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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 OSTI2024

Risk Analysis for Remote Operation of Microreactors

Microreactors are a subset of advanced nuclear reactors that can be factory fabricated, transportable, and self-regulating. They have the potential to be used in microgrids, rural and remote areas, or emergency response applications, replacing fossil fuel sources like diesel generators and enabling sustainable energy generation. In order to make microreactor operation cost-effective, it is likely that remote communications will be needed to reduce the number of personnel required to be on site. While remote operation of energy generation and other industrial control systems is common in other industries, it is not yet adopted in the nuclear community and has many perceived and actual risks. In this paper, the severity of the risks introduced by remote operations for microreactors are explored. The primary changes in the operations involve the addition of a remote communications network and a certification system for data and controls. These changes lend themselves to considerations of cyber risks, whether unintentional or adversarial, but the assessment considers not just cyber risks introduced, but also how physical and human factors-based risks will impact the remote operations system and change the overall risk profile. This initial assessment indicates that there are standard cyber and mitigation measures that can be put in place so the risk of doing remote operations does not dramatically increase compared to local operations. This evaluation is a critical step in the process of evaluating if remote operations of microreactors is a suitable solution to meet future sustainable grid needs

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2026

Statistical Uncertainty of Inhalation Dose Coefficients in Consequence Management: Propagated Dose Uncertainty in ICRP 66 Human Respiratory Tract Model

Reference inhalation dose models rely on deterministic biokinetics and reference computational phantoms, limiting their applicability to the variability present in population-specific exposures encountered in emergency response scenarios. Here, this study introduces REDCAL, a Python-based computational framework developed to propagate uncertainty in inhalation dose coefficients using the International Commission on Radiological Protection (ICRP) Publication 66 Human Respiratory Tract Model. REDCAL integrates ICRP deposition and clearance models, systemic biokinetics, and governing physics principles, and leverages Sandia National Laboratories’ Dakota toolkit for uncertainty quantification via Latin Hypercube Sampling. REDCAL was validated against DCAL, with biokinetic retention results differing by less than 1% and effective dose coefficients by less than 2% across all tested radionuclides. Stochastic sampling introduced variability in dose coefficients, with geometric standard deviations (GSD) in committed effective dose coefficients (CEDC) ranging from 1.0 to 1.5, based on lognormal distribution fits. Analysis demonstrated that variations in the activity median aerodynamic diameter (AMAD) notably influenced the computed CEDC values. Smaller particles (<1 µm) increased doses by 20–30% due to deeper lung deposition and prolonged retention for alpha emitting radionuclides, such as 241 Am and 239 Pu. Radionuclides with fast clearance, such as 133 I, demonstrated a dose reduction exceeding 50%, as AMAD increased beyond 5 µm due to upper airway deposition and rapid mucociliary clearance. The greatest GSD among the radionuclides reported in this study was for 241 Am. In most cases, the largest GSDs in the CEDC were associated with larger particle sizes, an expected outcome, as ICRP Publication 66 defines GSD in particle size as a function of AMAD, resulting in an extended tail of the lognormal distribution. The findings support improved inhalation dose assessments and enhance consequence management strategies for the U.S. Federal Radiological Monitoring and Assessment Center by quantifying uncertainty in dose coefficients and strengthening decision-making for emergency response scenarios.

Biokinetic Modeling↗
DOE OSTI2025

Electromagnetic response and emergent topological orders in transition metal dichalcogenide MoTe 2 bilayers

Twisted bilayer transition metal dichalcogenides, such as MoTe 2 , provide a versatile platform for exploring correlated topological phases. This work investigates the interplay between perpendicular magnetic and electric fields in tuning the electronic structure and emergent topological orders of twisted bilayer MoTe 2 (t-MoTe 2 ) across two distinct regimes: a low-twist-angle phase (θ ≈ 2.1°) hosting multiple Chern bands of identical Chern numbers per valley, and a higher-angle phase (θ ≈ 3.89°) featuring Haldane-like bands with opposite Chern numbers. Using a continuum model incorporating moiré potentials up to second harmonics, we compute the Hofstadter fractal spectra under applied fields, revealing Landau fan structures and magnetic-flux-dependent band topology. These fractal spectra are useful in studying emergent topological orders in terms of the composite fermion picture, where the statistical Chern-Simons flux is approximated as a uniform gauge field. We demonstrate that the system hosts both Jain-sequence fractional Chern insulators (FCIs) and non-Jain fractal FCIs with higher Chern numbers. As a result, the electric field suppresses composite fermion gaps and induces topological quantum phase transitions. Furthermore, our analysis extends to valley-contrasting flux attachment, proposing pathways to describe fractional quantum spin Hall states.

