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A Vacuum Drying Study of Simulated Failed Nuclear Fuel (FY23)

This report documents work performed under the Office of Spent Fuel and Waste Disposition’s (SFWD’s) Spent Fuel and Waste Science and Technology program for the US Department of Energy (DOE) Office of Nuclear Energy (NE). This work was performed to fulfill Level 4 milestone M4SF-23OR010203013. Over the 70 years of light-water reactor (LWR) operation, fuel rod failures have occurred during reactor operation. Based on the Unified Database that SFWD maintains, there are ~5,400 LWR fuel rods that developed leaks during reactor operation of the >19 million rods operated. The Unified Database indicates that ~4,200 of these rods remain in the spent fuel pool, and ~1,200 are in dry storage canisters. It is expected that all failed rods are “waterlogged” in the spent fuel pool, meaning the inside of the rods contain some volume of water. There are two related objectives of this work. The first is to develop a simple and inexpensive experiment to better understand removal of water from inside failed spent nuclear fuel (SNF) rods, and the second is to develop a model to predict drying of simulated failed fuel in the simple experiment. Once a model captures the phenomenon in the simple experiment, it can be extended to predict drying under more prototypical conditions.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Assessment of Cloud-Based Applications Enabling a Scalable Risk-Informed Predictive Maintenance Strategy Across the Nuclear Fleet

The current light water reactor fleet uses time-based or failure-based maintenance strategies to achieve high-capacity factors. But to make nuclear more competitive in the energy market, these reactors could utilize emerging technologies in terms of artificial intelligence (AI) and cloud computing to enable a cost-effective, predictive maintenance strategy. This report examines the feasibility of cloud computing for the nuclear industry’s needs in terms of the cloud’s computing capabilities, feasibility, and regulatory concerns. The technical viability of cloud computing was analyzed using one year worth of data from a boiling water reactor’s safety relief valve. Models were hosted on a local desktop, Idaho National Laboratory’s high-performance computer, and Microsoft Azure. Data was loaded, processed, and two types of models were trained in an A/B fashion. Based on the speed at which these actions were completed, it was used to determined that cloud computing has adequate computing resources. Additionally, the computing power can scale with the demanded load. To enable cloud computing in the existing fleet, additional sensors, networks, and other requirements must be implemented to ensure a smooth transition from current maintenance strategies. However, there is a benefit as the plant no longer needs manage their own servers, software, cybersecurity, and IT support staff. Many of these features can be offloaded on to the cloud provider. A comprehensive analysis was completed that showed the current annual cost of operating is more expensive than using cloud computing resources. Lastly, the regulatory framework does not explicitly address AI or autonomous control. Currently, the NRC and other regulatory bodies are evaluating providing guidance to address gaps rather than new regulations to address the use of AI and ML. But since many of the AI applications are focused on non-safety related applications, such as balance-of-plant components, they will likely have little or no regulatory restrictions or necessary approvals. Demonstrating how AI can improve maintenance and operation of these non-safety related systems seems like the likely path forward for implementing AI and cloud computing resources inside nuclear power plants (NPPs).

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

SATS Transient Fission Gas Release Test with Irradiated Fuel under Loss of Coolant Accident Conditions

The transient fission gas release (tFGR) during the temperature ramp associated with a loss-of-coolant accident (LOCA) in light-water reactors (LWRs) is likely a significant contribution to the total pressure in a fuel rod and may cause an unexpected rod burst. The lack of data related to tFGR continues to be a key gap in understanding LWR cladding burst behavior under LOCA conditions. To fully characterize this behavior, tFGR data must be collected from several different systems that can capture all relevant testing conditions. Oak Ridge National Laboratory (ORNL) has developed a system to measure the integral tFGR from irradiated fuel segments. This system was designed to integrate with the existing Severe Accident Test Station (SATS) and to build upon decades of experience capturing fission gas to characterize fuel behavior. The tFGR system consists of a sweep gas system to transport gases from the in-cell SATS apparatus to an out-of-cell fission gas detection system composed of a series of cold traps to capture the off-gas from the heating tests and a gamma spectrometry system to detect and measure 85 Kr. Initial system testing operations were completed during which 85 Kr collection and measurement were verified along with the ability to detect stable inert gases. A tFGR test with a high-burnup fuel specimen was successfully conducted by the in-cell SATS-tFGR system at ORNL. The posttest examination is under way, the result of which will be reported in FY24.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

