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DOE OSTI2025

Insights from Surrogate Industries on Remote Operations for Advanced Reactors

With development of advanced reactors, understanding the human factors considerations related to remote operations remains an important topic. This work presents insights captured from reviewing relevant surrogate industries with remote operations, as they may apply to advanced reactor development. This work provides insights into important human factors considerations for remote operations to ensure safe and reliable adoption of these prospective reactor technologies.

99 - GENERAL AND MISCELLANEOUS↗
DOE OSTI2021

Machine Learning Assisted Safety Modeling and Analysis of Advanced Reactors

With the advances in computational power and numerical methods, analysts can now rely on first-principle simulations to predict ultra-fine details in a variety of applications. Advances in machine learning (ML) have produced algorithms that can now learn high-level abstractions via hierarchical models. This project aims to leverage advances in ML techniques and the available high-resolution simulation data to develop a novel modeling and simulation (M\&S) methodology for reactor safety analysis. While application-agnostic ML techniques are available, complex physics constraints need to be incorporated into ML techniques to build ML-based closures for computationally efficient predictive simulations. This project intends to develop a physics-guided data-driven multi-scale methodology for M\&S of advanced reactors. The project focuses on thermal fluid (T/F) phenomena, which play major roles in advanced reactor safety. Specifically, we propose a data-driven coarse-mesh turbulence model based on local flow features for the transient analysis of thermal mixing and stratification in a sodium-cooled fast reactor (SFR). The model has a coarse-mesh setup to ensure computational efficiency, while it is trained by fine-mesh computational fluid dynamics (CFD) data with Reynolds-averaged Navier-Stokes (RANS) turbulence model to ensure accuracy. Three different neural networks are developed and tested for loss-of-flow transients in the hot pool of SFR, i.e. the densely connected convolutional neural network (DCNN), long-short-term-memory network based on proper orthogonal decomposition (POD-LSTM), and the DCNN informed by LSTM (DCNN-LSTM). The performances of these three neural networks are evaluated based on baseline models. The DCNN-LSTM model has been chosen for further hyperparameter optimization. Furthermore, based on a simplified two-dimensional case, uncertainty quantification (UQ) of the developed ML-based closure are investigated with three methods, i.e. Monte Carlo dropout, deep ensemble, and Bayesian neural network. The developed ML-based turbulent viscosity closure relation based on deep ensemble is then integrated into the system analysis module SAM and serves as a term in the conservation equations. Such a SAM-ML based procedure guarantees that the obtained results are consistent with the physical constraints of the thermal-fluid system. The SAM-ML simulation on the same loss-of-flow transient showed comparable accuracy with the CFD simulation but with a much coarser mesh setup. Last but not least, the ML-based closure improvement with the support of higher-fidelity data from large eddy simulation (LES) is discussed. As a first step towards this direction, a baseline LES simulation is performed to obtain comparable data with RANS results. Based on the early results, future investigation on further improving the ML-based closure is discussed. We believe the developed approach that combines scientific machine learning with nuclear system analysis code can benefit the advanced reactor community as more accurate safety analyses will better characterize reactor safety margins and reduce licensing efforts.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Advanced Reactors Spent Fuel & Waste Science and Technology Program

