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Integrating Data Sources for Improved Safeguards and Accountancy of Electrochemical Fuel Reprocessing Systems. Final Report

Electrochemical reprocessing (also commonly known as “pyroprocessing”) of used nuclear fuel is an alternative to aqueous reprocessing that confers a number of advantages, including the ability to process more recently-discharged fuel, smaller resultant waste volumes, and the lack of isolation of plutonium in the product stream. While electrochemical reprocessing systems have seen a significant research and development effort, nuclear safeguards and security of these systems remains under-developed, particularly given the significant differences in operating environment and process flowsheet compared with established aqueous methods. Objective 4 of DOE’s nuclear energy research and development activities in Nuclear Energy Research and Development Roadmap is: “Understand and minimize the risks of nuclear proliferation and terrorism.” Material Control & Accountancy (MC&A) programs at nuclear processing plants deter and detect theft and diversion of nuclear material by both outside and inside adversaries. Empirical modeling and data analytics of online measurements and state indicators can improve the timeliness of detection and reduce the uncertainty in accountancy measures. To support the development and demonstration of such methods, data are needed that capture expected measurement values collected throughout electrochemical reprocessing facilities. A review of the available literature of current research in measurements for electrochemical reprocessing systems identified twenty-two candidate measurement methodologies, which characterize fuel/salt composition, concentrations of various isotopes and elements, and operational parameters throughout the reprocessing facility. Four primary measurement methodologies have been simulated based on either physical simulations or empirical correlations: gamma emissions, neutron emissions, hybrid k-edge densitometry (HKED), and cyclic voltammetry. Initial investigation into the use of these measures for process monitoring and detection suggests the approach is viable and worthy of further investigation. This report summarizes efforts to generate signatures of key measurements during operation of electrochemical reprocessing facilities and initial investigation of data analytics to support process monitoring, diversion detection, and accountancy.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Using Cosmic Ray Muons to Assess Geological Characteristics in the Subsurface

Cosmic rays are energetic nuclei and elementary particles that originate from stars and intergalactic events. The interaction of these particles with the upper atmosphere produces a wide range of secondary particles that reach the surface of the earth, of which muons are the most prominent. With enough energy, muons can travel up to a few kilometers beneath the surface of the earth before being stopped completely. The terrestrial muon flux profile and associated zenith angle can be utilized to determine geological characteristics of a location (e.g., rock overburden and density) without having to use conventional methods such as boreholes. This work uses a low-power plastic scintillator-based muon detection system as a prototype for this non-destructive geological assay methodology. Four custom designed 102 cm x 51 cm x 5 cm plastic scintillation panels are used to realize two orthogonal detection planes. Optical photons from each scintillation panel are read using OnSemi J-Series 4x4 silicon photomultiplier (SiPM) arrays in conjunction with preamplifiers. Simultaneous triggers between detectors from two planes indicate a coincidence event which is recorded using the QuarkNet data acquisition system (DAQ) from Fermi National Accelerator Laboratory. A custom detector holder was designed to securely mount the detection system and rotate the panels along the zenith to collect data at variable angles. In order to quantify the systematic uncertainties associated with the detector, such as energy depositions and angular resolution of the detector design, a Monte Carlo (MC) simulation using Geant4 is being developed. Cosmic ray flux prediction will be included in the project by adding the CORSIKA MC code to the simulation toolchain. Simulated and experimental data will drive the development and validation of a reconstruction algorithm that, upon completion, is expected to predict average overburden and rock density. Extended detector exposure to muons can be used as a means to understand changes in the surrounding environment like rock porosity. On the experimental front, muons will initially be measured at the surface, establishing the baseline flux. This is followed by recording the muon flux at variable depths and zenith angles, where the data will be used by the reconstruction algorithm to predict the overburden. The result will be benchmarked against geological surveys. The measured flux data will also be used to benchmark independent and established models. Successful proof-of-concept demonstration of this technology can open doors for long term non-invasive geological monitoring. The detector design, experimental methodology, and the benchmarking efforts are detailed in this work.

