial intelligence, predictive modeling, and real-time data analysis to produce a comprehensive risk management tool that enables proactive, data-informed security strategies. The core inventive features of TACCRAB center on its unique risk algorithm, which dynamically calculates contextual risk by synthesizing historical data, near real-time streaming data from the checkpoints themselves, and AI-generated predictions. Unlike traditional risk assessment methods, TACCRAB utilizes a DT to provide comprehensive operational insights, allowing stakeholders to visualize, simulate, and optimize checkpoint configurations with unprecedented speed and contextual awareness. TACCRAB's key innovation lies in its ability to combine multiple complex inputs - including technology detection probabilities, resource availability, screening pathway characteristics, and threat actor behavioral patterns - into a unified risk calculation and update these inputs based on changing operational and environmental conditions. By leveraging a DT that continuously updates and learns from linked data, TACCRAB can suggest adaptive mitigation strategies that minimize risk while maintaining operational efficiency. Particularly novel is the platform's approach to decision support, which goes beyond static risk assessment. The DT provides dynamic metrics such as wait times, resource allocation effectiveness, and potential emerging threat scenarios, enabling users to view sophisticated, relevant what-if simulations and optimize checkpoint operations in near real-time. The system's architecture allows for generalized application across different screening environments, such as secure facilities, ports of entry, and soft targets, making it a versatile tool for security and operational management. The invention distinguishes itself through its comprehensive integration of predictive modeling, AI-driven pattern discovery, and user-friendly interface design. By combining these elements, TACCRAB transforms complex risk data into actionable insights, supporting decision-makers at various organizational levels - from booth agents making split-second screening decisions to checkpoint managers optimizing the day's resource allocation to strategic planners managing long-term investments.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2023

Developing VSC-HVDC Oscillation Damping Control Constraints in Unit Commitment

High-voltage direct current (HVDC) systems within the existing power grids will play a pivotal role in enabling high share of renewable power integration and transportation electrification. There is a need for transmission planning models to accurately capture the impact of VSC-HVDC oscillation damping control on the system planning and model the constraints in the security constrained unit commitment (SCUC) problem. In this paper, the SCUC problem in a hybrid DC-AC grid considering damping on electromechanical inter-area oscillation is studied. An electromechanical oscillation-driven transmission capability constraints are derived from system swing equation and incorporated into the SCUC. Multiple system damping control scenarios are set based on the extracted plausible bounds of damping coefficient and inertia constant to linearize the nonlinear expressions. The SCUC problem with proposed constraints is tested on the IEEE 73-bus reliability test system (RTS) case via PLEXOS. The impact of the proposed constraints on regional generation, inertia, power flow, annual system cost, and renewable energy curtailment are fully assessed.

damping control↗
DOE OSTI2025

An Advanced Cyber-Physical System Security Testbed for Substation Automation

A Cyber-Physical System (CPS) testbed serves as a powerful platform for testing and validating cyber intrusion detection and mitigation strategies in substations. This study presents the design and development of a CPS testbed that can effectively assess the real-time dynamics of a substation. Cyber attacks exploiting IEC 61850-based SV and GOOSE protocols are demonstrated using the testbed, along with an analysis on attack detection. Realistic timing measurements are obtained, and the time frames for deploying detection and mitigation strategies are evaluated.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Impact of drought on global food security by 2050

Drought is a major driver of crop production loss, threatening global food security as the population rises toward 9 billion by 2050. Using a process-based crop model within an Earth system model, we assess drought-related impacts on maize, soybean, rice, and wheat production at global and country levels. We then develop a food insecurity index combining drought impacts with socio-economic factors. Our results indicate that by 2050, globally averaged drought losses for combined maize, soybean, rice, and wheat production are <2%, though soybean losses reach 3.6%. Despite these small average changes at the global scale, 62 countries experience maximum production losses over 10%, and 24 countries over 20%. Our index identifies regions at greatest risk, including large parts of South America, Africa, Eastern Europe, and Southeast Asia. These results illustrate the need for drought adaptation to mitigate future drought impacts on crop production.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Federated benchmarking of medical artificial intelligence with MedPerf

