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DOE OSTI2025

Impact of Nuclear Power Plant Energy Storage on Grid Reliability and Generation Costs with Variable Power Generation

This report examines the impact of combining integrated energy systems (IES), specifically hydrogen-based energy-storage systems, with nuclear power plants (NPPs) on grid reliability and generation flexibility in scenarios with substantial variable-power generation from solar energy. The analysis focuses on the challenges and solutions associated with high-levels of solar energy penetration, highlighting the role of advanced energy-storage solutions and flexible-generation technologies in enhancing grid stability and reliability.

29 - ENERGY PLANNING, POLICY AND ECONOMY↗
DOE OSTI2025

Cyber-Physical Tabletop Exercise for Small Modular Reactor Facilities

U.S. nuclear power facilities face increasing challenges in meeting dynamic security requirements caused by evolving and expanding threats while keeping costs reasonable to make nuclear energy competitive. This evolving threat landscape includes adversaries having offensive cyber capabilities to attack information technology (IT) systems and operation technology (OT) systems. These adversaries may have the ability to attack the physical protection system (PPS) networks with potential consequential impacts that could degrade the effectiveness of the PPS. These cyber attacks may also be used to attack the safety and operational systems used to operate and ensure the safety of the reactor. Additionally, adversaries may gain access to unmanned aerial systems (UAS) that may be used to provide reconnaissance and surveillance of the facility, provide information to the adversaries, and be equipped with kinetic capabilities such as explosives or weapons that can be used to directly attack the facility. The Department of Energy’s Office of Nuclear Energy’s Advanced Reactor Safeguards and Security (ARSS) program funded Sandia National Laboratories (SNL) and Idaho National Laboratory (INL) to develop a cyber-physical tabletop exercise (TTX). This exercise was conducted on a hypothetical small modular reactor (SMR) facility, and only considered a potential adversary cyber attack on the PPS to a physical attack on the hypothetical facility to achieve a radiological release. This cyber-physical TTX is meant to provide lessons learned to integrate the cyber security system design and the physical protection system (PPS) design to decrease design, operation, and maintenance costs as well as increase effectiveness for defending against design basis threat attacks at the facility. This TTX will also provide a framework and method for SMR and microreactor vendors to conduct their own cyber-physical TTX and gain impactful insights to improving the cyber and physical protection system design for their SMR or microreactor facility design.

42 ENGINEERING↗
DOE OSTI2025

Modularization of Small Modular Reactor Facilities: Physical Protection Recommendations

U.S. nuclear power facilities face increasing challenges in meeting dynamic security requirements caused by evolving and expanding threats while keeping costs reasonable to make nuclear energy competitive. In consideration of the economic viability of small modular reactor (SMR) facilities, many designers and utilities are considering a modular approach to the construction and operation of these facilities. This modular approach considers building and operating a first unit; once the first reactor is in operation, construction will begin on a second reactor. This process would allow the vendor or utility to ensure production of energy and financial income while the second reactor is under construction. This project evaluates the feasibility of modular construction in terms of physical protection and identifies several recommendations for vendors and utilities considering this approach. To conduct this evaluation, a hypothetical three-unit SMR facility was developed, a physical protection system (PPS) was considered for the design, and a hypothetical design basis threat (DBT) was used to evaluate this PPS. Multiple outsider sabotage scenarios were examined, with adversary team sizes ranging from 4-to-8 to determine security system effectiveness. The results of this work will influence PPS designs and facility designs for U.S. domestic SMRs. This work will also demonstrate how a series of experimental and modeling capabilities across the Department of Energy (DOE) complex can impact the design and completion of security-by-design (SeBD) for SMRs considering modular construction. The conclusions and recommendations in this document may be applicable to all SMR designs.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

Machine-Learning Enabled Evaluation of Probability of Piping Degradation In Secondary Systems of Nuclear Power Plants

