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At least 1,279 records · Page 71

Safety Basis Compliant Flexible Operations [Capstone Project]

Compliant nuclear operations must be weighed against the radiological risk to the worker, public, and the environment. This project set out to look at one facility at Los Alamos National Laboratory (LANL or the Laboratory) and compare the risk with the operational restrictions associated with the Technical Safety Requirements (TSRs). The hope was to identify controls that could be reduced or simplified while maintaining compliance with 10 CFR 830, Nuclear Safety Management. This would result in increasing facility operational flexibility and efficiency. Controls were identified to be simplified or eliminated based on risk. This identification was initially envisioned from the perspective of reanalysis of the accident and hazard analysis consequences. Additionally, it was envisioned that fire testing could show that the consequences of a fire are not as dramatic as analyzed. Specific facility controls were identified that cause operational inefficiencies. Based on data collection, two controls were identified for further evaluation. The first control was combustible loading within the waste storage buildings, and the second control is related to the seismic power cutoff switch. In evaluating the combustible loading control, the thought is that the fire suppression system (FSS) provides adequate protection and the combustible loading controls do not need elevation to a TSR control. The FSS, along with the Fire Protection Program, would provide protection to prevent a fire from impacting large amounts of stored waste material. The seismic switch was more of a challenge. When reviewing the facility operation, it was determined that the facility does not operate anywhere near the established material-at-risk (MAR – radioactive material) limits. By adjusting these limits, a reduced consequence could be achieved and hence, a significant risk reduction achieved. A new operating mode would be used to achieve this reduction. A reduced MAR limit was successfully used as a test case for snow removal during this project. This project expands on that trial case as related to combustible loading and the seismic power cutoff switch TSRs. This will increase the efficiency of operations with reduced TSR controls while reducing overall facility risk. This is a win-win situation for Triad National Security, LLC (Triad) and the U.S. Department of Energy (DOE). Due to schedule and budgetary constraints, not all envisioned work scope was accomplished. However, it is maintained in this report for future efforts.

61 RADIATION PROTECTION AND DOSIMETRY↗

Trust-Enhancing Probabilistic Transfer Learning for Sparse and Noisy Data Environments

There is an increasing aspiration to utilize machine learning (ML) for various tasks of relevance to national security. ML models have thus far been mostly applied to tasks and domains that, while impactful, have sufficient volume of data. For predictive tasks of national security relevance, ML models of great capacity (ability to approximate nonlinear trends in input-output maps) are often needed to capture the complex underlying physics. However, scientific problems of relevance to national security are often accompanied by various sources of sparse and/or incomplete data, including experiments and simulations, across different regimes of operation, of varying degrees of fidelity, and include noise with different characteristics and/or intensity. State-of-the-art ML models, despite exhibiting superior performance on the task and domain they were trained on, may suffer detrimental loss in performance in such sparse data environments. This report summarizes the results of the Laboratory Directed Research and Development project entitled Trust-Enhancing Probabilistic Transfer Learning for Sparse and Noisy Data Environments. The objective of the project was to develop a new transfer learning (TL) framework that aims to adaptively blend the data across different sources in tackling one task of interest, resulting in enhanced trustworthiness of ML models for mission- and safety-critical systems. The proposed framework determines when it is worth applying TL and how much knowledge is to be transferred, despite uncontrollable uncertainties. The framework accomplishes this by leveraging concepts and techniques from the fields of Bayesian inverse modeling and uncertainty quantification, relying on strong mathematical foundations of probability and measure theories to devise new uncertainty-aware TL workflows.