Gadey, Harish Reddy↗

The 2023 terahertz science and technology roadmap

Abstract Terahertz (THz) radiation encompasses a wide spectral range within the electromagnetic spectrum that extends from microwaves to the far infrared (100 GHz–∼30 THz). Within its frequency boundaries exist a broad variety of scientific disciplines that have presented, and continue to present, technical challenges to researchers. During the past 50 years, for instance, the demands of the scientific community have substantially evolved and with a need for advanced instrumentation to support radio astronomy, Earth observation, weather forecasting, security imaging, telecommunications, non-destructive device testing and much more. Furthermore, applications have required an emergence of technology from the laboratory environment to production-scale supply and in-the-field deployments ranging from harsh ground-based locations to deep space. In addressing these requirements, the research and development community has advanced related technology and bridged the transition between electronics and photonics that high frequency operation demands. The multidisciplinary nature of THz work was our stimulus for creating the 2017 THz Science and Technology Roadmap (Dhillon et al 2017 J. Phys. D: Appl. Phys. 50 043001). As one might envisage, though, there remains much to explore both scientifically and technically and the field has continued to develop and expand rapidly. It is timely, therefore, to revise our previous roadmap and in this 2023 version we both provide an update on key developments in established technical areas that have important scientific and public benefit, and highlight new and emerging areas that show particular promise. The developments that we describe thus span from fundamental scientific research, such as THz astronomy and the emergent area of THz quantum optics, to highly applied and commercially and societally impactful subjects that include 6G THz communications, medical imaging, and climate monitoring and prediction. Our Roadmap vision draws upon the expertise and perspective of multiple international specialists that together provide an overview of past developments and the likely challenges facing the field of THz science and technology in future decades. The document is written in a form that is accessible to policy makers who wish to gain an overview of the current state of the THz art, and for the non-specialist and curious who wish to understand available technology and challenges. A such, our experts deliver a ‘snapshot’ introduction to the current status of the field and provide suggestions for exciting future technical development directions. Ultimately, we intend the Roadmap to portray the advantages and benefits of the THz domain and to stimulate further exploration of the field in support of scientific research and commercial realisation.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Data-driven Cyberattack Detection for Photovoltaic (PV) Systems through Analyzing Micro-PMU Data

With increasing exposure to software-based sensing and control, Photovoltaic (PV) systems are facing higher risks of cyber attacks. Here, to ensure the system stability and minimize potential economic losses, it is imperative to monitor operating states and detect attacks at the early stage. To meet this demand, Micro-Phasor Measurement Units (μPMU) are increasingly popular in monitoring distribution networks. However, due to the relatively low sampling rate, μPMU has not yet been used to detect and classify cyber-attacks in power electronics enabled smart grid. To our knowledge, this is one of the first attempts to use μPMU to detect cyber attacks that degrade the performance of power electronics systems. We propose to apply data-driven methods on micro-PMU data to implement attack detection. We have evaluated data-driven methods, including decision tree (DT), K-nearest neighbor (KNN), support vector machine (SVM), artificial neural network (ANN), long short-term memory (LSTM) and convolutional neural network (CNN). The proposed CNN model achieves the required performances with the highest 99.23% accuracy and 0.9963 F 1 score.

14 SOLAR ENERGY↗

Energy Improvements of Fire Station 71

Since 2018, the City of Shawnee, Kansas has completed two phases of the State of Kansas Facility Conservation Improvement Program (FCIP), an initiative that guarantees operational cost and energy savings through targeted construction improvements on City facilities and infrastructure. The City is currently in the third phase of this FCIP, where one of the projects included an investment in energy improvements for Fire Station 71 (FS 71). The City partnered with Navitas, an Energy Service Company (ESCO), to implement a Photovoltaic Solar Array on FS71. The purpose of this project was to invest in sustainable building improvements with Energy Conservation Measures (ECM) to bring cost savings to the City and to provide sustainable benefits to the residents of Shawnee. In the first task of the project, Navitas collaborated with the City of Shawnee and the Community Development Department to determine the optimal layout and schedule for the installation of the solar array on FS 71. In the second task of the project, Navitas installed the 99.8 kW DC Photovoltaic solar array system. This system installation comprised of racking, inverters, optimizers, load center, and disconnect, which were all installed at a total ECM price of $\$$247,948. The third task focused on start-up and commissioning of the array. Navitas installed a real-time data analytics information management system integrated with utility meters, which evaluates the operations of the utility system and verifies operation of equipment and ensures optimum operation for energy efficiency. In the final task of this project, this analytics system was used for monitoring and verification, which will continue to be used to evaluate the success of the project for the coming years. The primary goal of the project was to install the 99.8 kW DC PV solar array at FS 71 to demonstrate the viability of solar energy systems in essential municipal facilities. Fire stations are energy demanding structures, as they require a constant intake of power and have a high baseline energy usage. The success of solar arrays on a fire station exemplifies their energy efficiency and effectiveness and displays their potential for application on other city facilities. By installing a solar array at such a facility, the City sought not only to offset electricity usage but also to serve as a model for ECMs in other municipal facilities and infrastructure projects. From an economic standpoint, this project demonstrates the feasibility of renewable energy at the municipal level. The total project cost of $\$$247,948 was split evenly between city funds and award funding, minimizing financial risk while ensuring guaranteed long-term savings. Any excess savings that are beyond the guaranteed minimums remain with the city, which enables future investment in sustainable energy initiatives. This project provides many benefits to the public. In addition to reducing the environmental footprint of city operations, it lowers taxpayer-funded utility spending and improves the energy security of a critical facility. The knowledge gained from this implementation motivates the City to focus on similar efforts across other public facilities in future FCIP phases and other City projects.