The transition to condition-based, risk-informed automated maintenance will contribute to a significant reduction of operations and maintenance costs that account for the majority of nuclear power generation costs. Furthermore, of the operations and maintenance costs in U.S. plants, approximately 80% are labor costs. To address the issue of rising operating costs and economic viability, technologies used to perform online monitoring of piping and other secondary system structural components in commercial nuclear power plants (NPPs) are under evaluation. These online monitoring systems have the potential to identify when a more detailed inspection is needed using real time measurements, rather than at a pre-determined inspection interval thus reducing the maintenance cost. This paper describes distributed high-temperature stable fiber sensors fabricated in optical fibers through a roll-to-roll laser direct writing process using femtosecond lasers. Using phase-sensitive optical time domain reflectometry, distributed acoustic and vibration sensors can be developed and deployed to critical components and systems in NPPs to perform active measurements with spatial resolution down to 0.5-meter throughout the piping systems. Complex acoustic and vibration signatures harnessed by distributed sensors are registered and analyzed by artificial intelligence algorithms for degradation detection and flaw identification. Piping elbows with machined-in flaws were instrumented with fiber sensors. High-spatial-resolution data were used to develop and validate machine learning algorithms, including both linear and nonlinear regression, and classification. Additionally, classification and sensor analysis were also performed for data analysis. The paper concludes with recommendations and future work on applications of machine learning enabled high-resolution fiber sensors for piping degradation monitoring in current or future NPPs.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

The Cost of (In-) Accurate Waste Characterization in the U.S. Nuclear Power Industry - 20066

Proper disposal of waste has never been a human priority. Our history is full of examples of throwing away things with minimal effort or thought to consequence. That is until disease or toxicity become apparent and we realize we need to change. Unfortunately, we almost never have all the information we need at the time we make decisions. In addition to the technical and scientific issues, profits and politics are also factors. Newton's third law also applies to politics and so for every policy (action) put in place, there will be (opposite reaction) forces in play to push back against it. These forces are seldom balanced and so the reaction to the discovery of harm is to over-correct and destroy the benefit to be had. This of course causes those who want the benefit, or profit from it, to work to undermine or repeal those measures put in place to eliminate the harm. The issue is exacerbated when the problem to be solved is highly technical and at the edge of our science so that the harm and benefit cannot be easily or accurately quantified. At these times, reason often goes out the window and our decision makers are influenced by either greed or fear as these emotions are much easier to stoke. Those of us in the middle, with the charge to 'do the right thing for the least cost', are therefore frequently constrained and forced into actions that are neither technically the right thing to do and not cost effective. The cost of radioactive waste disposal is based on the concentrations of various radioisotopes in the waste. Some of these isotopes are relatively easy to quantify and some are not. Most laboratory methods for quantification are limited in the amount of activity that can be present during the measurement process. Current nuclear plants were not designed with the idea that taking truly representative waste samples would be important. The limits used to define waste class and therefore cost are precisely defined but the methods for determining those concentrations are far less precise. Improving the accuracy of radioactivity concentrations in waste and having consistent and reasonable oversight can reduce waste costs through active management of the process. So what can we do about it? Science may provide an answer. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2023

Development of a Technical, Economic, and Risk Assessment Tool for the Evaluation of Work Reduction Opportunities