97 MATHEMATICS AND COMPUTING↗

Synopsis of NREL's Automated Mobility District (AMD) Research Program and Associated Publications

An automated mobility district (AMD) envisions a system of integrated mobility options that serves major activity centers such as campuses, central business districts, and large medical facilities. The National Renewable Energy Laboratory (NREL) has been investigating the implementation prospects for fully automated passenger transport systems that are deployed to operate within dense urban settings. This document provides a synopsis of findings revealed over the last three phases of work, which have yielded insights into the creation and management of AMDs anticipated to use automated vehicle (AV) technology over the next decade. Phase I and Phase II tracked the deployment and lessons learned from 10 early-stage demonstrations of automated shuttle deployments, and their associated insights into the challenges for automated driving systems to achieve safe operations within district-scale deployments. Phase III began in-depth investigations of critical subsystem components, as automation, electrification, and on-demand service continue to converge within initial AMD operations. These directed studies focus on elements of electrification, curbfront/station management, the role of infrastructure sensing, and overall integration of AMD safety management in central, simultaneous coordination of multiple AMD fleets. Future research in AMDs includes systems engineering methodology (more frequently referred to as "digital twins") for planning, design, testing, and ongoing operation of AMDs; location (or co-location) of management functions; and human supervision and passenger communications for safety and security in unattended vehicles. The synopsis references the foundational research products (papers and presentations) that have been published through conference proceedings, journal articles, and NREL reports.

33 ADVANCED PROPULSION SYSTEMS↗

Control Room of the Future Testbed Workshop – After-Action Report

The U.S. Department of Energy’s Office of Electricity is supporting a one-year, multi-laboratory effort to define the needs and requirements for a Control Room of the Future testbed, or CROFT. The effort responds to increasing grid complexity driven by large new loads, dynamic generation resources, and the growing adoption of advanced technologies and tools, including artificial intelligence (AI) and machine learning (ML). To support safe, secure, and effective grid modernization, CROFT will focus on how emerging technologies and tools can be rigorously evaluated in realistic operational settings, with attention to human-machine interaction, cognitive load, and workforce readiness. The project team includes Argonne National Laboratory, Idaho National Laboratory, National Laboratory of the Rockies, and Pacific Northwest National Laboratory. As part of the scoping effort, the team conducted two industry-focused workshops: one at DTECH on February 5, 2026, informed by prior industry interviews, and a second on May 4, 2026, adjacent to IEEE T&D. These engagements brought together utilities, vendors, consultants, national laboratories, academia, and government stakeholders to identify and prioritize use cases, barriers, validation needs, data-sharing constraints, and near- and longer-term requirements. This feedback will directly inform CROFT’s architecture and research focus areas, ensuring the testbed is grounded in real-world operational needs and designed to evaluate emerging technologies and tools in realistic control-room environments.

artificial intelligence↗

Detection of DoS Attacks Using ARFIMA Modeling of GOOSE Communication in IEC 61850 Substations

Integration of Information and Communication Technology (ICT) in modern smart grids (SGs) offers many advantages including the use of renewables and an effective way to protect, control and monitor the energy transmission and distribution. To reach an optimal operation of future energy systems, availability, integrity and confidentiality of data should be guaranteed. Research on the cyber-physical security of electrical substations based on IEC 61850 is still at an early stage. In the present work, we first model the network traffic data in electrical substations, then, we present a statistical Anomaly Detection (AD) method to detect Denial of Service (DoS) attacks against the Generic Object Oriented Substation Event (GOOSE) network communication. According to interpretations on the self-similarity and the Long-Range Dependency (LRD) of the data, an Auto-Regressive Fractionally Integrated Moving Average (ARFIMA) model was shown to describe well the GOOSE communication in the substation process network. Based on this ARFIMA-model and in view of cyber-physical security, an effective model-based AD method is developed and analyzed. Two variants of the statistical AD considering statistical hypothesis testing based on the Generalized Likelihood Ratio Test (GLRT) and the cumulative sum (CUSUM) are presented to detect flooding attacks that might affect the availability of the data. Our work presents a novel AD method, with two different variants, tailored to the specific features of the GOOSE traffic in IEC 61850 substations. The statistical AD is capable of detecting anomalies at unknown change times under the realistic assumption of unknown model parameters. The performance of both variants of the AD method is validated and assessed using data collected from a simulation case study. We perform several Monte-Carlo simulations under different noise variances. The detection delay is provided for each detector and it represents the number of discrete time samples after which an anomaly is detected. In fact, our statistical AD method with both variants (CUSUM and GLRT) has around half the false positive rate and a smaller detection delay when compared with two of the closest works found in the literature. Our AD approach based on the GLRT detector has the smallest false positive rate among all considered approaches. Whereas, our AD approach based on the CUSUM test has the lowest false negative rate thus the best detection rate. Depending on the requirements as well as the costs of false alarms or missed anomalies, both variants of our statistical detection method can be used and are further analyzed using composite detection metrics.

