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DOE OSTI2022

Application of Artificial Intelligence in Detection and Mitigation of Human Factor Errors in Nuclear Power Plants: A Review

Human factors and ergonomics have played an essential role in increasing the safety and performance of operators in the nuclear energy industry. In this critical review, we examine how artificial intelligence (AI) technologies can be leveraged to mitigate human errors, thereby improving the safety and performance of operators in nuclear power plants (NPPs). First, we discuss the various causes of human errors in NPPs. Next, we examine the ways in which AI has been introduced to and incorporated into different types of operator support systems to mitigate these human errors. We specifically examine (1) operator support systems, including decision support systems, (2) sensor fault detection systems, (3) operation validation systems, (4) operator monitoring systems, (5) autonomous control systems, (6) predictive maintenance systems, (7) automated text analysis systems, and (8) safety assessment systems. Finally, we provide some of the shortcomings of the existing AI technologies and discuss the challenges still ahead for their further adoption and implementation to provide future research directions.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2020

Silica nanocluster binding rate coefficients from molecular dynamics trajectory calculations

Oxide nanoparticle growth from vapor phase precursors occurs in high temperature aerosol reactors first via the formation of nanoclusters, which are nanometer-scale condensed-phase species composed of 10 1 -10 2 atoms. The binding rate for nanoclusters, defined as the rate at which two nanoclusters collide with and stick to one another, is hence of interest in predicting nanoparticle size distribution functions in an aerosol. We have utilized molecular dynamics (MD) trajectory calculations to determine the homogeneous (equal-sized) and heterogeneous (disparate-sized) binding rate coefficients of SiO2 (silica) nanoclusters composed of 18, 144, and 333 atoms. MD trajectory calculations incorporated all-atom models of nanoclusters using a combined Born–Huggins–Mayer-Lennard-Jones potential model, which accounts for both short range interactions and electrostatic interactions. MD calculations were utilized to determine the binding probability as a function of both initial relative velocity and impact parameter; integration of the binding probability across impact parameter and relative velocity space yields the binding rate coefficient. MD trajectory calculations reveal that the most common type of encounters between nanoclusters leading to binding are grazing collisions, i.e. instances where collision would not occur without induced dipole potential influences. The resulting binding rate coefficients are found to be extremely weakly dependent on system temperature, which is in contrast to the use of rate coefficient models which are the product of a hard-sphere collision rate coefficient and a constant enhancement factor (leading to a rate coefficient proportional to the square root of temperature). Enhancement factors defined from MD trajectory calculations fall in the range of 3–9 as system temperature decreases from 1500 K to 300 K. Furthermore, such large values suggest that potential interactions need to be considered when modeling oxide nanocluster growth in the gas phase.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2023

Experimental and numerical investigation of flame stabilization and pollutant formation in matrix stabilized ammonia-hydrogen combustion

Ammonia (NH 3 ) is a carbon-free fuel that offers an attractive alternative for reducing greenhouse gas emissions. However, the slow flame speed, low heating value, and emissions of nitrogen-containing pollutants present significant issues for practical combustion applications. To address these issues, we investigate the use of matrix stabilized combustion. In this type of burner, combustion is performed within an inert porous ceramic foam, heat is recirculated by solid conduction and radiation, which enhances flame speed and combustion stabilization, thereby permitting combustion over a wide range of equivalence ratio conditions. We present a new porous media burner (PMB) capable of stabilizing NH 3 /air flames at ambient conditions. An extensive experimental characterization of the stability of this burner is conducted with up to 30% by volume of hydrogen (H 2 ) in the fuel stream. A 15:1 turndown ratio is demonstrated, with a high thermal power density of 62 MW m -3 . Concentrations of NO, unburnt NH 3 , and H 2 in the exhaust stream are measured. Two regimes are identified for low NO operation: rich and very lean. For rich conditions, NO emissions decrease with increasing equivalence ratio and decreasing H 2 blending. Unburnt NH 3 emissions follow opposite trends. These measurements are complemented by simulations in which the burner is represented by a coupled solid-gas reactor network. In conclusion, this model captures the burner’s pollutant emissions to good accuracy and is used to analyze the mechanisms of pollutant formation.