Efficient and cost-effective operation of a nuclear power plant (NPP) is essential to ensuring long-term economical and safe operation. Multiple cost saving opportunities exist, referred to here as work reduction opportunities (WRO). These WROs reduce plant operating costs by employing various cost-effective strategies (e.g., implementation of modern technologies). Identifying and objectively screening WROs is an essential task to help reduce overall costs. However, there is no comprehensive framework for assessing WROs in the nuclear industry and evaluating their impact on plant operations. This report presents a novel framework for systematically evaluating WROs from a technical, economic, and risk perspective. As NPPs continue to add new technology and implement modernization strategies into their current processes, potential WROs are commonly identified. Although most WROs have the potential to reduce costs, not all opportunities will result in significant cost savings due to unforeseen risks, large implementation costs, or benefits that fall short of expectations. Examples of this can be the result of a technology that is not fully developed, uncertainty in the amount of cost reduction, or difficulties introducing a new process into an organization. These uncertainties can manifest several ways and can result in a WRO with limited cost savings or even a loss of investment. The framework developed emphasizes the importance of effectively screening the WROs from a holistic perspective to objectively identify inefficiencies and ensure a positive impact to the organization. This report presents the Technical, Economic, and Risk Assessment (TERA) as a key methodology for the screening and evaluation of potential WROs. The TERA framework begins with a screening phase where the process is examined through a hybrid combination of Lean Six Sigma and Integrated Operations for Nuclear (ION) guiding principles. This framework examines the current processes using the Lean Six Sigma SIPOC (Suppliers, Inputs, Process, Outputs, Consumers) methodology but retains the ION key elements of People, Technology, Process, and Governance as important factors to the nuclear decision-making process. By combining the principles of Lean Six Sigma and ION, the developed screening process is specific to the nuclear industry in that it systematically evaluates WROs in order to implement new technology that is comprehensively evaluated. The TERA begins by mapping current processes as they relate to WROs and examining the inefficiencies. Furthermore, the created process map can be used to identify and evaluate potential solutions. Using key performance indicators (KPIs), the TERA evaluates each area—technology, economics, and risk—for uncertainties and to perform cost-benefit analysis. The results of the TERA are important KPIs that allow for an evaluation of different processes and technology implementations. This assessment enables decision-makers to compare various WROs based on metrics and then make informed decisions for which opportunity to implement first. This research includes not only the creation of the TERA framework, but also the evaluation of its performance. A case study for screening potential WROs at Southern Nuclear Company is presented that utilizes the TERA methodology. Through the use of TERA, various WROs were screened, and the solutions evaluated for cost-benefit expectations. The report concludes by summarizing the overall effort and implications for utility modernization. The performance of the screening and TERA are discussed as well as the impact on the nuclear industry. The TERA process enables utilities to evaluate and inform investment decisions for WROs and mitigate any potential risks. Through this research, we provide utilities with a valuable framework to optimize operations, reduce costs, and drive continuous process improvement.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

NSRD-20, Functional Testing of Novel MTC HEPA Filtration Media

To improve the safety of Department of Energy (DOE) nuclear facilities, this project aimed to develop ceramic high efficiency particulate air (HEPA) filters that also create a low pressure-drop (dP) in use. The filters under consideration use mini-tubular ceramic (MTC) HEPA filtration media made with different architectures. Once successful, this project will reduce life-cycle costs, including safety basis, operational, and waste-disposal costs. The technology’s mini-tubular geometry is known to reduce dP when compared to flow through membranes of equivalent mass and surface area. Low dP facilitates retrofitting advanced filters into existing DOE facilities to make them safer while simultaneously reducing operational costs. Operations of ventilation systems are a key cost driver for DOE nuclear facilities; reducing dP can significantly reduce DOE’s operational costs. However, the filtration efficiency (FE) of this type of filtration media depends on the architecture of the filter media in an unknown way and requires testing. Functional testing of filtration media with different architectures will establish the performance of the filtration media and will enable development of guidance on design requirements to optimize filter performance.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Early-stage oxidation and subsequent damage of the used nuclear fuel extractant TODGA; electron pulse radiolysis and theoretical insights

Radiation induced damage of extractant molecules is a well-known phenomenon responsible for reducing efficiency and increasing the waste and cost of reprocessing used nuclear fuel (UNF). As such, understanding early-stage (pico- to nanoseconds) radiation-induced reaction mechanisms is essential for informing the design of next generation extractants with enhanced radiation robustness. Here, in this work, we utilized picosecond and nanosecond electron pulse radiolysis experiments to probe the early-stage radioactive environment experienced by the organic phase extractant N,N,N',N'-tetraoctyldiglycolamide (TODGA), proposed for separating highly radioactive trivalent minor actinides (specifically americium and curium) from the trivalent lanthanides. Using comparisons to the similar ionization potential (IP) solute p-xylene, this work determined the mechanism of reaction with the ionized diluent (i.e., n-dodecane radical cation, DD˙ + ) is hole transfer to produce TODGA˙ + . At high TODGA concentrations (>100 mM), the majority of this transfer occurs faster than 10 ps via the capture of DD˙ + holes prior to their solvation with a C 37 = 300 mM. The surviving solvated holes were captured with k = (2.38 ± 0.15) × 10 10 M -1 s -1 . Attempts at subsequent hole transfer to lower IP solutes found that only 10% of holes were transferred, indicating bond rupture of TODGA˙ + occurs within 2.6 ns at 200 mM TODGA. Possible reaction pathways for the rapid decomposition of TODGA˙ + were explored using a combination of experiments and density functional theory (DFT) calculations.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2020