Based on the higher interest in Advanced Reactor (AR) deployment (e.g., ARDP ) for potential new fuel cycles, the Spent Fuel & Waste Science and Technology (SFWST) Program has begun to evaluate the possible implications of long-term management and final disposition of potential Advance Reactor spent nuclear fuels (SNF) that would be generated in potential advanced reactors. Safely managing and dispositioning the potential future AR SNF, and any other associated radioactive wastes, is the primary focus of this initial preliminary assessment of those. This paper summarizes three primary tasks the Spent Fuel & Waste Science and Technology (SFWST) Program is executing (or collaborating on) related to the back end of the nuclear fuel cycle (BENFC) for potential future advanced reactors: 1. Advanced Reactors Spent Fuel and Waste Streams: Strategies for the BENFC This set of activities define a high-level strategy for how to systematically approach, identify, and close research and development (R&D) gaps/potential issues associated with long-term management and final disposition of AR SNF and other possible AR waste streams. This task involves summarizing advanced reactor concepts, their likely SNF and other waste forms, and identifying previous experience with similar materials, for example from DOE-managed SNF, with closely related characteristics to the potential future AR SNF. Technical R&D gaps between the breadth of detailed understanding for safe storage, transportation and disposal of the existing light water reactor SNF fuel cycle (e.g., see NASEM, 2022) and potential future fuel cycles based on advanced reactors would then be identified. 2. Characterization and Packaging Options of Advanced Reactor SNF These activities evaluate characteristics and packaging options for advanced reactor spent fuel forms. The fuel forms are categorized into three types: (1) tri-structural isotropic (TRISO), (2) metallic, and (3) fuel salt. Emphasis is given to TRISO and metallic SNF and additional waste streams from such AR as driven by the near-term anticipated operation of the Xe-100 and the Natrium reactors as advanced-reactor demonstrations1. Preliminary information for the spent-fuel salt discharged from molten-salt reactors (MSRs) is examined to provide a baseline for future efforts. All calculations and assumptions in this work are based on publicly available information. The following characteristics are calculated or estimated for use in the preliminary assessments: SNF volume and mass, radiation/activity levels through time, thermal conditions through time, potential radionuclide source terms, chemical interactions and evolutions, disposal inventories, and waste-form lifetime. Using those characteristics, calculations to determine the applicability of existing canister designs were performed. These evaluations included geometric (e.g., dimension, volume) and mass/weight considerations, known operational approaches and loading procedures, physical and chemical considerations/conditions for storage environments, as-loaded radiation, thermal, and criticality analyses to identify constraints for storage, transportation, and disposal. 3. Back-End Management of Advanced Reactors (BEMAR) The DOE NE-8 organization has defined an Integrated Project Team to evaluate the Back End Management of Advanced Reactors (BEMAR) (includes DOE staff from a range of organizations (e.g., NE-81, NE-82, OCED) and national laboratory technical staff within the DOE NE-81 and NE-82 programs). This BEMAR group works directly with advance reactors developers to assess for the DOE the technical feasibility of storage, transportation, and disposal of AR SNF based on the characteristics provided by the developers to DOE (much of which is proprietary). The BEMAR is also tasked to develop rough-order-of-magnitude cost estimates to compare the waste management system for individual advanced reactors to existing light-water reactor management practices. To accomplish this, the BEMAR group is implementing a Systems Engineering approach.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Cyber Threat Assessment Methodology for Autonomous and Remote Operations for Advanced Reactors (Conference Presentation)

The next generation of Advanced Reactors include planned capabilities for both Autonomous (operating without human interaction for a set period-of-time) and Remote (operating with human interaction from a separate physical location) Operations. Existing Nuclear Reactor architectures include a set of safety and security constraints tightly coupled with personnel policies and procedures. As Advanced Reactors are fielded with these new Autonomous and Remote operational capabilities, the architectures and associated infrastructure services and components will perceivably expand the overall attack surface and risk calculations with regards to safe and secure operations. This paper is part of an FY21 work program focused on ensuring Advanced Reactor designs are informed with threat-based guidance on design and operation of Secure Architectures with a specific focus on the deployment of Autonomous Systems in support of Advanced Reactor Operations. The next phase of this research program is to complement produce a methodology for assessment of the cyber threat against these architectures as well as a catalogue of Use Cases to support the Advanced Reactor community in their implementation of Autonomous and Remote Operations.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Advanced Reactor Safeguards: 2022 Program Roadmap

The Advanced Reactor Safeguards (ARS) program was established in 2020 as part of appropriations for the Advanced Reactor Demonstration Program (ARDP) through the Office of Nuclear Energy in the Department of Energy. The goal of this program is to help address near term challenges that advanced nuclear reactor vendors face in meeting domestic Material Control and Accountancy (MC&A) and Physical Protection System (PPS) requirements for U.S. construction. The technical work in the program is meant to (1) support nuclear reactor vendors with advanced MC&A and PPS designs for next generation reactors, (2) provide technical bases for the regulator, and (3) promote the integration of Safeguards and Security by Design early in the design process. Existing domestic regulations for safeguards and security, as outlined in the Code of Federal Regulations, were written for large light water reactors, and rule-making efforts are underway to develop regulations more suited to different reactor designs. The ARS program seeks to remove roadblocks in the deployment of new and advanced reactors by solving regulatory challenges, reducing safeguards and security costs, and utilizing the latest technologies and approaches for robust plant monitoring and protection. This roadmap discusses the goals of the ARS program, current research, and program plan for the next five years.