Anyons↗
DOE OSTI2025

Consequence analyses of sabotage-induced radiological releases in high-temperature helium-cooled prismatic microreactors

Here, this study analyzes the radiological dose consequences of sabotage-induced accidents at three high-temperature helium-cooled prismatic microreactors (HTPMs) with thermal power ratings of 1, 10, and 50 MWt. Each HTPM employs uranium oxycarbide tristructural isotropic fuel enriched to 19.75 wt% high-assay low-enriched uranium. Simulations were conducted to estimate reactor core inventory at the point of fuel discharge––when the effective multiplication factor reduced to less than 1––representing peak radionuclide inventory. Postulated sabotage scenarios leading to reactor shutdown were analyzed at two intervals: immediately post-shutdown (0 h) and 3 days after shutdown using the SCALE code for radionuclide inventories and the RASCAL tool for dose consequences. Results show that although HTPMs benefit from inherent safety features and robust fuel design, radiological consequences scale with reactor power because of increased source term inventories. Smaller microreactors exhibited proportionally lower dose consequences. To support the economic and regulatory feasibility of microreactor deployment, this study emphasizes the value of a risk-informed, performance-based approach, as supported by regulations like 10 CFR Parts 100 and 53 in the United States. Microreactor developers should perform site-specific assessments of potential sabotage or low-probability, high-consequence events, especially when considering minimal on-site or full off-site emergency response.

Consequence↗
DOE OSTI2025

Consequence analyses of sabotage-induced radiological releases in sodium-cooled fast microreactors

Analysis of three sodium-cooled fast microreactors (SFMs) with thermal powers of 10, 30, and 50 MWt showed that smaller reactors result in lower radiological consequences during a postulated sabotage-induced event because of their reduced core inventory. All SFMs used U-10Zr metal fuel enriched to 15 wt% high-assay low-enriched uranium and operated until their respective effective multiplication factor (k eff ) reduced to less than 1 or until the end of their operational lifespan. Sabotage scenarios were simulated at this point, when the fuel inventory within the core contains the highest-level of radioactivity. Radionuclide core inventories were calculated using the SCALE code at shutdown and 3 days post-shutdown. Dose consequence analyses were performed for three sabotage scenarios using the RASCAL tool. As microreactor developers plan for minimal on-site or complete off-site emergency response, it remains essential to evaluate their physical protection needs and potential hazards, including assessing postulated sabotage-induced events that could become more relevant. SFM licensees should identify a credible worst-case, major accident, estimate release source terms, and perform dose consequence analyses to evaluate site-specific physical protection measures. In conclusion, this recommendation supports a risk-informed, performance-based approach, aligning with applicable regulatory requirements, i.e., 10 CFR Parts 100 and 53 rulemaking in the United States.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2025

LandScan Global 30 Arcsecond Annual Global Gridded Population Datasets from 2000 to 2022

Abstract Oak Ridge National Laboratory (ORNL) annually develops the LandScan Global (LSG) dataset, a 30 arcsecond global gridded population dataset representing global ambient human population distribution. This multivariable dasymetric model disaggregates census counts within administrative boundaries using ancillary data. Each country’s distribution reflects cultural and socioeconomic patterns; manual validations yield a unique global dataset for assessing populations at risk. For over two decades, LSG has been a standard for estimating populations at risk, aiding U.S. federal government, academia and humanitarian organizations. During disasters such as the 2004 Indian Ocean tsunami and the 2010 Haiti earthquake and geopolitical crises such as the Syrian civil war and the 2022 Russian invasion of Ukraine, LSG supported scientific and operational communities in emergency response and recovery. In 2022, LSG datasets from 2000 onward were made publicly available through ORNL’s LandScan Portal. This data descriptor details our methodology and the application of geospatial science and machine learning to geographic and demographic data, highlighting uses in urban resiliency, emergency management, disaster response, and human health and security.