IEC 61850 electrical substations↗

Predictive Analytics for Hydropower Fleet Intelligence

A primary challenge in hydropower industry is the ability to maintain cost-competitiveness, reliability, and security of hydropower assets through evolving power system contexts and aging of the fleet. Maintaining cost-effective and reliable operations under these conditions is expected to require new modernization and maintenance paradigms for changing contexts. Changes in existing practices for O&M will require an understanding of the current state and health of hydropower assets, and the impact of changing paradigms on asset health and reliability. The Hydropower Fleet Intelligence project is developing and evaluating standardized methodologies and analysis tools for data-driven asset reliability and management technologies for hydropower, leading to eventual predictive maintenance planning, repair/replacement decision making, and asset-reliability and cost-optimized operations. A key question is the feasibility of using existing data sets at hydropower facilities to perform assessments of asset reliability. This document uses data from hydropower facilities to assess the potential for using available analytics methods for asset reliability estimates. In addition to reliability assessments, the feasibility of using existing analytics techniques for several other potential applications is discussed. Finally, a case study that a data-driven model is trained to learn nominal operations via vibration data from an asset of a certain plant, and then utilized to identify anomalies on a similar asset from a different plant, highlighting the generic use of proposed Prognostics and Health Management (PHM) approaches.

Yucesan, Yigit↗

Mobile sampler for use in acquiring samples of terrestrial atmospheric gases

Samples of terrestrial atmospheric gasses from a free body of such gasses using a device characterized by a plurality of tubular bodies adapted to be mounted in side by side relation on a motorized highway vehicle in mutual parallelism with the axis of the normal path of travel for the vehicles. Each of the bodies is of a cylindrical configuration and has an axial opening at each of its opposite ends through which a linear flow path is defined. A pair of pivotally supported, spring-biased sealing caps is mounted adjacent to the ends of the body and continuously urged into a hermetic sealing relationship. A restraint for securing the caps against spring-urged pivotal displacement, includes a separable, normally tensioned line interconnecting the caps and an operable release mechanism for simultaneously releasing the caps for spring-urged displacement. A hot wire cutter is included for separating the line, whereby samples of air are trapped in the body as the caps are spring-driven to assume an hermetically sealed relation with the openings defined in each of the opposite ends of the body.

Tucker, C. E.↗

Expert system development methodology and the transition from prototyping to operations: FIESTA, a case study

A major barrier in taking expert systems from prototype to operational status involves instilling end user confidence in the operational system. The software of different life cycle models is examined and the advantages and disadvantages of each when applied to expert system development are explored. The Fault Isolation Expert System for Tracking and data relay satellite system Applications (FIESTA) is presented as a case study of development of an expert system. The end user confidence necessary for operational use of this system is accentuated by the fact that it will handle real-time data in a secure environment, allowing little tolerance for errors. How FIESTA is dealing with transition problems as it moves from an off-line standalone prototype to an on-line real-time system is discussed.

Happell, Nadine↗

Expert system development methodology and the transition from prototyping to operations - Fiesta, a case study

A major barrier in taking expert systems from prototype to operational status involves instilling end user confidence in the operational system. The software of different life cycle models is examined and the advantages and disadvantages of each when applied to expert system development are explored. The Fault Isolation Expert System for Tracking and data relay satellite system Applications (FIESTA) is presented as a case study of development of an expert system. The end user confidence necessary for operational use of this system is accentuated by the fact that it will handle real-time data in a secure environment, allowing little tolerance for errors. How FIESTA is dealing with transition problems as it moves from an off-line standalone prototype to an on-line real-time system is discussed.