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

Intrinsic value of the international benchmark projects, ICSBEP and IRPhEP, for advanced reactor development

The International Criticality Safety Benchmark Evaluation Project, a sanctioned program under the auspices of the Nuclear Energy Agency of the Organisation for Economic Co-operation and Development, has been a highly successful and productive collaboration, now encompassing over 5,000 evaluated experimental benchmarks trusted and relied upon throughout the international nuclear communities. The success of this project led to the development of the International Reactor Physics Experiment Evaluation Project, which is dedicated to the evaluation of benchmark experiment data to sustain current and future reactor physics validation needs. These exemplary programs, and their widely utilized handbooks, serve as gold standards to which other databases strive to emulate. The purpose of the two projects is to preserve modern and legacy experimental data and evaluate it in a standardized handbook format to provide quality benchmarks to support modern and future criticality safety and reactor physics validation. These two projects have often served as the mechanism through which historic and modern neutronics experiments are evaluated and shared across international borders, to best provide unique, high-quality peer-reviewed, and often otherwise unavailable, benchmark data. The contents of these handbooks are utilized not only in validating criticality safety, reactor physics, and advanced reactor calculations, but are used to validate neutronics calculations and nuclear data for most other nuclear applications. This paper discusses both international programs and available content to enable advanced reactor design validation.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Preliminary Analysis of Advanced Reactors Storage, Transportation, and Disposal

Based on the higher interest in Advanced Reactor (AR) deployment (e.g., ARDP[1]) for potential new fuel cycles, the Spent Fuel & Waste Science and Technology (SFWST) Program has begun to evaluate the possible implications of long-term management and final disposition of potential Advance Reactor spent nuclear fuels (SNF) that would be generated in potential advanced reactors. Safely managing and dispositioning the potential future AR SNF, and any other associated radioactive wastes, is the primary focus of this initial preliminary assessment of those. This paper summarizes the efforts by the Spent Fuel & Waste Science and Technology (SFWST) in evaluating characteristics and packaging options for advanced reactor spent nuclear fuel forms. The fuel forms were categorized into three types: (1) tristructural isotropic (TRISO), (2) metallic, and (3) fuel salt. This work emphasized TRISO and metallic SNF and waste streams because of the near-term anticipated operation of the Xe-100 and the Natrium reactors as advanced-reactor demonstrations. Preliminary information for the spent-fuel salts discharged from molten-salt reactors (MSRs) is also examined to provide a baseline for future efforts. All calculations and assumptions used publicly available information. The following characteristics are calculated or estimated for use in the preliminary assessments: SNF volume and mass, radiation/activity levels through time, thermal conditions through time, potential radionuclide source terms, chemical interactions and evolutions, disposal inventories, and waste-form lifetime. Using those characteristics, calculations to determine the applicability of existing canister designs were performed. These evaluations included geometric (e.g., dimension, volume) and mass/weight considerations, known operational approaches and loading procedures, physical and chemical considerations/conditions for storage environments, as-loaded radiation, thermal, and criticality analyses to identify constraints for storage, transportation, and disposal. The paper also includes a literature review and analysis on the storage, transportation, and disposal evaluations and experiences from reactors with similar fuel forms. Advanced-reactor vendors cite past experiences with Fort St. Vrain for TRISO and the Experimental Breeder Reactor II (EBR-II) for metallics that have major influences on fuel design. Finally, the paper includes preliminary concepts of operation for advanced-reactor SNF. This encompasses storage, transportation, potential treatment, and disposal activities from both a per-canister and systems-integration perspective.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Concept of Operations for Advanced Reactor Spent Nuclear Fuel Management

