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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Ageing Management for Extended Long-Term Dry Storage of Spent Nuclear Fuel and Transportation

The principal objectives of the Coordinated Research Project (CRP) and CRADA were to (1) investigate how ageing effects leading to degradation of materials used in the spent fuel dry storage systems could be managed by ageing management programs (AMPs) and (2) using existing AMPs as a basis, establish guidance on how to develop, generate, and maintain AMPs for dry storage systems of spent nuclear fuel (SNF) that can be accomplished in various ways. The PI (Dr. Liu) is an internationally recognized expert on ageing management for license renewal of nuclear power plants and independent spent fuel dry storage installations. Dr. Liu was invited by IAEA to participate in this CRP and served as Chair of the Working Group, supporting the IAEA CRP Lead, with other members from Argentina, the Czech Republic, France, Germany, Hungary, Japan, Pakistan, Spain, Switzerland, United Kingdom, and the United States of America. Argonne’s scope of work in the CRADA for the CRP included (1) ageing management guidance documents developed by Argonne for DOE and used by the Nuclear Regulatory Commission (NRC) and industry and (2) research leveraged from the DOE Office of Nuclear Energy on the mechanical properties of high-burnup fuel cladding and the ARG-US remote monitoring systems technology developed for the DOE Packaging Certification Program, Office of Packaging and Transportation, Office of Environmental Management.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Optimal Power Flow With State Estimation in the Loop for Distribution Networks

Here in this article, we propose a framework for running optimal control-estimation synthesis in distribution networks. Our approach combines a primal-dual gradient-based optimal power flow solver with a state estimation feedback loop based on a limited set of sensors for system monitoring, instead of assuming exact knowledge of all states. The estimation algorithm reduces uncertainty on unmeasured grid states based on certain online state measurements and noisy "pseudomeasurements." We analyze the convergence of the proposed algorithm and quantify the statistical estimation errors based on a weighted least-squares estimator. The numerical results on a 4521-node network demonstrate that this approach can scale to extremely large networks and provide robustness to both large pseudomeasurement variability and inherent sensor measurement noise.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Infrastructure-Based Cooperative Perception at a Traffic Intersection: Overview and Challenges: Preprint

Recent advancement in autonomous driving vehicles and V2X communication has attracted increasing attention towards Intelligent Transportation Systems to build a safe and reliable traffic intersection. However, most of the systems are still at the initial stages and require significant progress to become a reality. This paper presents an overview of NREL Infrastructure Perception and Control (IPC) framework which is an open-source track-data fusion engine which takes input from infrastructure-based perception sensors and cooperatively shared messages from Connected Autonomous Vehicles (CAVs) and Connected Vehicle (CVs) and the challenges associated with deploying such cooperative perception framework at a four-way traffic intersection in the city of Colorado Springs, CO, USA. The sensor data is collected by deploying two radars and two LiDAR sensors on the IPC mobile lab and two radars on diagonally opposite traffic poles at the proposed intersection. The sensor output results imply the need for rapid sensor calibration to bring the collective perception to a common coordinate frame, the importance of time synchronization between the sensors in order to capture accurate spatial and temporal alignment of the objects, and the need for a health monitoring system with fail safe closed-loop detection model for real-time deployment.

camera↗
DOE OSTI2023

Short-lived noble gas effluent trends from a research reactor

An understanding of anthropogenic sources of radioactive noble gases in the atmosphere is needed to enhance the discrimination ability of the International Monitoring System's sensors. These sources include commercial and research nuclear reactors and medical isotope production facilities. While abiding by local environmental ordinances these facilities all emit noble gas radioisotopes through normal operation. Here, this research presents measurements and analysis of noble gas isotopes ( 41 Ar, 135 Xe, 135m Xe, 137 Xe, 138 Xe, 87 Kr, 88 Kr, and 89 Kr) made directly at the stack of the High Flux Isotope Reactor (HFIR) at Oak Ridge National Laboratory. The Xe and Kr noble gases are concurrently observed with 41 Ar, a neutron activation product, when the reactor is operational. The magnitude of the Xe and Kr noble gases released is not constant over the HFIR cycle, but they temporally match the 41 Ar trend. An isotope activity ratio analysis of these shorter lived isotopes combined with the observation of the cycle's temporal trend helps understand the noble gas production mechanism at the HFIR. Isotopes with short half-lives are not useful for long-range environmental monitoring. However, these measurements could potentially be combined with atmospheric modeling to predict the background source term of the longer-lived Xe ratios at a monitoring station.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2022

