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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Análisis de Tareas del Inspector de Control de Calidad [Quality Control Inspector Job Task Analysis (Spanish Translation)]

El Laboratorio Nacional de Energía Renovable (NREL) ha sido contratado por el Programa de Asistencia para la Climatización (WAP) del Departamento de Energía de EE.UU. (DOE) para desarrollar y mantener los recursos en el marco del proyecto de Directrices para Profesionales de la Energía Doméstica (GHEP). El objetivo del proyecto GHEP es aumentar la calidad del trabajo realizado para la remodelación energética residencial en Estados Unidos a través de WAP y otros programas de remodelación residencial. Para cumplir el objetivo de “Establecer certificaciones nacionales de la mano de obra y normas de formación”, el DOE encargó al NREL el desarrollo de recursos GHEP, incluido un conjunto de certificaciones avanzadas, basadas en aptitud, para el personal de los profesionales de la energía doméstica (HEP). Desde 2010, el NREL ha reclutado voluntarios expertos en la materia de WAP y de la industria del mantenimiento del hogar para que formen parte de comités que desarrollen y actualicen programas de certificación y sus análisis de tareas (JTA) necesarios como base de programas de certificación y formación estandarizados. Las certificaciones HEP apoyan al WAP y al sector del mantenimiento de viviendas residenciales en general mediante el proceso de acreditación y el desarrollo de JTA definidos para auditores energéticos (EA) e inspectores de control de calidad (QCI). Este informe es un resumen de las actualizaciones más recientes (2022) del JTA del QCI. [The National Renewable Energy Laboratory (NREL) is contracted by the U.S. Department of Energy (DOE) Weatherization Assistance Program (WAP) to develop and maintain the resources under the Guidelines for Home Energy Professionals (GHEP) project. The purpose of the GHEP project is to increase the quality of work conducted for residential energy retrofits in the United States through the WAP network and other residential retrofit programs. This is the Spanish translation of NREL/TP-7A40-85789.]

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

Insights and Impacts of Credentials: Energy Auditor, Quality Control Inspector, and Certification Updates

Join this session to learn about recent and upcoming Home Energy Professional credential and resource updates from the National Renewable Laboratory (NREL) in support of the U.S. Department of Energy's Weatherization Assistance Program (WAP). NREL staff will provide an in-depth overview of improvements to the EA and QCI certification schemes. Be prepared to provide feedback and share new ideas in pursuit of continuous improvement within WAP. These certifications are critical to ensuring the highest standards of quality, safety, and efficiency within the Weatherization Assistance Program, helping to elevate the skills of professionals and drive the program's overall success.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Energy Auditor and Quality Control Inspector Certification Updates

This presentation discusses recent and future Home Energy Professional credential and resource updates at the National Renewable Energy Laboratory in support to the U.S Department of Energy's Weatherization Assistance Program (WAP). It will provide an in-depth overview of planned improvements to the EA and QCI certification schemes.

certification↗
DOE OSTI2025

Detection of Diversion in a Realistic Heat Pipe Microreactor Using Supervised Machine Learning

Microreactors (MRs) pose new challenges for international safeguards. Here, their small size and mass reproducibility make them ideal for deployment in greater numbers and in remote locations, making the job of safeguards inspectors more challenging. Machine learning (ML) is currently being applied to many fields to augment human performance and increase automation; in particular, ML could be used to provide insight for international inspectors to help detect the diversion of nuclear fuel from MR cores. Four ML model types (k-nearest neighbors, decision tree, random forest, and histogram-based gradient boosted ensemble) were trained on integrated flux and critical control drum angle data generated with Serpent 2 for a realistic heat pipe MR design, achieving nearly 100% binary classification accuracy of nominal and diversion core configurations by the end of 1 full power year for three of the four model types. Regression model variants were also trained, using the same input data, for predicting the number of fuel pins diverted. Root-mean-square errors below 5% of the total number of fuel pins were achieved by the 1 full power year mark for all models.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Inspecta Technical Report

Sandia National Laboratories (SNL) is in the process of creating Inspecta (International Nuclear Safeguards Personal Examination and Containment Tracking Assistant), an Artificial Intelligence (AI)-powered smart digital assistant (SDA) with robotic capabilities, aimed at enhancing the effectiveness, efficiency, and safety of international nuclear safeguards inspections. This innovative tool is designed to assist inspectors on-site by supporting or automating tasks that are typically mundane, hazardous, or susceptible to errors. In 2021, the development team established the specifications for Inspecta by analyzing International Atomic Energy Agency (IAEA) documents and consulting with former IAEA inspectors and subject matter experts. This process involved aligning in-field inspection tasks with existing commercial or open-source technologies to outline a roadmap for the initial prototype of Inspecta, while also identifying areas needing further research and development. From 2022 – 2024, the focus has shifted to integrating a critical inspection activity, the examination of seals, into an early version of Inspecta. This has involved developing both the software and hardware capabilities necessary for this task. This report outlines the ongoing advancements in Inspecta's functionalities, specifically those supporting the seal examination process.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Inspecta Technical Report

