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At least 1,423 records · Page 79
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Commercial integration of advanced nuclear energy with Artificial Intelligence (AI): Possible implications

The integration of advanced nuclear technologies (both fission and fusion) with artificial intelligence (AI) presents unprecedented national security challenges and opportunities. As fusion energy approaches commercial viability alongside advanced Small Modular Reactors (SMRs), their integration with AI and Artificial General Intelligence (AGI) systems could fundamentally transform the global energy and AI landscapes — two pillars of national security. This document briefly examines how AI could accelerate nuclear energy development and deployment while altering existing power structures, a lot could be done to deepen the discussions. Simultaneously, it observes how nuclear-powered AI may expedite advances toward AGI and beyond. These issues are deeply interconnected and thus need to be examined as a whole and more comprehensively than what’s being summarized here. For instance, AI-powered autonomous operation of nuclear facilities could reduce human error but introduce new cybersecurity vulnerabilities and uncertainties. Further investigation would also address how AI-enhanced nuclear technologies might complicate proliferation concerns through advanced fuel cycle management, nuclear materials production and safeguard. The strategic advantage gained by first entities achieving successful AI-nuclear integration could reshape global and national security framework. Timely analysis of these implications may be crucial for policymakers seeking to harness these technologies' benefits while effectively mitigating their potential risks.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Non-stationary precipitation design standards for stormwater infrastructure modernization at USAF installations

The resilience of defense infrastructure systems to a changing climate is critical for national security. Climate induced recurrent flooding is already impacting over 20 U.S. Air Force installations, underscoring the urgency of revisiting precipitation standards and stormwater infrastructure design. Despite growing scientific knowledge and an expanding set of tools for updating outdated precipitation standards based on the assumption of climate stationarity, the adoption of climate informed analyses remain limited in practice. This study utilizes an existing framework to update Intensity (or Depth)-Duration-Frequency (DDF) curves using an ensemble of future climate projections. Change factors in precipitation estimates are derived and applied to six USAF installations across the U.S. The analysis is further extended to evaluate the implications of climate-informed DDFs on stormwater infrastructure performance and flood analysis at Tyndall AFB. Results indicate that the current design precipitation estimates are likely to become obsolete in all six USAF bases by the end of the century. The wide range of change factors across 32 GCM ensembles highlights the need to integrate uncertainty and evolving scientific data into infrastructure planning. The study also finds that the impacts of a changing climate vary spatially and temporally, emphasizing the value of localized analysis for infrastructure decision-making. The work advances ongoing DoD and societal efforts to implement adaptation strategies aimed at enhancing infrastructure resilience.

Intensity-duration-frequency curves↗
DOE OSTI2021

Survey of Cyber Risk Analysis Techniques for Use in the Nuclear Industry

Using traditional probabilistic risk analysis methods for severe accident safety risk management on non-digital systems, structures, and components at nuclear power plants is well-established. In contrast, cyber risk analysis of digital assets is still an immature field with unproven techniques due, in part, to the continuously changing threat environment and the challenge of digital assets failing in unexpected ways. As the nuclear fleet continues to adopt digital instrumentation and control systems, it is increasingly important to have effective and efficient cyber risk analysis techniques to support risk management decisions, such as risk elimination by system redesign or risk mitigation by implementation of prioritized security controls. To understand the state of the art in cyber risk analysis for future research, we surveyed 36 publications across ten application domains. We describe our survey methodology and rate each technique based upon scope, adoptability, and repeatability. In this work, we examine the unique constraints of the nuclear industry and outline the strengths and weaknesses of using the cyber risk analysis techniques in the industry, highlighting gaps with current techniques. We also discuss challenges and potential research directions for advancing the science for both existing and new advanced reactors.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Sparse-Data Deep Learning Strategies for Radiographic Non-Destructive Testing