Environmentally Adaptive, Multiband Software-Defined-Radar for Monitoring of Item of Interest in a Dynamically Cluttered Room

High-resolution multi-frequency radars when networked together, form a robust and seamless monitoring system for high-valued items. The multi-look-direction radar network investigated by LLNL and DSI, operates at 77 GHz and 5.8GHz, and is capable of detection at centimeter resolution movement of objects of interest. This dual frequency radar (unlike optical methods) can operate under various environments with conditions such a smoke, dust, and other natural or manmade obscurations. In addition, the multiband network radar is based on low-cost FCC approved EM specifications and can be scaled with the dimensions of the room and objects under consideration by user-defined inputs. Furthermore, the underlying radar signal processing based on software-defined radar engine is adaptive to its operational environment, where operators can input the size of the facility and object of interest and the distance between the object and radar. Finally, this multi-frequency radar employs a host of change detection and machine learning algorithms to reach performance levels in terms of high probability of detection and low false alarm rates while the monitoring state of the object can be reported remotely.

42 ENGINEERING↗
DOE OSTI2020

AATTENUATION—The Atmospheric Attenuation Model for CSP Tower Plants: A Look-Up Table for Operational Implementation

Attenuation of solar radiation between the receiver and the heliostat field in concentrated solar power (CSP) tower plants can reduce the overall system performance significantly. The attenuation varies strongly with time and the average attenuation at different sites might also vary strongly from each other. If no site specific attenuation data is available, the optimal plant design cannot be determined and rough estimations of the attenuation effect are required leading to high uncertainties of yield analysis calculations. The attenuation is caused mainly by water vapor content and aerosol particles in the lower atmospheric layer above ground. Although several on-site measurement systems have been developed during recent years, attenuation data sets are usually not available to be included during the plant project development. An Atmospheric Attenuation (AATTENUATION) model to derive the atmospheric transmittance between a heliostat and receiver on the basis of common direct normal irradiance (DNI), temperature, relative humidity, and barometric pressure measurements was developed and validated by the authors earlier. The model allows the accurate estimation of attenuation for sites with low attenuation and gives an estimation of the attenuation for less clear sites. However, the site-dependent coefficients of the AATTENUATION model had to be developed individually for each site of interest, which required time-consuming radiative transfer simulations, considering the exact location and altitude, as well as the pre-dominant aerosol type at the location. This strongly limited the application of the model despite its typically available input data. In this manuscript, a look-up table (LUT) is presented which enables the application of the AATTENUATION model at the site of interest without the necessity to perform the according complex radiative transfer calculations for each site individually. This enables the application of the AATTENUATION model for virtually all resource assessments for tower plants and in an operational mode in real time within plant monitoring systems around the world. The LUT also facilitates the generation of solar attenuation maps on the basis of long-term meteorological data sets which can be considered during resource assessment for CSP tower plant projects. The LUTs are provided together with this manuscript as supplementary files. The LUT for the AATTENUATION model was developed for a solar zenith angle (SZA) grid of 1°, an altitude grid of 100 m, 7 different standard aerosol types and the standard AFGL atmospheres for mid-latitudes and the tropics. The LUT was tested against the original version of the AATTENUATION model at 4 sites in Morocco and Spain, and it was found that the additional uncertainty introduced by the application of the LUT is negligible. With the information of latitude, longitude, altitude above mean sea level, DNI, relative humidity (RH), ambient temperature (Tair), and barometric pressure (bp), the attenuation can be now derived easily for each site of interest.

