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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 307 records · Page 17

Enhancing Post-Irradiation Examination (PIE) Efficiency with High-Throughput Experiments

Nuclear materials testing is essential for understanding changes in reactor environments, but traditional methods are costly and time-consuming. High-Throughput Experimentation (HTE) enables rapid screening and optimization of material properties by significantly increasing the number of specimens in the experiment. In this work, HTE methods were employed to irradiate novel materials at the Advanced Test Reactor (ATR) at Idaho National Laboratory. A total of 367 sub-sized tensile specimens were irradiated using the standard capsule design. To facilitate HTE, automated systems such as the Automated Mechanical Testing System were implemented for mechanical testing within hot cell environments, thereby reducing the need for manual interaction with hot cell manipulators and significantly lowering both the cost and duration of experiments. Digital image correlation (DIC) was used to measure displacement during mechanical testing, providing precise, non-contact measurement capabilities. The methodologies developed in this research will support the advancement of HTE techniques for future nuclear materials testing experiments at ATR. This approach allows for more efficient and cost-effective evaluation of new materials, ultimately leading to improved reactor performance, enhanced safety, and extended longevity within the nuclear industry.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗

SNM Radiation Signature Classification Using Different Semi-Supervised Machine Learning Models

The timely detection of special nuclear material (SNM) transfers between nuclear facilities is an important monitoring objective in nuclear nonproliferation. Persistent monitoring enabled by successful detection and characterization of radiological material movements could greatly enhance the nuclear nonproliferation mission in a range of applications. Supervised machine learning can be used to signal detections when material is present if a model is trained on sufficient volumes of labeled measurements. However, the nuclear monitoring data needed to train robust machine learning models can be costly to label since radiation spectra may require strict scrutiny for characterization. Therefore, this work investigates the application of semi-supervised learning to utilize both labeled and unlabeled data. As a demonstration experiment, radiation measurements from sodium iodide (NaI) detectors are provided by the Multi-Informatics for Nuclear Operating Scenarios (MINOS) venture at Oak Ridge National Laboratory (ORNL) as sample data. Anomalous measurements are identified using a method of statistical hypothesis testing. After background estimation, an energy-dependent spectroscopic analysis is used to characterize an anomaly based on its radiation signatures. In the absence of ground-truth information, a labeling heuristic provides data necessary for training and testing machine learning models. Supervised logistic regression serves as a baseline to compare three semi-supervised machine learning models: co-training, label propagation, and a convolutional neural network (CNN). In each case, the semi-supervised models outperform logistic regression, suggesting that unlabeled data can be valuable when training and demonstrating value in semi-supervised nonproliferation implementations.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

Quantitative Holdup Determinations Using Coded-Aperture Gamma-Ray Imaging

Passive gamma-ray imaging can be used to create images of distributed nuclear materials. Inherently quantitative, the images provide a means to directly determine the amount of nuclear material in the imager’s field of view. However, to take advantage of quantitative imaging, one must correct for changes to the imager’s efficiency across the image. This paper presents work on detailed calibration of a coded-aperture imager based on a portable, mechanically cooled, high-purity germanium detector. This enables the use of gamma-ray imaging as a tool to determine nuclear holdup. By applying the calibrations to images of small amounts of distributed 235U, quantity estimates within a few percent of the actual amounts present were obtained, validating the approach.

Ziock, Klaus-Peter↗

Design considerations for high entropy alloys in advanced nuclear applications

The demanding operating environments of advanced nuclear reactors require the development of new nuclear materials that can withstand their increased physical, chemical, thermal, and radiation-related challenges. High-entropy alloys (HEAs) have shown often-impressive mechanical, thermomechanical, and corrosion-resistant properties, and offer a massive, unexplored compositional space which allows for the targeted development of application-specific materials. Furthermore, although still in a nascent stage, research has shown that HEAs may exhibit unique irradiation tolerance, including reduced defect production and resistance to irradiation-induced swelling and hardening. The mechanisms behind this increased tolerance are not yet well-understood, although the HEA-specific attributes of a complex energy landscape, reduced thermal conductivity, and shift in defect migration energies and pathways provide promising explanations. Here this work assesses the current and future challenges faced by structural nuclear materials, identifying the specific applications in which HEAs may provide a competitive advantage compared to industry-standard materials with the aid of Ashby material selection maps. Considerations are provided for the design of future nuclear HEAs, including calculations of nuclear-relevant properties to assist in the initial down-selection of elements depending on application requirements (e.g., low neutron capture for in-core applications), narrowing the existing compositional space of HEAs to a manageable scope.