CTF Validation and Verification: Version 4.4

Coolant-Boiling in Rod Arrays- Two Fluids (COBRA-TF) is a thermal/hydraulic (T/H) simulation code designed for light water reactor (LWR) analysis. It uses a two-fluid, three-field (i.e., fluid film, fluid drops, and vapor) modeling approach. Both subchannel and 3D Cartesian forms of nine conservation equations are available for LWR modeling. The code was originally developed by Pacific Northwest Laboratory in 1980 and has been used and modified by several institutions over the last several decades. COBRA-TF is also used at the Pennsylvania State University (PSU) by the Reactor Dynamics and Fuel Modeling Group (RDFMG) and has been improved, updated, and subsequently became the CTF. One part of the improvement process includes validating the methods in CTF. This document seeks to provide a certain level of certainty and confidence in the predictive capabilities of the code for the scenarios it was designed to model—rod bundle geometries with operating conditions that are representative of prototypical pressurized water reactor (PWR)s and boiling water reactor (BWR)s in both normal and accident conditions. This is done by modeling a variety of experiments that simulate these scenarios and then presenting a qualitative and quantitative analysis of the results that demonstrates the accuracy to which CTF is capable of capturing specific quantities of interest.

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Status of Mechanistic Fission Gas Model in High-Burnup Fuel

A desire to increase fuel burnup to decrease the cost of nuclear power plants has led to significant interest within the nuclear industry to develop improved understanding of high-burnup nuclear fuel microstructure and the potential for fuel fragmentation, relocation, and dispersal that contribute to burnup and safe operating limits. This milestone report describes joint research activities and program planning to develop mechanistic models for high-burnup UO 2 microstructure, including both intra- and intergranular gas bubble populations and fission gas release, specifically associated with transient release. This model development is being extensively leveraged against a rapidly growing experimental database of high-fidelity electron microscopy characterization of commercial, light water reactor fuel in the as-irradiated condition as well as that following simulated loss-of-coolant test conditions. This report describes the status of model development, highlights recent microstructural data, and summarizes the data needs to complete initial development and experimental validation of mechanistic models of fission gas and microstructural evolution at high burnup, as well as transient fission gas release.

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Evaluation of Thermal Neutron Scattering Cross Section of Uranium Silicide with Ab Initio Lattice Dynamics

Uranium silicide (U 3 Si 2 ) is a candidate material for the high-density nuclear fuel in commercial light water reactors [1], [2]. Its higher uranium density, 11.3 g-U/cm3, compared to that of uranium dioxide (UO 2 ), 9.7 g-U/cm3, can improve the performance of a nuclear reactor while using low enriched uranium (LEU) and diversify the choice of cladding materials [1]–[3]. It also has a higher thermal conductivity than UO 2 , which can reduce the thermal stress on the material caused by a temperature gradient across the fuel pellet and provide a larger margin for some postulated accidents [1], [2], [4]. Furthermore, compared to U3Si, another high-density fuel candidate, it has better resistance to in-pile swelling due to less irradiation-induced rapid amorphization [1], [3]. Corresponding to its importance in nuclear engineering, many previous studies have reported the properties of U3Si2. Experiments showed that U 3 Si 2 is a paramagnetic (PM) metal, where a slight linear increase in magnetic susceptibility was measured with increasing temperature [5], [6]. In addition, thermodynamic quantities such as thermal expansion coefficient, heat capacity, and thermal conductivity were experimentally determined over a wide temperature range [1], [7], [8]. In several computational studies, ab initio atomistic simulations based on density functional theory (DFT) were performed to calculate various properties including elastic constants, electronic density of states (DOS), and phonon dispersion curves [9]–[12]. Nevertheless, thermal neutron scattering cross sections, which are critical to the prediction of the parameters in reactor physics that are ultimately related to reactor criticality, have not yet been evaluated for U3Si2. The scattering cross section can be calculated from the phonon DOS, or the energy spectrum of lattice vibrations, of the crystalline system [13], [14]. However, there is also no experimental data available for the phonon DOS of U 3 Si 2 . While some computational studies reported the phonon DOS and/or dispersion curves from ab initio simulations [9]–[12], the accuracy cannot be guaranteed because it is unclear whether the spin-polarization behavior of PM U 3 Si 2 was properly described. In the present study, the thermal neutron scattering cross section for U 3 Si 2 is evaluated for the first time by calculating the phonon DOS for U3Si2 from ab initio lattice dynamics (AILD) simulations based on DFT. First, U 3 Si 2 is modeled based on the experimental structure, and AILD simulations are performed on the modeled U3Si2 to optimize the structure. Next, AILD simulations are performed for supercells with atomic displacement to calculate Hellmann-Feynman forces. Based on the calculated forces, partial phonon DOSs for U and Si are obtained, and the thermal neutron scattering law (TSL) for U 3 Si 2 is finally evaluated. To verify the accuracy of the calculations in the present study, the calculation results are compared with experimental data on the structure and heat capacity of U3Si2 [1], [7], [8], [15].