14 SOLAR ENERGY↗
DOE OSTI2022

Characterization of PIPS detectors for measurement of radioxenon

The International Monitoring System arm of the Comprehensive Nuclear-Test-Ban Treaty Organization utilizes sampling of atmospheric radioxenon to scan the world for nuclear testing events. Current designs utilized in the field involve plastic scintillator cells run in coincidence with Sodium Iodide (NaI) or High Purity Germanium (HPGe) detectors. The use of plastic scintillators as electron detectors exhibit some issues in comparison to other materials. Silicon detectors are analyzed as an alternative to plastic scintillators for beta detection based on their higher energy resolution and lowered memory effect. A radioxenon detection setup was created with the intent of measuring radioxenon samples using coincidence counting between silicon and NaI detectors as well as silicon and HPGe. Finally, the absolute efficiency of both setups is calculated and compared.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2020

Update of Emission Factors of Greenhouse Gases and Criteria Air Pollutants, and Generation Efficiencies of the U.S. Electricity Generation Sector

The last decade has seen a steady evolution of the electricity generation sector. Fuels used for electricity generation have shifted from coal to cleaner energy sources such as natural gas and renewables including solar, wind, and other renewable sources. The share of U.S. electricity generated from coal decreased from 45% in 2010 to 24% in 2019, and is expected to decrease further to 13% by 2050. The conversion efficiency of electricity generation has also increased gradually for fuels such as natural gas due as less-efficient old generators are retired and more-efficient generators replace them. These changes in the electricity generation industry are likely to cause changes in the emissions from power generation units. Emission factors of greenhouse gases (GHG) including CO 2 , CH 4 , and N 2 O, and criteria air pollutants (CAPs) including CO, NO x , PM 10 , PM 2.5 , and SO x , from power plants are important parameters for estimating life-cycle emissions associated with vehicle electrification, energy systems, and the production of materials and chemicals. The electricity generation technologies and associated emission factors in the Greenhouse Gases, Regulated Emissions, and Energy Use in Technologies (GREET) model need to be updated to reflect recent developments in the electricity generation sector. The most recent update of the electricity generation emission factors in GREET adopted a mixed method. The emission factors of CH 4 , N 2 O, NO x , and SOx were estimated using a “topdown” approach by dividing the total emissions by the total net electricity generation, because emission data of these pollutants are readily available in the Emissions & Generation Resource Integrated Database (eGRID). For other CAPs such as CO, VOC, PM 10 , and PM 2.5 , emission data were not reported in eGRID. A “bottom-up” method was used to estimate the emission factors for these pollutants by considering generic uncontrolled emission factors and the pollutant removal efficiencies of emission control technologies adopted in the electricity generation sector. However, the uncontrolled emission factors and the emission removal efficiencies of various emission control technologies considered in the 2012 study came from the legacy AP-42 emission factors, and may not reflect the actual emission performances of the electricity generation sector of today. To leverage new data that recently became available, especially emission data measured from continuous emission monitoring systems (CEMS), we developed a new “top-down” approach to estimate efficiencies and GHG and CAP emission factors for electricity generation from combustion of individual fuel types by individual combustion technologies on the basis of power-generation data from U.S. Energy Information Administration’s (EIA’s) form EIA-923, and plant emission data from Environmental Protection Agency’s (EPA’s) Clean Air Markets Division (CAMD) dataset and National Emissions Inventory (NEI) dataset. Detailed discussion of the method and data used in this study can be found in Section 2.1. With this topdown approach, we aim to improve the estimates of energy efficiencies and emission factors for power plants using a more consistent methodology, and to update the emission factors, generation efficiencies, and generation technologies mixes in GREET to reflect recent technology advancements in the electricity generation sector.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2022