36 MATERIALS SCIENCE↗

Development of spectroscopy apparatus for molten salt reactor safeguards and material characterization

A molten salt reactor (MSR) produces nuclear fission energy using mixture of fissile and non-fissile salts. Salt in the reactor functions as the nuclear material and the coolant allowing for a safer design. International nuclear safeguards is the monitoring of nuclear reactors, nuclear fuel, and irradiated material to prevent the proliferation of nuclear weapon grade material in hostile foreign nations. The mixture of salt creates a proliferation risk as it generates a conglomeration of fuel, daughter nuclei, and corrosive material. A method to monitor and measure the materials present in the reactor is essential to the scalable deployment of MSRs. The objective of this project was to design a spectroscopy apparatus for aqueous salt so it can be measured and collected consistently in the aerosol phase.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

Material Control and Accounting Regulatory and Technical Considerations for Microreactors

New microreactors must comply with the Material Control and Accounting (MC&A) regulations in 10CFR74. The objective of MC&A is to verify that the nuclear material is not stolen or diverted to unauthorized users. Microreactors have unique features which pose new challenges to addressing these regulations. This work considers general approaches and methods for microreactor MC&A based on the reactor life cycles which have been proposed by microreactor vendors. One key aspect of MC&A is measurement of the nuclear material. Measurement of microreactor fuel could be especially important because the cores may be sealed for up to 20 years, preventing direct visual confirmation. Measurements could also be especially challenging due to the thick shielding designed around microreactors. This work evaluates a range of techniques used in medical, industrial, and nuclear fields. The cost, time, and performance of the techniques were estimated. Finally, for a promising technique of using in-core neutron detectors, the feasibility was analyzed in detail.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

A Molten Salt Aerosol Spectroscopy Approach to Online Process Monitoring in Molten Salt Reactors

Recent research and development in molten salt reactors (MSRs) has led to many advanced reactor designs, many of which have demonstrations planned in the next decade. However, a significant challenge that must be overcome before liquid fueled MSRs become viable globally is nuclear material accountancy (NMA) and safeguards. Liquid-fueled MSRs are problematic to safeguards because the nuclear material is in the bulk phase, inventories are constantly changing, and there are potentially many outlet pathways that must be monitored, especially in designs with online chemical processing. At the Idaho National Laboratory, we have developed a process monitoring tool to circulate molten salt through a nebulizer and optical cell, where laser-induced breakdown spectroscopy (LIBS) and ultraviolet-visible (UV-VIS) are applied to track the elemental and oxidation states of the constituents in the salt aerosol. This approach has the potential to provide information on the actinides, fission products, and corrosion in the reactor or process. Preliminary testing in aqueous praseodymium chloride (PrCl3) and neodymium chloride (NdCl3) showed good sensitivity detection limits n developed calibration curves. Additional tests and analysis or ongoing in aqueous solutions while equipment is being scaled up for high temperature molten salt testing. Results for continued testing as well as a status of the molten salt design and anticipated commissioning will be presented.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

Non-Destructive Plutonium Assay in Pyroprocessing Bulk Materials with a 3D Boron-Coated-Straw Detector Array

Assessment of plutonium content through all the processing steps is needed and is a challenging task. While several destructive assay methods have been developed for nuclear material accountability, a nondestructive assay (NDA) system for the assessment of plutonium in bulk materials is still needed. This system should withstand pyroprocessing harsh environments and have consistent sensitivity and accuracy despite different fuel form factors. We aim to enable the accurate assessment of the plutonium content of nuclear material during pyroprocessing to improve the separation process and enhance its proliferation resistance. We plan to achieve this goal by developing and demonstrating a new 3D boron-coated-straw neutron detector array (3D-BCSDA) with high efficiency and spatial resolution.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Assessing the Impact of Increased Verification Measurements of Category III/IV Material Receipts