HAZARD ANALYSIS OF DIGITAL ENGINEERED SAFETY FEATURES ACTUATION SYSTEM IN ADVANCED NUCLEAR POWER PLANTS USING A REDUNDANCY-GUIDED APPROACH

Replacing the existing aging analog instrumentation and control (I&C) systems with modern safety control and protection digital technology offers one of the foremost means of performance improvements and cost reductions for the existing nuclear power plants (NPPs). However, the qualification of digital I&C systems remains a challenge, especially considering the issue of software common-cause failures (CCFs), which are difficult to address. With the application and upgrades of advanced digital I&C systems, software CCFs have become a potential threat to plant safety because most redundant designs use similar digital platforms or software in the operating and application systems. With complex designs of multilayer redundancy to meet the single-failure criterion, digital I&C safety systems (e.g., engineered safety-features actuation system [ESFAS]) are of a particular concern in the U.S. Nuclear Regulatory Commission (NRC) licensing procedures. This paper applies a modularized approach to conduct redundancy-guided systems-theoretic hazard analysis for an advanced digital ESFAS with multilevel redundancy designs. Systematic methods and risk-informed tools are incorporated to address both hardware and software CCFs, which provide guidance to eliminate the triggers of potential single points of failure in the design of digital safety systems in advanced plant designs.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

AI for Interpreting Nuclear Power Plant Documents for Power Uprates

To reduce the cost and time needed for regulatory compliance, nuclear power plants (NPPs) can utilize artificial intelligence (AI) to assist in interpreting complex and voluminous documents that typically span thousands of pages. Usually, the process of interpreting a plant’s technical specifications (TSs) and associated documents is labor intensive. This study aims to understand what processes state-of-the-art large language models (LLMs) can automate and to identify the pitfalls associated with using LLMs to reduce human labor costs and time. This research uses a recent AI technology called retrieval augmented generation (RAG), which retrieves pages of information from TSs and associated documents to assist with NPP power uprates (cleared to produce more power). LLMs are integral to RAG because they create human-like responses based on the retrieved information, aiding in the interpretation and application processes. A baseline case demonstrates how LLMs can operate successfully for a power uprate application. Then five use cases show five types of potential failures: (1) RAG retrieving the incorrect information, (2) RAG misinterpreting the retrieved information, (3) RAG relying on knowledge not contained in the retrieved information, (4) RAG hallucinating, and (5) RAG refusing to answer. The results of the five use cases suggest that automating the human interpretation of TSs and associated documents with AI should be approached with caution. A subject-matter expert reviewed the AI outputs from the five use cases and concluded that an LLM can produce technical information that is needed to produce power uprate applications in certain instances.

21 - SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLAN↗
DOE OSTI2023

Silicon carbide fiber manufacturing: Cost and technology

Significant advances have been made in the past decade concerning silicon carbide fiber manufacturing methods resulting in near-stoichiometric small-diameter fibers that meet the property requirements for most of the ceramic matrix composites (CMC) and nuclear applications. The manufacturing cost, however, remained prohibitively high, preventing the use of it in different applications requiring much lower cost. Silicon carbide (SiC) fiber reinforced CMC is dominated by the cost of SiC fiber which comprises more than 50 % of the finished part cost. Here, this article provides insight into the SiC fiber manufacturing costs and highlights the need for an alternative SiC fiber precursor and manufacturing method. Analysis of the existing polycarbosilane (PCS)-based SiC fiber manufacturing shows that the crosslinking (curing) and raw material preparation steps are high-cost steps that need lower cost options. Alternative SiC fiber precursor should be sought for lowering the cost of SiC fibers.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Development of Thermal Tomography Imaging System for In-Service Nondestructive Evaluation of Additively Manufactured Components