Foam Fracturing Study for Stimulation Development of Enhanced Geothermal Systems

This is a final technical report for the project: Foam Fracturing Study for Stimulation Development of Enhanced Geothermal Systems (EGS). The goal is to demonstrate the feasibility of foam fracturing in EGS applications. The project, led by Oak Ridge National Laboratory (ORNL), was conducted in collaboration with Temple University. The report describes the research activities with Task 1 at ORNL: foam fracturing testing system development and experimental study on foam fracturing, and Task 2 at Temple University: foam testing and foam characterization. Main findings are: 1. A foam fracturing test system has been developed at ORNL, which can be used to perform foam fracturing under pressure up to 6,000 psi. The system monitors foam density during fracturing online and is capable of testing materials in both monotonic and cyclic (up to 50 Hz) injections. 2. Foam fracturing tests were carried out on Charcoal black granite specimens with a blind borehole to the middle length. Two diameters of blind borehole were tested; G2 series: 9.53 mm and G3 series: 4.76 mm. N2-in-water foam was used with AOS as a surfactant. 3. There was a hole-size effect on fracture initiation pressure. The effect is smaller in the case of foam, which was influenced by the high penetrability of gas in foam. Breakdown pressure showed a behavior just as that of fracture pressure; namely an increased value for small hole samples, while the effect in water fracture was more impressive than in foam fracture. 4. Water mass was reduced in foam fracturing within similar range of breakdown pressures. In G2 series, it was decreased from 10.44 g for water fracturing to 5.17 g, representing more than 50% water reduction. Therefore, there is the potential to reduce water use in EGS stimulation through foam fracturing. 5. Use of cyclic injection has the potential to reduce the breakdown pressure and seismicity in EGS application. Experiments using 4-s cycle period found that specimens can be fractured with a low number of cycles. The fatigue pressure was approximately 64 - 77% of monotonic breakdown pressure for water fracturing and 58 - 94% of the breakdown pressure for foam fracturing. 6. A foam stability testing system has been developed that can test foam at 220 Deg C to 2,000 psi. Tested components of candidate foams included two gases: N2 and CO2; 4 surfactants: AOS, SDS, NP-40 and CTAC; 5 stabilizing agents: guar, bentonite clay, borate salt, silica NPs, and GO. 7. N2 and AOS provided the most stable performance over the tested ranges. Furthermore, the AOS foam with stabilizing agents of guar and borate salt (crosslinker) offered the highest half-life of 20 minutes at 200 Deg C and 1,000 psi. 8. Arrhenius equation and modified power law have been demonstrated to fit well the half-time vs. temperature and pressure data, respectively. These relations can be useful to provide the suggestion for future foam stability study. This submission contains the supporting data developed during the project: 1) A final technical report 2) Granite fracturing data in monotonic and cyclic injections with water and N2 foam Foam performance data in various temperatures and pressures, including half-time, is submitted separately.

15 GEOTHERMAL ENERGY↗
DOE OSTI2026

Hourly PM 2.5 Estimates across California from 2018 to 2023

This study presents a new data set of hourly PM 2.5 concentrations across California from 2018 to 2023 at a three-kilometer resolution. This data set was developed by assimilating observations from PurpleAir and the U.S. EPA Air Quality System monitors into wildfire smoke forecasts from the High-Resolution Rapid Refresh Smoke (HRRR-Smoke) model using the Gridpoint Statistical Interpolation (GSI) three-dimensional variational data assimilation framework. Archived forecasts of modeled wildfire smoke PM 2.5 from HRRR-Smoke create the background field for assimilation, which is then corrected using surface observations of total PM 2.5 . The resulting reanalysis from GSI provides an estimate of total PM 2.5 that minimizes error from both the observational and the model data. Validation results indicate strong performance, with monthly R 2 values ranging from 0.73 to 0.91 across the six-year data set, comparable to other PM 2.5 data sets. Case studies are presented for three major fire events, the 2018 Camp Fire, 2019 Kincade Fire, and 2020 Lightning Complex Fires to demonstrate the data set’s fidelity in resolving plume dynamics and local exposure patterns. Root-mean-squared error averaged over each month scales with average PM 2.5 concentrations, resulting in a low error under typical conditions but higher absolute errors during extreme smoke events. This is the first long-term, hourly PM 2.5 data set of its kind for California and enables the generation of subdaily exposure metrics, such as peak hourly concentrations, exceedance durations, and time-of-day exposure peaks. The novelty and strong validation of this data set make it a compelling resource for future studies on the impact and significance of subdaily PM 2.5 exposure.

PM2.5↗
DOE OSTI2022

Continuous Emulation and Multiscale Visualization of Traffic Flow Using Stationary Roadside Sensor Data

