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DOE OSTI2023

Status Report on Regulatory Criteria Applicable to the Use of Artificial Intelligence (AI) and Machine Learning (ML)

Although the interest in the use of artificial intelligence (AI) and machine learning (ML) in nuclear energy is increasing rapidly, at present their implementation is limited. This rapid increase in interest is not surprising considering that implementing AI and ML technology would allow for continuous monitoring, facilitate the implementation of predictive maintenance with optimized staffing plans, enable automation and autonomy opportunities that could drastically reduce fixed operation and maintenance costs, and provide training for operations and maintenance. Other industries are using AI for construction, and in the nuclear arena AI could provide great benefit in decommissioning activities. The ability of AI and ML to operate in real time vastly increases their potential impact. Before AI can be used in design, operations, or as a regulatory tool, the specifics on the regulations applicable to the use of AI for nuclear power applications need to be established. The difficulty is that the specific use cases will dictate the applicability of regulations. For example, even within the application domain associated with operations, the regulations might vary if the AI is used to create a virtual reference for plant operations or is used for training, optimization of maintenance intervals, prioritization of maintenance activities, etc. Different still is if the AI is to be used for design or setting technical specifications, which will introduce additional requirements. US Nuclear Regulatory Commission (NRC) licensing reviews are based on an applicant’s design meeting its performance assessment based on (1) safety goals and objectives, (2) deterministic and/or probabilistic analysis of accident scenarios, and (3) quantitative assessment of design alternatives against the safety goals and objectives using accepted engineering tools, methodologies, and performance criteria. The current regulatory framework does not explicitly address AI or autonomous control. However, as implementing AI technology will require the use of a digital platform, it must meet the requirements of an instrumentation and control (I&C) system. The regulatory requirements for AI, which will be incorporated into the I&C system, will be very dependent on how it is used (i.e., its functionality, safety classification, etc.). The licensing process is primarily risk-based with the identification of components and systems as nonsafety, important to safety, or safety related. A risk-informed approach allows further gradation of components and systems based on risk metrics such as core damage frequency or large early release fractions. Thus, the use cases and the risk categorization of impacted systems and components will determine the regulatory requirements. Regardless of how AI is used it presents new opportunities for risk-informing operating, maintenance, and regulatory decisions. Trustworthiness, transparency, and the ability to validate and verify the results will be paramount in showing that the systems and plant still meet their performance requirements. This report describes the results of research to identify regulatory implications of AI technologies and their uses. Specifically, this report reviews current regulatory guidance relevant to the application of AI for design (including design changes or new designs including advanced reactors), construction, operations, training, maintenance, research, testing, and as a regulatory tool. AI can be automated at different levels from purely informative purposes to autonomous controls. The focus of this review included determination of constraints on the application of AI technology, identification of any regulatory gaps or uncertainties, and clarification of anticipated technical basis information likely to be important for regulatory acceptance of these technologies. Currently, any use of AI at nuclear power plants is focused on nonsafety-related applications. The NRC and other regulatory bodies are evaluating providing guidance to address gaps rather than create new regulations to address the use of AI and ML. This approach seems to be the best to encourage AI development without adding regulatory uncertainty.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

Integrated Operations for Nuclear: Work Reduction Opportunity Demonstration Strategy

EXECUTIVE SUMMARY The Light Water Reactor Sustainability Program Plant Modernization Pathway has been working with industry for a number of years to leverage digital technology to extend the life and improve the performance of the existing fleet through modernized technologies and improved processes for plant operation and power generation. This includes development of modernization solutions to improve reliability and economic performance while addressing US nuclear industry’s aging and obsolescence challenges. The objective of these efforts is to deliver a sustainable business model that enables US nuclear industry to remain competitive. Digital Infrastructure (DI) research has established a technical foundation for these efforts. This effort began with technical analysis and support for a safety-related instrumentation and control (I&C) pilot upgrade being performed at Constellation Energy Generation’s Limerick Nuclear Plant. The following publicly available reports were produced as part of this effort. • INL/EXT-20-61079, Vendor-Independent Design Requirements for a Boiling Water Reactor Safety System Upgrade [1] • INL/EXT-20-59371, Business Case Analysis for Digital Safety-Related Instrumentation & Control System Modernizations [2] • INL/EXT-20-59809, “Safety-Related Instrumentation and Control Pilot Upgrade: Initial Scoping Phase Implementation Report and Lessons Learned [3] • INL/RPT-23-72105, Safety-Related Instrumentation and Control Upgrade: Conceptual – Detailed Design Phase Report and Lessons Learned [4]