Sandia National Laboratories (SNL) has developed Inspecta (International Nuclear Safeguards Personal Examination and Containment Tracking Assistant), an AI-powered smart digital assistant (SDA) equipped with robotic capabilities. This innovative tool aims to enhance the effectiveness, efficiency, and safety of international nuclear safeguards inspections. Inspecta is designed to assist inspectors on-site by supporting or automating tasks that are often mundane, hazardous, or prone to errors. In 2021, the development team established the specifications for Inspecta by thoroughly analyzing International Atomic Energy Agency (IAEA) documents and consulting with former IAEA inspectors and subject matter experts. This process involved aligning in-field inspection tasks with existing commercial and open-source technologies, thereby creating a roadmap for the initial prototype of Inspecta and identifying areas requiring further research and development. From 2022 to 2025, the focus shifted to integrating a critical inspection activity—the examination of seals—into an early version of Inspecta. This phase has involved the development of both software and hardware capabilities essential for this task. This report outlines the advancements in Inspecta’s functionalities, particularly those that support the seal examination process.

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

Investigation of U content in J-swipe/PIC samples

This final report documents the results of an evaluation of the U content in J-swipes for the International Atomic Energy Agency (IAEA). J-swipes are manufactured with inked numbers (1–30) and U backgrounds that are considered consistent across different lots and manufacturing times. These characteristics make them ideal for use by IAEA inspectors for pre-inspection check samples to ensure inspectors are not cross-contaminating sites. However, recent work has found elevated U concentrations in the inked numbers compared with the J-swipe material. To determine whether the inked numbers correlate with the U backgrounds, triplicate U content measurements were made on Swipes 1, 2, 11, 22, and 28. Triplicates of each swipe were processed through the standard chemistry used by the Oak Ridge National Laboratory Network of Analytical Laboratories team and analyzed for U content by isotope dilution via multicollector inductively coupled plasma mass spectrometry. Finally, samples were made by mass consisting of only ink areas and only cotton swipe material to determine the trace element differences between the cotton and the ink.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2026

Artificial Intelligence in Nuclear Safeguards; Evaluating Safeguards and Security Risks and Benefits for Advanced and Small Modular Reactor Deployments

Rapidly growing interest in advanced and small modular reactor (A/SMR) technologies presents challenges as well as opportunities for implementing international safeguards and security. A/SMR deployments are expected to be more numerous, more geographically dispersed, and more varied in their designs, placing new demands on the data systems and analytical tools used to support oversight (Alberti et al., 2023; Canadian Nuclear Safety Commission et al., 2024). Because of this variability, the importance and reliance on data systems for A/SMR deployments is expected to be higher than for previous reactor generations. Artificial Intelligence and Machine Learning (AI/ML) offer potential capabilities to address the high variability inherent in A/SMR technology. The beneficiaries of AI-assisted tools include facility operators, government regulators, IAEA inspectors, and A/SMR vendors. This report analyzes how AI/ML-assisted technologies can strengthen the implementation of IAEA safeguards and security measures. It also identifies AI-assisted tools to strengthen operator, facility, and regulator knowledge management practices and examines the potential risks AI/ML-based tools may introduce to IAEA safeguards and security efforts. It concludes with a set of hypothetical, standards-style requirements for AI/ML systems used in safeguards contexts, grounded in an inspector-centric view of system verification. Despite the potential benefits of AI/ML systems, understanding potential intentional and unintentional failure modes is critical for ensuring adequate protection of nuclear materials and facilities. Unique features of A/SMRs including sealed cores, remote and novel paradigms of operation, off-site reactor fabrication, novel fuel forms, and varied refueling requirements, introduce challenges for traditional safeguards technological approaches (Pensado et al., 2024; Federation of American Scientists, 2025). AI/ML systems deployed to address these challenges may introduce new risks requiring systematic evaluation rooted in both AI-specific risk frameworks, such as the NIST AI Risk Management Framework (NIST AI RMF), and established cyber risk management standards such as NIST SP 800-30 (National Institute of Standards and Technology [NIST], 2023; NIST, 2012).