Happell, Nadine↗

Robotic tape library system level testing at NSA: Present and planned

In the present of declining Defense budgets, increased pressure has been placed on the DOD to utilize Commercial Off the Shelf (COTS) solutions to incrementally solve a wide variety of our computer processing requirements. With the rapid growth in processing power, significant expansion of high performance networking, and the increased complexity of applications data sets, the requirement for high performance, large capacity, reliable and secure, and most of all affordable robotic tape storage libraries has greatly increased. Additionally, the migration to a heterogeneous, distributed computing environment has further complicated the problem. With today's open system compute servers approaching yesterday's supercomputer capabilities, the need for affordable, reliable secure Mass Storage Systems (MSS) has taken on an ever increasing importance to our processing center's ability to satisfy operational mission requirements. To that end, NSA has established an in-house capability to acquire, test, and evaluate COTS products. Its goal is to qualify a set of COTS MSS libraries, thereby achieving a modicum of standardization for robotic tape libraries which can satisfy our low, medium, and high performance file and volume serving requirements. In addition, NSA has established relations with other Government Agencies to complete this in-house effort and to maximize our research, testing, and evaluation work. While the preponderance of the effort is focused at the high end of the storage ladder, considerable effort will be extended this year and next at the server class or mid range storage systems.

Shields, Michael F.↗

Technology for a NASA Space-Based Science Operations Grid

This viewgraph representation presents an overview of a proposal to develop a space-based operations grid in support of space-based science experiments. The development of such a grid would provide a dynamic, secure and scalable architecture based on standards and next-generation reusable software and would enable greater science collaboration and productivity through the use of shared resources and distributed computing. The authors propose developing this concept for use on payload experiments carried aboard the International Space Station. Topics covered include: grid definitions, portals, grid development and coordination, grid technology and potential uses of such a grid.

Bradford, Robert N.↗

Elastomeric load sharing device

An elastomeric load sharing device, interposed in combination between a driven gear and a central drive shaft to facilitate balanced torque distribution in split power transmission systems, includes a cylindrical elastomeric bearing and a plurality of elastomeric bearing pads. The elastomeric bearing and bearing pads comprise one or more layers, each layer including an elastomer having a metal backing strip secured thereto. The elastomeric bearing is configured to have a high radial stiffness and a low torsional stiffness and is operative to radially center the driven gear and to minimize torque transfer through the elastomeric bearing. The bearing pads are configured to have a low radial and torsional stiffness and a high axial stiffness and are operative to compressively transmit torque from the driven gear to the drive shaft. The elastomeric load sharing device has spring rates that compensate for mechanical deviations in the gear train assembly to provide balanced torque distribution between complementary load paths of split power transmission systems.

Isabelle, Charles J.↗

A Comparison of Bearing Measurements to Surface Features Generated Using Stereophotoclinometry and Surface Feature Navigation Techniques

The Origins Spectral Interpretation Resource Identification Security Regolith Explorer (OSIRIS-REx) mission to the asteroid Bennu completed successful two-and-a-half year proximity operations in May 2021. The mission comprehensively mapped Bennu at unprecedented detail and collected a sample of Bennu’s surface to return to Earth. Throughout proximity operations, the OSIRIS-REx navigation team used the maps made of Bennu’s surface to navigate in the Bennu environment with high accuracy through the use of precise and accurate optical navigation data, radiometric data, and force modelling. The primary type of optical navigation measurements extracted from the images captured by OSIRIS-REx (particularly after first entering orbit around Bennu) were observations of known features on Bennu’s surface. Two related but different techniques/tools were used to extract these observations from the images: the Goddard Image Analysis and Navigation Tool Surface Feature Navigation (GIANT SFN) and Stereophotoclinometry (SPC) Autoregister. In this paper we compare the differences between the observables extracted using GIANT SFN and SPC Autoregister, explain the differences, and discuss where each technique is best suited.