Additive manufacturing (AM) is an emerging method for cost-efficient fabrication of nuclear reactor parts. AM of metallic structures for nuclear energy applications is currently based on laser powder bed fusion (LPBF) process, which can introduce internal material flaws, such as pores and anisotropy. Integrity of AM structures needs to be evaluated nondestructively because material flaws could lead to premature failures due to exposure to high temperature, radiation and corrosive environment in a nuclear reactor. Thermal tomography (TT) provides a capability for non-destructive evaluation of sub-surface defects in arbitrary size structures. We investigate TT of AM stainless steel 316L specimen with imprinted internal porosity defects using relatively low-cost, small form factor infrared (IR) camera based on uncooled micro bolometer detector. Sparse coding related K-means singular value decomposition (SVD) machine learning, image processing algorithms are developed to improve quality of TT images through removal of Additive white Gaussian noise without blurring the images. Following initial qualification of an AM component for deployment in a nuclear reactor, a compact TT can also be used for in-service nondestructive evaluation (NDE). With capability to perform in-service NDE of the AM component lifecycle, TT data can be used for development of a component digital twin. MIT research reactor (MITR) has been identified as a representative environment to perform investigation of feasibility of in-service NDE during shutdown. Preliminary study of radiation level in the MITR viewport, with geometric parameters potentially compatible with compact TT system, has been conducted.

36 MATERIALS SCIENCE↗
DOE OSTI2023

The Cost Drivers and The Most Time-Consuming Activities of the MARVEL Microreactor Project

This study aims to identify what drives cost and what project activities are the most time consuming within a microreactor project such as MARVEL. Identifying these cost and time drivers is necessary since nuclear projects are vulnerable to schedule delays and cost increases. This work also paves the way for possible cost reductions, decreasing the MARVEL levelized cost of energy and reducing the microreactors' construction time which in turn leads to a lower cost of interest during construction

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2022

Assessment of the Effect of Prototypic High-Burnup Operating Conditions of Fuel Fragmentation, Relocation, and Dispersal Susceptibility

The US nuclear energy industry is investigating strategies that further reduce the cost of energy production by using its existing fleet of nuclear generating stations. Most nuclear power plant operating costs are associated with purchasing fresh fuel assemblies or the efficiency of the reactor core design. Material costs are typically beyond the operator’s control; however, the core design optimizations offer potential operational savings. The core design envelope available to operators is constrained by two primary regulatory criteria: an enrichment limit of 5% 235 U and a burnup limit of 62 GWD/tU. These constraints have resulted in renewed efforts by the nuclear industry to pursue extending the peak rod-average burnup beyond 62 GWd/tU. This effort will likely require additional safety analyses beyond what is currently accepted by the US Nuclear Regulatory Commission. The purpose of this work is to demonstrate a best estimate plus uncertainty pin-by-pin high-burnup loss of coolant accident analysis technique to assess full-core high-burnup fuel fragmentation, relocation, and dispersal (FFRD) and identify approaches for minimizing or potentially mitigating FFRD through core design optimizations.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

Duke Energy Carbon-Free Resource Integration Study

Duke Energy has partnered with the National Renewable Energy Laboratory (NREL) to evaluate pathways to achieving their carbon-free targets and to assess the operational impacts of the resulting system. This report details findings from Phase II of the Duke Low Carbon Resource Integration study, which consisted of three separate but interrelated analyses: (1) a resource assessment exploring the technical and economic potential and characteristics of wind and solar resources in the Carolinas; (2) capacity expansion modeling identifying the least-cost investment pathways for achieving 70% CO 2 emissions reductions in North Carolina by 2030 and a net-zero electricity system by 2050; and (3) detailed production cost modeling of power system operations at the higher shares of low- and zero-carbon emitting generation sources, informed by the capacity expansion modeling portion of the analysis. The analysis finds that Duke Energy can approach the 2030 and 2050 emissions target in North Carolina through investment in a combination of solar, wind, and storage along with maintaining its existing nuclear fleet. The average cost of CO 2 abatement in the Carolinas through 2021-2050 is on the order of $\$27-33$ per metric ton (range of $\$9-34$ per metric ton across key sensitivities).Duke Energy can expected increased interchange with neighbors to help balance higher levels of solar, although the ability to do this will depend on whether neighboring regions also move to integrate more carbon-free resources. As Duke Energy moves toward both the 2030 and 2050 targets, addressing energy needs during the winter peak period becomes particularly important, and the system relies on the availability of resources such as renewable or hydrogen combustion turbines, seasonal storage, or other similar technologies that are dispatchable but able to operate at low capacity factors.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2023

