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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

On-the-fly response function generation method for composite coarse mesh

The hybrid stochastic deterministic transport code COMET, based on the incident response expansion theory, is used to model reactor cores with high fidelity and formidable computational speed. COMET models a reactor core using a library of incident flux response expansion coefficients that are pre computed for all the unique lattice cells (e.g., fuel assemblies, reflector blocks, etc.) in the core. In order to further improve its computational efficiency in pre-calculating the response library a new response function generation method is developed to compute the response functions for the composite coarse meshes made of a smaller set of unique lattices on the fly within the COMET's deterministic transport core sweep. The efficiency is achieved by eliminating a number of unique lattices that can be made up from the reduced set of unique meshes on the fly. The numerical process consists of the following steps. First, the boundary condition on composite coarse mesh boundaries is projected onto the expansion basis to compute the incident flux moments on external surfaces of all the basic (reduced set of unique) coarse meshes. Secondly, the deterministic sweeping solver in COMET is used to converge on the outgoing/incoming flux expansion moments crossing interfaces between the basic coarse meshes. Thirdly, the response functions for the composite coarse meshes are constructed as a superposition on the fly. The new response function generation method was tested on 88 composite coarse meshes consisting of CANDU fuel bundles and moderator blocks. It was found that response functions generated by the new method agree very well with those generated by direct Monte Carlo calculations. The average and maximum relative differences in the surface-to-surface response coefficients computed by the two methods are 0.10% and 0.20%, respectively. Similarly, the average and maximum relative differences in the response fission densities are 0.13% and 0.43%, respectively. These discrepancies are within one standard deviation of the stochastic uncertainties. The new method is five times faster than the original direct Monte Carlo method. The size of the response function library for the new method is five times smaller than that for the original method, leading to significantly less requirement for the computer hard drive space and memory. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2022

NLIT 2022 Axonius Presentation

Axonius, a cybersecurity asset management tool used at INL, provides visibility into users, devices, software, and hardware in use at the lab. This visibility, provided by aggregating data on lab entities from many tools' perspectives, makes incident response, configuration management, and IT operations more capable.

42 ENGINEERING↗
NASA NTRSDate not supplied

Applying Satellite Data to Support Disaster Response and Emergency Management Decision Making

Using the vantage point of space, satellite observations provide information about the Earth that can serve a critical role in building situational awareness and filling in data gaps during disaster response. NASA’s Earth Science Division ( studies the Earth as a system and develops technologies to improve the quality of life here on our home planet. Within NASA ESD, the Disasters Program and its Disasters Response Coordination System (DRCS) aims to advance Earth science data and information to support management decisions that prevent or mitigate the impacts of disasters. Using a whole-of-NASA approach to coordinate and mobilize the Agency’s assets and expertise to provide geospatial information during disasters, this work brings the utility of Earth observation information to emergency management and disaster response and reduces the impacts of disasters on lives and livelihoods .This poster will introduce the utility of satellite and geospatial information to disaster response through examples of recent DRCS incident response activations and highlight the DRCS model that employs a user-centered activation framework beginning with direct requests from responders and ending with after-action assessments that feed lessons learned and process improvements.

Remote Sensing↗
DOE OSTI2022

WPTO Navigator

Protecting hydroelectric plants from incidents that adversely impact their cyber-physical systems presents unique challenges due to the plants’ widely dispersed geographic locations and varied configurations as well as the relative nascent nature of the cyberattacks targeting these facilities. To help hydroelectric plants better respond to and mitigate cybersecurity incidents, this Department of Energy Water Power Technologies Office Navigator aligns the processes within the National Institute of Standards 800-61r2 Computer Security Incident Handling Guide with the emergency actions within the FEMA 64 Emergency Action Plan Framework. This work is to be used at a hydroelectric plant to quickly understand how the plant responds to a cyber incident in relationship to the actions involved in an emergency action plan involving a hydroelectric plant. In addition to this product, there are three other products meant to be distributed to a hydroelectric plant to assist in their cyber incident response and recovery. The first, a report on the processes of building a R&R flip book based on a large set of existing guidance. The second, a handy flip book meant to be distributed to hydroelectric plants to assist them during a cybersecurity incident occurring on a hydroelectic plant. And the third is a comprehensive set of resources to assist an operator in locating appropriate guidance during the recovery process.

13 HYDRO ENERGY↗
NASA NTRS1994

Optimization of two dimensional gratings for very long wavelength quantum well infrared photodetectors

We have performed a detailed study of two-dimensional grating coupling for quantum well infrared photodetectors in the very long wavelength spectral region lambda is approximately 16 - 17 microns. Using calculations based on the modal expansion method we quantitatively explain the double peaked responsivity spectrum. By optimizing the grating parameters we achieve a normal incidence responsivity and detectivity which are three times larger than the 45 deg angle of incidence geometry.