14 SOLAR ENERGY↗

Los Alamos National Laboratory Floodplain Assessment for the West Road Post and Cable Fencing Project

The National Nuclear Security Administration (NNSA), a semi-autonomous agency within the U.S. Department of Energy (DOE), is proposing to take action at Los Alamos National Laboratory (LANL) to install post and cable or in-kind barriers along West Road at selected locations near the Los Alamos County ice-skating rink in Los Alamos Canyon (Figure 1). The proposed project is intended to improve vehicular and pedestrian safety on West Road by reducing traffic hazards associated with unsafe roadside parking and reduce wildland fire hazards associated with vehicles driving and parking on vegetation. West Road crosses approximately 0.35 miles (mi.) (1,900 feet (ft.)) of the Los Alamos Canyon floodplain at the bottom of Los Alamos Canyon. Project activities within the floodplain include blocking access to the informal roadside parking along either side of West Road in Los Alamos Canyon.

42 ENGINEERING↗

US Department of Energy, Office of Science High Performance Computing Facility Operational Assessment 2021: Oak Ridge Leadership Computing Facility

Oak Ridge National Laboratory’s (ORNL’s) Leadership Computing Facility (OLCF) continues to surpass its operational target goals of supporting users; delivering fast, reliable computational ecosystems; creating innovative solutions for high-performance computing (HPC) needs; contributing to the community to build the next generation HPC workforce, and managing risks, safety, and security associated with operating some of the most powerful computers in the world. The results can be seen in the cutting-edge science conducted by users and the praise from the research community. Calendar year (CY) 2021 saw continued excellence in research supported by the OLCF’s leadership-class computing resources, including Summit (the nation’s most powerful supercomputer), the global scratch file system Alpine, the Scalable Protected Infrastructure (SPI), the Exploratory Visualization Environment for Research in Science and Technology (EVEREST), and the archival mass-storage resource High-Performance Storage System (HPSS). While maintaining access and exceptional user support for Summit, the OLCF continued to make progress on the installation and deployment of Frontier, which will be the nation’s first exascale system when it comes online at the start of CY 2023. Users have already begun running and optimizing scientific codes on Crusher, the OLCF test and development system equipped with Frontier’s architecture. Throughout the year, the OLCF maintained a strong culture of operational excellence, including risk management, workplace safety, and cybersecurity. The OLCF’s rigorous risk management strategy anticipated and mitigated risks, and at this time there are no high-priority operational risks. Similarly, ORNL and the OLCF were committed to operating under the US Department of Energy’s (DOE’s) safety regulations that ensure a safe workplace. Technical staff tracked and monitored existing threats and vulnerabilities within the OLCF while continually developing tools and practices to enhance operations without increasing the facility’s risk. CY 2021 was filled with outstanding results and accomplishments, including a very high rating from users on overall satisfaction for the eighth consecutive year; a tremendous number of node hours delivered to 1,671 researchers on Summit; and the successful delivery of the allocation split of roughly 60%, 20%, and 20% of core-hours offered for the Innovative and Novel Computational Impact on Theory and Experiment (INCITE), Advanced Scientific Computing Research Leadership Computing Challenge (ALCC), and Director’s Discretionary (DD) programs, respectively (Section 2). COVID-19 research remained a focus in 2021, and the ALCC and DD programs allocated over 1 million Summit hours to the COVID-19 High Performance Computing Consortium. These accomplishments, coupled with the high utilization rates (i.e., overall and capability usage), represent the fulfillment of the promise of leadership class machines: efficient facilitation of leadership-class computational applications.

97 MATHEMATICS AND COMPUTING↗

Frost prediction using machine learning and deep neural network models

This study describes accurate, computationally efficient models that can be implemented for practical use in predicting frost events for point-scale agricultural applications. Frost damage in agriculture is a costly burden to farmers and global food security alike. Timely prediction of frost events is important to reduce the cost of agricultural frost damage and traditional numerical weather forecasts are often inaccurate at the field-scale in complex terrain. In this paper, we developed machine learning (ML) algorithms for the prediction of such frost events near Alcalde, NM at the point-scale. ML algorithms investigated include deep neural network, convolution neural networks, and random forest models at lead-times of 6–48 h. Our results show promising accuracy (6-h prediction RMSE = 1.53–1.72°C) for use in frost and minimum temperature prediction applications. Seasonal differences in model predictions resulted in a slight negative bias during Spring and Summer months and a positive bias in Fall and Winter months. Additionally, we tested the model transferability by continuing training and testing using data from sensors at a nearby farm. We calculated the feature importance of the random forest models and were able to determine which parameters provided the models with the most useful information for predictions. We determined that soil temperature is a key parameter in longer term predictions (>24 h), while other temperature related parameters provide the majority of information for shorter term predictions. The model error compared favorable to previous ML based frost studies and outperformed the physically based High Resolution Rapid Refresh forecasting system making our ML-models attractive for deployment toward real-time monitoring of frost events and damage at commercial farming operations.