42 ENGINEERING↗

DOE OSTI2020

Optimizing long-term monitoring of radiation air-dose rates after the Fukushima Daiichi Nuclear Power Plant

Radiation air dose rates near the Fukushima Daiichi Nuclear Power Plant (FDNPP) have been steadily decreasing over the past eight years since the release of radioactive elements in March 2011. Currently, the radiation monitoring program is expected to transition to long-term monitoring after most of the remediation activities are completed. The main long-term monitoring objectives are to (1) confirm the continuing reduction of contaminant and hazard levels, (2) provide assurance for the public, (3) accumulate the basic datasets for scientific knowledge and future preparation, and (4) detect changes or anomalies in contaminant mobility (if they occur), or any unexpected processes or events. In this work, we have developed a methodology for optimizing the monitoring locations of radiation air dose-rate monitoring. Our approach consists of three steps in order to determine monitoring locations in a systematic manner: (1) prioritizing the critical locations, such as schools or regulatory requirement locations, (2) diversifying locations that cover the key environmental controls that are known to influence contaminant mobility and distributions, and (3) capturing the heterogeneity of radiation air-dose rates across the domain. Therefore, for the second step, we use a Gaussian mixture model to identify the representative locations among multiple environmental variables, such as elevation and land-cover types. For the third step, we use a Gaussian process model to capture and estimate the heterogeneity of air-dose rates across the domain. Employing an integrated dose-rate map derived from Bayesian geostatistical methods as a reference map, we distribute the monitoring locations in such a way as to capture the heterogeneity of the reference map. Our results have shown that this approach allows us to select monitoring locations in a systematic manner such that the heterogeneity of air dose rates is captured by the minimal number of monitoring locations.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2023

Sensitivity Analysis of Effectiveness of FLEX Strategies Using a CDF-Based Importance Measure Under Accident Conditions

One of the lessons learned from the Fukushima Daiichi nuclear power plant (NPP) accident is strengthening the station blackout (SBO) mitigation capabilities by enhancing defense in depth for all existing and new NPPs. One of the possible remedies is diverse and flexible coping strategies (FLEX). The objective of this study is to address the benefits of FLEX in various accident scenarios in terms of both risk and cost. FLEX was originally devised against SBO accidents. In this research, we investigate the fundamental plant responses against accidents considering two fundamentally different cases: accidents that lead to high pressure on the primary side and accidents that lead to low pressure on the primary side. Several uncertainties are associated with the characteristics of the FLEX portable equipment. Specifically, the time for FLEX deployment may depend on several factors such as type of accident, point of injection, availability of safety systems, battery backup timings, and human actions. This study utilizes a dynamic risk assessment framework to analyze accident scenarios and suggests a novel importance measure, which is a cumulative distribution function– based importance metric that characterizes the influence of input distribution on complete output distribution. The importance of the existing and newly developed FLEX strategy based on risk significance is illustrated with examples. The suggested measure provides clear insight into how FLEX affects risk of the whole system and additional risk margins thanks to new safety systems.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2020

First Principle based Thermal Conductivity Modeling of Metal Alloys with Applications on Uranium Alloys

Thermal conductivity is an important materials property related to heat transport, which is essential to many applications, ranging from thermoelectrics to nuclear reactor materials. High- quality thermal conductivity data is critical to these materials and their associated technologies, including the nuclear fuel materials like traditional oxide fuels and metallic uranium (U) fuels, e.g. U-Zr and U-Mo alloys. And thermal conductivity modeling is widely used to interpolate or extrapolate experimental data, to obtain high-quality thermal conductivity data over wide temperature and composition range, and to understand the impacts of different factors including defects and microstructures. However, a general thermal conductivity model for metal alloys which can work regrading different phase components is still missing. Also, for U alloys, a thermal conductivity model working with different phases is needed. Therefore, in this work, we developed thermal conductivity models for metal alloys, based on ab-initio calculations, semi-classical physics rules, and limited experimental data. The goals of these models are to help obtain high- quality thermal conductivity data within a little experimental input as possible, have models that are extendable to varying microstructures, including different types of irradiation effects, and provide mechanistic understanding of heat transfer in the modeled alloys. In this work, our model solves several challenges in the development. The DFT-BTE approach is applied to decrease the reliance on experimental data and make the model extendable to composition changes and defects. A practical and efficient way to combine the DFT inputs with physics rules is pointed out in this work too. A staged approach, which starts from simple cases of elemental metals, then extends to solid solutions, different compound phases, and multi-phase mixtures, is presented to work with the metal alloys in different phase components. Our models are demonstrated respectively on aU for elemental metal model, on U-Zr and U-Mo alloys in aU temperature range for multi-phase mixture model, on high-temperature U-Zr, U-Nb, and U-Mo alloys in the body-centered cubic phase for concentrated solid solution model, and on irradiated U-Mo alloys for irradiated metal alloy model. All models show great agreement with experimental data. In these demonstrations, our model shows its advantages compared to previous empirical fitting model. Our model requires fewer experimental data, due to the inputs from DFT. The quantitative insights into the different physical factors are provided in our model, as it incorporates the electron and phonon scattering mechanisms. Our model also can be extended to incorporate the contributions of point defects, grain boundaries, and noble gas bubbles, to integrate their effects on heat transfer. This model can serve as both a foundation for understanding the more complex thermal conductivity of realistic U alloy fuels and a useful tool to guide further modeling of thermal conductivity to aid materials and device design.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2020