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Challenges and Technology-Driven Opportunities for Safeguarding Microreactors

Nuclear microreactors (MRs) represent a new class of reactors characterized by their compactness, portability, and low power output. These features enable MRs to supply electricity and process heat to remote areas like military bases; inaccessible locations; small grids, such as on islands; or disaster impacted areas. Compared to traditional light water reactors, MRs have a unique set of attributes that need to be considered for the implementation of safeguard strategies. Current safeguard methodologies are reactor technology specific and are employed on large, stationary reactors where there is easy access by safeguards inspectors and where safeguard equipment can be easily installed and retrofitted. While there are numerous benefits to MRs, their compact size, portability, scalability, and operational lifetime create challenges to the traditional safeguard approaches, thus needing novel safeguard strategies. Here, this paper addresses the unique challenges posed by MRs to the international nuclear safeguards regime, including limited human resources, and explores how technology advancements can help mitigate these challenges. Specifically, it examines novel technologies that could contribute to establishing a comprehensive safeguards framework for MRs. These safeguards-enabling technologies encompass safeguards by design, remote sensing and monitoring technologies, applications of artificial intelligence and machine learning algorithms, utilization of digital twins, and system of systems assessments. While each of these safeguards-enabling technologies offers partial solutions to the challenges posed by MRs for the international safeguards regime, none of them alone can entirely address these challenges. Consequently, a combination of the safeguards-enabling technologies outlined in this paper is recommended to establish a robust safeguards regime for MRs.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2024

DOC-DICAM: Domain Aware One Class Defect Identification in Composite Aerostructure Material

Fiber-reinforced composites are a common material used in the design of aircraft structures due to their good tensile strength and resistance to compression. During the manufacturing process, these structures are thoroughly inspected for flaws and defects to ensure structural integrity during commercial use. Non-destructive testing (NDT) is a collection of inspection methods that allow inspectors to evaluate material without altering it. Due to the high safety standards in aerospace manufacturing, the NDT process is done manually and can be a significant bottleneck in the development workflow. In this paper, we develop an AI-based assistance tool to drastically reduce inspection time. Typical AI workflows require large amounts of annotated data, but defects rarely occur resulting in strong class imbalance. To overcome this, we formulate the problem of defect identification as an anomaly detection task in which our primary focus is learning non-defect characteristics. To do this, we develop a multi-task self-supervised learning framework that embeds problem specific domain knowledge into the deep learning model. We verify our method using fuselage data generated in a production environment. As a result, we show that our method can effectively identify defects and requires minimal training and inference time.

anomaly detection↗
DOE OSTI2025

DCVD Image Analysis Algorithm

The purpose of the software algorithm is to assist in the sustainability and improvement of the Cerenkov viewing devices, especially the DCVD, used by Euratom and the IAEA safeguards inspectors to verify the presence and completeness of spent nuclear fuel.

McGinnis, Brent [Pacific Northwest National Labora↗
DOE OSTI2024

Non-nuclear Component Signatures for Warhead Dismantlement Confirmation

The verification of warhead dismantlement is expected to be an important component in future arms reduction treaties. Historic approaches developed with future arms control treaty verification in mind often involve intrusive measurements, process monitoring, and/or inspector presence to provide confidence that an authentic warhead has been dismantled. This work explores the possibility of reducing the negative impacts of these invasive approaches while also delivering a method that is more likely to provide non-sensitive data that can be shared with not only other nuclear weapons states but also non-nuclear weapons states partners. This work explores a novel approach for verifying dispositioned non-nuclear weapon components, providing confidence post-dismantlement that a treaty accountable item that was dismantled was in fact a treaty-relevant nuclear weapon system as declared. This method provides an alternative to intrusive inspection processes in nuclear weapons production environments, which would require significant changes to the host’s operational behaviors. It achieves this by identifying intrinsic neutron-induced signatures of non-nuclear components to determine their authenticity and estimate the duration they were exposed within a nuclear weapons system using technologies that are already in use for other national security applications. Intrinsic radiation effects studies are already a part of the stockpile aging and surveillance evaluations. However, none of these technologies and approaches have been previously considered for verification applications of non-nuclear component disposition. In this report, we introduce modeling studies that have been used to identify the most promising candidate parts and materials with signatures that are measurable and actionable. These models have been validated with laboratory measurements of signatures induced by the exposure of candidate materials to neutrons over a range of times. Predictive modeling then demonstrates the methodology for estimating exposure times and/or limits. Laboratory measurements of authentic non-nuclear parts from a dismantled warhead demonstrate the feasibility of employing these signature measurements. And finally, a concept of operations (CONOPS) for the potential use of this methodology is presented.