97 MATHEMATICS AND COMPUTING↗

Radiological Recovery Logistics Tool - 20161

Argonne is building and testing a tool, the Radiological Recovery Logistics Tool (RRLT), that can be used during the response and recovery from a radiological or nuclear incident to effectively allocate appropriate commercial and public works equipment to mitigate, remove, and contain radiological contamination. The requirements for this tool - as well as development of the resulting software - is overseen by a steering committee of stakeholders from DHS's National Urban Security Technology Laboratory (NUSTL), the Federal Emergency Management Agency (FEMA), and the Environmental Protection Agency (EPA). One essential requirement is for RRLT to support the efficient and appropriate allocation of resources for a radiological response. Subsequent discussions between ANL and stakeholders have solidified the nature of this support to include identification of the types of resources to be allocated. The study reported in this paper has both factored fundamental concepts and connections out of this identification process and created a Knowledge Base detailing support goals, response scenarios, and efficacy information on dozens of equipment types. In short, RRLT will dynamically apply these findings to situational conditions surrounding contamination incidents. RRLT's Domain, the model of elements, ideas and relationships with which the tool will work, draws concepts from technical reports and stakeholder vocabularies to connect response goals and scenarios to types of equipment that offer utility towards those goals in those scenarios. RRLT's Knowledge Base will contain details on dozens of equipment types and facilitate the operator's discovery and consumption of these details most pertinent to a dynamically selected subset of goals. The core of its Domain Model is based on a report authored by this team. This report [1] contains a comprehensive list of proposed equipment to accomplish various missions or scenarios that might arise after a large-scale radiological contamination incident in an urban environment or critical infrastructure. The report divides potential response and recovery efforts into five support goals: Survey and monitoring of the contaminated area; Mitigation of received dose to first responders: Decontamination (gross and final) of buildings, vehicles, roadways, parks, and other surfaces: Waste management of solid waste generated during recovery operations: and Containment of wastewater and other waste generated during the response and recovery phases. RRLT's development is driven by use cases. A use case is an intention with which a user approaches the software. Use cases are grouped into delivery increments to schedule development, testing, and presentation to stakeholders. This model partitions the system into seven increments: User Arrival and Authentication, Search and Navigation, Equipment Recommendation, Plan Management, Content Management, and Expanded Access. Once a user 15 authenticated, RRLT will present the user with a dashboard that allows them to explore or search RRLT's content. The dashboard will also include a 'Plan' panel for collecting decisions and relevant observations about an incident at hand to facilitate development of an equipment list. RRLT will offer three general modes of access to items in the knowledge base: - Keyword search for direct discovery of items, - Navigation along predetermined paths from recovery goal towards equipment types, and - Interactive guidance towards equipment types by an autonomous software agent: the Equipment Recommendation Wizard. This presentation will detail progress in the development of the RRLT and also discuss opportunities for those interested in providing feedback on its content and functionality. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Sequential Perturbation-based FDIA Detection using DERs for Unbalanced Distribution System

The power distribution system with its reliance on automated monitoring and control infrastructure makes it a complicated cyber-physical system and vulnerable to various cyber-attacks. This paper proposes a moving target defense inspired false data injection attack (FDIA) detection mechanism for an unbalanced distribution system. In the proposed grid diagnosis service framework, the distribution system operator judiciously manipulates power outputs of a subset of inverter-based distribution energy resources (DERs) to create secret low magnitude voltage perturbations which are inconsequential to the normal operation of the grid. A mixed-integer-linear-programming algorithm is developed to select the optimal set of DERs that can create a voltage perturbation signal of the required magnitude at each sensor location at a minimum cost. Then, a sequential detector is applied that detects for the FDIA as measurements are received from individual sensors. The performance of the proposed perturbation-based FDIA detection framework is demonstrated via simulation of the IEEE 123 bus test system.