FY20 Status Report on Creep Rupture Testing to Support the Development of Alloy 709 Code Case

This report provides an update on the status of the creep rupture testing on the first commercial heat of Alloy 709 in support of the Alloy 709 Code Case development. A creep test laboratory has been set up at ANL that comprises of 15 indirectly loaded test frames capable of testing ASTM-size specimens of the commercial heat of Alloy 709. The systems are equipped with high temperature furnaces capable of operation up to 1000°C in an air environment. During FY18, uniaxial ASTM-sized creep specimens were fabricated from 9 Alloy 709 plates that were processed by AOD, ESR, and ESR-homogenized routes and subsequently solution annealed at 1050, 1100, and 1150°C, and creep-rupture tests were performed at 330MPa and 600°C. The test results led to the down selection of the ESR-1100°C condition to support the code case. In FY19, 15 creep-rupture tests of the ESR-1100°C material, requiring the use of Type K thermocouples, were initiated to support the 100,000-hour Code Case. 8 tests were completed in FY19. In FY20, 6 tests were completed at the time of writing this report. In addition, 1 more test were loaded in FY20, using Type S thermocouples, and was completed. This report presents the data from the completed tests in FY20 and also the microstructural characterization of the fractured specimens. The creep data enabled the preliminary analysis of the creep behavior of this material. The characterization showed that in brittle fractures, the pores were narrow and thin, and elongated in the direction perpendicular to the loading direction, while in ductile fractures, the pores were much rounder. Dense precipitates were observed in all the samples, the size of which grew with test temperature. Some of the precipitates could be identified to be M23C6 based on their cuboid shape.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2022

Mechanisms of Retention and Transport of Fission Products in Virgin and Irradiated Nuclear Graphite