Revisions to the US Department of Energy (DOE) regulations for material control and accountability are expected to dramatically increase the number of verification measurements required upon receipt of nuclear material transfers. Material categories and types that were not routinely quantitatively measured upon receipt (Category III and IV) have been added to the more detailed regulations on shipments and receipts of nuclear materials. In anticipation of this change to the regulations, this project was initiated to identify measurement needs in the DOE complex with respect to performing these additional quantitative measurements. The results of surveying multiple DOE facilities to understand the scope of the impact and the potential measurement capability needs are presented.

Bean, Robert↗

Semi-automatic image annotation using 3D LiDAR projections and depth camera data

Efficient image annotation is necessary to utilize deep learning object recognition neural networks in nuclear safeguards, such as for the detection and localization of target objects like nuclear material containers (NMCs). This capability can help automate the inventory accounting of different types of NMCs within nuclear storage facilities. The conventional manual annotation process is labor-intensive and time-consuming, hindering the rapid deployment of deep learning models for NMC identifications. This paper introduces a novel semi-automatic method for annotating 2D images of nuclear material containers (NMCs) by combining 3D light detection and ranging (LiDAR) data with color and depth camera images collected from a handheld scan system. The annotation pipeline involves an operator manually marking new target objects on a LiDAR-generated map, and projecting these 3D locations to images, thereby automatically creating annotations from the projections. The semi-automatic approach significantly reduces manual efforts and the expertise in image annotation that is required to perform the task, allowing deep learning models to be trained on-site within a few hours. The paper compares the performance of models trained on datasets annotated through various methods, including semi-automatic, manual, and commercial annotation services. The evaluation demonstrates that the semi-automatic annotation method achieves comparable or superior results, with a mean average precision (mAP) above 0.9, showcasing its efficiency in training object recognition models. Additionally, the paper explores the application of the proposed method to instance segmentation, achieving promising results in detecting multiple types of NMCs in various formations.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

Support for Advanced Fuel Fabrication MC&A Approaches

This report summarizes the key activities of the Material Protection, Accounting, and Control Technologies (MPACT) program’s safeguards training work package for FY25. The work focused on two main areas: domestic safeguards training and the development of new technologies for nuclear material accounting and control (NMAC). A key development during this FY was the delivery of NMAC statistics for US Nuclear Regulatory Commission requirements refresher course. The course objective was to assist industry in meeting the MC&A program requirements for fuel cycle facilities; this training focused on front-end bulk fuel cycle processes. At the same time, a report was prepared on the research output of an effort that focused on the benefits of commercial fuel debundling for NMAC and waste management. The MPACT team evaluated various technologies and proposed a fuel debundling detector that integrates gamma spectroscopy and neutron detection as the most practical solution. The scope of activities under this work package for FY26 focuses on developing a fundamental nuclear material control plan, also known as MC&A plan, for tristructural isotropic (TRISO) fuel fabrication facilities. This plan will address the various NMAC requirements for facilities that handle Category II.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Threat Sources for Creating Synthetic Urban Search Data

Equivalent point source energy emission distributions were computed for various threat sources for use in simulating the detector responses for urban search scenarios. The sources include standard isotopic sources used in detector testing, medical and industrial sources occasionally encountered in urban searches, and several types of special nuclear materials. Most of the equivalent point source distributions represent small sources inside some amount of shielding, but the special nuclear material sources represent volumetrically distributed sources in spheres of metal. Text-based inputs for emission distributions are available for the Monte Carlo transport codes Monte Carlo N-Particle, SCALE/MAVRIC, and Omnibus/Shift, any of which can easily be converted to other formats. These sources were developed for use in the Radiological Anomaly Detection and Identification (RADAI) project and the follow-on project, the RADAI-Extended project, sponsored by the National Nuclear Security Administration Office of Defense Nuclear Nonproliferation Research and Development.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Corrosion testing needs and considerations for additively manufactured materials in nuclear reactors