Science & Technology - Other Topics↗
DOE OSTI2024

Evaluating Liquid Waste Transfers and their Impacts to the SRS Tank Farm to Support Operations and Closure

The Liquid Waste (LW) contractor at the Savannah River Site, Savannah River Mission Completion (SRMC), supports the storage, processing, and safe disposition of legacy, radioactive liquid waste. The LW Tank Farms contain approximately 127 million liters (33.5 million gallons) of liquid waste within 43 active, underground waste tanks. To meet mission critical milestones for the closure of waste tanks and processing of 34 million liters (9 million gallons) of salt waste per year by the LW Salt Waste Processing Facility (SWPF), an increase in Tank Farm operations, including waste tank transfers, is required. Waste is compiled in salt and sludge batches in the Tank Farms and transferred to SWPF and the Defense Waste Processing Facility (DWPF) for treatment. All waste tank transfers, such as waste removal and batch compilation transfers, must be pre-evaluated to ensure Documented Safety Analysis (DSA) requirements are met via Evaluated Transfer Approval Forms (ETAFs). Facility conditions and configurations may change as a result of a waste transfer. These changes must be reflected in the Tank Farms Emergency Response Datasheet (ERD), which contains data utilized for operation and emergency situations.

Peterson, Shelby R.↗
DOE OSTI2024

Clean Energy Cybersecurity Accelerator: Cohort 2 - runZero Public Report

The U.S. Department of Energy (DOE) Office of Cybersecurity, Energy Security, and Emergency Response (CESER) sponsors the Clean Energy Cybersecurity Accelerator™ (CECA) to expedite the deployment of emerging security technologies that address the most urgent security concerns facing modern and future electric grids. CECA Cohort 2 assessed solutions focused on hidden risks due to incomplete system visibility and device security and configuration. Improving visibility can be achieved through operational technology (OT) asset identification solutions, including capabilities like automatic discovery, vulnerability reporting, and configuration monitoring. Solutions that monitor and identify assets in information technology (IT) networks in other domains are widely used; however, there is far less adoption of monitoring solutions for operational technology environments. Wider adoption may increase with increased confidence in the ability for these solutions to understand and respond to the specific requirements of OT environments. CECA Cohort 2 evaluated the active and passive asset discovery capabilities of market-ready solutions, documented and analyzed results, and identified gaps in functionality or capabilities. This report and describes how these results can help advance the adoption of these and similar solutions in the electric sector.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

Cyber Labeling for Energy Industrial IoT

The U.S. Department of Energy’s (DOE) Office of Cybersecurity, Energy Security and Emergency Response (CESER), at the request of the Deputy National Security Advisor for Cyber and Emerging Technologies, Anne Neuberger, initiated research in 2023 to develop a cybersecurity labeling proof-of-concept for energy products to expand on the Federal Communications Commission’s (FCC) proposed U.S. Cyber Trust Mark program. DOE mobilized researchers from six National Laboratories to develop and gather feedback on a proof-of concept label for solar inverters and smart meters, which serve as representative products for market-facing energy sector Industrial Internet of Things (IIoT). This report details the research team’s process across two phases and the resulting findings, which include challenges facing cyber labeling programs and recommendations to implement an expanded IIoT cyber labeling program in the U.S.

32 - ENERGY CONSERVATION, CONSUMPTION, AND UTILIZA↗
DOE OSTI2025

Natural Hazard Forecast Alert Grid Risk System

Weather events cause most power outages. Often, we even get notifications on our phones to take cover or be prepared for an imminent event. If electric grid utilities had a similar warning that also included probable scenarios and the equipment involved, they could prepare and minimize the effects. Idaho National Laboratory had a project with the U.S. Department of Energy’s Cybersecurity, Energy Security, and Emergency Response program to develop a grid alert application that receives messages from the existing emergency alert system, filters and determines components possibly affected by the emergency event, calculates probable scenarios using MASTERRI (Modeling And Simulation for Targeted Reliability and Resilience Improvement). For high-risk events, the application can then send alert links to subscribed electric distribution utility operations staff to allow them to see and evaluate the scenarios and the impact in a web based interactive map tool. This proof of concept application used data from utilities and organizations, such as the international regulatory body North American Electric Reliability Corporation, which have complied historical failure data of elements that comprise the U.S. electric grid. Nominal failure rates are obtained from this data. To make this tool possible, estimated failure rates were calculated for different component types given the alert type, severity, and location. Historic weather-related grid element failures were correlated with historic weather events from the Integrated Public Alert & Warning System. These correlated events and failures are used along with Bayesian updates from the historical norms to provide a modified failure rate for grid elements in the alert areas and calculate probable scenarios. Working with an industry collaborator, actual grid models and data were used for demonstration cases. This report outlines the work performed for this project.