Geometry Optimization↗

Review and Assessment of Available Data Regarding the Behavior of Sodium Aerosols

Recently, there has been a resurgence of interest in advanced (non-light water) reactor designs, including sodium fast reactors (SFRs). In parallel, multiple efforts are underway to develop risk informed, performance-based licensing pathways for advanced reactors. However, such licensing approaches depend on the accuracy of the associated safety assessments, including mechanistic source term (MST) analyses. Unlike historical source term assessments, which utilizes bounding estimates of radionuclide release, MSTs attempt to realistically estimate the transport and retention of radionuclides for specific transient scenarios. For SFR MST analyses, the behavior of radionuclide aerosols is a key factor, as noted in recent studies. Due to the use of sodium as the primary coolant, many potential transient scenarios involve the release of radionuclide aerosols in conjunction with sodium aerosols. For such scenarios, sodium may be the dominant aerosol species, compared to that of released radionuclides. Therefore, understanding the behavior of sodium aerosols is particularly important to an accurate assessment of aerosol transport. Although many approaches to aerosol modeling exist, it is vital to establish their capabilities in evaluating sodium aerosol behavior for SFR analyses.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Non-LWR Fuel Cycle Scenarios for SCALE and MELCOR Modeling Capability Demonstration

To assess the modeling and simulation capabilities for radionuclide characterization, criticality, and shielding in the nuclear fuel cycle of non-light–water reactor (LWR) technologies, the US Nuclear Regulatory Commission (NRC) initiated a collaborative project between the NRC, Sandia National Laboratories (SNL), and Oak Ridge National Laboratory (ORNL) with the goal to demonstrate capabilities of MELCOR and SCALE to calculate accident scenarios in all stages of the nuclear fuel cycle for relevant non-LWRs. The first project task was to develop representative nuclear fuel cycles and identify potential hazards and accident scenarios in the individual fuel cycle stages based on publicly available information. Because the nuclear fuel cycle is not established for any non-LWR concept, many assumptions were made, and it is anticipated that the details of the fuel cycles will eventually look different.

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RFA-17-14597, Methodology for Meeting Containment System Principal Design Criteria to Maximize the Passive Safety Value in Advanced Nuclear Energy Economic Competitiveness

Advanced (Non-Light Water) Reactors are being designed with Passive Safety as an essential and integral feature. To help streamline the licensing of advanced reactors, the DOE and the NRC have drafted Principal Design Criteria (PDCs) for advanced reactors. A question that remains to be answered is: how an Advanced Reactor take credit for passive safety features inherent in certain advanced reactors while at the same time complying the evolving PDC.

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BISON Fuel Fragmentation Relocation and Dispersal (FFRD) Assessment Database for Eventual Use in Bayesian Calibration

Existing light-water reactor (LWR) fuel vendors have been interested in seeking increased discharge burnups of nuclear fuel rods for improved economics for quite a few years. With increased burnups come additional challenges that must be addressed. It has been experimentally observed that average burnups higher than the current regulatory limit of 62 MWd/kgU may undergo fuel fragmentation, relocation, and dispersal (FFRD) during a loss-of-coolant accident (LOCA). Industry must demonstrate approaches to mitigate FFRD. In an effort to support industry, the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program within the U.S. Department of Energy (DOE) has for several years invested in developing multiscale models and creating a validation/assessment database for these models to study the mechanisms driving FFRD. This report provides an update on changes made to the assessment database and new models added to BISON to support the study of fuel rod behavior during FFRD. An effort has been initiated this year to begin adding dedicated inputs to the publicly available Virtual Test Bed (VTB) repository for industry use. A section of this report details the efforts made in this area. NEAMS has recently developed new capabilities in the Multiphysics Object-Oriented Simulation Environment (MOOSE) framework’s stochastic tools module for calibration using Bayesian inference. The goal in the future is to use these capabilities to calibrate and identify weaknesses in the existing BISON models for FFRD. The report concludes with a discussion on the models most likely to benefit the most from such calibration.

