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At least 145 records · Page 8

Control rod drive mechanism with heat pipe cooling

A representative cooling system for a nuclear reactor control rod drive mechanism (CRDM) includes an evaporation section located within or next to the CRDM and a condensation section fluidly coupled to the evaporation section. The cooling system includes a set of heat fins coupled to drive coils in the CRDM and heat pipes that extend through the drive coils and heat fins. A fluid evaporates while in the evaporation section of the heat pipes from heat generated by the CRDM and moves out of the evaporation section into the condensation section in the heat fins. The fluid cools and condensates while in the condensation section, recirculating back into the evaporation section. This passive natural circulation cooling system reduces or eliminates the number of water hoses, piping, and other water pumping equipment typically used for cooling a CRDM thereby increasing nuclear reactor reliability and simplifying nuclear reactor operation and maintenance.

Lobscheid, Christian↗

Development of Whole System Digital Twins for Advanced Reactors: Leveraging Graph Neural Networks and SAM Simulations

Here, in this work, we introduce a novel method to develop whole system digital twins (DTs) for advanced nuclear reactors. This method treats a complex reactor system as a heterogeneous graph: with the system components as different types of graph nodes and their physical interconnections as edges. Based on the heterogeneous graph, a graph neural network combining graph convolution and temporal node attention is developed as the DT, facilitating a comprehensive understanding of the system's dynamic behavior. By utilizing the System Analysis Module (SAM) code for simulating various operational transients, we develop a graph-based database that trains the DT. This DT is characterized by two primary functions: It can infer the entire system's status using sparse node information, and it can predict the progress of transients based on current and historical system information. Our approach is validated through case studies on the Experimental Breeder Reactor II (EBR-II) system and a generic Fluoride-salt-cooled High-temperature Reactor (gFHR), demonstrating the DT's accuracy in forecasting operational transients. The DT's rapid computation capabilities enhance its potential for supporting advanced reactor operations, offering benefits in intelligent simulation, autonomous control, and anomaly detection, paving the way for improved safety analysis and intelligent component health management for advanced reactor systems and reducing their operations and maintenance cost.

EBR-II↗

Optimizing chemistry for designing oxidation resistant FeCrAl alloys

Abstract Traditionally, FeCrAl alloys played an important role in high-temperature applications due to their ability to form a passive Al oxide film at temperatures above ~ 800 °C. Recently, FeCrAl alloys became of interest for the application of accident tolerant nuclear fuel cladding. This study covers work done at GE Research for better understanding the role of Al, Cr, and Mo in oxidation kinetics and thermodynamics. Several models and commercial prototype alloys have been tested in hydrothermal corrosion autoclave loops, at low temperature steam exposure (~ 400 °C), high temperature steam exposure (~ 1000 °C or higher), and high temperature air exposures. The results provide insights on how chromium and aluminum play a significant role in both high temperature and low temperature oxidation of FeCrAl. Additionally, machine learning tools are used to gain further insights on both predicting future optimized chemistries for balancing the properties of hydrothermal corrosion, low and high temperature steam oxidation, and thermal aging (which is exacerbated due to radiation in a nuclear reactor environment). GE plans to use this framework to further optimize the FeCrAl alloy system for use in nuclear reactor environments. Graphical abstract

Roy, Indranil (ORCID:0000000336124323)↗

An Approach to Automate tools for the Risk Assessment of Digital Instrumentation and Control Systems

Reliable digital instrumentation and control systems (DI&C) are integral for sustaining the continued operation of nuclear power plants. These systems ensure that nuclear reactors operate safely, efficiently, and within regulatory requirements. Yet, the cost of designing and licensing new nuclear DI&C can be prohibitively expensive. Under the U.S. Department of Energy Light Water Reactor Sustainability Program, Idaho National Laboratory has developed a framework for supporting the risk-informed design of DI&C systems by offering methods to support the identification, quantification, and evaluation of risks for various DI&C design architectures. The framework indicates potential software failure modes and provides pathways for quantifying the potential for these software failures, including common cause failures. Using the framework’s systematic approach, challenges for assessing risks within new and existing nuclear DI&C systems can be reduced. Nevertheless, the current framework can be further improved using the convenience of automation. This paper introduces the development of Software for the Hazard Identification and Evaluation of Digital Systems (SHIELDS). SHIELDS is an engineering software package that enables the identification, elimination, and mitigation of potential risks and reduces the burden of deploying reliable DI&C systems. This work introduces plans and techniques to digitize and improve the manual risk assessment modules of the framework. These improvements will save time and increase the repeatability and usability of the framework, making it more accessible to a wider range of users. Ultimately, this introduces SHIELDS and how its modules support efficient development of safe and reliable DI&C systems.