Attack Detection↗

Subtask 1.3 – Integrated Carbon Capture and Storage for North Dakota Ethanol Production

The Energy & Environmental Research Center (EERC), in partnership with Red Trail Energy, LLC (RTE), a North Dakota ethanol producer; the North Dakota Industrial Commission (NDIC) Renewable Energy Program (REP); and the U.S. Department of Energy (DOE), conducted a feasibility and implementation study for a commercial carbon capture and storage (CCS) effort. This subtask provided technical support and developed recommended practices of how small-scale industrial CO2 emitters (<1,000,000 tonnes of CO2 emitted annually) may economically deploy CCS. The 64-million-gallon dry mill RTE ethanol facility, emitting an average 180,000 tonnes of CO2 annually, was the subject of the case study. The positive outcome of this research, which shows technical and economic potential for ethanol–CCS in North Dakota, has resulted in RTE acquiring an approved Permit to Drill on December 2, 2019, for a stratigraphic test well in early 2020, a necessary step toward a North Dakota CO2 Storage Facility Permit (SFP) for the RTE CCS effort. Outcomes include 1) validating the Broom Creek Formation as a regional target for CCS, 2) determining the full carbon life cycle of an industrial fuel production facility with CCS, 3) developing a field implementation plan (FIP) for small-scale CCS, and 4) determining the validity and pathway for using CCS to meet low-carbon fuel (LCF) standards. The technical team included the EERC, RTE, Trimeric Corporation, Schlumberger Carbon Services, and Computer Modelling Group (CMG). Findings from activities conducted November 2016 – May 2020 are summarized as follows. Several key steps have been accomplished toward validating the Broom Creek Formation as a CO2 injection and storage target at the RTE CCS site, including verification of the presence and structure of sandstone layers that may comprise the potential CO2 storage reservoir and the several thousand feet of overlying confining zone. Work included site characterization using existing data, interpretation of seismic data within the study area, and geologic modeling simulation of CO2 injection. Interpreted results estimate 3000 feet of confining zone between the Broom Creek Formation (storage target) and the lowermost underground source of drinking water (e.g., the Fox Hills Formation). The thickness of the Broom Creek injection target varies 230–420 ft within the survey area. Results were used to inform the location of a stratigraphic test well and associated characterization test program. No impediments were identified within the targeted CO2 storage complex that would prevent the project from moving forward. A stratigraphic test well is the next step to validate these results and to acquire remaining data necessary to develop a North Dakota CO2 SFP application. The EERC generated full carbon life cycle estimates for CCS integration with the RTE ethanol facility. Results indicated that an average 40% reduction in CO2 emissions is possible through CCS implementation. Approximately half of the carbon in the overall life cycle for a dry mill ethanol plant is generated through the fermentation process and emitted to the atmosphere; this is the CO2 stream targeted for CCS. The remaining carbon is attributed to corn feedstock farming (diesel, fertilizer), energy for fuel processing (natural gas, electricity), and transportation (diesel) of the fuel product. Life cycle carbon estimates are also affected by the anticipated energy consumption of a potential capture facility, which depend on the type of CO2 product generated. For example, a 30%–40% net CO2 emission reduction is estimated if a liquefied CO2 facility were incorporated compared to a 40%–50% net CO2 reduction if a supercritical “injection-grade” CO2 product is generated; i.e., more energy is required to further refine the CO2 stream, affecting the full carbon life cycle estimates. A CCS FIP was developed and initiated at the RTE CCS site, resulting in the development of several guidance documents: a CO2 Capture Process Design Package, a North Dakota CO2 geologic Storage Permits Template, and a Public Outreach Package for CCS in North Dakota. General FIP components include CO2 capture system, pipeline and well designs; monitoring, verification, and accounting (MVA) plans; geologic characterization and testing programs; and permitting and outreach plans. Vendor bids were also acquired for the CO2 liquefaction facility. Near-surface characterization (groundwater and soil gas sampling) and geologic characterization (seismic survey) were initiated to inform development of a UIC Class VI-compliant MVA plan compliant with a North Dakota CO2 SFP. Designs (well and geologic testing) were completed for a stratigraphic test well compliant with a North Dakota CO2 SFP. In addition, the outreach plan was executed, including community open houses, meetings with city/county/state officials, and development of public materials. Although other entities continued to mature incentive programs in 2019–2020, California and the Internal Revenue Service (IRS) currently provide the most advanced economic opportunities for CCS integrated with fuel production. The California Low-Carbon Fuel Standard (LCFS) adopted a CCS Protocol in January 2019, allowing submittal of a design-based pathway (DBP) application for an approved temporary (not certified) carbon intensity value for a fully engineered facility. An ethanol–CCS DBP application to the California LCFS Program (officially approved February 28, 2020) was developed to show that the RTE CCS effort meets LCFS requirements. The approved DBP provides confidence to advance the project and supports potential investments. Other entities continue to mature incentive programs. The IRS issued guidance in February 2020 that addresses the definition of beginning of construction and revenue procedure on partnerships for the Enhancement of Carbon Dioxide Sequestration Credit (a.k.a. Section 45Q) CCS tax credit program; the IRS anticipates issuing further guidance on issues such as secure geologic storage, utilization qualifications, and recapture of claimed credits. Maturing incentive programs coupled with workable permitting regulations provide confidence to advance CCS projects in North Dakota and support financial investment to proceed with designing, constructing, and implementing CCS projects at small-scale fuel production facilities. The largest hurdles for CCS implementation at small-scale industrial systems are often business/economic-related (i.e., not technical). Market uncertainty already exists for agriculture-based alternative fuels such as corn ethanol, for which production has increased by ~33%, and prices have correspondingly lowered since 2015. Passing the Section 45Q tax credit program improves economic feasibility for CCS but may require external investors for a small business to achieve maximum benefits. Public–private partnerships with NDIC and DOE have resulted in foundational technical and regulatory knowledge, growing stakeholder confidence, and a pathway to implementation that enables similar industrial CCS projects in the region to advance. This subtask was funded through the EERC–DOE Joint Program on Research and Development for Fossil Energy-Related Resources Cooperative Agreement No. DE-FE0024233. Nonfederal funding was provided by NDIC and RTE. The authors would also like to thank CMG, ESRI, IHS, Neuralog, and Schlumberger for allowing the use of their software packages in support of this work.