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Operation of the Fast Neutron Coincidence Collar (FNCL) with a DD-Neutron Generator

For more than 30 years, the quantitative assay of the 235 U content of light water reactor fresh fuel assemblies relied on measuring coincidence neutrons from fissions induced by an Am(Li) neutron source using 3 He based detectors. The Fast Neutron Collar (FNCL) developed by the International Atomic Energy Agency (IAEA), replaces traditional 3 He proportional counters with an array of liquid scintillator detectors arranged about the fuel assembly to provide improved measurement precision and reduced sensitivity to gadolinium poison rods. The FNCL relies on Am(Li) neutron sources that are no longer commercially available. This work examines the replacement of Am(Li) sources with a commercial off the-shelf deuterium–deuterium (DD) neutron generator. In addition to mitigating supply concerns, the neutron generator offers advantages in measurement precision and potential automation of sequential passive/active neutron measurements. This report presents the initial performance results for both the integrated DD/FNCL and Am(Li)/FNCL assays of compact depleted uranium, low-enriched uranium, and highly enriched uranium standards along with an estimate of the expected performance for fresh fuel assemblies. A discussion of the design and operation of the “FNCL Analysis and Simulation Software” is also provided.

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Mechanical creep testing and characterization of Cr coated Zircaloy

Zirconium based cladding has been developed for use in light water reactor fuel applications due to the material’s desirable low neutron scattering cross section. To help improve corrosion resistance in accident conditions, such as a loss of coolant accident (LOCA), a chromium coating can be applied to the outer diameter of the Zircaloy tube. Cladding strength at reactor relevant temperatures is important for the structural performance. Stress relaxation creep testing was performed on Cr coated Zircaloy-4 to measure strain rate as a function of stress for 350 and 650°C. These were performed at both 5 ± 1 % and 7.5 ± 1 % strain. The lower temperature provides results near normal operating temperature, while the higher temperature provides results relevant to off-normal conditions where recrystallization will take place. Characterization was also performed to analyze the structure of the Cr coating and Zircaloy-4 as well as the interface between the two.

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Irradiation creep model for α-Fe: Dislocation climb in the presence of stress fields (Final Report)

Irradiation creep is known to be an important process for structural materials in nuclear environments, potentially leading to creep failure at temperatures where thermal creep is generally negligible. While there is a great deal of data for irradiation creep in steels and zirconium alloys in light water reactor conditions, much less is known for first wall materials under fusion energy conditions. Lacking suitable fusion neutron sources for detailed experimentation, modeling, and simulation can help bridge the dose-rate and spectral-effects gap and produce quantifiable expectations for creep deformation of first wall materials under standard fusion conditions. In this work, we present a comprehensive model for irradiation creep created from merging a crystal plasticity representation of the dislocation microstructure and a defect evolution simulator that accounts for the entire cluster dimensionality space. Both approaches are linked by way of a climb velocity that captures dislocation-biased defect absorption and a dislocation strengthening term that reflects the accumulation of defect clusters in the system. We carry out our study in Fe under first wall fusion reactor conditions, characterized by a fusion neutron spectrum at temperatures between 300 and 800°K.

36 MATERIALS SCIENCE↗

Advanced Fuel Cycle Cost Basis Report: Module D1-1: Uranium-based Ceramic LWR Fuel Fabrication (Rev.2)

Cost module on LWR fuel fabrication to accompany the Advanced Fuel Cycle Cost Basis Report. In this update, we are adding detailed life cycle cost data and a calculated, levelized fabrication cost derived from a non-proprietary bottom-up estimate prepared in 1978 by Oak Ridge National Laboratory (ORNL) (Judkins and Olsen 1978a). In 2018, the 1978 ORNL estimate was escalated by SA&I authors to 2017 USD using factors that represent inflation, escalation above inflation typical of nuclear projects, and the effects of more stringent safety and environmental regulations. In this FY-21 document, the $/kgU results in 2017 USD from the unpublished 2018 interim study (Williams and Ganda 2018) can be escalated to 2020 USD using a factor of 1.052. The literature-based unit cost (or price) data from previous (2004–2017) AFC-CBRs are escalated to 2020 USD using factors from Chapter 8 of the main FY-21 AFC-CBR document. This data, in addition to the results of the updated bottom-up estimate, are used to define the “what-it-takes” (WIT) range for the unit fabrication costs for conventional ceramic UOX light-water reactor (LWR) fuel. This FY-23 document also includes calculated unit costs for accident-tolerant LWR fuels (ATFs) of three different types. Some of these fuels constitute a ceramic pelletized form with fuel meat uranium compounds other than UO2 (a.k.a.,. UOX), thus the change in the title of this module in which the word “UO2” is changed to “Uranium-based Ceramic.”