Andrew Liounis↗

INL FY 2021 Laboratory Overview

The INL FY 2021 Laboratory Overview is an opportunity for INL to share its achievements and plans for the future with the entire Laboratory, stakeholders, and the public. This document outlines how INL will advance its clean energy and national security objectives in the future and highlights FY 2020 accomplishments across the Laboratory in science and technology, community outreach, and operations.

07 ISOTOPE AND RADIATION SOURCES↗

Assessing the Threat: Weaving Cybersecurity into the Building Development Process

Today’s connected lighting systems have the potential to reduce energy consumption and operational costs via the use of the data they collect and share with other building systems (e.g., HVAC, building automation, security). However, many market available products are new to being networked, and when networked components in lighting and other building systems are not sufficiently secured, they present opportunities for criminals to exploit. Further, security vulnerabilities in one system can be used as lateral steppingstones that allow access to other prized assets on the same network. These cybersecurity concerns could deter the adoption and use of connected systems, which then could jeopardize long-term national objectives for reduced energy usage. The workflows described here and presented in more detail in the referenced reports are examples of how these frameworks and tools can be put to practical use during system design and specification.

attack surface, Building development, threat analy↗

It's Not Just About the Megawatts - ARC Industry Forum, The Future of Power Generation

As the world transitions to less carbon intensive energy portfolios, much of the attention understandably centers on generating capacity – replacing megawatts of fossil fuel with megawatts of solar, wind, nuclear, hydroelectric, hydrogen, and more. The actual operation of a reliable grid needs more than just megawatts though: adequate quantities of a portfolio of essential reliability services; flexible and capable power delivery systems; governance to operate in 5-10 minute intervals, forecast hourly, and plan and build on a generational time horizon; and dependable and secure communications. We can choose our fuel mix for climate reasons, but the grid itself and the society that relies upon it impose constraints on those choices that we ignore at our peril.

13 HYDRO ENERGY↗

ARCADE (Advanced Reactor Cyber Analysis and Development Environment)

SAND2025-11780O ARCADE (Advanced Reactor Cyber Analysis and Development Environment) software performs cybersecurity experiments on Defensive Cyber Security Architectures (DCSA) for Distributed Control Systems (DCSs). The application is integrated into a cohesive environment that performs cyber risk analyses and reduces costs. ARCADE can investigate the entire cyber-attack surface of a DCS from the physics of control, down to the firmware of individual components with automated efficiency. ARCADE has five major functional components: the Data Broker system, the virtualization environment, the cyber-attack simulator, the cyber-physical analysis system, and the physics simulator. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Valme, Romuald↗

Energy Material Network Data Hubs

In early 2015 the United States Department of Energy conceived of a consortium of collaborative bodies based on shared expertise, data, and resources that could be targeted towards the more difficult problems in energy materials research. The concept of virtual laboratories had been envisioned and discussed earlier in the decade in response to the advent of the Materials Genome Initiative and similar scientific thrusts. To be effective, any virtual laboratory needed a robust method for data management, communication, security, data sharing, dissemination, and demonstration to work efficiently and effectively for groups of remote researchers. With the accessibility of new, easily deployed cloud technology and software frameworks, such individual elements could be integrated, and the required collaboration architecture is now possible. The developers have leveraged open-source software frameworks, customized them, and merged them into a platform to enable collaborative energy materials science, regardless of the geographic dispersal of the people and resources. After five years in operations, the systems are demonstratively an effective platform for enabling research within the Energy Material Networks (EMN). This paper will show the design and development of a secured scientific data sharing platform, the ability to customize the system to support diverse workflows, and examples of the enabled research and results connected with some of the Energy Material Networks.

97 MATHEMATICS AND COMPUTING↗