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2020

Fossil Power Plant Cyber Security Life-Cycle Risk Reduction, A Practical Framework for Implementation

Market conditions are forcing fossil electricity generation facility owners and operators to implement advanced digital technologies. These technologies enable efficiencies, operational flexibility, operations and maintenance efficiencies, and adapting to a transitioning workforce. These digital technologies, however, can increase the cybersecurity attack surface. The purpose of this research was to develop a holistic cybersecurity risk reduction framework for fossil generation facilities. The framework begins with assessing how cyber risk changes across facility life cycles, including plant, system, vendor, and business life cycles. The next phase performs consequence analysis to prioritize high consequence events. Focusing on high consequence events allows owners to use a graded, risk-informed approach to prioritize cybersecurity efforts. The final phase identifies the digital asset attack surface in sensors and instrumentation and control equipment. After the vulnerabilities are identified, the owner selects mitigating cybersecurity control measures (or countermeasures) based on the risk analysis from the previous phases. This report describes the current industry cybersecurity best practices in fossil generation that are based on the first principles for cybersecurity engineering. The report is divided into five sections that describe the implementation of the risk reduction framework and present identified research, methodological, and technology gaps that were identified through this course of research and development.

01 COAL, LIGNITE, AND PEAT↗

DOE OSTI2020

Fossil Power Plant Cyber Security Life-Cycle Risk Reduction: A Practical Framework for Implementation

20 FOSSIL-FUELED POWER PLANTS↗

DOE OSTI2020

Fossil Power Plant Cyber Security Life-Cycle Risk Reduction: A Practical Framework for Implementation

20 FOSSIL-FUELED POWER PLANTS↗

DOE OSTI2026

Automation of Nanoparticle Synthesis Processes in a Plasma Environment Using LabVIEW

This work presents an automated control system for the synthesis of nanomaterials by plasma-enhanced chemical vapor deposition (PECVD), implemented using the LabVIEW software environment. The main objective of the study is to develop an integrated hardware-software platform that enables sequential control of the key stages of the PECVD process, including vacuum chamber preparation, pressure monitoring, working gas supply, plasma ignition, power matching, cyclic nanomaterial growth, and optical monitoring of nanoparticles in the plasma environment. The use of LabVIEW made it possible to integrate actuator control, experimental parameter acquisition, and realtime process visualization within a single automated system. The automated cycle begins with evacuation of the reaction chamber to a predefined base pressure. Transition to the next stage is permitted only after the specified pressure threshold has been reached, ensuring reproducible initial conditions for each experiment. The program then controls the supply of the working gas through mass flow controllers (MFCs). In this work, two gas-flow control modes were considered: analog control using a 0-5 V voltage signal and digital communication via RS-232 interface. It was shown that the analog approach requires accurate scaling of the control voltage, since applying 5 V corresponds to full-scale opening of the controller and results in the maximum gas flow. In contrast, the RS232 interface enables the gas flow rate to be specified directly in sccm, improving the accuracy, flexibility, and convenience of gas-environment control. After pressure stabilization, LabVIEW initiates RF plasma ignition and executes the RF matching algorithm aimed at minimizing reflected power and improving the stability of the plasma process. A separate software module implements the cyclic nanomaterial growth mode, in which the plasma-on time, plasma duration, and total number of synthesis cycles are predefined. This approach makes it possible to control material accumulation on the substrate and to correlate the process parameters with the morphological characteristics of the resulting nanostructures. The final module of the system is designed for optical monitoring of the nanoparticle cloud density in dusty plasma. For this purpose, the change in the intensity of laser radiation passing through the plasma region is recorded using a photodetector and a Keithley 2401 measuring unit connected to LabVIEW via RS-232 interface. The difference between the initial and modified optical signal intensity is used as a diagnostic parameter characterizing the formation and temporal evolution of nanoparticles. The developed system demonstrates that LabVIEW can be effectively applied not only for the automation of individual instruments, but also for the implementation of a complete digital control cycle for PECVD-based nanomaterial synthesis.