Medical artificial intelligence (AI) has tremendous potential to advance healthcare by supporting and contributing to the evidence-based practice of medicine, personalizing patient treatment, reducing costs, and improving both healthcare provider and patient experience. Unlocking this potential requires systematic, quantitative evaluation of the performance of medical AI models on large-scale, heterogeneous data capturing diverse patient populations. Here, to meet this need, we introduce MedPerf, an open platform for benchmarking AI models in the medical domain. MedPerf focuses on enabling federated evaluation of AI models, by securely distributing them to different facilities, such as healthcare organizations. This process of bringing the model to the data empowers each facility to assess and verify the performance of AI models in an efficient and human-supervised process, while prioritizing privacy. We describe the current challenges healthcare and AI communities face, the need for an open platform, the design philosophy of MedPerf, its current implementation status and real-world deployment, our roadmap and, importantly, the use of MedPerf with multiple international institutions within cloud-based technology and on-premises scenarios. Finally, we welcome new contributions by researchers and organizations to further strengthen MedPerf as an open benchmarking platform.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Digital Assurance for High Consequence Systems: 2024 Mission Campaign White Paper

This Sandia National Laboratories Mission Campaign (MC) seeks to create the technical basis that allows national leaders to efficiently assess and manage the digital assurance of high consequence systems. We will call for transformative research that enables efficient (1) development of provably secure systems and secure integration of untrusted products, (2) intelligent threat mitigation, and (3) digital risk-informed engineering trade-offs. Ultimately, this MC will impact multiple national security missions; it will develop an informed Digital Assurance for High Consequence Systems (DAHCS) community and expand Sandia partnerships to build this national capability.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Reassessment of PHDS Fulcrum40h High Purity Germanium (HPGe) Detector System Performance

This report presents a comprehensive evaluation of the updated PHDS Fulcrum40h High Purity Germanium (HPGe) detector system, benchmarking its performance, usability, and software capabilities against the current National Nuclear Security Administration (NNSA) Nuclear Emergency Support Team (NEST) HPGe Detector System Requirements Document. Systematic measurements were conducted using a single Fulcrum40h detector to assess key parameters including gamma efficiency and resolution, neutron detection efficiency, gamma pulse-pileup response, and gamma-to-neutron crosstalk. The Fulcrum40h system, acquired in August 2022, has undergone recent updates by PHDS to address deficiencies identified following the initial NEST requirements release. The results provide critical insights into the detector’s operational capabilities and compliance with NNSA NEST standards.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

Assessing the impact of demand response on peak demand in a developing country: The case of Ghana

Peak demand on electricity grids is a growing problem that increases costs and risks to supply security. Residential sector loads often contribute significantly to seasonal and daily peak demand. Demand response refers to consumer actions that change the utility load profile in a way that reduces costs or improves grid security by applying price signals and automated load shedding technologies. The methodologies that are used to achieve demand response can hardly be applicable in developing countries. Peak pricing of electricity, for instance, can hardly be implemented in many developing countries as high prices would disproportionately affect the many low-income households who do not have the capacity to take action to avoid paying high peak prices. This study aims to develop demand response methodology that can be applied in developing countries to achieve residential peak demand reduction. We use a consumer preference survey to develop a methodology suitable for developing countries. The method of diversified demand is used with energy audit and monitored data to estimate the potential peak load reduction and its cost-effectiveness for Ghana. Results show that peak reduction of 15-210 MW is expected by 2040 with a positive return on investment of 2-22% for all designed scenarios.