To fulfill the design and licensing requirements for advanced reactors, the U.S. Department of Energy (DOE) is specifically interested in targeted research to quantify the mechanisms of fission product transport and retention in graphitic grades that will likely be used in next-generation very/high temperature reactors, fluoride salt-cooled high temperature reactors and molten salt reactors. We have examined an integrated experimental-computational approach to determine the diffusivities of selected fission products – ruthenium (Ru) and silver (Ag) in five nuclear graphite grades – POCO AXF-5Q, POCO ZXF-5Q, PCEA, IG110, and NBG-18. Experimental investigation for diffusion of other fission products (iodine, cesium, and krypton) in graphite could not be carried out due to extreme evaporation due to high vapor pressure, despite several attempts incorporating various experimental schemes. Experimental investigation with irradiated graphite could not be carried out because necessary approval to transport irradiated graphite could not be obtained due to procedural reasons at ORNL and national policy change in UK. An effort was made to “produce” by ion sputtering, but it was discontinued because the outcome did not adequately represent irradiated graphite. Thin film and “cup-and-cap” methods were employed to deposit fission products, diffusion annealed were carried out in an argon atmosphere, and concentration profiles were determined by dynamic secondary ion mass spectroscopy depth profiling technique. Regardless of graphite type, anomalous diffusion behavior of Ru (i.e., lower than expected based on Arrhenius temperature dependence) at an intermediate temperature, around 600 to 700 °C, was observed. Diffusion behavior of silver on the other hand agreed well to the Arrhenius temperature dependence although the excessive evaporation of silver hampered the accurate determination of diffusivities at temperature higher than 900 °C. In general, silver was observed to diffuse faster than Ru in the temperature range compared from 500 to 900 °C, had consistently had higher pre-exponential factor corresponding to higher jump frequency. To understand the abnormal diffusional behavior of Ru in graphite in intermediate temperature range, a detailed microstructural analysis was carried out. Clustering of Ru into particles on the surface of graphite was observed around 700 °C corresponding to de-wetting and spheroidization. This change would influence the boundary condition of diffusion, although features of clustering was much smaller (<1 mm) than the SIMS raster size (120 x 120 mm). Raman spectroscopy also demonstrated that Raman peak intensity for Ru decreased significantly for samples annealed higher than 700 °C and presence of Ru in graphite altered the crystallinity of graphite. To further elucidate the abnormal diffusion behavior observed in intermediate temperature investigated, the vibrational properties of graphene, bilayer graphene and Kr atoms in bilayer graphene were investigated with molecular dynamics. Krypton, which is a fission product, was introduced between a bilayer graphene system to evaluate (i) whether the phonon dispersion curves change with high temperature in bilayer graphene (ii) whether the addition of Kr atoms between the bilayer introduces any significant change in the vibrational properties, and (iii) whether any change in the vibrational properties can be correlated to the diffusive behavior of Kr atoms. The results show that the Kr atoms indeed exhibit an anomalous diffusive behavior at 550°C. Phonon analysis shows that a few phonon frequencies are enhanced as much as 20 to 30 % with the addition of just 0.2 at.% Kr. So, this may explain the unexpected self-diffusivity of fission products.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2022

Tritium diffusion and formation in the bulk and defective surface of γ-LiAlO2 pellets: First-principles investigation

In tritium-producing burnable absorber rods (TPBAR), γ-LiAlO2 is used in the form of an annular ceramic pellet enriched with the 6Li isotope. When irradiated in a pressurized water reactor (PWR), the 6Li pellets absorb neutrons and produce tritium (3H) through 6Li + n 3H + α. The 3H chemically reacts with the metal getter where it is captured and leads to formation of a metal hydride. For TPBARs to enable effective tritium production in PWRs, we investigated the 3H diffusion pathways in the bulk and surface of γ-LiAlO2 with different concentrations of lithium defects. The calculated results for bulk and low-index surfaces, thermal conductivity, 3H activation energy barriers, and the 3H diffusion coefficients in γ-LiAlO2 are in good agreement with the available experimental values. In the bulk, our results show that the smallest activation energy barrier is 0.63 eV for substitutional 3H diffusion with a diffusion coefficient of 3.25x10-12 m2/s. After 3H diffused from bulk to the surface, it could form different species (such as 3H2, 3H2O, C3H4) depending on the surface structure, vacancy types and the impurity carbon. Our results indicate that the 3H2 is the main product from γ-LiAlO2 pellets. As the number of VLi vacancies and 3H atoms increases under irradiation (3H-rich condition), 3H2O release could increase from the surface of γ-LiAlO2 pellets.

Jia, Ting↗

DOE OSTI2022

Submersible Multistage Centrifugal Pump for Versatile Test Reactor Cartridge Test Loop