PECVD↗

DOE OSTI2023

Creating a Simulation Platform for Research and Development of Advanced Control Methods

Advanced nuclear reactors are essential to meet the changing energy requirements throughout both the United States and the rest of world. In addition to other features, they are designed to enable deployment in remote locations and operate in a fully (or near-fully) autonomous manner, which will require a new control paradigm. To realize autonomously operating reactors, the U.S. Department of Energy’s Nuclear Energy Enabling Technologies Advanced Sensors and Instrumentation (NEET ASI) program conducts research and development into the enabling technologies and methods needed, including digital twins, machine learning, and risk modeling, in addition to various types of control methods. These technologies and methods are the key foundations needed to achieve fully autonomous systems. To develop and evaluate the technologies and methods necessary for achieving autonomous operations, it is critical to identify a software tool capable of integrating all the required elements. In surveying the available solutions, no software platforms were identified that could accomplish what was needed without introducing drawbacks. This challenge was the motivation for the current effort: to develop a software platform that can seamlessly integrate autonomouscontrol-enabling technologies and methods, allowing for accelerated research and development and transfer of ideas. The resulting platform, known as the Control and Optimization Modular Modeling Application for Nuclear Deployment (COMMAND), is Python-based, and leverages open-source tools to provide flexibility and facilitate building upon prior research. It is designed to enable advanced reactor developers to deploy and test advanced control technologies and methods coupled with their own models, solutions, and hardware. Given the substantial undertaking of developing such a platform, the current effort focused on laying down scalable, flexible software foundations and infrastructure, then demonstrating the platform via a use case. These foundations included developing generic modules, which contain the base variable and system blocks (the information and functional building blocks, respectively, that can be used to design a simulation) and the data handling and storage blocks needed to exchange information between the various blocks; as well as enablingtechnology-specific modules. This platform was evaluated via a use case, which was to simulate and control a process for the Microreactor Automated Control System (MACS) test bed. While MACS is not currently directly coupled to any specific microreactor physics, it was initially developed in concert with the Microreactor Applications Research Validation and Evaluation (MARVEL) microreactor, and so the MARVEL physics are used here. As part of this use case, several enabling-technology-specific blocks within COMMAND were integrated, including a proportional integral derivative (PID) control block, a Reactor Excursion and Leak Analysis Program (RELAP5-3D) block, and an anomaly detection block. The COMMAND software platform was successfully demonstrated to achieve the scalability and flexibility objectives of this effort and will be leveraged by the program’s research efforts to advance state of the art control methodologies towards autonomous operations of advanced reactors. As new use cases are created and implemented, it is anticipated that COMMAND will continue to grow and evolve to meet new requirements.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2026

MARVEL Instrumentation, Control, and Software Considerations

This paper details the various I&C considerations and design decisions made throughout the MARVEL (Micro-reactor Applications Research Validation and Evaluation) project, including sensor and actuator selection, safety-related functionality, digital control hardware and software, and testing methodologies. Key challenges such as managing radiation, temperature, and space constraints are discussed, along with the trade-offs between using standard equipment and custom solutions. The successful integration of off-the-shelf components, the emphasis on minimizing safety-related instrumentation, and the lessons learned from prototyping and testing are highlighted. The authors aim to provide insights that can benefit future micro-reactor designs and emphasize the importance of real-world testing in advancing reactor technology.