Sarusi, G.↗
DOE OSTI2023

RCT Module 2.13: Radiological Incidents and Emergencies [Slides]

Emergency and incident response planning requires a detailed plan be in place. Each incident may be unique, and no plan can be expected to give an exact solution to every problem; however, a step-by-step approach for responding to a problem will ensure appropriate response.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2025

Advanced Reactor Safeguards & Security Program: Cybersecurity Scenarios

The use of digital control systems and automation in advanced nuclear power systems introduces different types of vulnerabilities compared to legacy (i.e. analog) control systems that cyber adversaries can exploit. These vulnerabilities pose a challenge to reactor operators and cyber operations staff due to the dynamic nature of the event in which a human response or a lack of response can potentially evolve into a worsening plant condition. Using the Department of Homeland Security Cyber and Infrastructure Security Agency’s (CISA) critical infrastructure exercise framework, this document presents several cyber security scenarios typical of digital control systems that could be used in advanced reactor designs. These scenarios can be used in tabletop exercises to evaluate cyber security posture or conduct training on different aspects of cyber security, including detection, threat hunting using indicators of compromise, evaluating incident response, risk mitigation, incident reporting, information sharing and recovery.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRSDate not supplied

Fire Front Detection and Tracking for Autonomous sUAS in STEReO

The Scalable Traffic Management Emergency Response Operations (STEReO) project aims to incorporate unmanned aerial systems (UAS) into wildfire incident response to safely quicken response times, improve operator awareness, and scale-up aircraft operations.Autonomous UAS can be used to relieve human operators of dull, dirty, and dangerous tasks such as checking for re-ignitions and geo-locating fires. To geo-locate fires, the UAS must be able to detect whether a fire is present and also have the necessary information to stamp a location. Furthermore, the UAS should be able to track the fire front to determine the extent of the fire. This study presents a fire front detection and tracking methodology for an autonomous small UAS (sUAS). The methodology is evaluated in simulation.

Autonomous UAV,Wildfire,Detection,Tracking↗
DOE OSTI2023

Canada-US Blended Cyber-Physical Security Exercise (Final Report)

The Canada-US Blended Cyber-Physical Exercise was a successful, first of its kind, multiorganization and multi-laboratory exercise that culminated years of complex system development and planning. The project aimed to answer three driving research questions, (1) How do cyberattacks support malicious acts leading to theft or sabotage [at a nuclear site]? (2) What are aspects of an effective combined cyber-physical response? (3) How to evaluate effectiveness of that response? Which derived the following primary objectives, 1. The May 2023 Cyber-Physical Exercise shall present a cyber-attack scenario that supports malicious acts leading to theft or sabotage. 2. The May 2023 Cyber-Physical Exercise shall define aspects of an effective combined cyber-physical response. 3. Analysis of the May 2023 Cyber-Physical Exercise shall evaluate the effectiveness of the incident response against pre-established exercise evaluation criteria. 4. Analysis of the May 2023 Cyber-Physical Exercise shall assess the effectiveness of the evaluation criteria itself. 5. Exercises shall be performed in a real-life environment. The team believes these objectives were met, and the evidence will be presented in this report. Due to the novelty of the exercise, there were several lessons learned that will be presented in this report.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2026

Validating Protection System Behavior with Machine Learning in a Master State Overseer

As power system protection devices continue the widespread transition from analog to digital, they become increasingly intricate. The internal functions and communication between critical grid components must now be significantly more complex to keep up with the demands of the modern smart grid. This brings increased difficulty in maintenance and monitoring, making it harder to identify potential misoperation, power anomalies, and cyber threats. Such issues are often only pinpointed after an exhaustive and costly post-mortem analysis, when a major outage or damage has already occurred. A solution is needed for validating protection systems as they operate, independently evaluating grid state and confirming whether the protection system is behaving accordingly. As opposed to incident response, this acts as a constant verification mechanism that raises a flag when subtler issues are noticed, catching them earlier and preventing larger incidents. This work presents the implementation of such a system, expanding on the prototype developed by the authors in a previous paper. This is accomplished with a machine learning (ML) system capable of validating the performance of protection systems by classifying anomalous events and characterizing protection system responses based solely on available current and voltage measurements. Additionally, this system is contextualized within a larger, modular Master State awareness Overseer (MSO) framework, responsible for monitoring, analyzing, and managing an electric grid.

