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Worrall, Louise G.

Publications and source records attributed to Worrall, Louise G..

Neutron Coincidence Measurements of Uranium-233 Oxide

Renewed international interest in thorium-fueled advanced reactors has challenged the safeguards community to address future proliferation concerns. Thorium-based technology presents many benefits but does not eliminate the proliferation risks associated with producing and processing fissile material. A byproduct of thorium-fueled reactors is uranium-233, which is classified as a direct-use material. As a result, the development of new or improved methods to characterize and measure materials containing 233U must mirror the pace of development of reactors and facilities that produce such material. Research is underway to assess, develop, and test approaches for safeguarding nuclear materials within the thorium fuel cycle. Neutron signatures from the nondestructive assay (NDA) of materials containing 233U are being quantified to inform the potential characterization of these materials. Using a traditional neutron coincidence counter and a series of well-documented 233U oxide samples, initial measurements have been made to assess the feasibility of 233U characterization and discrimination from other uranium isotopes, primarily 235U, using a combination of measurement techniques and analysis methods. Data acquisition is performed in list mode, allowing for a variety of analyses to be performed on the raw data that is not available using traditional shift register technology. Measurements were performed in passive and active configurations to quantify the strength of signal and to validate simulations in support of this work. This paper presents and discusses the results of the initial measurements of 233U oxide performed at Oak Ridge National Laboratory.

Lockhart, Madeline↗

Safeguards for the Lithium Fluoride Thorium Reactor: A Preliminary Nuclear Material Control and Accounting Assessment

This report was prepared by Oak Ridge National Laboratory (ORNL) for Flibe Energy Inc. (FEI), a US-based advanced reactor company founded in 2011 and headquartered in Huntsville, Alabama. FEI is developing the lithium-fluoride thorium reactor (LFTR), which is a modern two-fluid molten salt reactor (MSR) design operating on a thorium/ 233 U fuel cycle. FEI intends for LFTR to become a self-sustaining clean energy source that can create or breed its own fuel from thorium. Each LFTR is intended to breed enough fissile material to compensate for the amount it consumes. Consequently it would not require fissile replenishment during its operational lifetime. This self-sustaining nature would eliminate the need for uranium enrichment infrastructure to support LFTRs after the first generation.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Molten Salt Reactor Signatures and Modeling Study

Molten salt reactor (MSR) technologies, either liquid fueled and cooled or only liquid cooled, pose specific, unique challenges for safeguards of the special nuclear material during the operation, fueling, and maintenance of the reactor. MSRs are one type of Generation IV technologies being invested in and considered for U.S. domestic fabrication primarily for electricity and process heat production. These designs have generated growing commercial interest for several reasons, including high (≈40%) thermal efficiency, ease of fueling, improved use of uranium fuel, potential utilization of thorium fuel, and proposed inherent safety features. U.S. companies have several planned designs that differ in fuel, cooling, and neutron energy spectrum. Driven by commercial interest and the intent of licensing MSRs, the U.S. Nuclear Regulatory Commission (NRC) has developed a vision and strategy to accommodate non-light water reactors (LWR), which include MSRs (U.S. Nuclear Regulatory Commission 2019). In addition, the Department of Energy (DOE) through the Office of Nuclear Energy (NE) Office of Advanced Reactor Technologies (ART), …sponsors research, development and deployment (RD&D) activities through its Next Generation Nuclear Plant (NGNP), Advanced Reactor Concepts (ARC), and Advanced Small Modular Reactor (aSMR) programs to promote safety, technical, economical, and environmental advancements of innovative Generation IV nuclear energy technologies. Reactor types considering the use of salts, liquid metals, or gases for coolant fall under both ARC and aSMR. Therefore, Research Design & Development is being pursued by DOE-NE through national laboratories, universities, and international and industrial collaborations. Additionally, the U.S. is a member of the Gen IV International Forum (GIF). The GIF is a cooperative, multinational organization to guide and carry out research and development needed for the GEN IV reactor systems (Forum 2018). GIF evaluated numerous reactor concepts and down-selected to the six most feasible advanced reactor technologies: gas-cooled fast reactor (GFR), lead-cooled fast reactor (LFR), MSR, supercritical watercooled reactor (SCWR), sodium-cooled fast reactor (SFR), and very high temperature reactor (VHTR). In support of the growing interest domestically and internationally, the Materials Protection, Accounting, and Control Technologies (MPACT) campaign, under the DOE-NE Fuel Cycle Technologies (FCT) program, engages in R&D activities by developing advanced instrumentation and analysis for safeguards and security of modern, advanced nuclear fuel cycle (non-LWR) facilities. Because of the historic experience in the operation of the Aircraft Reactor Experiment (ARE) and the Molten Salt Reactor Experiment (MSRE) (Robertson, MSRE Design and Operations Report Part I 1965), Oak Ridge National Laboratory (ORNL) is heavily engaged in the various R&D activities through the DOE complex related to MSRs including national technical leadership of the DOE-NE MSR campaign. This report discusses and presents the outcomes of the FY19 MPACT MSR Safeguards task. The challenges presented by MSRs for nuclear material accountancy and control (NMAC) and associated safeguards will be investigated. The objective of this research is to explore and compile the safeguards requirements and identify measurement signatures through an initial high-level MSR design and develop complementary advanced simulation and modeling capabilities. A high-level ORNL-developed MSR design called the Molten Salt Demonstration Reactor (MSDR) (Bettis, Alexander and Watts 1972) was used as the target reactor design for this research. The MSDR model incorporates technology from the MSRE and the Molten Salt Breeder Reactor (Robertson, Conceptual Design of a Single-Fluid Molten-Salt Breeder Reactor 1971). But the MSDR is a 750 MWth graphite moderated liquid fueled (low-enriched uranium) MSR compared to the MSRE’s of 7.5 MWth. The focus of this report is to discuss the evaluation of novel signatures, correlations, and indicators to understand the applicability of current safeguards instrumentation to MSRs using the modeling results from the MSDR.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Development of a Neutron List Mode Collar (LMCL) and a List Mode Response Matrix Analysis Concept