46 - INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AN↗

DOE OSTI2023

Application of NEAMS Multiphysics Framework for Species Tracking in Molten Salt Reactors

This report from Idaho National Laboratory (INL) summarizes the key modeling and simulation activities conducted under the Department of Energy (DOE) Molten Salt Reactor (MSR) Campaign during the Fiscal Year 2023 (FY23). The focus of the work was to leverage state-of-the-art modeling capabilities from the DOE Nuclear Energy Advanced Modeling and Simulation (NEAMS) codes to enable novel multiphysics and multiscale modeling and simulation of MSRs. Through collaboration with NEAMS code developers, advanced multiphysics analysis capabilities for MSR systems were demonstrated by coupling depletion, thermal-hydraulics, and thermochemistry into an innovative framework for chemical species transport in MSRs. As a result, the framework can track nuclides throughout their lifetimes in the core, from production (depletion) to advection throughout the salt volume (thermal-hydraulics) and off-gassing or precipitation outside of the salt (thermochemistry). This work supports the near-term deployment of MSRs by integrating the synergistic efforts between the DOE’s MSR Campaign and NEAMS program. The resulting framework will help better connect system design modelers with experimentalists to better understand and predict complex physical behaviors in MSRs. Researchers and MSR developers alike can now leverage these new modeling and simulation capabilities to perform novel analyses with applications including: • MSR dynamics during normal operational transients and accident scenarios • Off-gas system design and performance for fuel cycle and depletion analysis • Corrosion and active chemistry control for reactor component health and lifetime determination • Source term, decay heat and activity determination in accident scenarios • Special nuclear material accountancy and chemical forensic analysis for safeguards • Digital twin development of experiments and experimental reactor demonstrations • Measurement requirements for instrumentation and control design • Uncertainty and sensitivity analysis of missing data to inform future experimental data collection.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2022

Draft Methodology for Cybersecurity Analysis for Adoption of Wireless Technology in Nuclear Power Plants

The report is delivered as DOE-NE Cybersecurity Program Milestone M2CT-22IN1104014-Industry cybersecurity guidance adoption status. The milestone is specifically to document the process and the status of the efforts towards developing guidance in support of industry’s adoption of wireless communication technologies. To transform the operation of nuclear power plants, including domestic light-water reactors, advanced reactors, microreactors, and fission battery, for grid and non-grid applications, secure and resilient wireless capabilities are required. In addition, to realize new operational concepts such as autonomous operation and remote monitoring, advanced sensor, and instrumentation, wireless technology is essential. However, industry implementation is low, and there is no technical basis for how to understand and address potential risks for wireless communications for critical plant functions. A methodology with a technical basis for implementing secure wireless communication is crucial. This wireless adoption methodology is intended to assist a licensee in identifying an appropriate technological approach for securing wireless communications in nuclear power plant. However, this methodology does not provide guidance for addressing wireless design criteria or for addressing all the cybersecurity commitments in licensees’ cybersecurity plans (CSPs) including addressing security impact analysis that a licensee must perform before an update to a Critical Digital Asset (CDA). This methodology guides a licensee through a process of evaluating a proposed wireless implementation and drafting a plant change notification for an example use case. The example is a generic/nonproprietary version of the first test case of the methodology, which, if successfully implemented, is part of the consideration for protecting other functions’ use of wireless in a cybersecure manner.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2022

Initial Scoping Efforts for a Plant-Wide Digital Infrastructure Modernization Business Case Study

This research report describes the preparatory efforts to perform a BCA on an expanded set of digital upgrades envisioned for implementation at the Luminant?s Comanche Peak nuclear plant. It captures efforts to scope the digital upgrade effort to enable performance of the BCA. The final BCA will be the subject of a subsequent report. LWRS pilot research in this area is intended to enable this effort and to provide a roadmap to others to follow. INL appreciates the Luminant?s participation in this research.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2023

Pilot Business Case Analysis for Digital Infrastructure

The Inflation Reduction Act Has Provided an Opening to Dramatically Change and Improve the Economics of Nuclear Power Until recently, the commercial nuclear sector has faced unprecedented financial challenges driven by low natural gas prices and subsidized renewables, in a marketplace that did not reward carbon-free baseload capacity. The industry is also plagued by labor shortages, increasingly obsolete labor-centric operating models and antiquated analog technology that threaten the viability of the long-term operations of domestic nuclear facilities. In this context, the economic survival of nuclear power plants requires an efficient and technology-centric operating model that harvests the native efficiencies of advanced technology. Such transformations have been made in many other industries – notably, oil and gas. The passage by Congress of the Inflation Reduction Act (IRA) in 2022 provides nuclear operators with unprecedented economic incentives to pursue these upgrades. To realize the benefits of these incentives and achieve the necessary transformations in the nuclear operating model, the nuclear industry must overcome both the continuing unease about licensing pathways and uncertainty related to implementation costs.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2024