24 - POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS2023

Machine Learning Framework for Hazard Extraction and Analysis of Trends (HEAT) in Wildfire Response

This research proposes a natural language processing enabled risk analysis framework, named Hazard Extraction andAnalysis of Trends (HEAT), and applies the framework to the ICS-209-PLUS data set of wildfire incident responseforms. The HEAT framework produces safety- and risk- relevant analyses, consisting of: (1) a set of hazards extractedfrom text data, (2) a primary analysis using hazard-relevant metrics, such as rate and severity, to form an FMEA-styletable and risk matrix, (3) a time series analysis of metric trends, and (4) a secondary analysis examining potentialpredictors for hazards. Results from HEAT provide quantitative risk-relevant information for high-level hazards doc-umented in existing-state operations. Because of the generalizability of the steps and limited data requirements, HEATcan be applied to any dataset containing narrative text, thus providing a framework for data-driven machine learning-enabled quantitative risk analysis across a variety of domains. To demonstrate HEAT in a case study, we apply theframework to the ICS-209-PLUS dataset of wildland fire incident response forms. Hazards identified in wildfire re-sponse arise from environmental conditions, the mission, and the wildland urban interface. The resulting risk matrixidentifies evacuations as high-risk hazards, while all other identified hazards are medium or serious risk.

natural language processing↗
NASA NTRSDate not supplied

Wildfire Emergency Response Hazard Extraction and Analysis of Trends (HEAT) through Natural Language Processing and Time Series

A methodology for Hazard Extraction and Analysis of Trends (HEAT) is proposed and conducted on a data set of wildfire incident response forms, known as ICS-209-PLUS.The HEAT processes: (1) extract a set of hazards from a data set, (2) calculate hazard-relevant metrics in a primary analysis, (3) analyze trends over time in metrics using timeseries, and (4) examine potential explanations for metric trends using a secondary analysis. Hazards are extracted from narrative data in the ICS-209-PLUS based on a framework previously developed by the authors, using natural language processing. Metrics examined for each hazard include operational time to occurrence, rate of occurrence, frequency, and severity. Primary results include a taxonomy of hazards present in the data set with relevant quantitative metrics. The most frequent hazards identified are environmental and include hazardous terrain. Most hazards occur on average between 35-55% containment. Incidents with hazards tend to have a higher average severity score when compared to the average score for all incidents. Time series of the metrics and relevant predictors, including fire characteristics, fire intensity, and operations, are created to facilitate further analysis. Secondary results used to determine which factors best predict hazard frequency include a correlation matrix and regression analysis. These findings are relevant to safety for current, as well as emerging wildfire operations, and are an exploratory first step in developing historical data-driven risk assessment models.

Sequoia R. Andrade↗
DOE OSTI2025

A Software/Hardware Framework for Efficient and Safe Emergency Response in Post-Crash Scenarios of Battery Electric Vehicles

The adoption rate of battery electric vehicles (EVs) is rapidly increasing. Electric vehicles differ significantly from conventional internal combustion engine vehicles and vary widely across different manufacturers. Emergency responders (ERs) and recovery personnel may have less experience with EVs and lack timely access to critical information such as the extent of the stranded energy present, high-voltage safety hazards, and post-crash handling procedures in a user-friendly manner. This paper presents a software/hardware interactive tool named Electric Vehicle Information for Incident Response Solutions (EVIRS) to aid in the quick access to emergency response and recovery information. The current prototype of EVIRS identifies EVs using the VIN or Make, Model, and Year, and offers several useful features for ERs and recovery personnel. These features include integration and easy access to emergency response procedures tailored to an identified EV, vehicle structural schematics, the quick identification of battery pack specifications, and more. For EVs that are not severely damaged, EVIRS can perform calculations to estimate stranded energy in the EV’s battery and discharge time for various power loads using either EV dashboard information or operational data accessed through the CAN interface. Knowledge of this information may be helpful in the post-crash handling, management, and storage of an EV. The functionality and accuracy of EVIRS were demonstrated through laboratory tests using a 2021 Ford Mach-E and associated data acquisition system. The results indicated that when the remaining driving range was used as an input, EVIRS was able to estimate the pack voltage with an error of less than 3 V. Conversely, when pack voltage was used as an input, the estimated state of charge (SOC) error was less than 5% within the range of 30–90% SOC. Additionally, other features, such as retrieving emergency response guides for identified EVs and accessing lessons learned from archived incidents, have been successfully demonstrated through EVIRS for quick access. EVIRS can be a valuable tool for emergency responders and recovery personnel, both in action and during offline training, by providing crucial information related to assessing EV/battery safety risks, appropriate handling, de-energizing, transport, and storage in an integrated and user-friendly manner.