46 - INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AN↗

Gen IV Education and Training Working Group Webinars’ Initiative

Collaboration and support among national laboratories, industry, universities, and research and development organizations are vital to not only maintain a skilled and competent nuclear workforce but also to avert the risk of human resource shortages. As stated in a recent IAEA paper [1], the world nuclear electrical generating capacity is projected to increase to 554 GW(e) by 2030 and up to 874 GW(e) by 2050 (Fig. 1). This represents a 42% increase over current levels by 2030 and a doubling of the current capacity by 2050. To promote Education and Training (E&T) on Gen IV reactor systems and other nuclear related topics of interest, the Gen IV Education and Training Working Group (ETWG) identifies and advertises training courses; engages collaboration with other international education and training organizations; delivers webinars dedicated to Gen IV systems; and maintains a modern social medium platform to exchange information and ideas on Gen IV R&D topics, as well as on related GIF education and training activities. At the end of June 2020, the GIF ETWG has produced, podcasted and posted forty-one webinars covering the six Gen IV systems and various subjects addressing e.g. the economics of the nuclear fuel cycle, sustainability aspects of Gen IV systems, nuclear fuels and materials challenges, the thorium fuel cycle, energy conversion systems, and lessons learned for knowledge management and preservation. This paper describes the development of these webinars from the initial concept to its full realization, with future webinars planned in 2021, addressing topics such as materials and fuels performance for advanced reactors, small modular reactor.

Paviet, Patricia D.↗

Development and experimental evaluation of an acoustic flow meter prototype for measuring air flow

Here, this study outlines the development and testing of a flow meter prototype specifically designed for use in nuclear reactor environments. The meter uses flow-induced vibration to measure flow rates and is designed for remote monitoring in harsh environments where radiation can damage electronics. The device generates a vibration signal produced by a feedback system when fluid flows out of an orifice and interacts with a downstream wedge. The frequency of the vibration signal corresponds directly to flow rate and velocity. The study investigates geometric parameters intrinsic to the prototype, such as orifice height, width, edge distance, and chamber length. Different configurations were also tested, including a bypass loop with variable cross-sections around the device. The investigation results reveal the impact of these geometric parameters on the vibration signal output, providing valuable insights for future design improvements and enhancing the effectiveness of flow metering systems used in nuclear reactor applications.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Exploring Advanced Computational Tools and Techniques with Artificial Intelligence and Machine Learning in Operating Nuclear Plants

This report presents the project Idaho National Laboratory conducted for Nuclear Regulatory Commission to explore the advanced computational tools and techniques, such as artificial intelligence (AI) and machine learning (ML), for operating nuclear plants. The report reviews the nuclear data sources, with the focus on the operating experience data, that could be applied by advanced computational tools and techniques. Plant-specific and generic (national and international) data from different sources are described. The report describes the relationships between statistics and AI/ML and then introduces the most widely used AI/ML algorithms in both supervised and unsupervised learning. The report reviews the recent applications of advanced computational tools and techniques in various fields of nuclear industry, such as reactor system design and analysis, plant operation and maintenance, and nuclear safety and risk analysis. Finally, the report presents the insights from the project on the potential applicability of AI/ML techniques in improving advanced computational capabilities, how the advanced tools and techniques could contribute to the understanding of safety and risk, and what information would be needed to provide meaningful insights to decision makers. The report also documents an NRC survey on the current state of commercial nuclear power operations relative to the use of AI and ML tools as well as the role of AI/ML tools in nuclear power operations was published by the NRC as in FRN NRC-2021-0048 in April 2021. A summary of the survey including the survey questions, survey participants, survey responses, and the conclusions and insights derived from the survey is provided in the report. Finally, the report investigates potential applications of using AI/ML in operating NPPs and advanced reactors (both advanced LWRs and advanced NLWRs) to improve nuclear plant safety and efficiency. Three main application fields are defined and discussed: (1) plant safety and security assessments; (2) plant degradation modeling, fault and accident diagnosis and prognosis; and (3) plant operation and maintenance efficiency improvement.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Evaluation of Power Fluidic Pumping Technology for Molten Salt Reactor Applications