This presentation presents a preliminary description of a concept of operations to incorporate advanced-reactor spent nuclear fuel (SNF) into an integrated waste-management system (IWMS). The evaluation includes SNF from four advanced-reactor concepts with the following fuel types: (1) small modular reactors using oxide fuels, (2) tristructural-isotropic (TRISO) fuels, (3) metallic fuels, and (4) fuel salts. To provide context for the proposed concept of operations for advanced reactors, a comparison is made with traditional light-water reactors (LWRs) to identify potential gaps in the IWMS. The technical differences between advanced reactors and LWRs are assessed to determine the feasibility of managing advanced-reactor waste streams using existing operations and technology. This presentation emphasizes fuel types from Advanced Reactor Demonstration Program reactors: Xe 100, which uses TRISO fuel and Natrium, with its metallic fuels while also analyzing management options for molten-salt reactors and advanced light-water reactors (ALWRs). Understanding the storage, transportation, and disposal requirements of SNF is dependent on both the quantity and characteristics of the SNF generated by nuclear reactors. This presentation provides a high level overview, comparing the anticipated concept of operations for different SNFs from advanced reactors. The IWMS includes at-reactor storage, transportation, potential off-site storage, potential treatment, and disposition. To assess the potential effect of advanced-reactor concept of operations on the IWMS, estimates were made for fuel characteristics that contribute to storage, transportation, disposal, and possible treatment of advanced-reactor SNF. These include canister heat load, dose rates, and criticality-control limits, which are important for determining the condition and configuration of the advanced reactor SNF. At-reactor storage of LWR SNF traditionally involves a spent-fuel pool (SFP) before transfer to an independent spent-fuel storage installation. However, some advanced-reactor concepts, particularly those using TRISO and salt fuels, do not anticipate the use of an SFP. This difference in at-reactor storage could impact the IWMS. Additionally, transportation of advanced-reactor SNF may include additional processes tied to potential off gassing, and transportation of microreactor SNF may occur within the reactor vessel. Some advanced-reactor SNF could also undergo treatment to meet requirements of an acceptable waste form for disposition, and the treatment location will be a major contributor to efficiently performing IWMS responsibilities. Moreover, the quantity of SNF generated is an important consideration for IWMS because it could affect the size of the transportation fleet and potential off-site storage requirements. Additionally, volume and heat load are the primary drivers for SNF disposition. This presentation compares potential packaging options for advanced reactor SNF with traditional LWR packaging to provide a high-level comparison for the needs of the IWMS for advanced-reactor SNF.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

Advanced Reactor Safeguards and Security - Advanced Delay Technologies

As a new generation of reactors is developed, reducing the cost of physical security without impacting the required system effectiveness will help to make new reactors economical. This report discusses several access delay technologies available to help improve the overall effectiveness of the physical security system. These technologies include both passive and active delay elements, as well as guidance on best practices related to security by design principles.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

A comparative study on deep learning models for condition monitoring of advanced reactor piping systems

Advanced nuclear reactors offer innovative applications due to their portability, reliability, resiliency, and high capacity factors. To operate them on a wider scale, reducing maintenance life-cycle costs while ensuring their integrity is essential. Autonomous operations in advanced nuclear reactors using augmented Digital Twin (DT) technology can serve as a cost-effective solution by increasing awareness about the system’s health. A key component of nuclear DT frameworks is the condition monitoring of safety systems, such as piping-equipment systems, which involves acquiring and monitoring the plant’s sensor data. Here, this research proposes a condition monitoring methodology utilizing deep learning algorithms, such as multilayer perceptions (MLP) and convolutional neural networks (CNNs), to detect degradation and its severity in nuclear piping-equipment systems. Sensor signals are processed to obtain the power spectral density and the Short-Time Fourier transform, and feature extraction methodologies are proposed to develop degradation-sensitive data repositories. The performance of MLP, one-dimensional (1D) CNN, and 2D CNN within the proposed condition monitoring framework is compared using a finite element model of a 3D piping system subjected to seismic loads as the application case study. Various approaches, such as dropout, k-Fold validation, regularization, and early stopping of training the network, are investigated to avoid overfitting the models to the input sensor data. The predictive capability and computational capacity of the deep learning algorithms are also compared to detect degradation in the Z-pipe system of the Experimental Breeder Reactor II (EBRII). The Z-pipe system is subjected to harmonic excitations that represent normal operating loads, such as pump-induced vibrations. The findings of the study indicate that the proposed artificial intelligence (AI)-driven condition monitoring framework demonstrates superior prediction accuracies with a 2D CNN, whereas the MLP exhibits higher computational efficiency.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