Cyber Risk Considerations for Nuclear Digital I&C Systems

Many engineers and scientists researching modeling and analysis methods for nuclear energy advancement are focused on proof-of-concept and early-stage development for new reactor designs. Since instrumentation and control (I&C) systems are traditionally developed later in the systems engineering lifecycle, researchers may be unfamiliar with modern digital technology used in these I&C systems. It is even more likely that they are unfamiliar with the cyber risks associated with them. This paper provides a brief overview of nuclear digital I&C systems before examining the importance of cyber risk management at nuclear reactors and the benefits of including Cyber-Informed Engineering throughout the systems engineering lifecycle. The primary goal is for engineers and scientists to develop a mindset that incorporates cybersecurity as another discipline alongside safety when designing and developing new technologies, regardless of technology readiness level.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2022

Integration of Control Methods and Digital Twins for Advanced Nuclear Reactors

Advanced nuclear reactors offer a new set of features to energy generation, due to their ability to adapt to variable energy demand, operate autonomously, be deployed in rural locations and monitored remotely, afford compact size and lower power ratings, and rely on novel technologies to achieve safer operations. Thus, a requirement for the success of these reactors is the use of intelligent forms of control to track changing power demands, make autonomous decisions, and reduce the need for human involvement. Regulatory requirements pertaining to control of nuclear reactors could be met via historical means of control; however, these are not expected to enable the level of highly autonomous operations desired in advanced nuclear reactors. Historical control methods rely on both logical and high-performance (HP) control. These two types of control are usually used separately, with a human element being introduced whenever decisions are cascaded from one science to another. AI/ML control, on the other hand, can replace the human element in the current U.S. fleet of nuclear power plants (NPPs) by acting as a supervisory optimizer that understands the plant internal/external variables in order to make control decisions, and can easily handle non-linear and multi-input/multi out (MIMO) decisions—another requirement for advanced nuclear reactors that could be difficult to handle via logical and HP control. Because of the harsh operating environments produced in advanced reactors, resulting in the frequent failure of sensors and other types of equipment, and considering the lack of operating history for advanced nuclear reactors, control of advanced nuclear reactors would necessitate relying on a model that can track and adapt to the actual process (i.e., a digital twin). This digital twin can make approximations when knowledge and data are unavailable and would evolve as more knowledge is gained. The reactor control must also be risk-informed to account for the high-consequence nature of advanced reactors. This report introduces a high-level (i.e., not method- or process-specific) integration of the three different control and digital twinning methods able to meet the requirements for advanced nuclear reactors. These methods could be applied during both the operational and design stages of these reactors. The aim is to demonstrate how each method interfaces with and highlights enabling solutions necessitated by the unique features of advanced nuclear reactors.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2023

Safety-Related Instrumentation and Control Pilot Upgrade: Conceptual - Detailed Design Phase Report and Lessons Learned