Power Fluidics™ (PF) is a NuVision Engineering proprietary technology which uses gases to control the flow of other fluids in industrial applications. This unique technology has several advantages over traditional centrifugal pumps. Molten salt nuclear reactors and associated systems have unique fluid handling demands. This report explores the applicability of PF to molten salt systems. Several potential applications are identified, necessary modifications of existing PF technology for salt service are discussed, and a path for development and demonstration is proposed.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Degradation of impact toughness in cast stainless steels during long-term thermal aging

Cast austenitic stainless steels (CASSs) have been extensively used for the large components of nuclear reactor primary coolant systems. Since the cast steels inevitably contain degradable metastable phases and replacement of the large coolant system components is impractical, the thermal embrittlement of CASS components has been a serious concern in the extended-term operation of nuclear power plants. This study aimed to systematically measure and analyze the effect of long-term thermal aging on the Charpy impact toughness to provide a comprehensive understanding of thermal degradation behavior and a practical aging model to predict the degree of thermal degradation in the cast stainless steels. Additionally, the materials tested in the research include eight CASS alloys (two CF3s, one CF3M, three CF8s, and two CF8Ms) and two reference wrought materials (304L and 316L), in which the nominal δ-ferrite content ranges from ~2% to 33%. These stainless steels have been thermally aged at two light water reactor (LWR) temperatures (290 and 330 °C) and at two accelerated-aging temperatures (360 and 400 °C) for up to 30,000 h; these include both under-aged and over-aged conditions relative to the extended service lifetime (80 years). Charpy impact testing was performed for aged and non-aged specimens, and the impact (absorbed) energy parameters were correlated with a new aging parameter (A). Both the reduction of impact fracture toughness and the shift of ductile-brittle transition temperature were strongly dependent on the δ-ferrite content and degree of thermal aging. A linear relationship was found between the increasing rate of the index transition temperature T 41J and aging parameter A; base on which an empirical model was proposed for prediction of the transition temperature as a simple function of the aging parameter (A) and δ-ferrite content (F). Finally, the critical aging parameter for embrittlement (AC) was evaluated and compared with the existing δ-ferrite content criteria.

36 MATERIALS SCIENCE↗

Business Case Analysis for Digital Safety-Related Instrumentation & Control System Modernizations

This LWRS research seeks to assist in breaking the impasse which has precluded digital safety system upgrades by generating and demonstrating a process and related business case tool to enable a Business Case Analysis (BCA). The purpose of a BCA is to show such upgrades can be economically justified. This BCA methodology first systematically establishes a forecast of expected lifecycle costs for I&C identified for upgrade by: • Definitively bounding the scope of current I&C systems envisioned for upgrade. • Collecting historical labor and material usage data that bound cost contributors related to the systems to be upgraded. • Synthesizing and analyzing the data to establish lifecycle cost forecasts for the current systems. In collaboration with engineers familiar with the attributes of the digital equipment to be used in the upgrade and how it is envisioned to be applied, cost savings categories and expected savings in those categories are then identified and applied using the analysis tools developed for this purpose. The result is an estimate NPV of savings enabled by the upgrade. This includes both direct cost savings (e.g., surveillance labor costs) as well as cost avoidance items (e.g., inventory carrying costs). Finally, when utility-provided digital upgrade costs estimates are included, the resultant BCA provides an NPV for the upgrade project. Development of a useful BCA methodology requires a real-world basis. With the cooperation of Exelon Generation (“Owner”), an Exelon-owned 2-Unit BWR Station (“Station”) was used as the foundation for this research. Exelon is pursuing a digital upgrade of current, first-echelon, safety-related I&C systems at these units, including the following: • Reactor Protection System (RPS) • Nuclear Steam Supply Shutoff System (N4S) • Emergency Core Cooling Systems (ECCS) • Anticipated Transient Without Scram (ATWS) Mitigation System

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Design Basis Model for Hosting Small Modular Reactors

An aggressive transition from fossil fuels to other types of energy implies the need to construct a large number of nuclear power plants in the near future. However, the real and perceived risks of nuclear energy remain a significant impediment to this transition. This paper describes a comprehensive work process that combines the rigor of model-based systems engineering (MBSE) with 1) the Idaho National Laboratory's (INL) decades of experience with small reactors and with 2) modern project delivery processes. The objective is to reduce the risk of building new facilities or converting existing facilities to nuclear power generation.