Radiography is an imaging technique used in a variety of applications, such as medical diagnosis, airport security, and nondestructive testing. We present a deep learning system for extracting information from radiographic images. We perform various prediction tasks using our system, including material classification and regression on the dimensions of a given object that is being radiographed. Our system is designed to address the sparse-data issue for radiographic nondestructive testing applications. It uses a radiographic simulation tool for synthetic data augmentation, and it uses transfer learning with a pre-trained convolutional neural network model. Using this system, our preliminary results indicate that the object geometry regression task saw an improvement of 70% in the R-squared value when using a multi-regime model. In addition, we increase the performance of the object material classification tasks by utilizing data from different imaging systems. In particular, using neutron imaging improved the material classification accuracy by 20% when compared to x-ray imaging.

convolutional neural networks↗
DOE OSTI2021

Bioeconomic benefits of managing fishing effort in a coexisting small- and large-scale fishery game

Abstract Fishing systems provide employment, income generation, poverty alleviation, and food security. The coexistence of small-scale fisheries (SSFs) and large-scale fisheries (LSFs) increases management complexity. Management actions have ecological and social implications that must be addressed carefully. We applied a bioeconomic game-theoretical model to the four-gear mullet fishery in southern Brazil—one industrial LSF (purse seine) and three artisanal SSFs (gillnet, beach seine, and drift net). All fishing gears target adult individuals during mullet's reproductive migration. First, we explored whether the current fishing efforts of all fishing gears could persist over time. Second, we investigated their interactions through a non-cooperative game. Finally, we studied the response of these interactions when fishing effort was restricted. We found that when the current fishing effort was maintained, the stock reduced to 26.4% of its capacity in 25 years. In addition, under non-cooperation, the traditional beach seine fleet exited the fishery. Interestingly, the constrained scenario had a coexistence output with increasing values for the final stock size and the per capita labour income, suggesting that limiting fishing effort can maintain all fishing gears in the fishery with social and ecological benefits.

de Azevedo, Eric Zettermann Dias (ORCID:0000000323↗
DOE OSTI2020

Secure Design and Development Cyber Security Capability Maturity Model” (SD2-CM2)

The "Secure Design and Development Cyber Security Capability Maturity Model" (SD2-CM2) allows electrical system managers to assess the maturity of their cybersecurity systems, including designs reflecting internet of things devices (IOT). The content provides best practices in the field and users can assess the level of their designs. Modules are "Content" and "Infrastructure"

Gourisetti, Sri Nikhil Gupta↗
DOE OSTI2020

49109 UTrain Delta Training

Upon successful completion of this training, the learner will understand how the upgraded interface, functional, and security features of the Laboratory's UTrain Learning Management System impacts administrative users.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2020

Extreme Scale Infrasound Inversion and Prediction for Weather Characterization and Acute Event Detection

Accurate and timely weather predictions are critical to many aspects of society with a profound impact on our economy, general well-being, and national security. In particular, our ability to forecast severe weather systems is necessary to avoid injuries and fatalities, but also important to minimize infrastructure damage and maximize mitigation strategies. The weather community has developed a range of sophisticated numerical models that are executed at various spatial and temporal scales in an attempt to issue global, regional, and local forecasts in pseudo real time. The accuracy however depends on the time period of the forecast, the nonlinearities of the dynamics, and the target spatial resolution. Significant uncertainties plague these predictions including errors in initial conditions, material properties, data, and model approximations. To address these shortcomings, a continuous data collection occurs at an effort level that is even larger than the modeling process. It has been demonstrated that the accuracy of the predictions depends on the quality of the data and is independent to a certain extent on the sophistication of the numerical models. Data assimilation has become one of the more critical steps in the overall weather prediction business and consequently substantial improvements in the quality of the data would have transformational benefits. This paper describes the use of infrasound inversion technology, enabled through exascale computing, that could potentially achieve orders of magnitude improvement in data quality and therefore transform weather predictions with significant impact on many aspects of our society.