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NRC Multiphysics Analysis Capability Deployment FY21: Part 3

This report details the progress and activities of Idaho National Laboratory (INL) on the Nuclear Regulatory Commission (NRC) project “Development and Modeling Support for Advanced Non-Light Water Reactors.” The deliverables completed for this report are: Deliverable 1c: the capability to model gas mixtures was added to Pronghorn. A test problem mimicking the conditions achieved in a depressurized loss of forced cooling (DLOFC) event was solved with both RELAP-5 and Pronghorn. Pronghorn employed a finite vol ume method with the Kurganov-Tadmor discretization. The comparison between the mass fraction spatial profiles computed with RELAP-5 and Pronghorn clearly shows the presence of numerical artifacts (i.e., overly diffusive behavior at low Mach numbers). We confirmed that the problem disappears at higher Mach numbers. We recommend future work on the implementation of a low Mach finite volume formulation to better treat low Mach number problems. Deliverable 2a: we demonstrated two approaches to model the radiation/conduction/natural convection heat transfer across a stagnant gas for the PBMR-400 design using Pronghorn. The first approach is based on the net radiation method, which relies on the computation of view factors with the Multiphysics Object-Oriented Simulation Environment (MOOSE) ray tracing capability. The second method is a traditional thermal resistance approach. The test problems include both 2D and 3D geometries. In all cases, the results show very good agreement during a DLOFC transient. This confirms that the faster thermal resistance method produces solutions that are equivalent to the net radiation method for this geometry. Deliverable 3d: we demonstrated the use of the advection kernel for the delayed neutron precursor equation in Griffin with a 2D MSFR model. The results appear physical but further verification is recommended. We also recommend the addition of conjugate heat transfer to compute the temperatures and model the thermomechanic behavior of the reflectors and other structures. Significant memory and performance issues were encountered in the 3D axisymmetric model. Future work is recommended in this area. Task 8g: this task allows multidimensional MOOSE applications to be coupled to system codes (RELAP-7 and SAM). We implemented a faster multiphysics iteration coupling algorithm, which provides an overall 6× acceleration of the 3D-1D coupling of the core multidi- mensional fluid flow solver and the 1D primary and secondary loop model.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Methodological guidelines on concrete degradation based on predictive models and the release of MOSAIC for industry use

In light-water reactors (LWRs), the concrete biological shield (CBS) designates the concrete structure directly facing the reactor pressure vessel (RPV). The primary function of the CBS is to protect equipment and personnel from the neutron and gamma radiation exiting the RPV. Most CBSs in operation in the United States also provide structural support to the RPV. Based on a long-term structural analysis, the structural integrity of the CBS to transfer the in-service passive load to the foundation, dynamic loading during an earthquake, and thermal loading during a loss-of-coolant accident (LOCA) must be maintained. Based on test reactor data for accelerated conditions, the mechanical properties of irradiated concrete are affected when exposed to neutron fluence higher than ≈ 10 19 n.cm -2 (E > 0.1 MeV). At 80 years of operation, the fluence estimates at the surface of the CBS range between 1×10 19 and 7×10 19 n.cm -2 (E > 0.1 MeV): the fluence value depends mostly on the design. Although fluence attenuates through the CBS by virtue of the shielding properties of concrete, about 5% to 10% of the CBS wall depth is affected by high fluence. The main degradation mechanism is the so-called radiation-induced volumetric expansion (RIVE) caused by the amorphization of aggregate-forming minerals. RIVE causes large deformation of up to 18% in pure quartz, and it also reduces the structural properties of concrete. The structural effects of long-term exposure to fast neutron irradiation in LWRs was studied in the report entitled “Assessment of the Effect of the Irradiation-Induced Degradation on the In-Service Structural Performance of the Concrete Biological Shields” (M3LW-23OR0403013). This report illustrates that (1) irradiation-induced damage expands further than the region subject to a cumulative fluence of 10 19 n.cm -2 (E > 0.1 MeV) to reach the steel reinforcement location, and (2) the irradiation-induced damage region shows no substantial residual bearing capacity and should not be accounted for in the integrity assessment of the CBS.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