This report was prepared for the Safeguards Program of the US Department of Energy’s (DOE’s) National Nuclear Security Administration (NNSA), Office of Defense Nuclear Nonproliferation Research and Development (DNN R&D). The report presents the development of the neutron nondestructive assay system, the List Mode Collar (LMCL) for the project OR16-List Mode for Collar-PD1La “List Mode Response Matrix for Advanced Correlated Neutron Analysis for Nuclear Safeguards.” The new list mode electronics developed under this project, and a spatial analysis concept called the List Mode Response Matrix are also described in this report. Analysis algorithms based on classification methods are published in a separate report. This research addresses the need to expand the capabilities of current nondestructive assay systems used for nuclear safeguards applications and considers the sustainability of safeguards technologies by the development of a “retrofit” concept using electronics based on modern standards. Furthermore, employing list mode data acquisition enabled the development of a spatial analysis concept and empirical measurement of a spatial response not previously used for safeguards neutron counting applications or measured in a traditional neutron collar detector and, therefore, provides new capability.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Safeguards Technology for Thorium Fuel Cycles: Research and Development Needs Assessment and Recommendations

This report presents Safeguards Technology for Thorium Fuel Cycles: Research and Development Needs Assessment and Recommendations prepared for the National Nuclear Security Administration (NNSA) Office of Defense Nuclear Nonproliferation Research and Development (DNN R&D) Safeguards Program by a multilaboratory team from Oak Ridge National Laboratory, Los Alamos National Laboratory, and Y-12 National Security Complex. It documents key findings of a 2-year scoping study on “Safeguards Technology Needs Assessment for Leading Thorium Fuel Cycles” (project OR18-V-SG Tec Needs Th Fuel Cycles-PD1Lb).

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Development and evaluation of a list mode neutron coincidence collar for spatial response measurements of fresh fuel assemblies