58 GEOSCIENCES↗
DOE OSTI2021

Tensor Text-Mining Methods for Malware Identification and Detection, Malware Dynamics Characterization, and Hosts Ranking

Malware is one of the most persistent and costly cyber threats endangering reputation, confidentiality, integrity, and availability for organizations and national security. Consequently, many of the incident detection and prevention systems, and incident responders have begun to utilize machine learning as a helper in the fight against malware and other cyber threats. However, cyber defenders rely on interpretability and generalizability, yet the popular machine learning methods are black-box and often use traditional supervised solutions that do not generalize to novel malware. Therefore, there is a need to improve the existing solutions. At the same time, the majority of the prior research ignored essential evaluation criteria when reporting the results of their methods, which disables the safe reproducibility of the methods in a production environment. Tensor decomposition, on the other hand, enables interpretable unsupervised analysis of the large-scale data for the discovery of hidden patterns. Our findings, performed on real-world and large-scale experiments, show that tensor factorization-based methods yield performance results that surpasses or competes with existing supervised solutions with the added benefit of interpretability and generalizability. With the ability to analyze complex and large-scale data using tensors, we report results that reflect real-world production environments. We propose to develop new game- changing tools for malware identification and characterization that can trace malware evolution, rank the infected or malicious hosts, and streamline the work of incident response teams, malware analysts, and incident detection and prevention systems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

UAS Activity Profile Survey

Commercial vendors, trying to tap into the physical protection of critical infrastructure, are offering nuclear facilities the opportunity to borrow detection counter-unmanned aircraft systems (CUAS) equipment to survey the airspace over and around the facility. However, using one vendor or method of detection (e.g., radio frequency [RF], radar, acoustic, visual) will not necessarily provide a complete airspace profile since no single method can detect all UAS threats. Using several detection technologies, the unmanned aircraft systems (UAS) Team, who supports the U.S. National Nuclear Security Administration (NNSA) Office of International Nuclear Security (INS), would like to offer partners a comprehensive airspace profile of the types and frequency of UAS that fly within and around critical infrastructure. Improved UAS awareness will aid in the risk assessment process.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

A geospatial risk analysis graphical user interface for identifying hazardous chemical emission sources

Background: Performing back trajectory and forward trajectory using the Hybrid Single-Particle Lagrangian Integrated Trajectory Model (HYSPLIT) is a reliable approach for assessing particle transport after release among mid-field atmospheric models. HYSPLIT has an externally facing online interface that allows non-expert users to run the model trajectories without requiring extensive training or programming. However, the existing HYSPLIT interface is limited if simulations have a large amount of meteorological data and timesteps that are not coincident. The objective of this study is to design and develop a more robust tool to rapidly evaluate hazard transport conditions and to perform risk analysis, while still maintaining an intuitive and user-friendly interface. Methods: HYSPLIT calculates forward and backward trajectories of particles based on wind speed, wind direction, and the corresponding location, timestamp, and Pasquill stability classes of the regions of the atmosphere in terms of the wind speed, the amount of solar radiation, and the fractional cloud cover. The computed particle transport trajectories, combined with the online Proton Transfer Reaction-Mass Spectrometry (PTR-MS) data (https://figshare.com/articles/dataset/ARL_Data_from_PROS_station_at_Hanford_site/19993964), can be used to identify and quantify the sources and affected area of the hazardous chemicals’ emission using the potential source distribution function (PSDF). PSDF is an improved statistical function based on the well-known potential source contribution function (PSCF) in establishing the air pollutant source and receptor relationship. Performing this analysis requires a range of meteorological and pollutant concentration measurements to be statistically meaningful. The existing HYSPLIT graphical user interface (GUI) does not easily permit computations of trajectories of a dataset of meteorological data in high temporal frequency. To improve the performance of HYSPLIT computations from a large dataset and enhance risk analysis of the accidental release of material at risk, a geospatial risk analysis tool (GRAT-GUI) is created to allow large data sets to be processed instantaneously and to provide ease of visualization. Results: The GRAT-GUI is a native desktop-based application and can be run in any Windows 10 system without any internet access requirements, thus providing a secure way to process large meteorological datasets even on a standalone computer. GRAT-GUI has features to import, integrate, and convert meteorological data with various formats for hazardous chemical emission source identification and risk analysis as a self-explanatory user interface. The tool is available at https://figshare.com/articles/software/GRAT/19426742.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1990