24 - POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Clean Energy Cybersecurity Accelerator: Cohort 2 - Asimily Public Report

The U.S. Department of Energy (DOE) Office of Cybersecurity, Energy Security, and Emergency Response (CESER) sponsors the Clean Energy Cybersecurity Accelerator (TM) (CECA) to expedite the deployment of emerging security technologies that address the most urgent security concerns facing modern and future electric grids. CECA Cohort 2 assessed solutions focused on hidden risks due to incomplete system visibility and device security and configuration. Improving visibility can be achieved through operational technology (OT) asset identification solutions, including capabilities like automatic discovery, vulnerability reporting, and configuration monitoring. Solutions that monitor and identify assets in information technology (IT) networks in other domains are widely used; however, there is far less adoption of monitoring solutions for operational technology environments. Wider adoption may increase with increased confidence in the ability for these solutions to understand and respond to the specific requirements of OT environments. CECA Cohort 2 evaluated the active and passive asset discovery capabilities of market-ready solutions, documented and analyzed results, and identified gaps in functionality or capabilities. This report and describes how these results can help advance the adoption of these and similar solutions in the electric sector.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Correlation Between Weather Alerts and Grid Component Failures for Grid Alert

Weather events cause most grid failures. Often, we even get notifications on our phones to take cover or be prepared for an imminent event. If electric grid utilities had a similar warning that also included probable scenarios and the equipment involved, they could prepare and minimize the effects. Recent research at Idaho National Laboratory into electric grid risk analysis methods resulted in a tool that allows for the development of the most likely scenarios given failure probabilities of grid components. INL has a project with the U.S. Department of Energy’s Cybersecurity, Energy Security, and Emergency Response (CESER) program to develop a Grid Alert application that receives messages from the existing emergency alert system, filters and determines components possibly affected by the emergency event, calculates probable scenarios uses MASTERRI and then notifies the utility if there is significant risk. Historical failure data of elements that comprise the U.S. electric grid have been compiled by utilities and organizations such as the international regulatory body North American Electric Reliability Corporation (NERC). Nominal failure rates are obtained from this data. To make this tool possible, estimated failure rates are needed for different component types given the alert type, severity, and location. Historic weather-related grid element failures are correlated with historic weather events from Integrated Public Alert & Warning System (IPAWS). These correlated events and failures are used along with Bayesian updates from the historical norms to provide a modified failure rate for grid elements in the alert areas and calculate probable scenarios. This discusses the Grid Alert project plan but focuses on the data gathered and process used in determining failure rates for possible grid failure scenarios.

24 - POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Cybersecurity for the Operational Technology Environment (CyOTE) (Final Technical Report)

Electric grids have historically been susceptible to both physical attacks and environmental hazards but the implementation of smart grids, remote management, and self-healing networks, has now made the grid vulnerable to cyber attacks. To address risks introduced by routable connectivity, utilities must establish dynamic solutions to identify, protect, detect, respond to, and recover from cyber security threats and vulnerabilities. In response to the evolving threat landscape U.S. Department of Energy-Office of Cybersecurity, Energy Security, and Emergency Response (DOE CESER) initiated the Cybersecurity for the OT Environment (CyOTE) pilot program, a U.S. Department of Energy (DOE) effort designed to leverage U.S. intelligence capabilities to prevent, detect, or mitigate a cyber attack on utility operational technology (OT) networks. As part of the CyOTE pilot, The Southern Company (Southern Company or Southern) researched, evaluated and deployed emerging Commercial off the Shelf (COTS) technologies and cyber security monitoring architectures to provide previously unrealized network visibility and situational awareness through deep packet inspection and data analytics. This Final Scientific/Technical Report documents the objectives, methodology, lessons learned, and results of Southern Company’s participation in the CyOTE pilot from December 2018 to September 2023.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Development of Emergency Vehicle Preemption Strategies on Smart Corridors in a Digital Twin Environment

Emergency Response Vehicles (ERVs), such as firetrucks, ambulances, etc. operate with the purpose of saving lives and mitigating property damage. As such, ERV travel-time reductions may result in significant benefits to the community. A common strategy to improve travel times is Emergency Vehicle Preemption (EVP). EVP seeks to reduce ERV delays by providing the right-of-way to ERVs as they approach an intersection. This study proposes a new Dynamic Preemption strategy that determines the need for preemption prior to the ERV reaching the vicinity of the intersection, utilizing real-time data streams. This paper evaluates the effectiveness of some existing and proposed preempt control strategies using a digital twin testbed consisting of a series of signalized intersections on an urban arterial in Georgia. The best EVP strategy maximizes the improvement in ERV travel time while minimizing the adverse effect of preemption on the traffic in conflicting directions. Therefore, this study evaluates both the positive impact of EVP on the ERV as well as the adverse impact on the cross-street traffic. The study found that the potential exists for significant improvements in ERV travel time with the proposed Dynamic Preemption strategy, with minimal impact to the conflicting traffic. For the simulation corridor there was a 20% reduction in the ERV travel times with the implementation of the Dynamic Preemption strategy, compared to traditional EVP practices.