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

Advanced Diagnosis and Accelerated Testing of Balance of System Components for Utility Scale PV Installations: October 1, 2022-September 30, 2024

A study of the durability of PV Balance of System components was performed. Specifically, wire cable jackets and cable connectors were examined within the direct current (DC) PV Power Transmission Chain (PTC). Degraded and failed samples have been obtained from utility PV installations to provide feedback on the degradation modes and the related damage-enabling considerations in today's PV systems. An industry interface group (including system owners, system inspectors, component manufacturers, and test labs) was used to help identify and obtain field-failed samples, for feedback (including samples and experimental design), and to facilitate the subsequent dissemination of the results of this study. Samples were empirically studied using accelerated stress testing with steady-state conditions (cable jackets) in addition to combined-accelerated stress testing (cable jackets, connectors and uncapped connectors). Steady-state accelerated testing has been performed using at least one applied stressor (e.g. UV light) to aid understanding of jacket durability relative to its application. Component- and material-focused failure analysis was conducted to develop an understanding and advise the PV industry. In-depth characterization will be applied selectively to field- and artificially aged-samples, to gain scientific understanding of the structural, chemical, electrical, mechanical, and thermal properties enabling degradation.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Puck and Puck/SAW Loop Seals (Final Report)

Tamper-indicating devices (TIDs), also known as seals, play a crucial role in various sectors including international nuclear safeguards, arms control, domestic security, and commercial products, by ensuring that monitored or high-value items are not accessed undetected. These devices do not block access but alert to unauthorized tampering. With adversaries' capabilities evolving, there's a pressing need for seals to advance in terms of effectiveness (e.g., better tamper indication and unique identification), and new technology can improve the efficiency of installation and verification. Passive loop seals, widely used in international nuclear safeguards to ensure that continuity of knowledge is maintained on declared items, face stringent International Atomic Energy Agency (IAEA) requirements that surpass those met by commercial products. The metal cup seal (Figure 1, left), a staple IAEA seal, is robust but requires significant resources for post-use verification – specifically, the seal’s unique identity can only be verified at IAEA headquarters after removal from facilities. Further, the seal has been in use for decades and seal types should periodically be replaced to counter adversarial efforts for defeating seals. In 2020, the IAEA outlined about 40 requirements for a new passive loop seal, aiming for in-situ verification, minimal external tool use, unique identification (UID), and clear tamper indication. In response, research and development efforts focused on creating a new passive loop seal that meets these criteria and in 2022 the IAEA announced the completion of the Field Verifiable Passive Loop Seal (FVPS) (Figure 1, right). Concurrently to the IAEA’s efforts, Sandia National Laboratories (SNL) and Oak Ridge National Laboratory (ORNL) designed, developed, and tested two seal versions – Puck and Puck/SAW, with Puck based on the IAEA’s requirements and including a novel visually-obvious tamper response, and Puck/SAW adding additional beneficial capabilities like the ability to receive a unique identifier from a standoff distance and monitoring the wire integrity. Puck/SAW was specifically designed and developed to address sealing applications in dry spent fuel storage facilities, where the number of sealed spent fuel containers results in heavy verification burden and inspector safety issues related to radiation exposure. These efforts are described in this Executive Summary.

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

Análisis de Tareas del Auditor Energético [Energy Auditor Job Task Analysis (Spanish Translation)]

El Laboratorio Nacional de Energía Renovable (NREL), bajo el contrato con el Programa de Asistencia para la Climatización (WAP) del Departamento de Energía de EE.UU. (DOE), desarrolla y mantiene los recursos en el marco del proyecto Directrices para Profesionales de la Energía Doméstica (GHEP). El objetivo del proyecto GHEP es aumentar la calidad del trabajo de remodelación energética residencial realizado por WAP y otros programas de remodelación residencial en Estados Unidos. Para cumplir el objetivo de “Establecer certificaciones nacionales de la mano de obra y normas de formación”, el DOE encargó al NREL el desarrollo de recursos GHEP, incluido un conjunto de certificaciones avanzadas, basadas en aptitud, para el personal de los profesionales de la energía doméstica (HEP). Desde 2010, el NREL ha reclutado voluntarios expertos en la materia de WAP y de la industria del mantenimiento del hogar para que formen parte de comités que desarrollen y actualicen programas de certificación y sus análisis de tareas (JTA) necesarios como base de programas de certificación y formación estandarizados. Las certificaciones HEP apoyan al WAP y al sector del mantenimiento de viviendas residenciales en general mediante el proceso de acreditación y el desarrollo de JTA definidos para auditores energéticos (EA) e inspectores de control de calidad (QCI). Este informe es un resumen de las actualizaciones más recientes (2022) del JTA del EA. [The National Renewable Energy Laboratory (NREL) is contracted by the U.S. Department of Energy (DOE) Weatherization Assistance Program (WAP) to develop and maintain the resources under the Guidelines for Home Energy Professionals (GHEP) project. The purpose of the GHEP project is to increase the quality of work conducted for residential energy retrofits in the United States through the WAP network and other residential retrofit programs. This is the Spanish translation of NREL/TP-7A40-85300.]

29 ENERGY PLANNING, POLICY, AND ECONOMY↗