42 ENGINEERING↗

Gamma-Ray and Cosmic Ray Muon Modalities for Cargo Inspection

Screening and inspection of cargo containers are two essential methods to nondestructively examine the contents of shipment. These methods enable the detection of illicit transportation of unauthorized materials such as nuclear and radioactive materials, explosives, drugs, and so on, typically at borders or secure facilities. Although high-energy X-ray transmission is a standard system and is widely used for cargo inspection, the inherent challenges of high false-positive rates and high attenuation factors necessitate the development of complementary techniques that can increase the detection efficiency and accuracy in large and dense materials. Gamma-rays, which possess higher penetration characteristics because of their high energy, offer an alternative nonintrusive modality for cargo scanning. They represent a promising inspection method when compared to X-rays for three reasons: (1) improved ability to detect nuclear and radioactive materials, (2) higher inspection throughput rates, and (3) lower false-positive rates. Currently, there are two main gamma-ray inspection techniques, active and passive interrogation. Active interrogation can be further grouped into (1) gamma-ray transmission imaging and (2) neutron-induced gamma-ray emission detection. Gamma-ray transmission imaging utilizes differences in material densities for mapping the shipment contents and detecting anomalies. It is analogous to the X-ray transmission method; however, the high-energy photons make it more difficult to shield against, which enables more efficient performance in large and dense material inspection. Neutron-induced gamma-ray emission inspection is designed for the detection of nuclear and radioactive material because those materials emit characteristic gamma-rays when they are activated by neutron absorption. On the other hand, passive interrogation techniques rely on high-efficiency detectors to detect radiation emitted from hidden special nuclear or other radioactive materials. Similar to passive interrogation, cosmic ray muon monitoring and imaging are relatively new techniques that do not require external radioactive sources. These techniques have received attention as a potential next-generation radiographic probe to identify illicit transportation of nuclear and radioactive materials in cargo containers. Cosmic ray muons have unique features, (1) much higher energies than X-rays or gamma-rays (on the order of 10−1—104 GeV), (2) enhanced penetration capability, and (3) natural occurrence, thereby eliminating the need for induced radiation sources. These features enable cosmic ray muons to be utilized for detection of special nuclear materials in high-background-noise environments. By analyzing incoming and outgoing muon trajectories, scattering angles, and energies, it has been shown that it would be possible to locate hidden and well-shielded materials in cargo containers via three-dimensional muon tomography images or signal analysis. Gamma-rays, cosmic ray muons, and other nonintrusive cargo inspection modalities are complementary to each other, allowing them to address various cargo inspection conditions (i.e., scanning time, cost, radiation exposure level, and types of target materials). This chapter presents a detailed review of the theoretical fundamentals and technical principles behind the current gamma-ray and cosmic ray muon modalities for cargo inspection. Additionally, critical assessments and suggestions for the future directions to advance the use of gamma and muon modalities are discussed.