Artificial Intelligence/Machine Learning Technologies for Advanced Reactors (Workshop Summary Report)

A workshop on artificial intelligence and machine learning (AI/ML) for advanced reactors (AR) was held October 5-6, 2021. The workshop was to be attended in-person at ANL but COVID restrictions forced the workshop to go virtual. The objectives of the workshop were to identify the most promising AI/ML opportunities for improving advanced reactor design, optimizing plant performance, and enhancing economic competitiveness and to develop an understanding of the scientific, engineering and licensing challenges facing their application. The workshop planning committee included GAIN, EPRI and NEI and members of three national laboratories (ANL, INL, and ORNL). The workshop was attended by more than 200 individuals representing academic and scientific institutions and the nuclear power industry. The definition put forth for an AI/ML system was one that perceives its environment and takes actions that maximize its chance of achieving its goals. In this report AI/ML refers to next generation algorithms that include deep learning, statistical analysis and data analytics and associated scientific computing and their potential application to the design, licensing, operation and maintenance of ARs. These methods typically incorporate models built from process data and may also include data generated by simulations that represent the behavior of a system. The workshop was organized in response to the growing interest in application of AI/ML for improving the economic competitiveness of nuclear energy. Increasingly more resources are being allocated to investigating the benefits of AI/ML methods. The DOE created the Artificial Intelligence & Technology Office to promote their development. And within the Office of Nuclear Energy, resources have been allocated to explore and understand the potential benefits of AI/ML. Additionally, the national laboratories are strategically positioned with DOE computing facilities such as Summit, Perlmutter, Aurora and Frontier that support large-scale simulations, hybrid HPC models with AI surrogates, and the exploration of new types of generative models emerging from multi-model data streams and sources. The workshop was organized with members of the AR community to understand the effort and to identify the level of interest and progress in this emerging technology. The workshop discussions focused on identifying opportunities for AI/ML across diverse areas of the nuclear industry and identifying current scientific and engineering challenges for advanced reactors that might be addressed through transformational uses of AI/ML. Discussion panels focused on four high-interest technical domains for advanced reactors: design, maintenance and operations, energy storage, and materials. The results of those discussions are summarized in this report. This includes opportunities that were identified for exploiting AI techniques and methods to improve the efficacy and efficiency of reactor analysis and to improve the operation and optimization of advanced reactors. Advanced reactor developers expressed an interest in learning more about AI/ML methods and their application. This included understanding whether ML methods can provide an advantage over existing nonlinear data regression methods for collapsing high-fidelity simulation results into faster running models. A consensus emerged that AR advances planned for the next decade will benefit from the use of AI/ML tools. The need exists to understand and model complex systems across length scales and modalities. AI/ML is a tool for discovery that can yield a set of engineering principles for use by nuclear engineers, licensing bodies, and operators to solve problems in plant design, safety analyses, autonomous operation, and predictive maintenance. While AI/ML represents a new set of tools, an awareness by the nuclear community of the full potential is still in the early stages so there is a need to increase awareness. It appears that the wide-spread adoption of AI/ML tools for ARs would be facilitated by future educational workshops that describe foundational methods and capabilities and describe successful applications.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2021

Gap Assessment on Sensors and Instrumentation for Advanced Reactors

The Sensor Technologies for Advanced Reactors Virtual Workshop—sponsored by the Gateway for Accelerated Innovation in Nuclear (GAIN), the Electric Power Research Institute, and the Nuclear Energy Institute—was held to exchange information on sensors and sensor technologies of interest to advanced nuclear technology developers, commercial instrument suppliers, and sensor researchers from Department of Energy (DOE) national laboratories, universities, and industry. The workshop objectives were to discuss measurement requirements and sensor needs for advanced reactor concepts, understand current national laboratory capabilities and accelerated development approaches for sensors and instrumentation, and identify gaps so as to inform applicable DOE Office of Nuclear Energy (DOE-NE) research programs. Due to the complexity of holding group discussions on individual gaps, a survey was sent to workshop participants, and personalized one-on-one feedback sessions were held to elicit additional information. Summaries of these sessions are provided in this gap assessment report.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