Diawuo, FA↗
DOE OSTI2022

Electric Grid Supply Chain Review: Large Power Transformers and High Voltage Direct Current Systems

The report “America’s Strategy to Secure the Supply Chain for a Robust Clean Energy Transition” lays out the challenges and opportunities faced by the United States in the energy supply chain as well as the federal government plans to address these challenges and opportunities. It is accompanied by several issue-specific deep dive assessments, including this one, in response to Executive Order 14017 “America’s Supply Chains,” which directs the Secretary of Energy to submit a report on supply chains for the energy sector industrial base. The Executive Order is helping the federal government to build more secure and diverse U.S. supply chains, including energy supply chains. The need to modernize and increase the capacity of the U.S. power grid is increasing due to growing population, aging infrastructure, grid resilience requirements, operational flexibility needs, and a growing portfolio of renewable energy. As part of the Paris Climate Agreement the United States has committed to reducing its net greenhouse gas emissions by 50 to 52 percent below 2005 levels in 2030 and has set a goal of 100 percent carbon pollution free electricity by 2035 (The United States of America Nationally Determined Contribution, 2021). Meeting these targets will require a significant expansion of the power system to integrate a large amount of new renewable resources (United States Department of State & United States Executive Office of the President, 2021). However, many critical components supporting the power grid have limited to no domestic manufacturing capacity and face complex challenges in supporting a rapid expansion of the grid to meet multiple objectives, including decarbonization goals. This report focuses on two key grid components: large power transformers (LPTs) and high-voltage direct current (HVDC) transmission.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

West Virginia University Industrial Assessment Center (Final Progress Report)

The Industrial Assessment Center at West Virginia University has been successful in workforce development, and in generation of energy savings for manufacturing facilities during the period 2016 to 2021. Graduate and undergraduate students have benefited from energy assessment experience and most of them have found good positions as energy engineers and analysts in the industrial sector. Several peer reviewed research papers in archival journals as well as conference papers on the topic of energy engineering and assessment have been published. The implemented energy savings for manufacturing facilities have been significant in the areas of lighting, compressed air, process heating, steam, HVAC, chillers and cooling towers, and motors. In addition, water use reduction, smart manufacturing applications to save energy, cyber security evaluation, energy management, productivity improvements and waste reduction opportunities that lead to energy intensity reductions have been explored. The students have obtained an opportunity to interact with energy efficiency and productivity improvement professionals at various conferences and workshops and their research has generated important results. In summary, the West Virginia University Industrial Assessment Center (WVU-IAC) has fulfilled its mission in regard to workforce development, energy efficiency for manufacturing facilities, and laid a strong platform enhancing sustainability through reductions in carbon emissions achieved through energy efficiency and energy management initiatives and reductions in water usage and waste reduction. During the project period (2016-2021) the WVU-IAC has made numerous energy efficiency, water use reduction, waste reduction, and productivity improvement recommendations, a significant number of them having been implemented by the manufacturing facilities. The research adds significant understanding to the area of energy efficiency, water and waste reduction, and productivity improvement. The technical effectiveness and economic feasibility of the methods and techniques investigated and demonstrated through this project have been exemplary, resulting in significant recommended and implemented resource savings and reductions in carbon emissions. The project has been of significant benefit to the public owing to replication of results within the industrial sector, thus reducing operating costs for businesses that result in increase of growth and employment, as well as community benefits in terms of reductions in carbon emissions.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS2023

Risks of Synchronized Low Yields Are Underestimated in Climate and Crop Model Projections

Simultaneous harvest failures across major crop-producing regions are a threat to global food security. Concurrent weather extremes driven by a strongly meandering jet stream could trigger such events, but so far this has not been quantified. Specifically, the ability of state-of-the art crop and climate models to adequately reproduce such high impact events is a crucial component for estimating risks to global food security. Here we find an increased likelihood of concurrent low yields during summers featuring meandering jets in observations and models. While climate models accurately simulate atmospheric patterns, associated surface weather anomalies and negative effects on crop responses are mostly underestimated in bias-adjusted simulations. Given the identified model biases, future assessments of regional and concurrent crop losses from meandering jet states remain highly uncertain. Our results suggest that model-blind spots for such high-impact but deeply-uncertain hazards have to be anticipated and accounted for in meaningful climate risk assessments.