42 ENGINEERING↗

Comparative Analysis of Standard and Advanced USL Methodologies for Nuclear Criticality Safety

The American National Standards Institute/American Nuclear Society national standards 8.1 and 8.24 provide guidance on the requirements and recommendations for establishing confidence in the results of the computerized models used to support operation with fissionable materials. By design, the guidance is not prescriptive, leaving freedom to the analysts to determine how the various sources of uncertainties are to be statistically aggregated. Due to the involved use of statistics entangled with heuristic recipes, the resulting safety margins are often difficult to interpret. Also, these technical margins are augmented by additional administrative margins, which are required to ensure compliance with safety standards or regulations, eliminating the incentive to understand their differences. With the new resurgent wave of advanced nuclear systems, e.g., advanced reactors, fuel cycles, and fuel concepts, focused on economizing operation, there is a strong need to develop a clear understanding of the uncertainties and their consolidation methods to reduce them in manners that can be scientifically defended. In response, the current studies compare the analyses behind four notable methodologies for upper subcriticality limit estimation that have been documented in the nuclear criticality safety literature: the parametric, nonparametric, Whisper, and TSURFER methodologies. Specifically, the work offers a deep dive into the various assumptions of the noted methodologies, their adequacies, and their limitations to provide guidance on developing confidence for the emergent nuclear systems that are expected to be challenged by the scarcity of experimental data. Here, to limit the scope, the current work focuses on the application of these methodologies to criticality safety experiments, where the goal is to calculate a bias, a bias uncertainty, and a tolerance limit for k eff in support of determining an upper subcriticality limit for nuclear criticality safety.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

Design, Manufacturing and Performance Considerations in Reactor System, Components and Materials

Idaho National Laboratory (INL) is the national and global leader of the Department of Energy (DOE) ’s nuclear energy research, development, and demonstration programs. Developing critical design criteria of new advanced reactor systems, components and materials requires an understanding of fabrication and the irradiation environment during normal operating and accident conditions. Next generation researchers and designers, are, therefore challenged not only by demands for ever improved performance but must also work to shorten the development and commercialization lifecycle for new nuclear reactors and systems to remain competitive. This provides unique and exciting opportunities for all contributors to this field of study. This presentation will offer a strategic overview of the competitively funded R&D awards by the Advanced Methods for Manufacturing (AMM) program of the DOE’s office of Nuclear Energy (NE). This program conducts research and development (R&D) to accelerate innovations by reducing the cost and schedule of constructing new nuclear plants and to make fabrication of nuclear power plant components faster, cheaper, and more reliable. By evaluating state-of-the-art practices found in other large manufacturing industries, the nuclear community has identified six major areas of innovation to reach the objectives of this DOE-NE program. Additionally, typical research case studies performed at INL, will be presented, showing the vast variety of opportunities for which, the next generation of researchers can seek solutions.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

FLASSH 1.0: Full Law Analysis Scattering System Hub

Nuclear technologies, such as thermal reactors and critical systems, are driven by reaction rates which are directly dependent on thermal neutrons. The ability to calculate reaction rates is directly linked to the capability to predict and understand the cross sections. For atoms bound within a material structure, the available modes of energy exchange are captured in the Thermal Scattering Law (TSL, i.e. S(α,β)). The TSL is fundamentally a material property and can be defined explicitly to account for the excitation and deexcitation of the lattice energy states. This work describes the development of the Full Law Analysis Scattering System Hub (FLASSH) which calculates the TSL and cross sections. FLASSH is a modern code which has been designed to produce accurate TSL evaluations, remove historical approximations, and improve formulations while making advance physics accessible and simple to use.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

High-Reliability Systems and the Control of National Security Data and Information