Roy, Somdut [Georgia Institute of Technology]↗
DOE OSTI2026

Hurricane Helene: Energy Systems Impact and Situational Insights in East Tennessee

This situational report focuses specifically on energy system performance and interdependencies associated with Hurricane Helene’s impacts across East Tennessee. It does not attempt to identify root causes, evaluate broader emergency response structures, or assess agency effectiveness. Rather, it aims to illuminate how energy disruptions intersected with other lifeline services, particularly water, transportation, and communications, and identify the infrastructural and logistical conditions that shaped those outcomes. Where possible, this report seeks to highlight both constraints and successful practices that emerged during the event.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

SURVEILLANCE DETECTION FOR TRANSPORTATION OPERATIONS PERSONNEL TO PREVENT HIJACKING, THEFT, SABOTAGE, AND MALICIOUS SECURITY EVENTS DURING TRANSPORTING NUCLEAR MATERIAL

The secure transportation of high-consequence materials, including nuclear and radiological assets, is a critical global priority in the face of escalating terrorism, security threats, and violent protests targeting these operations. Effective surveillance detection—the ability to identify, assess, and respond to potential threats across a continuum of scenarios—is paramount in addressing these challenges. This paper outlines a phased, multi-tiered training program designed to strengthen the surveillance detection capabilities of organizations responsible for nuclear material transport. The proposed training program adopts a progressive approach, gradually increasing in technical complexity to provide participants with comprehensive knowledge and tools for implementing robust security strategies. It targets a wide spectrum of stakeholders, including competent authorities, regulators, inspectors, shippers, carriers, law enforcement, and emergency response personnel, equipping them to plan, evaluate, and safeguard nuclear material transportation effectively. Each phase of the program emphasizes distinct elements of the surveillance detection continuum and transport security, focusing on critical topics such as threat identification, adversary task timelines, protective methodologies, and attack mitigation strategies. The training framework is anchored in technical exchanges and scenario-driven courses that reflect real-world complexities and challenges. By addressing the surveillance detection continuum comprehensively—from early threat assessment to active countermeasures—the program reinforces global efforts to secure nuclear assets. It aligns with international security objectives and fosters a strong security culture within participating organizations, ensuring personnel are prepared to counter potential threats and maintain the safe, secure movement of these materials. Ultimately, this initiative aims to enhance preparedness, security, and response capabilities, supporting the global mission to safeguard high-consequence materials against evolving threats.

Zineddin, Dr. Z. [ORNL] (ORCID:0009000848740725)↗
DOE OSTI2024

Cybersecurity Operational Research, Experimentation, Innovation, and Integration (COREII)

The Department of Energy’s Cybersecurity, Energy Security, and Emergency Response Office (CESER) has partnered with Idaho National Laboratory (INL) and energy companies to develop COREII. This research initiative aims to align with the national cybersecurity strategy, enhance the resilience of critical energy infrastructure, facilitate efforts to improve grid-enhancing technologies (GET) and major effects from other critical and emerging technologies, and to enable discovery of innovative solutions for emerging cybersecurity challenges

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2025

Machine Learning for Scalable and Optimal Load Shedding Under Power System Contingency

Prompt and effective corrective actions in response to unexpected contingencies are crucial for improving power system resilience and preventing cascading blackouts. The optimal load shedding (OLS) accounting for network limits has the potential to address the diverse system-wide impacts of contingency scenarios as compared to traditional local schemes. However, due to the fast cascading propagation of initial contingencies, real-time OLS solutions are challenging to attain in large systems with high computation and communication needs. In this paper, we propose a decentralized design that leverages offline training of a neural network (NN) model for individual load centers to autonomously construct the OLS solutions from locally available measurements. Our learning-for-OLS approach can greatly reduce the computation and communication needs during online emergency responses, thus preventing the cascading propagation of contingencies for enhanced power grid resilience. Numerical studies on both the IEEE 118-bus system and a synthetic Texas 2000-bus system have demonstrated the efficiency and effectiveness of our scalable OLS learning design for timely power system emergency operations.

24 POWER TRANSMISSION AND DISTRIBUTION↗