Submersible multistage centrifugal pumps are ideal for pumping in narrow confined spaces and achieving necessary head pressures and flow rates. Once a diameter is determined then manipulation of the number of stages and motor speed are all that are required to meet desired flow conditions. The Versatile Test Reactor (VTR) closed loop cartridge systems will need forced convection cooling independent of the main reactor. A multistage centrifugal pump can meet the necessary flow rates and pumping pressures while minimizing space taken. The pump considered for this work was based off a deep well submersible pump, a variation of a multistage centrifugal pump. We experimented with two pump sizes, 5 cm (2 inch) and 7.5 cm (3 inch) diameters. These diameters were chosen to fit into the inner diameter of standard 5 and 7.5 (2 and 3 inch) Schedule 40 pipe, respectively. This made the design for the test loop both simpler and less expensive as the need for an engineered pump housing was eliminated. Initial test cartridge planning indicated space for only a 5 cm (2 inch) diameter pump, though early testing of this size showed the need for an abnormally high-speed and high-power motor. Fine tuning of the cartridge design allowed a pump size increase to 7.5 cm (3 inches), which was the pump size most extensively tested in this work. The test loop is composed of various sizes of PVC and aluminum piping components in a loop configuration. The pump is driven by a Pittman 250 W (1/3 horsepower) electric motor with maximum speed of 3,450 RPM. Testing consisted of running the pump at a constant motor speed while varying a control valve to restrict flow through the loop, with differential pressure and flow rate recorded. This was done for one and two stage configurations for the 5 cm (2 inch) diameter impeller design and one, two, and three stage configurations for the 7.5 cm (3 inch diameter) impeller design, respectively. Due to pumping power requirements, two and three stage 7.5 cm (3 inch) diameter impeller testing at higher flowrates lowered the motor speed substantially. In regions where motor speed could not be maintained constant, the data were discarded. The test loop was also reconfigured to allow for the pump to be tested for pressure drop in a stalled or inoperable (0 RPM) flow condition. Demonstration of adequate natural convection cooling of the test cartridge fuel type is necessary under accident conditions, and this will depend upon the flow resistance through the impeller assembly when the pump is not operating. Thus, accurate knowledge of the effective impeller assembly loss coefficient is important for safety evaluations. The test loop was modified to provide water inlet and outlets on either side of the pump impeller stack, and a metered flow of lab water was provided in order to measure the pressure drop across the cartridges as a function of flowrate. Data from the pump head curve testing developed as part of this work and supported by analysis using pump head affinity laws indicates that a three stage 7.5 cm (3 inch) pump impeller design will meet target requirements for coolant flow within the VTR cartridge sodium cartridge at full power conditions [1] with margin; this corresponds to a flowrate of 45 l/min (12 gpm) at a pressure drop of 6.1 m (20 feet) of water head. The results of the pressure loss measurements across the impeller assembly when the pump is stationary (i.e., at 0 RPM) indicate that the pressure loss coefficient is 0.921 for a two impeller stack configuration; this value is calculated based on the flow velocity through the minimum available flow area within a single stage of the impeller which corresponds to 1.4 cm2.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2023

Preliminary Characterization and Evaluation on FFF Manufactured 316H and ODS Steels

The Advanced Materials and Manufacturing Technology (AMMT) program develops cross-cutting technologies in support of a broad range of nuclear reactor technologies and maintains U.S. leadership in materials and manufacturing technologies for nuclear energy applications. The overarching vision of AMMT is to accelerate the development, qualification, demonstration, and deployment of advanced materials and manufacturing technologies to enable reliable and economical nuclear energy. Solid-state advanced manufacturing techniques can overcome some of the challenges in liquid-based additive manufacturing (AM) processes and should therefore be considered in material design and manufacturing as well. The work presented in this report forms part of a study on solid-state AM techniques of 316 stainless steels (SS) and oxide dispersion strengthened (ODS) steel components and supports the vision and goals of the AMMT program relevant to accelerate the development and deployment of advanced manufacturing processes. Achieving this can provide a safety improvement through larger safety margins, economic benefit for higher efficiency during operation, and a cost reduction through more effective manufacturing processes and less waste. This study provides preliminary information on development of the fused-filament fabrication (FFF) process using different powder types to demonstrate the sensitivity, and therefore the characterization of these sample components. The full solid-state manufacturing feasibility study will be completed and reported in a final feasibility evaluation during 2025. The study investigation used two 14YWT ODS powder batches, which provided information and the effect of different powder morphologies on manufacturability. The two 316SS powders demonstrated the effect of powder size on the manufacturability using FFF. Two product forms, namely a honeycomb structure and flat samples, were manufactured to demonstrate the flexibility of product form.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Baseline Hypothetical Facility for the Production of 131 I and 99 Mo using Activation Targets