Atmospheric dynamics↗
DOE OSTI2021

Factors Determining Commercially Optimal Development Strategies for CO 2 Storage With and Without CO 2 -EOR

This report is a draft white paper on the factors determining commercially optimal development strategies for CO 2 storage with and without CO 2 -EOR. The draft report provides a summary of accomplishments during the first budget period of the Southeast Offshore Storage Resource Assessment for the Gulf of Mexico (SECARB Offshore GOM) project. It also identifies “Next Steps” to be undertaken during Budget Period II. A final white paper will be prepared at the end of Budget Period II. The goal of this draft white paper is to expand the knowledge base required for commercially viable, secure, longterm, large-scale carbon dioxide (CO 2 ) subsea storage in the U.S. Gulf of Mexico (GOM), both with and without enhanced hydrocarbon recovery. This effort supports the U.S. Department of Energy’s (DOE) long-term objective of ensuring a comprehensive assessment of the potential for offshore CO 2 subsea storage in the GOM. The groundwork that has been completed in the draft white paper advanced by expanding the membership of the Southern States Energy Board’s (SSEB) existing Southeast Offshore Storage Resource Assessment (DE-FE0026082) GOM government-industry partnership during the next budget period. Further, the team plans to consult with U.S. federal and state agencies to develop recommendations to remove barriers and streamline the regulatory process to encourage subsea CO 2 storage with or without enhanced hydrocarbon recovery.

02 PETROLEUM↗
NASA NTRS2003

Environmental Assessment for the NASA First Response Facility

NASA intends to construct a First Response Facility for integrated emergency response and health management. This facility will consolidate the Stennis Space Center fire department, medical clinic, security operations, emergency operations and the energy management and control center. The alternative considered is the "No Action Alternative". The proposed action will correct existing operational weaknesses and enhance capabilities to respond to medical emergencies and mitigate any other possible threats. Environmental impacts include are emissions, wetlands disturbance, solid waste generation, and storm water control.

Kennedy, Carolyn↗
DOE OSTI2025

VA EDH Advanced Software Pipeline Framework Report: Enhancing Automation and Scalability

The VA Environmental Determinants of Health (EDH) Advanced Software Pipeline Framework is designed to enhance the efficiency, scalability, and security of geospatial data processing workflows. This framework integrates modern data orchestration and containerization technologies, including Prefect for workflow automation, Docker for containerization, and PostgreSQL/PostGIS for geospatial data storage and analysis. It ensures standardized, reproducible, and automated data processing, supporting VA objectives related to substance use risk assessment and recovery research. The pipeline addresses key scalability and performance challenges through horizontal and vertical scaling, high-performance computing (HPC) integration, parallel processing, task caching, and dynamic resource allocation. These optimizations improve throughput and reduce latency, allowing the system to efficiently manage large and complex datasets. Additionally, security and compliance measures—such as data encryption (SSL), Role-Based Access Control (RBAC), and adherence to GDPR and HIPAA standards—safeguard sensitive information throughout data transmission and storage. A key implementation of this framework includes the automation of shelter list geolocation workflows, ensuring that up-to-date data is readily available for VA decision-making. Lessons learned from this project include the transition from in-memory processing to incremental storage writes, improving resource management and reliability. Future enhancements aim to expand automation, integrate AI-driven anomaly detection, and incorporate high-performance computing resources. This framework provides a scalable, secure, and adaptable solution for managing geospatial datasets, reinforcing the VA’s ability to support clinical and strategic initiatives through data-driven decision-making.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

When ChatGPT Meets Vulnerability Management: The Good, the Bad, and the Ugly

Vulnerability management is a very challenging and time-consuming task. For many organizations, security operators need to learn about the properties of vulnerabilities to prioritize and mitigate them. Due to the lack of automated tools for vulnerability assessment, operators usually manually search for and read related information from sources online. Recent advances in large language models, like ChatGPT, open up an opportunity for time savings and may prompt operators to use these models as vulnerability information sources. In this work, we evaluate the ability of ChatGPT and several of its siblings to accurately answer user questions about vulnerability properties as well as to provide information for how to mitigate a vulnerability. We also explore their summarization capabilities when multiple vulnerability advisory documents are provided. We find that the models perform poorly on information retrieval tasks, but they perform quite well on summarization.

McClanahan, Kylie↗