Verification of numerical models for seismic fluid-structure interaction analysis of internal components in liquid-filled advanced reactors

Earthquake shaking of a liquid-filled advanced reactor induces fluid-structure interaction (FSI) between the reactor vessel (tank), its internal components, and the contained liquid. Seismic design, qualification, and risk assessment of such reactors must consider fluid-structure responses, their geometries and support conditions, and three-directional seismic inputs, all of which require numerical simulations. Numerical models used for analysis of safety-related nuclear equipment must be verified and validated. Here, this paper verifies numerical models of submerged components using analytical solutions. Seismic FSI analysis of the numerical models is performed using the Arbitrary Lagrangian-Eulerian (ALE) and Incompressible Computational Fluid Dynamics (ICFD) solvers in LS-DYNA. Prior analytical solutions are reworked in this paper, and calculation errors are identified and corrected. The solutions address frequencies of two concentric cylindrical pipes filled with liquid: the inner pipe is a submerged component, and the outer pipe contains the liquid. A unitless frequency coefficient is defined and presented for pipes of different materials, filled with different liquids, and with a range of dimensions for application to advanced reactors. The numerical models are verified here by comparing the lateral frequencies of submerged components with those calculated using the corrected analytical solutions. Recommendations for verification of numerical models of internal components in advanced reactors for seismic FSI analysis are provided. Although the unitless frequency coefficients and verification procedures are developed for application to advanced nuclear reactors, they are broadly applicable to FSI analysis of submerged components in liquid-filled vessels such as storage tanks, boilers, and steam generators.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2024

Providing Experimental Infrastructure for Accelerating Advanced Reactor Demonstrations through the National Reactor Innovation Center

A suite of experimental infrastructure projects has been developed by the National Reactor Innovation Center to accelerate advanced reactor demonstrations and facilitate their development, addressing crucial gaps in data, materials characterization, and modeling. First, the Molten Salt Thermophysical Examination Capability (MSTEC) provides a specialized platform for post-irradiation characterization of molten salt reactor fuel, coolant salts, and structural materials, essential for supporting the design and operation of advanced reactors and future commercial molten salt reactor development and licensing. The Virtual Test Bed (VTB) complements these efforts by leveraging advanced modeling and simulation tools to evaluate reactor performance and safety. Serving as a library of reference models, the VTB offers a database of multiphysics reactor models, facilitating rapid safety evaluations and includes continuous software quality assurance, crucial for accelerating deployment while maintaining reliability. Additionally, the Helium Component Test Facility (HeCTF) addresses the need for high-temperature helium-cooled reactor component testing. As the first-of-its-kind facility in the United States, HeCTF emulates high-temperature gas reactor conditions, reducing time and cost associated with component validation, thereby accelerating reactor development. Finally, In-cell Thermal Creep Frames provide a unique solution for obtaining thermal creep data from irradiated materials, critical for materials qualification and licensing. Developed by the National Reactor Innovation Center, these compact frames enable the examination of previously irradiated materials, overcoming traditional limitations and enhancing the understanding of mechanical properties crucial for reactor development. Collectively, these experimental infrastructure projects form a comprehensive framework aimed at expediting advanced reactor demonstrations, fostering innovation, and ensuring the viability of next-generation nuclear energy solutions.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

Fuel Fabrication Capability Assessment in Support of Advanced Reactor Deployments