With the advent of the next-generation traffic monitoring systems, there has been a significant increase in the spatial-temporal resolution of vehicle mobility data in many cities. Effective analysis and visualization of such data can provide transportation planners with data-driven insights, which can facilitate the understanding of multiscale traffic dynamics. In this paper, we present a web-based traffic emulator for emulating and visualizing near-real-time and historical traffic flows on highways using data from road-side sensors. To construct a continuous traffic flow, the emulator adopts an analytical pipeline that can (a) integrate traffic data collected from discrete road-side radar detection sensors, (b) interpolate traffic conditions (vehicle speed and volume) on unmeasured road segments based on traffic flow theory, and (c) generate lane-specific vehicle trajectories and movements using a mathematically optimized representation of the road network. Our app also provides an integrated visual workflow that allows users to explore the interconnected traffic dynamics using an appropriate traffic flow visualization selected based on the level of detail. We devise two innovative geo-visualization techniques that utilize an animated strips-network representation and a lane usage matrix to visualize lane performances. To ensure a smooth emulation of large-scale traffic flow in an easy-to-access web environment, we implement the emulator using client-side GPU-accelerated techniques. Lastly, we close with a case study that visualizes traffic dynamics of two scenarios - an afternoon peak hour and a traffic accident - in Chattanooga, Tennessee. Our app visualizes the responses of traffic dynamics during different traffic conditions, and to the presence of the traffic accident at different spatial scales.

42 ENGINEERING↗
DOE OSTI2020

A Review of Global Radioxenon Background Research and Issues

Among the most important problems for the world-wide nuclear explosion monitoring is the interference of naturally occurring and man-made radionuclides. The International Monitoring System (IMS) of the Comprehensive Nuclear-Test-Ban Treaty (CTBT) frequently detects these interferences using sensitive radionuclide measurement equipment. We commonly refer to the presence of radionuclides that are relevant to the CTBT but do not originate from a nuclear explosion as “background”. Backgrounds are highest near the sources but are known to have regional and global effects on the IMS. This review paper summarizes much of the relevant work in the area of background and discusses issues of interest for nuclear explosion detection.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2023

Impact of environmental backgrounds on atmospheric monitoring of nuclear explosions

Radionuclide monitoring for nuclear explosions includes measuring radioactive aerosol and noble gas concentrations in the atmosphere. The International Monitoring System (IMS) of the Comprehensive Nuclear Test Ban Treaty (CTBT) has made such measurements for decades, revealing much about how atmospheric radioactivity impacts the sensitivity of the network. For example, civilian emissions of radioiodine make a substantial regional impact, but a minor global impact, while civilian radioxenon emissions create major regional and complex global impacts. This example statement is strongly influenced by the minimum signal level anticipated to be interesting. The original design of the IMS anticipated relatively large signal levels, and the accomplished IMS network substantially meets or exceeds the sensitivity needed to detect those signal levels. Much lower signal levels can be motivated, which could require reconsideration of station sensitivity. Using measured and simulated background concentrations, various possible desired signal levels, and an innovative anomaly threshold, maps of sensitivity and a station ranking are developed for current and future stations. These provide a strong motivation for additional experimentation to learn about sources and the potential plusses of new technology.

Eslinger, Paul W.↗
DOE OSTI2023

Virtual sensing of wind turbine hub loads and drivetrain fatigue damage, Virtuelle Sensoren für die Messung von Hauptwellenlasten und Ermüdungsschäden im Antriebstrang von Windenergieanlagen

Abstract: This paper presents a Digital Twin for virtual sensing of wind turbine aerodynamic hub loads, as well as monitoring the accumulated fatigue damage and remaining useful life in drivetrain bearings based on measurements of the Supervisory Control and Data Acquisition (SCADA) and the drivetrain condition monitoring system (CMS). The aerodynamic load estimation is realized with data-driven regression models, while the estimation of local bearing loads and damage is conducted with physics-based, analytical models. Field measurements of the DOE 1.5 research turbine are used for model training and validation. The results show low errors of 6.4% and 1.1% in the predicted damage at the main and the generator side high-speed bearing respectively. Zusammenfassung: In diesem Aufsatz wird ein digitaler Zwilling für Windenergieanlagen vorgestellt, welcher die virtuelle Erfassung der Hauptwellenlasten und die Zustandsüberwachung von Ermüdungschäden und der verbleibende Nutzungsdauer der Antriebsstranglager ermöglicht. Der digital Zwilling nutzt Messdaten des Supervisory Control and Data Acquisition (SCADA) Systems und des Zustandsüberwachungssystems des Antriebsstranges (CMS). Die Berechnung der Hauptwellenlasten ist mit datenbasierten Regressionsmodellen umgesetzt, während die Berechnung der Lagerkräfte und der Ermüdungsschaden mit physikbasierten Modelle durchgeführt wird. Für die Modellentwicklung und -validierung werden Feldmessdaten der DOE 1.5MW Turbine eingesetzt. Die Abweichungen in den Ermüdungsschäden am Hauptwellenlager und am Generatorwellenlager betragen lediglich 6,4% beziehungsweise 1,1%.