This report describes a hypothetical facility for production of medical radioisotopes via activation under the Proliferation Resistance and Optimization (PRO-X) program. The facility uses neutron activation of non-special nuclear material (SNM) to produce the medical isotopes 131 I and 99 Mo at a throughput of 60 Ci/week of 131 I and 5 Ci/week of 99 Mo. The hypothetical design was carried out using a 10 MWt research reactor. The precursors used for the activation process were TeO2 for 131 I and MoO 3 for 99 Mo. The processes are performed in 3 hot cells used for target receipt, extraction, purification low specific activity (LSA) generator introduction, and packaging. A fourth hotcell is used for waste processing. The hot cell processing area takes up a footprint of 15.4 m 2 with the total footprint of the facility, including space for administrative offices, non-rad labs, quality assurance, and radiation buffer areas set at 763 m 2 . Waste is produced at a weekly rate of 257.8 g low activity solid waste and 8032.7 mL of low activity liquid waste, 8032 mL of which is water. This baseline hypothetical facility for production of medical isotopes via activation was then compared and contrasted to the hypothetical facility for production of medical isotopes via fission products to show the differences in approach for the two production modes. The two production modes had several highlighted differences including the overall facility and hot cell layout, the type and amount of waste produced by the respective facilities, and economic factors impacting production mode. Finally, a decision tree for which production mode might be more beneficial for an entrant into medical isotope production was developed based on the differences examined and the desired output of medical isotopes desired by the entrant.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2025

Microreactor Assembly Transportation Cask Model Description for Criticality Safety Validation Basis Assessment

Criticality safety analyses are completed on a transportation cask used for microreactor assembly shipment to provide an example of model and analysis to industry for reproducing this type of study on their microreactor fuel shipment. The fuel assembly considered is based on a gas-cooled microreactors (GC-MR), which utilizes HALEU fuel in the form of TRISO particles and utilizes various design options considered in industry designs. Various versions of this GC-MR assembly were studied, with and without YH 2 moderator, providing similar conclusions.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2020

High-energy synchrotron x-ray study of deformation-induced martensitic transformation in a neutron-irradiated Type 316 stainless steel

An unusual tensile deformation behaviour in the form of a propagating band along the sample gauge was observed in two neutron-irradiated 316 stainless steel samples during room-temperature tests, leading to a combination of high strength and high ductility. These bands were not observed in an unirradiated counterpart. With the help of in situ high-energy synchrotron x-ray diffraction, the phase-specific crystal information was tracked at different deformation levels in each sample. Post-irradiation and post-deformation samples were examined using electron microscopy to characterize various microstructural features. All samples displayed a deformation-induced martensitic phase transformation, which was identified as a second strain-hardening mechanism accompanying the dislocation hardening. The deformation-induced martensitic transformation was rationalized by the effect of applied stress on the effective martensite start temperature. The results showed that the irradiation did not alter the dislocation hardening and the martensitic transformation mechanisms, but the increased yield strength in irradiated materials facilitated the localized phase transformation at the onset of plastic deformation, in contrast to the unirradiated material which required pre-straining. The hardening effect of the martensitic transformation reduced the tendency towards necking and mitigated the loss of ductility in the irradiated material by carrying the deformation in the form of a propagating band. Despite the beneficial effect from the martensitic transformation, this study indicates that this mechanism cannot not be activated at typical operating temperatures of nuclear reactors.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Detection of Diversion in a Realistic Heat Pipe Microreactor Using Supervised Machine Learning

Microreactors (MRs) pose new challenges for international safeguards. Here, their small size and mass reproducibility make them ideal for deployment in greater numbers and in remote locations, making the job of safeguards inspectors more challenging. Machine learning (ML) is currently being applied to many fields to augment human performance and increase automation; in particular, ML could be used to provide insight for international inspectors to help detect the diversion of nuclear fuel from MR cores. Four ML model types (k-nearest neighbors, decision tree, random forest, and histogram-based gradient boosted ensemble) were trained on integrated flux and critical control drum angle data generated with Serpent 2 for a realistic heat pipe MR design, achieving nearly 100% binary classification accuracy of nominal and diversion core configurations by the end of 1 full power year for three of the four model types. Regression model variants were also trained, using the same input data, for predicting the number of fuel pins diverted. Root-mean-square errors below 5% of the total number of fuel pins were achieved by the 1 full power year mark for all models.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2023