Smart hands for the EVA retriever

Dexterous, robotic hands are required for the extravehicular activity retriever (EVAR) system being developed by the NASA Johnson Space Center (JSC). These hands, as part of the EVAR system, must be able to grasp objects autonomously and securely which inadvertently separate from the Space Station. Development of the required hands was initiated in 1987. Outlined here are the hand development activities, including design considerations, progress to date, and future plans. Several types of dexterous hands that were evaluated, along with a proximity-sensing capability that was developed to initiate a reflexive, adaptive grasp, are described. The evaluations resulted in the design and fabrication of a 6-degree-of-freedom (DOF) hand that has two fingers and a thumb arranged in an anthropomorphic configuration. Finger joint force and position sensors are included in the design, as well as infrared proximity sensors which allow initiation of the grasp sequence when an object is detected within the grasp envelope.

Hess, Clifford W.↗
NASA NTRS1994

A Motionless Camera

Omniview, a motionless, noiseless, exceptionally versatile camera was developed for NASA as a receiving device for guiding space robots. The system can see in one direction and provide as many as four views simultaneously. Developed by Omniview, Inc. (formerly TRI) under a NASA Small Business Innovation Research (SBIR) grant, the system's image transformation electronics produce a real-time image from anywhere within a hemispherical field. Lens distortion is removed, and a corrected "flat" view appears on a monitor. Key elements are a high resolution charge coupled device (CCD), image correction circuitry and a microcomputer for image processing. The system can be adapted to existing installations. Applications include security and surveillance, teleconferencing, imaging, virtual reality, broadcast video and military operations. Omniview technology is now called IPIX. The company was founded in 1986 as TeleRobotics International, became Omniview in 1995, and changed its name to Interactive Pictures Corporation in 1997.

Source record↗
NASA NTRS2005

Engineering Ultimate Self-Protection in Autonomic Agents for Space Exploration Missions

NASA's Exploration Initiative (EI) will push space exploration missions to the limit. Future missions will be required to be self-managing as well as self-directed, in order to meet the challenges of human and robotic space exploration. We discuss security and self protection in autonomic agent based-systems, and propose the ultimate self-protection mechanism for such systems-self-destruction. Like other metaphors in Autonomic Computing, this is inspired by biological systems, and is the analog of biological apoptosis. Finally, we discus the role it might play in future NASA space exploration missions.

Sterritt, Roy↗
NASA NTRS2003

Future Directions in Space IT

This slide presentation addresses three areas of interest in space and ground information technology domains for NASA (i.e., Deep Space Exploration, National Security and air transportation. It reviews the concept of System Wide Information Management (SWIM) and defines the interest that NASA has in the development of the SWIM concept.

information technology services↗
NASA NTRSDate not supplied

A physician’s working group guides COVID-19 prevention in a mission critical environment

Background A team was assembled at the National Aeronautics and Space Administration’s (NASA) Johnson Space Center (JSC) to help navigate the shifting COVID-19 pandemic. Their goal was to mitigate the impact of COVID on astronauts, other essential personnel, and the human spaceflight program. This team supplemented the JSC Pandemic Incident Response Group, whose function is to set policy for the overall management of JSC’s COVID-19 mitigations for all onsite mission-essential and mission-critical activities, including health policy. Context The first mission to return to Earth from the International Space Station at the start of the pandemic returned when there was limited information about the transmission and prevention of COVID-19. The medical leadership at JSC determined that a dedicated team was required to navigate the uncharted waters of the pandemic. Description of Activities Issues tackled by this panel included: prevention of COVID-19 transmission during altitude, dive, and spacecraft training – activities that require prolonged close contact between multiple individuals who often cannot safely wear face masks; mitigating the risks of domestic and international travel for essential personnel; securing COVID-19 testing from local and foreign hospital systems; acquiring antigen and PCR analyzers for in-house testing; and the development of quarantine policies for crewed spacecraft launches and landings in Kazakhstan and the United States. The panel also provides clinical return-to-work guidance for cases of COVID-19 in essential personnel.

covid↗
DOE OSTI2020

Kraken Imager and Camera Systems

Presentation describes the Kraken imager and camera systems under development for use at the Nevada National Security Site for work conducted by the National Nuclear Security Administration.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