COBRA-SFS Version 6.2.1 User Guide: A Thermal Hydraulic Analysis Code for Spent Fuel Storage and Transportation Casks

This document is an updated and reduced version of the complete documentation of the COBRA-SFS thermal analysis code (COolant Boiling in Rod Arrays – Spent Fuel Storage) (Michener et al. 1995). This manual provides the analyst with input instructions and fundamental guidelines for contrasting models using COBRA-SFS. COBRA-SFS is designed to analyze the dry storage and transportation casks that house spent or used nuclear fuel. The primary focus and application is on square light water reactor fuel assemblies, however the code also has the capability to model hexagonal assemblies and is will suited to any geometry that can be defined as an extruded 2-D map.

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Process Anomaly Detection for Sparsely Labeled Events in Nuclear Power Plants

An essential aspect of online monitoring, subtle anomaly detection increases the detection lead time for equipment failure and enables a nuclear power plant (NPP) to mitigate unexpected partial or full outages, resulting in significant cost saving to the plant. Once an anomaly is detected by plant staff, its cause and severity are investigated. Because the vast majority of anomalies require some level of investigation, including some that require time-consuming examination, before they are passed over to the engineering organization for further analysis, plants are often equipped with tools to assist the staff in performing anomaly detection. Those tools operate as a black box and are often based on statistical methods that establish sensor correlations using preconfigured mathematical models and flag correlation deviations as anomalies. Due to the number of anomalies detected at a given NPP on a daily basis, a significant number of flagged anomalies usually await examination for days or weeks. A primary cause of this backlog is that the methods used by the tools generate many false positives. Though this is usually attributed to oversensitive model settings due to very narrow normal operation bands, it can also be associated with the model development being inadequate for the process being monitored, or with missing model inputs that could have explained misclassified positives. The performance of anomaly detection tools impacts their plant acceptance and utilization, especially when the effort to address false positives generated by the tool depletes the value or cost saved by using that tool. Thus, means to advance anomaly detection performance have been investigated by the Department of Energy’s Light Water Reactor Sustainability program. Previous and ongoing efforts have targeted unsupervised machine-learning (ML) methods, which do not require the labeling of any data fed into the ML model. By contrast, in supervised anomaly detection methods, every data point is labeled as either a normal or abnormal process condition, and the model is trained to replicate the classification process. Supervised methods usually outperform unsupervised methods, due to the added value in differentiating normal from anomalous states of the monitored process. An NPP’s corrective action program requires it to track and document, via a dedicated report, the resolution of any issues that occur within the plant. Once created, each report is reviewed by a plant screening committee, and several classifications and decisions are made. Recently, a collaborating NPP developed an artificial intelligence and ML-based classifier to categorize a condition report (CR) into classes that can serve to label the data as normal or anomalous. Applying CRs as labels represents a semi-supervised use case. Semi-supervised ML assumes that labels exist for some data points (i.e., labeled anomalies, in this case) but not for the rest. In this effort, semi-supervised ML methods were used to fuse data from CRs with anomaly detection methods in order to test the hypothesis that partially labeled anomalies would improve the accuracy of the anomaly detection methods. Specifically, two methods were used. The first is the deep Semi-supervised Anomaly Detection (deep SAD) method, which can handle labels ranging from fully unsupervised to fully supervised cases. The second is a newly designed ML method developed specifically for this effort and referred to as the high-order feature (HOF)-based method. To evaluate these two methods in controlled environments, synthetic data generators were developed and used. The first datasets used a spring-mass-damper (SMD) system simulator commonly found in mechanical engineering references. This was used to create two use cases: a one- and a three-mass system. Anomalies were introduced by changing the spring and damper coefficients while the system was actuated by random forces. The second datasets used the commercial Dymola-Modelica software to build a simplified nuclear reactor model. Anomalies were added in the form of corrupted sensor readings and/or control commands. The deep SAD method was tested using the SMD system, while the HOF method was tested using both datasets. Application of the deep SAD semi-supervised ML method demonstrated that labels can generate increased confidence in detecting true anomalies. This helped increase the number of true positives and decrease the number of false negatives—something that would aid in addressing the backlog of possible anomalies. Application of the HOF method demonstrated that labels can aid in down selecting from a candidate set of features to a more optimal subset in order to better differentiate between normal and anomalous conditions.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