On the Language of Reliability: A System Engineer Perspective

In its classical definition, risk is defined by three elements: what can go wrong, what are its consequences, and how likely is it to occur? While this definition makes sense in a regulatory-based framework where for the current fleet of operating light water reactors (LWRs), the risks associated with nuclear power plants typically are characterized in terms of core damage and large early release frequency (LERF), this approach does not provide a useful snapshot of the health of the plant from a broader perspective. This is due to the very narrow context in which the term “risk” typically is defined as nuclear safety aspects that have the potential to impact public health. In this paper, we take the viewpoint of nuclear safety that is reflective of the current fleet of operating LWRs for which core damage frequency and LERF are appropriate metrics. For other advanced reactor designs, other more applicable technology neutral metrics of reactor safety metrics would be specified. A possible alternate path would start by redefining the word risk with a broader meaning that better reflects the needs of a system health and asset management decision-making process. Rather than asking how likely an event could occur (in probabilistic terms), we can ask how far this event is from occurring. Our approach starts by defining and quantifying component and system health in terms of a “distance” between its actual and limiting conditions, i.e., determination of the margin that exists between the current state/condition and the state where the component/system is no longer capable of achieving its intended function. A margin is a measure that is more reflective of the current state or performance of a component, and therefore more closely tied to decisions that are made on an ongoing basis. Further, we will show how, given the data available from plant equipment reliability and monitoring (e.g., pump vibration data) and prognostic (e.g., component remaining useful life estimation) data, a margin can be described and determined for all types of maintenance approaches (e.g., corrective or predictive maintenance). We show how classical reliability models (e.g., fault trees) can be used to quantify the system margin provided component margin values. In the approach described in this paper, the propagation of margin values through classical reliability models are not performed using classical probabilistic calculations applied to sets (as performed in a typical plant probabilistic risk assessment). Instead, we show how it is possible to propagate margin values through Boolean logic gates (i.e., AND and OR operators) through distance-based operations.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2022

Ensuring a Nuclear Power Plant Safe State Following an EMP Event - Task 7 Deliverable: EMP Testing of Secondary Coupling to Instrumentation Cables

Sandia National Laboratories performed tests to address the potential vulnerability concerns of a coupled High-Altitude Electromagnetic Pulse (HEMP) inducing secondary coupling onto critical instrumentation and control cables in a nuclear power plant, with specific focus on early-time HEMP. Three types of receiving cables in nine configurations were tested to determine transfer functions between two electrically separated cables referenced to the common mode input current on the transmitting cable. One type of transfer function related the input short circuit current and resulting open circuit voltage on the receiving cable. The other transfer function related the input short circuit current and the resulting short circuit current on the receiving cable. A 500 A standard HEMP waveform was input into the transfer functions to calculate peak coupling values on the receiving cables. The highest level of coupling using the standard waveform occurred when cables were in direct contact, with a peak short circuit current of 85 A and open circuit voltage of 9.8 kV, while configurations with separated cables predicted coupling levels of less than 5 A or 500 V.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2023

Coolant Pump Predictive Data Analytics from Signatures Generated by the Recursive Short Time Fast Fourier Transform

Although a nuclear reactor is a hostile environment for sensors and signal transmissions, the reactor core is amenable to acoustic communication. An acoustic measurement infrastructure installed at the Advanced Test Reactor (ATR) nozzle trench area records acoustic signals that can capture reactor operating states. The distinct states produce unique signatures that can be identified and tracked using data processing and data analytics. The infrastructure relies on acoustic transmission through ATR in-pile structural components, piping, and coolant that transmit acoustically modified signals generated by the coolant pumps. This paper will discuss results from using the Recursive Short Time Fast Fourier Transform (RSTFFT) technique used to process acoustic signals and provide signatures that are identified and monitored by analytics. The RSTFFT is applied to ATR data to understand the vibration levels and signatures for different operating regimes as displayed by the spectrogram. The combination of coolant pumps for normal and high-power operation generate unique signatures. These acoustic signatures are used to develop machine learning approaches to automatically classify operating regimes. Two machine-learning models, Support Vector Machines and Linear Discriminant Analysis, were developed to classify two event classes. Class 1 is a normal steady-state operation, and Class 2 is any event that is due to start up, shut down, or other actions. Both types of machine learning models had over a 96% prediction accuracy for the two classes. These results lay the foundation for predictive analytic frameworks that can be leveraged by ATR to optimize operations and maintenance.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