25 ENERGY STORAGE↗
DOE OSTI2022

Radiological Data Assessment Guidance for Emergency Response

This document provides guidance on how to apply data quality practices to measurements and information collected during the response and recovery to a radiological release. The process of applying data quality practices to measurement data is called data assessment. All data quality practices applied during a radiological incident response must balance the rigorous and time-consuming process normally applied to, for example, site decommissioning and decontamination, with the time- and resource-constraints present during emergency response. The guidance in this document presents the application of data quality practices for data assessment in a graded approach, where the recommended rigor increases as the response continues through its phases and as time and resource constraints relax.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Oakland University Cybersecurity Center (Final Scientific/Technical Report)

This report summarizes the outcomes of Award DE-CR0000023, “Oakland University Cybersecurity Center,” a 31-month project funded by the U.S. Department of Energy Office of Cybersecurity, Energy Security, and Emergency Response (CESER). The project addressed cybersecurity risks facing small and medium-sized manufacturers (SMMs) transitioning to Industry 4.0. The project integrated customer discovery, applied research, and cybersecurity training development. A total of 51 cybersecurity assessments identified significant gaps in baseline practices, incident response, and workforce capability. Research efforts produced a scalable mitigation framework tailored to SMM environments, and workforce analysis identified persistent talent gaps. Eight cybersecurity training modules were developed and deployed via Oakland University’s Professional and Continuing Education (PACE) platform. All objectives were completed, with 98.93% federal budget utilization and cost share exceeding requirements. The project establishes a scalable model for strengthening cybersecurity resilience and workforce capacity across U.S. manufacturing supply chains.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS2011

Data Mining of Network Logs

The statement of purpose is to analyze network monitoring logs to support the computer incident response team. Specifically, gain a clear understanding of the Uniform Resource Locator (URL) and its structure, and provide a way to breakdown a URL based on protocol, host name domain name, path, and other attributes. Finally, provide a method to perform data reduction by identifying the different types of advertisements shown on a webpage for incident data analysis. The procedures used for analysis and data reduction will be a computer program which would analyze the URL and identify and advertisement links from the actual content links.

Collazo, Carlimar↗
NASA NTRS2019

Scalable Traffic Management for Emergency Response Operations (STEReO)

The Scalable Traffic Management for Emergency Response Operations (STEReO) project aims to apply various NASA technologies, such as Unmanned Aircraft System (UAS) Traffic Management (UTM) services, onboard-vehicle autonomy, novel approaches to communications and connectivity, and remote/virtual collaboration interfaces to current-day emergency response efforts to natural disasters. Today's emergency response efforts are based on long-standing procedures that are manaul in nature, and could benefit from modernization. In particular, the use of UAS vehicles is limited, primarily due to concerns surrounding dangerous interactions between manned/unmanned operations. STEReO hopes to introduce data exchanges that improve shared situation awareness, reduce manual coordination procedures, enable scalable and high-density air operations, collectivley bringing a positive impact to the incident response. When successful, STEReO technologies will improve efficiency and timeliness of the response and recovery phases of a disaster, resulting in substantial reductions to community harm, and will also accelerate NASA’s development of high-density resilient operations, benefitting other projects relying on increasing levels of autonomy and connectivity. The prepared material provides an overview of the STEReO project, for presentation at the 2019 Convergent Aeronautics Solution (CAS) Showcase event. The CAS showcase brings together all of the current CAS execution activities, highlighting NASA's high-risk investments in aeronautics research.

Mercer, Joey↗
DOE OSTI2023

From Count Rates to Quantifying Isotopic Activities – Field Analysis of Radiation Monitoring Data

The Nevada National Security Site (NNSS) provides a comprehensive bicoastal radiological and nuclear emergency response to United States Department of Energy/National Nuclear Security Administration. A major part of the support is to provide systematic radiological search for lost or stolen sources, Radiological search is a core competency of the NNSS with its origin dating back to nuclear weapons test era. Search operations from multiple platforms is the common thread among the various NNSS assets, which include Aerial Measuring System (AMS), Maritime Support Team (MST), National Capitol Response (NCR), National Search Team (NST) and Radiological Assistance Program (RAP). Information collected and analyzed during search operations add to the actionable intelligence for the law enforcement agencies and provide valuable guidance for the tactical resolution of a nuclear or radiological crisis. Search is an intelligence and situational awareness driven operation and most often called upon during a radiological emergency, however it can be brought into play to thwart a potential threat by providing monitoring and surveillance support. The Office of Nuclear Incident Response (NA-84) serves as the technical leader in responding to and resolving nuclear and radiological threats worldwide and integrates its efforts with other NNSA stakeholders (e.g., NNSA office of Defense Nuclear Non-proliferation NA-22). The response includes expertise in the areas of radiological search, render safe, and consequence management. This article will discuss the methodologies, tools, procedures, and techniques to extract maximum radiological characterization information (isotopic composition, activities for individual isotopes, threat assessment etc.) from field monitoring or Search operation data.

61 RADIATION PROTECTION AND DOSIMETRY↗