Historically, regulatory barriers have precluded nuclear plant safety-related (SR) Instrumentation and Control (I&C) system modernizations. These barriers have been largely addressed by industry and United States Nuclear Regulatory Commission (NRC) efforts, including development of the License Amendment Request (LAR) Alternate Review (AR) process for digital I&C upgrades. The U.S. Department of Energy (DOE) and the Idaho National Laboratory (INL) are supporting a SR I&C pilot upgrade at the Limerick Generating Station (LGS) to demonstrate this process and capturing associated lessons learned for the benefit of industry. In 2021, a paper summarizing lessons learned as captured in INL/EXT-20-59809, Safety Related Instrumentation & Control Pilot Upgrade Initial Scoping Phase Implementation Report and Lessons Learned was presented at the 12th NPIC & HMIT conference. It is recommended that readers of this paper review reference 1 or the associated Nuclear Journal paper for context. This paper summarizes activities performed and lessons learned for the conceptual design phase and portions of the detailed design phase as captured in INL/RPT-23-XXXX, “Safety-Related Instrumentation and Control Pilot Upgrade: Conceptual - Detailed Design Phase Report and Lessons Learned.” The portions of the effort covered by reference 2 include conceptual design phase activities from December 2020, through completion in November 2021, and detailed design activities through September 2022. These efforts and associated detailed documentation in reference 3 are intended to support similar industry upgrades as a foundation stone for a Digital Transformation that will improve plant safety, reliability, and operational performance while lowering plant total cost of ownership.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2022

3D Frequency Domain Reflectometry Digital Twin of an Electrical Cable: A First Glance

Electrical cables within nuclear power plants (NPPs) are critical components required for power, control, and instrumentation systems which may be exposed to stressors, such as elevated temperatures and gamma radiation. Such stressors can lead to a reduction in the remaining useful life of electrical cables, jeopardizing the safety of NPP systems. To evaluate the effect of stressors on the degradation of electrical cables, electrical reflectometry methods are commonly employed. Frequency domain reflectometry (FDR) is a non-destructive electrical reflectometry method that uses transmission line theory to detect degradation or impedance changes within electrical cables. However, in most cases FDR is only applied to de-energized cables, limiting the application in NPPs as the cable system must be taken offline. In this work, we explore the development of an FDR digital twin to predict the degradation of an electrical cable exposed to elevated temperature, which is expected to reduce the need for offline FDR. A 3-conductor low-voltage electrical cable was selected for evaluation of the digital twin. The fully three-dimensional digital twin was developed in COMSOL using the RF module. A cable length of 30-m and frequency bandwidth of 400 MHz was selected to mimic real-world application of FDR. Over a 1-m region, the permittivity of the insulation was varied by up to 20% to model thermal degradation. The results demonstrate accurate detection of the insulation damage region, supporting further investigation of the FDR digital twin using real-world data and machine learning for predictive damage estimation or remaining lifetime.

Spencer, Mychal P.↗

DOE OSTI2023

Integrating Control Methods and Digital Twins for Advanced Nuclear Reactors

Advanced nuclear reactors offer new capabilities such as the ability to adapt to variable energy demand, operate autonomously with remote supervision, be deployable in rural locations, be compact in size, afford lower power ratings, and rely on novel techniques for increased operational safety. However, realizing these capabilities requires intelligent control systems that can track changing power demands and make autonomous decisions based on these demands. The unique aspects of advanced reactors (e.g., strict regulatory requirements, harsh operating environments, high consequences, highly coupled dynamics, evolving knowledge, and limited operating histories) directly impact the design and deployment of control systems for these reactors. The present work identifies and evaluates these aspects so as to develop a set of control system requirements to guide future research and development. To meet these requirements, a layered control system approach is proposed that integrates digital twins with different control paradigms. This work aims to demonstrate how different methods interface with enabling solutions, and to identify any gaps that need to be researched.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2025

Control-Agnostic Beam Instrumentation with Redis at the Core

Redis isn’t a database — it’s our protocol. Fermilab’s RedisAdapter provides a high-performance, control-system-agnostic bridge between digitized beam data and downstream consumers such as ACNET and EPICS. It forms the foundation of three new software components deployed across MicroTCA-based digitizers: GMMDM, a runtime for memory-mapped data movement from Zynq-based platforms; GRAFE, a front end for Redis-to-ACNET presentation; and GREFE, an EPICS IOC front end. Together, these tools enable modular, standardized instrumentation pipelines. Precision timing is handled via White Rabbit PPS distribution, allowing nanosecond-scale synchronization across crates. This architecture, originally prototyped in Booster BPM systems, is now deployed on modern hardware and designed to meet the performance, modularity, and scalability requirements of the PIP-II era.

Steinkamp, Derek [Fermilab] (ORCID:000900027228626↗