A traditional safeguards neutron coincidence counting system, the Neutron Coincidence Collar, has been modified to incorporate individual preamplifiers on each of its 18 3He tubes in active interrogation mode. When used with list mode data acquisition (LMDA) and analysis, a signal from each 3He tube can be recorded and analyzed to allow a spatial response measurement to be performed on an item based on count rate and 3He tube location within the system. The ultimate goal of this project is to demonstrate the capabilities of a list mode response matrix for the nondestructive assay of fresh nuclear fuel assemblies. To enable partial defect detection of fuel pin locations and absences within an assembly, the project aims to extend well-established correlated neutron analysis techniques on a preexisting Neutron Coincidence Collar by extracting a greater number of useful signatures from the system than are currently generated. LMDA, combined with the addition of multiple preamplifiers, facilitates this capability by increasing the number of simultaneous signals that can be measured; this allows an in-depth analysis of neutron coincidence events to determine a fissioning item’s location based on the measured doubles count rate in various channel logic coincidence combinations. All of this can be done from a single measurement pulse train in offline analysis, which is the major benefit provided by LMDA. Through various stages of development and testing, a Mirion Technologies model JCC-71 Neutron Coincidence Collar has been successfully retrofit with modern electronics designed in-house at Oak Ridge National Laboratory, matching preexisting JAB-01 electronics performance, while maintaining the original system footprint. This paper presents these various stages of development and experimental evaluation of the proof of concept system.

Moore, Angela S.↗

Machine Learning Approaches for Nuclear Material Accounting Data from Irradiation and Reprocessing

We are currently exploring data analysis methods for their ability to strengthen the synthesis and evaluation of information generated within domestic and international safeguard regimes. Safeguard data typically includes rich heterogenous datasets amenable to advanced data analytics methods, such as machine learning. We have converted transactional data containing both numerical and categorical attributes from a domestic nuclear material control and accountability (NMC&A) system into a low-dimensional numerical structure via linear principal component analysis. This data representation allows for global structure discovery via cluster analysis, which can characterize the typical behavior of each of the primary types of transaction events. Furthermore, the structure of the top principal components captures the “typical behavior” of the data and is thus amenable to anomaly detection through statistical hypothesis testing. We explored this capability by generating erroneous permutations of the data and computing the Q-residual quantity increase associated with the information loss when these data are projected into the low-dimensional principal component analysis space representative of typical transactions.Future work will focus on identifying data transformations (e.g., graph networks) that more closely align with the inherent structure of these transactions to explain more salient information and disambiguate the underlying nuclear process—in this case, irradiation and reprocessing—from artifacts of NMC&A system transactional record keeping data.

Drescher, Adam↗

Updates to Relevance Vector Machine: Multiclass Classification, Variable Selection, and Proof-of-Concept Application to Safeguards Fresh Fuel Verification using List-Mode Neutron Collar Data

To expand the capabilities of safeguards authorities to verify the integrity of fresh fuel assemblies, Oak Ridge National Laboratory has retrofit the existing electronics of the JCC-71 uranium neutron coincidence collar, which contains 18 3 He neutron detectors and an external 241 AmLi(α, n) neutron interrogation source arranged to surround a fresh nuclear fuel assembly. The new electronics system allows analysts to record list-mode neutron multiplicity data in addition to the singles and doubles rates that are currently measured. Based on previous proof-of-concept research, analysis of these new data will identify off-normal fuel configurations in an assembly and characterize or localize the specific partial fuel defects. The purpose of this report it to document the analysis algorithm development and then to demonstrate its capability for the safeguards verification of fresh fuel assemblies using list mode neutron collar data. To analyze the complex list-mode data collected with the upgraded uranium neutron collar, multivariate classification algorithms are being developed using a novel classification method, the relevance vector machine. This approach may be applied to multiclass problems to estimate the probability that test data belongs to one of many possible classes of data. In addition, our method identifies the most useful variables/channels for making predictions, which illuminates the basis for the model’s predictions, and this interpretability is largely unique among data analytics methods. Variable selection occurs during model training and parameter tuning and does not need any external hyperparameter tuning routines. Finally, we apply the modified relevance vector machine to a simulated dataset of list-mode neutron collar data generated with the radiation transport code MCNP. The method can correctly identify off-normal fuel configurations, categorize the data according to four fuel defect scenarios, and rank the channels in the data according to prediction utility. For nuclear safeguards applications, it is concluded that this method has the potential to increase the sensitivity and reliability to detect missing fuel rods from a standard 17 x 17 Pressurized Water Reactor (PWR) fresh fuel assembly. Within this analysis, “off-normal” (i.e., missing fuel rods) were correctly classified in 17 simulated test scenarios with one quarter (25%) of the fresh fuel rods missing using a training data set of 58 simulated measurements.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