Bae, Junghyun↗

In Situ Atmospheric Plume Thermometry via Carbon Monoxide Spectral Profile: Laboratory and Field Validation

For small molecules with large rotational constants, knowing the relative intensities of the ro-vibrational transitions can be used to determine the temperature within a gas plume. We demonstrate the use of carbon monoxide (CO) as an in situ spectroscopic probe of gas plume temperature by application of both laboratory and standoff Fourier transform infrared spectroscopy to monitor the CO spectral response at different temperatures. Here, the measured CO rotational contours were analyzed using a simple Boltzmann model to deduce the population distribution of the J-levels, from which the in-plume temperature is deduced. The method was vetted by comparing deduced temperatures in both static laboratory measurements of known temperatures, as well as field measurements using a simulated smokestack release. For the smokestack experiments, spectroscopically deduced temperatures were compared to readings from a series of thermocouples placed at strategically sampled distances along the plume trajectory. Both the spectroscopically-derived and thermocouple-measured temperatures revealed an expansion-induced (mixing) rapid cooling of the plume, with the infrared thermometry values displaying greater temperature values which are believed to better represent the actual plume temperatures.

Analysis of rotational structure↗

Momentum informed muon scattering tomography for monitoring spent nuclear fuels in dry storage cask

Development of an effective monitoring method for spent nuclear fuel (SNF) in a dry storage cask (DSC) is important to meet the increasing demand for dry storage investigations. The DSC investigation should provide information about the quantity of stored SNF, and quality assurance of materials should be possible without opening the cask. However, traditional nondestructive examination (NDE) methods such as x-rays are difficult to deploy for DSC investigation because a typical DSC is intentionally designed to shield against radiation. To address this challenge, cosmic ray muons (CRMs) are used as an alternative NDE radiation probe because they can easily penetrate an entire DSC system; however, a wide application of muons is often hindered due to the naturally low CRM flux (~10 4 muons/m 2 /min). This paper introduces a newly proposed imaging algorithm, momentum-informed muon scattering tomography (MMST) , and presents how a limitation of the current muon scattering tomography technique has been addressed by measuring muon momentum. To demonstrate its functionality, a commercial DSC with 24 pressurized light water reactor fuel assemblies (FAs) and the MMST system were designed in GEANT4. Three noticeable improvements were observed for MMST system as a DSC investigation tool: (1) a signal stabilization, (2) an enhanced capability to differentiate various materials, and (3) statistically increased precision to identify and locate missing FAs. The results show that MMST improves the investigation accuracy from 79 to 98% when one FA is missing and 51% to 88% when one-half FA is missing. The advancement of the NDE technique using CRM for DSC verification is expected to resolve long-standing problems in increasing demand for DSC inspections and nuclear security.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Comprehensive Land Use and Environmental Stewardship

Comprehensive Land Use and Environmental Stewardship (CLUES) Report serves as a summary document of the land use and environmental stewardship activities occurring on the Idaho National Laboratory (INL) Site (Desert) and the Research and Education Campus (REC) within Idaho Falls. Land and facility use planning and decisions at the INL Site are guided by a comprehensive planning process in accordance with the United States (U.S.) Department of Energy (DOE) Order 430.1C, “Real Property Asset Management,” which states "Establish a data-driven, risk-informed, performance-based approach to the life-cycle management of real property assets that aligns the real property portfolio with DOE mission needs; acquire, manage, positively account for, and dispose of real property assets in a safe, secure, cost-effective, and sustainable manner; and ensure the real property portfolio is appropriately sized, aligned, and in the proper condition to support efficient mission execution." Land use planning, like Campus Master Planning and 5-Year Facility Planning, provides a means for better, more sustainable use of the INL Site in a coordinated effort to ensure current and future mission needs are met, including acquisition, recapitalization, maintenance, disposition, real property utilization and long-term stewardship. This document and all functions of INL are guided by the DOE Vision for INL and the INL Mission and builds on the baseline established in the FY 2015 CLUES Report. However, it delivers a revised structure with focus on new resource management zones, which provide organization of key management considerations and access restrictions to optimize land use and environmental stewardship. A new set of thematic Guiding Principles presented in this report provide the intent and sustainable management direction to protect the INL Site natural environment. They demonstrate that the mission and vision of DOE and INL can be realized with inclusion of first of a kind technology, private sector development, and globally recognized testing and demonstration. This CLUES Report encourages comprehensive management decision-making with additional resource discussions for sustainability, the built environment, and the ecological landscape at the INL Site. Enhanced resource considerations and trends emphasize the importance of air, land use, environmental, subsurface, and cultural resources. The INL Site supports exceptional and interdependent resources. A diversity of bat species are accommodated by culturally significant caves distributed around the Site. Big game species like elk, deer, and moose seek vegetation communities which are protected by long-term stewardship and monitoring programs.