17 WIND ENERGY↗
DOE OSTI2022

Coincidence measurements of radioxenon using passive implemented planar silicon (PIPS) detector

The Comprehensive Test Ban Treaty (CTBT) bans nuclear weapons testing and establishes the International Monitoring System (IMS) for the purpose of treaty verification. IMS is a detector network that confirms that global nuclear activity is peaceful in nature. These detector systems use β-γcoincidence measurements to characterize atmospheric samples containing radioxenon isotopes. The goal of this work is to use the system consisting of two sodium iodide detectors and two PIPSbox detectors to characterize isotopically pure samples of 131m Xe, 133m Xe, 133 Xe, and 135 Xe via β, γ, and β-γ coincidence measurements.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2020

Seismic monitoring and high-frequency noise using arrays in the Arabian Peninsula

Seismic arrays provide useful tools for regional seismic monitoring. Two small-aperture, regionally-oriented arrays, QWAR and HQAR, were deployed in Saudi Arabia and Oman in 2012 and 2016. We utilize a time-domain beampacking method, similar to frequency-wavenumber analysis, to examine the performance of the arrays in terms of slowness and azimuthal bias and event detection capabilities. Additionally, we investigate persistent ambient noise sources recorded by the arrays. We find that the arrays provide slowness vectors with biases comparable with similar-sized arrays of the International Monitoring System in other locations around the world. At QWAR, regional events of magnitude 3.0 and above are detected a majority of the time, and as magnitudes increase to 4.0 and above, the detection rate is greater than 82%. Finally, strong noise generation, primarily with slownesses characteristic of Lg waves, is found in the directions of the northern Arabian/Persian Gulf and southern Red Sea and may be a factor in event detection capabilities.

58 GEOSCIENCES↗
DOE OSTI2022

Feature extraction for subtle anomaly detection using semi-supervised learning

The demand for automated and effective monitoring techniques has soared with the increased digitization of industrial monitoring systems. State-of-the-art machine learning methods are effectively detecting abrupt changes in system states. However, these methods lack comparable maturity in detecting subtle changes that may be signs of incipient faults. This manuscript argues that the current anomaly detection methods can be enhanced by exploring weak patterns to enable subtle variation detection. Specifically, the concept of semi-supervised learning is employed, with labels representing knowledge about some anomalous conditions of a system. The basic idea is to extract a candidate set of weak patterns discarded by state-of-the-art baselining algorithms. With few labeled anomalous data, the algorithm selects the weak patterns and allows for their possible fusion using the highest sensitivity to the labeled anomalies. Here, the method’s applicability is demonstrated using a representative pressurized water reactor (PWR) model simulated by Dymola.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Survey of prospective techniques for molten salt reactor feed monitoring

Safeguards verification measurements of nuclear material content in fresh fuel salt for liquid-fueled molten salt reactors (MSRs) are likely to be required as part of nuclear material accountancy for International Atomic Energy Agency safeguards. Here, this paper presents a comprehensive review and evaluation of 18 potential candidate techniques to quantify total uranium and 235 U for input accountancy measurements for liquid-fueled MSRs. As part of an overall screening and down-selection effort to identify the most promising techniques for further development for an MSR feed monitoring system, this paper defines eight figures of merit (FOMs): reasonably achievable measurement uncertainty, measurement time required, capital cost, burden upon the facility operator, maintenance intensity, technological maturity, human capital requirements for operation, and whether the technique introduces a path for potential material removal. Each candidate technique is then evaluated across these FOMs to identify the techniques with the highest potential for future development for fresh fuel accountancy measurements in MSRs. Our findings indicate that no single technique or combination thereof currently has the requisite technological maturity for immediate implementation in nuclear material accountancy at a liquid-fueled MSR facility. While several promising techniques are identified, there is a critical lack of experimental data for most systems in the context of molten salt applications.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