More than 30 U.S. companies are designing a variety of advanced reactor concepts, and several companies are planning to demonstrate their reactor designs in the mid-2020s to late 2030s time frame. In 2020, the U.S. Department of Energy (DOE) announced a series of awards under the Advanced Reactor Demonstration Program (ARDP) to accelerate the successful deployment of 10 of these reactors under three pathways. TerraPower and X-energy were awarded grants under the Advanced Reactor Demonstration Program to deploy their respective Natrium reactor and Xe-100 reactor designs in the next 7–10 years. These demonstrations are in addition to several parallel programs, including the U.S. Department of Defense’s (DoD’s) interest in the development of microreactors, and interest of the National Aeronautics and Space Administration in space nuclear power and propulsion. The National Reactor Innovation Center’s (NRIC’s) mission is to accelerate the demonstration and deployment of advanced reactors; NRIC is partnering with several reactor developers and harnessing the world-class capabilities of the U.S. National Laboratory system to deliver on its mission. Several of these reactor designs will require advanced fuel forms that are not commercially available today, including metal fuel, molten salt fuel, TRi-structural ISOtropic (TRISO) particle fuel, and uranium nitride fuel. Recognizing that there may be potential gaps in the laboratory-scale process development and pilot-scale first-of-a-kind (FOAK) production of these fuel forms leading to delivery of the FOAK cores, NRIC commissioned this study to look at the challenges that need to be overcome for successful deliveries, including the evaluation of existing facilities and the potential need for a new fuel fabrication facility.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Reactor System Safety: A case for New and Advanced Reactors

This presentation covers a generic overview of reactor system safety testing, analysis, and related research and development (R&D) focusing on new and advanced reactor systems. This presentation is prepared for graduate-level student seminar talks. No specific reactor design information is provided. Only publicly available information and related published articles and book contents are utilized.

21 - SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLAN↗
DOE OSTI2022

Integration of Wireless Sensor Networks and Battery-free RFID for Advanced Reactors

To address an important need for Nuclear Power Plants (NPPs) to significantly reduce the amount of the required cables for sensor data communications, this Phase I SBIR effort successfully developed and demonstrated a novel low-cost proof-of-concept prototype of a secure wireless sensor network backbone communications system. This system combines commercially available low power, low cost XBEE wireless communications network and passive (battery-free) Radio Frequency Identification (RFID) systems to report individual sensor data and their location through the containment wall for rapid response to anomalies in nuclear facilities. This WIreless Sensing and Locating (WISLO) system network architecture allows non-intrusive wireless collection of sensor data with the sensor’s accurate location information from inside of the instrumentation or containment area with minimal need for power sources. The multi-node sensor data in the containment area is wirelessly transmitted to outside through the metal reinforced concrete walls without the need for any batteries. The WISLO system could be readily used in current reactor fleet and future advanced reactors, as well as in small modular reactors (SMR). The WISLO system is the first dual frequency battery-free trough the wall communications backbone system developed specifically for use in nuclear power plants. It not only can modernize the sensor monitoring practices in the existing reactor fleet, but also offers a secure, low-cost solution to advanced reactors and SMRs by removing cables and issues related to them such as cable integrity, reporting delays, and installation and maintenance costs. The intent is to improve process safety, reliability, efficiency, and cost effectiveness to the monitoring and maintenance process in current and future plants. As we address the next productization and manufacturing capabilities in the next phase, this system will serve the needs of many commercial and government applications in remote monitoring of sensor data that demand battery-free transmission of sensor data such as Internet-of-Things (IOT).

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Human Factors Considerations for Anticipated Uses of Autonomy in Advanced Reactor Technologies

The objective of this report is examine anticipated advanced reactor designs that incorporate high levels of autonomy in operation of advanced reactor systems or facilities, and to begin identifying the human factors engineering (HFE) considerations relevant to those designs. The insights gained will help identify areas where U.S. Nuclear Regulatory Commission (NRC) may need to develop or update review guidance to adequately address HFE considerations essential for safe operation. The adequacy of existing guidance, along with recommendations for updates or new guidance, may be addressed in future reports. We use the term “landscape analysis” to describe the review, analysis, and characterization of publicly available information on the anticipated future state of the industry regarding particular technologies or operational concepts. This landscape analysis considers the potential range of advanced reactor automation concepts that may be used for monitoring and controlling nuclear systems and facilities, including the potential for highly automated, near autonomous, or fully autonomous operation of advanced nuclear reactors.

99 - GENERAL AND MISCELLANEOUS↗