99 GENERAL AND MISCELLANEOUS↗

Quantum sensing for emerging energy technologies

The ability to exploit quantum phenomena has enabled sensing technologies with detection limits below the classical limit. Sensors with applications in energy discovery, production, transportation, and consumption can be enhanced through quantum or hybrid quantum-classical sensors. Here, in this Review, we provide an overview of commercial and emerging quantum sensor platforms and their opportunity areas specific to advanced energy technologies. Key examples include: power grid-enhancing-technologies, where quantum magnetometers can detect powerline and transformer faults; electric vehicle-to-grid applications, where chip-scale atomic clocks can enable grid synchronization; and carbon capture and storage, where quantum gravimeters and single-photo LiDAR can detect microscopic leaks. Quantum sensor deployment requires further research into miniaturization and ruggedization for field deployment, cost-reduction, and workforce development. The maturation of clean energy technologies and quantum sensors provide opportunities for synergy, with the integration of quantum sensors into advanced energy technologies maximizing their security, reliability, and efficiency.

critical metals↗

Repatriated Desert Bighorn Sheep Population on the Nevada National Security Site

Ecological studies have been conducted on the Nevada National Security Site (NNSS) since the 1960s. Desert bighorn sheep (Ovis canadensis nelsoni) were considered rare visitors on the NNSS, with only 9 recorded observations between 1963 and 2009, all of which were males. Females and young were not documented definitively until winter 2011, when several were killed by a radio-collared female mountain lion (Puma concolor). Following these observations, we initiated a study of desert bighorn sheep on the NNSS to better understand their movements/interactions with other populations, prevalence of disease, population size, origin, radionuclide burdens and potential radiological dose to humans that may consume harvested animals away from the NNSS. We captured and radio-collared 6 sheep (2 females, 4 males) in November 2015, and 15 (7 females, 8 males) in November 2016. We sampled blood for genetic and disease testing and collected nasal swabs for respiratory disease testing. Sheep from the NNSS spent most of their time around Shoshone Mountain, Fortymile Canyon, and Yucca Mountain but also moved to Bare Mountain, Thirsty Canyon, and Black Mountain. Females greatly expanded their core and overall home ranges during spring, whereas males expanded their home ranges during summer. Of 18 sheep sampled for disease, 12 showed an immune response to Mycoplasma ovipneumoniae, and 5 had the bacteria present. Genetic testing revealed that the ancestry of NNSS sheep is from the Bare Mountain (1991-1995, within 24 km of our study area), Specter Range (1990-1995, within 32 km of our study area), and Stonewall Mountain (1975-1983, within 72 km of our study area) reintroduced populations. Radionuclide burden in NNSS sheep was minimal with no significant difference from sheep captured on the Nevada Test and Training Range and northern Nevada. One marked adult male was legally harvested off the NNSS north of Bare Mountain. Finally, this recently colonized reproducing population of sheep on the NNSS warrants further monitoring, protection, and inclusion in resource management plans.

60 APPLIED LIFE SCIENCES↗

Nuclear Material Control & Accounting for Pebble Bed Reactors (FY 2023 Summary Report)

This report discusses the work done under the US Department of Energy NE-5 Advanced Reactor Safeguards and Security Program during FY 2023. It provides a summary of material control and accounting (MC&A) for pebble bed reactors (PBRs) and addresses some of the main challenges with current PBR MC&A approaches that will inform safeguards and security by design efforts. The efforts to date have focused on tristructural isotropic (TRISO) pebble fuel material accounting and control including working with partners in industry, loss and production of nuclear material as part of reactor operations, burnup modeling and measurements, uncertainty quantifications for such modeling and measurements, statistical approaches needed, and measurement methods. The unique fuel management and utilization in a PBR, where the fuel in spherical form is introduced and circulates through the reactor, poses special challenges for MC&A. This contrasts with traditional water-cooled reactors in which the fuel is contained in large assemblies and can be easily identified and counted. Even online fueled reactors, such as the CANDU reactors (none of which operate in the United States), are significantly different because the fuel is still contained in relatively large assemblies, is uniquely identified, and the number of assemblies that pass through the core on an annual basis is much fewer than the hundreds of thousands that circulate in a PBR, none of which are uniquely identified. Additionally, the nature of the TRISO fuel results in very low heavy metal loading with each pebble containing less than 10 g of uranium and on the order of less than 1 g of fissile material. This low fuel density and the robustness of the TRISO particles are major features of the TRISO fuel from a safety basis as each TRISO particle and pebble acts as a containment for the nuclear material and fission products during normal and accident conditions. This also results in very low plutonium loading per pebble during normal operations, which is on the order of 0.1 g at full burnup. A major feature of PBRs is that they will allow for significantly higher burnup, on the order of 160 GWd/THM compared to the burnup of traditional LWRs, which is on the order of 45 GWd/THM. This is achieved by monitoring the pebbles as they circulate through the reactor and allowing them to be reintroduced into the core until the desired burnup is achieved and they are removed from the reactor and enter the spent fuel storage areas.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