Additive manufacturing (AM) technologies have developed rapidly in recent years, creating new opportunities and challenges for the nuclear industry; however, adoption requires that their corrosion performance be evaluated. Here, we discuss known reactor-specific corrosion issues for multiple reactor types and engineering concerns such as regulations and standards. A review of corrosion studies conducted on select AM alloys informs a discussion on key bulk and surface factors likely to impact corrosion behaviors. Recommendations to assess corrosion performance for AM materials are provided, including management of the unique nature of as-built AM surfaces and the inherent process variability that occurs for AM components.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

4th Big Data for Nuclear Power Plants Workshop 2023

The Ohio State University and Idaho National Laboratory organized the 4 th Big Data for Nuclear Power Plants Workshop in November, 2023 in Columbus, Ohio. Workshop topics were chosen to understand the challenges and gaps that need to be addressed to maximize the impact of data on the nuclear industry, as well as the associated applications and risks. Discussions were focused around six specific application areas: Operation and Maintenance; Machine Learning in Nuclear Materials and Advanced Manufacturing; Cybersecurity; High-Performance Computing and Massive Computation; Big Data and Digital Twins; and Nuclear Non-Proliferation. The opportunities, challenges, and risks identified in the six focus areas explored in this workshop are diverse, but some common themes emerge, such as the importance of data integrity, quality, coverage, privacy, and traceability. Big data and AI/ML tools can be leveraged to reduce costs, optimize human tasking, and reduce human error across various application areas. In order for the nuclear industry to benefit from big data and advanced analytic capabilities, it is essential to address challenges and risks, such as data privacy, model reliability, and computational resource availability. Learning from other industries that have successfully implemented big data and AI/ML technologies, like the aerospace industry, can help the nuclear industry successfully integrate these technologies.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Reducing the Risk of Airborne Contamination through Intelligent Container Surveillance

DOE Manual 441.1-1 provides a set of performance criteria that nuclear material storage containers must achieve to provide protection to the worker, public, and environment. At Los Alamos National Laboratory, the SAVY-4000 is the container of choice for nuclear material storage, meeting all Manual requirements. At the outset, polymer components of the SAVY 4000 were considered to be life-limiting components due to their performance degradation resulting from radiation exposure. However, recent annual surveillance results revealed another life-limiting phenomenon for the container: a deterioration of the package integrity through corrosion of the stainless steel components, primarily the body. Container surveillance remains the choice method of observing, measuring, and tracking container health in service.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

A Review of Nuclear Forensics: 2016-2020

The study of nuclear forensics harkens back to the Manhattan Project-era, when scientists first started to analyze the debris from the 1945 Trinity test. Political turmoil stemming from the Cold War and the rehabilitation of Germany following WWII has led to new challenges in international security involving nuclear proliferation. Nuclear materials have, on occasion, been lost, misplaced, or stolen from former Soviet countries, and illicit materials have been interdicted all over the world. The National Technical Nuclear Forensics Center (NTNFC) was established in 2006, and has been at the forefront of drive to advance nuclear forensic capabilities in the United States. The ultimate goal of nuclear forensics is to examine nuclear and other radioactive materials using analytical techniques to determine origin and history of the material, particularly in the context of law enforcement investigations. Nuclear forensics can be divided into two parts: predetonation and post-detonation. Pre-detonation forensics, as the name implies, is the investigation of a nuclear material or weapon that has not been detonated or involved in an explosion, whereas postdetonation forensics is the study of activation or fission products in debris or the environment following the use of a nuclear or radiological dispersal device (RDD). Both parts require a number of analytical chemical and radiochemical techniques to determine identification of the material. Many advancements in analytical techniques, including rapidity, sample size, and forensic signatures have been made in recent years. The analytical methods that can be used in a nuclear forensic investigation, such as mass spectrometry and gamma spectroscopy, have been described in detail in previous reviews, including Straub et.al, and will not be explained here. This review will discuss recent publications (from 2016 to present) describing advancements of techniques such as radiochronometry, morphology, development of novel reference materials, and inter-laboratory collaborations for both pre- and post-detonation nuclear forensics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