High-reliability systems are characterized by catastrophic implications in the event of failure. These implications can include substantive damage to the environment, social order, and loss of life. Examples of high-reliability systems include nuclear submarines, nuclear reactors, the electric grid, and nuclear weapons. Due to the catastrophic implications of failure, there are heightened awareness and control mechanisms surrounding related data and information. However, defining the difference between data and information is often ambiguous across scholarly disciplines and in United States policy and legislation. For high-reliability systems, the implications of ambiguity between data and information may affect the security of United States interests and even cost lives. For security, data are raw facts or figures without context, while information is the compilation or articulation of data that forms context. Security depends on clarity in the differences between data and information and how to control them. Control is necessary to ensure that data and information are not unintentionally released to foreign governments, the public, or those without need-to-know. A primary concern in the practice of security is the control of data to avoid the unintended conversion to information. Intra-institutionally, this control is highly complex given the amalgam of legacy data systems and the numerous and constantly evolving nature of modern data systems that were not necessarily designed to be integrated. The complexity of this concern is augmented when institutions are part of interinstitutional collaborations or networks of public-private partnerships that share data and information. Additionally, institutions that share data as a function of policy and legislative action— particularly formally integrated data and information system infrastructures—may be at higher security risk. This paper will present an intra-institutional paradigm that utilizes and integrates concepts from numerous disciplines to frame a critical and underspecified practical issue in security—controlling for the unintended conversion of data to information.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

High-Reliability Systems and the Control of National Security Data and Information

High-reliability systems are characterized by catastrophic implications in the event of failure. These implications can include substantive damage to the environment, social order, and loss of life. Examples of high-reliability systems include nuclear submarines, nuclear reactors, the electric grid, and nuclear weapons. Due to the catastrophic implications of failure, there are heightened awareness and control mechanisms surrounding related data and information. However, defining the difference between data and information is often ambiguous across scholarly disciplines and in United States policy and legislation. For high-reliability systems, the implications of ambiguity between data and information may affect the security of United States interests and even cost lives. For security, data are raw facts or figures without context, while information is the compilation or articulation of data that forms context. Security depends on clarity in the differences between data and information and how to control them. Control is necessary to ensure that data and information are not unintentionally released to foreign governments, the public, or those without need-to-know. A primary concern in the practice of security is the control of data to avoid the unintended conversion to information. Intra-institutionally, this control is highly complex given the amalgam of legacy data systems and the numerous and constantly evolving nature of modern data systems that were not necessarily designed to be integrated. The complexity of this concern is augmented when institutions are part of inter-institutional collaborations or networks of public-private partnerships that share data and information. Additionally, institutions that share data as a function of policy and legislative action—particularly formally integrated data and information system infrastructures—may be at higher security risk. This paper will present an intra-institutional paradigm that utilizes and integrates concepts from numerous disciplines to frame a critical and underspecified practical issue in security—controlling for the unintended conversion of data to information.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

Griffin Capability Improvements in Support of Ex-core Deep-Penetration Problems

Advanced reactor designs, especially portable reactors that are designed to be located closer to humans and operate autonomously, require the ability to accurately compute the ex-core neutron and gamma flux solutions in terms of shielding design optimization to reduce dose rates at the vessel boundary and detector signal prediction to drive the reactor control system. The Nuclear Energy Advanced Modeling and Simulation program has prioritized improvements to the Griffin discrete ordinates (SN) solver for deep-penetration problems in fiscal year 2025. Significant advancements have been made to the Griffin methodologies for solving ex-core deep-penetration problems for steady-state, fixed-source and transient calculations. This work presents the methodology improvements as well as a comprehensive demonstration with a Transient Test Reactor model and measurements.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗

Development of a Representative Molten Chloride Fast Reactor Model to Assess the Impact of Nuclear Data

The SCALE code system was employed to conduct a preliminary investigation of nuclear data impacts for a fast spectrum molten chloride salt reactor. A computationally effective depletion model that is representative of the reactor system was successfully developed and used to conduct fuel depletion simulations. Development of this model draws from the SLICE method that was developed at Oak Ridge National Laboratory to enable generation of fuel compositions for an advanced reactor core at equilibrium operation. Eigenvalue uncertainty calculations using the ENDF/B-VII.1 nuclear data library were performed for the reactor in the fresh fuel state and an irradiated fuel state. It was determined that the primary driver of eigenvalue uncertainty was the uncertainty in the 235U (n, 𝛾) cross section. Uncertainty calculation results from this study were compared to results available for a different fast system, a sodium-cooled fast reactor, to confirm similarities and identify differences with respect to nuclear data impacts between the two fast advanced reactor systems.

Hirji, Rakim [Georgia Institute of Technology]↗