Advanced Fuel Cycle Cost Basis Report: Supporting Documents 2 Production Based Costing

The purpose of this section is to outline a method of cost analysis whereby a significantly better representation of “should achieve” costs may be attained for NOAK systems. Based on economists’ notions of producer theory, and grounded in the cost analysts’ and project managers’ tool called the Work Breakdown Structure (WBS), this section describes best practices in cost estimation. It then illustrates how the Code of Accounts (COA) structure, developed by the Economic Modeling Working Group (EMWG) of the Generation IV International Forum in “Cost Estimating Guidelines for Generation IV Nuclear Energy Systems [EMWG 2007] (hereafter “Gen IV Guidelines Document”), can be used to differentiate “should achieve” versus “did experience” costs.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

The Rise in the Utilization of IoT Devices in Nuclear Facilities

The term Internet of Things (loT) encompasses everything connected to the internet, but it is increasingly being used to define objects that "talk" to each other. A broader term is that loT are the devices that connect to each other and to the internet. It has been mentioned that loT offers the potential for a "Forth industrial revolution" (1). This is primally because of the ease of use and quick link-up of devices within an area. This poses options for great interactivity but also create security concerns as many of these devices may not have been vetted for industrial use. By allowing for the intercommunication of these devices and combining with automated systems, we can now gather information, provide analysis and create automotive actions. This allows for faster response times as well as lowering the overall cost for operations in nuclear power facilities. (2)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Non-destructive structural characterization of graphite components using mechanical resonance and deep learning

As compared to conventional nuclear reactors, microreactors have the potential to significantly reduce construction timelines and capital costs, decreasing the barriers for advanced nuclear reactor technologies. However, the lower power output of these microreactors (typically < 20 MWe) creates challenging economics if operation and maintenance costs cannot be sufficiently reduced. The compact size of these designs presents an opportunity for comprehensive in-situ structural health monitoring to provide real-time feedback in order to reduce operational costs associated with maintenance and downtime. Many microreactor concepts use graphite for both in-core neutron moderation and as a structural material, which has typically required some form of periodic and laborious inspection. This report provides a description and assessment of recent work with graphite to couple acoustic-based experimental measurements and characterization with machine learning models to mature structural health monitoring capabilities and generate benefits for the nuclear microreactor industry. With resilient embedded sensors in development in other programs funded by the US Department of Energy’s Office of Nuclear Energy and elsewhere, the work described herein builds upon previously funded efforts to mature non-destructive testing technology that relates measured vibrational signatures to structural changes, using a combination of new experimental measurements and machine learning processing. Building on past successful demonstrations of predictive workflows to identify structural changes in a hexagonal stainless steel test article with excellent acoustic propagation, we first performed baseline characterization on graphite samples with canonical geometries to ensure compatibility and confidence in the applied techniques for a material with distinctly different mechanical properties. In contrast to efforts in previous years, we worked exclusively with unidirectional vibration data that is more comparable to those expected from the existing embedded sensor technologies which are suitable for deployment in a reactor setting. Established acoustic and modern machine-learning-based characterization approaches were applied to the resulting datasets from these simple geometries. Both approaches were found to be highly capable of detecting even small geometric irregularities amongst nominally identical samples. As such, we then moved to testing these approaches for detection of artificial local stress perturbations introduced into a more complex geometry: a hexagonal block with drilled holes. A main outcome of this work is that a generalizable ML workflow can be used to detect and predict the characteristics of small artificial anomalies in a graphite component with a relevant geometry. While this work was performed using surficial vibration data, we expect the approach to be flexible and viable for other monitoring scenarios, such as those with different arrangements or types of sensor arrays. As compared to previously funded efforts, an existing ML workflow based on neural networks was enhanced through the addition of recently developed Fourier neural operators. As applied to previously collected and new vibration datasets, prediction accuracies of anomaly characterizations were greatly improved with minimal added computational cost. As trained on small durations of vibration data (tens of seconds) collected over a realistic number of locations, the model was able to reliably determine the presence of a subtle stress anomaly and begin to provide location estimates. Such an approach is likely to be viable for more relevant reactor damage scenarios for graphite components, such as progressive crack growth or creep.

36 MATERIALS SCIENCE↗