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Framework for Greenhouse Gas Emissions Reduction Planning: Building Portfolios

The goal of this framework for greenhouse gas (GHG) emissions reduction planning (ERP) is to provide guidance to organizations seeking to reduce GHG emissions for their building portfolios and vehicle fleets. The process described in this framework helps organizations develop an actionable plan that prioritizes emissions reduction measures, identifies solutions, and lays out a phased pathway to achieve deep emissions reductions. The plan aims to result in the achievement of Scope 1 and 2 GHG emissions reduction targets, in alignment with goals set within the U.S. Department of Energy’s (DOE’s) Better Climate Challenge, as well as longer term emissions reduction goals.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

U.S. Efforts in Support of Examinations at Fukushima Daiichi - November 2022 Meeting Notes and Information Request Status

Information obtained from Fukushima Daiichi Nuclear Power Station (Daiichi) is required to inform future Decontamination and Decommissioning (D&D) activities, improving the ability of the Tokyo Electric Power Company Holdings, Incorporated (TEPCO Holdings) to characterize potential hazards and to ensure the safety of workers involved with cleanup activities. This information also has important implications for the safety and operation of U.S. commercial nuclear power plants. This document summarizes results from the Fiscal Year 2023 (FY2023) U.S. effort to review Daiichi information and extract insights to enhance the safety of existing and future nuclear power plant designs. This U.S. effort, which was initiated in 2014 by the Department of Energy Office of Nuclear Energy, is completed by a group of experts in reactor safety and plant operations that identify examination needs and evaluate recent Daiichi examination data to address these needs. Fukushima-related information and associated discussions during these meetings benefit operating, new, and advanced reactors. Significant safety insights have been and are continuing to be obtained in several areas: system and component performance, radionuclide surveys and sampling, debris end-state location, combustible gas effects, and plant operations and maintenance. In addition to reducing uncertainties related to severe accident modeling progression, these insights have and continue to be used to update guidance for severe accident prevention, mitigation, and emergency planning. Furthermore, Daiichi-related activities, such as code modeling improvements and analysis, testing, and new technology deployment efforts, have the potential to offer additional benefits to the operating fleet and new LWR and non-LWR designs. U.S. evaluations of obtained examination information and input regarding future Daiichi examinations are of interest to several organizations within Japan. Since its inception, the U.S. has provided consensus input for high priority time-sequenced examination tasks and supporting research activities. In their Mid-to-Long-term Examination Plan for 1F investigations, TEPCO included all remaining U.S. consensus information requests and additional information requests they identified. TEPCO periodically provides reports on the status of these requests (reflecting D&D priorities, new insights from investigations, and new technologies that become available). Hence, U.S. experts agreed that it was appropriate for TEPCO to track and prioritize these information requests as D&D progresses. U.S. experts will continue to review and comment on the information obtained from examinations and, as needed, provide additional details and relevant background material to support future examinations. As documented in this report, several other items, such as additional details on information requests pertaining to ex-vessel examinations, relevant references from prior research, additional documents to provide insights regarding recent investigation findings, and reviews of recently released documents, were agreed to during the FY2023 meeting.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Coupled Decay Heat and Thermal Hydraulic Capability for Loss-of-Coolant Accident Simulations

As the nuclear energy industry considers ways to achieve improved economics in the current fleet of light-water reactors (LWRs), one possible approach is to operate each cycle for longer durations. This causes a greater portion of the fuel to be burned and reduces the frequency of outages, which ultimately reduces the cost to operate the reactor. However, this also leads to higher burnup fuels than has traditionally been allowed in these reactors. Thus, there are concerns about integrity of high-burnup (HBu) fuel, especially during accident conditions such as loss-of-coolant accidents (LOCAs), as shown by Capps et al.. To investigate these concerns, advanced modeling and simulation capabilities are being leveraged to determine the susceptibility of HBu fuel to fuel fragmentation, relocation, and dispersion (FFRD). Improvements have previously been made to fuel performance capabilities to more accurately model these phenomena; multiphysics simulations have also been conducted to determine the power and burnup histories of the HBu fuel, which are needed as inputs for the fuel performance calculations. Most recently, new statistical approaches have been developed to identify a subset of fuel rods that have greater FFRD susceptibility, reducing the total number of fuel performance simulations required. Prior LOCA simulations have relied on the TRACE systems code, which can model the core and primary loop during accident conditions. TRACE includes many models for various aspects of the primary loop, but two sets of models are important for this report. First, TRACE uses a lumped-fuel approach for modeling the core. This approximates the ~50,000 fuel rods in the core with a much smaller number of rods. The rods can be lumped in various ways as determined by the user. For example, one lumped rod may be used to represent all rods in an assembly, sometimes with an additional rod representing the hottest fuel rod. However, due to runtime constraints and complexity of modeling, a more common approach is to group several assemblies or larger regions of the core into single lumped rods. These lumping schemes apply not only to fuel rods but to flow channels as well. Second, TRACE has several different models for treating decay heat, ranging from pregenerated decay heat curves based on an ANSI/ANS-5.1 standard (hereinafter abbreviated simply as ANSI) to explicit time-dependent heat inputs from the user. None of these models account for differences in isotopics between different rods, which is an approximation the work in this report seeks to eliminate. This report focuses on the implementation of coupled decay heat capabilities in the Virtual Environment for Reactor Applications (VERA) code suite to address a gap identified in previous LOCA simulations. This constitutes an improvement for both the lumped-fuel and decay heat models in TRACE. VERA has been developed to perform high-fidelity, whole-core multiphysics simulations for LWRs. Previously, during the Consortium for Advanced Simulation of LWRs (CASL) program, the emphasis was on providing accurate steady-state analysis—with a secondary focus on reactivity insertion accident (RIA) analysis—to address operational challenges in the nuclear energy industry. Under the Department of Energy (DOE) Nuclear Energy Advanced Modeling and Simulation (NEAMS) program, these capabilities are being extended to a broader range of transient analyses with the goal of quantifying the risk of fuel failures such as FFRD. To properly model such conditions with VERA, decay heat calculations have been integrated with the multiphysics to enable rod-by-rod thermal hydraulic (TH) conditions to be driven by the decay heat in long-running accidents such as LOCAs.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Visualization of the High-Burnup Spent Fuel Rod Phase 1 Test Plan: Technical Memo - Spent Fuel and Waste Disposition (Technical Memo)

Twenty-five high-burnup fuel rods were extracted from seven different fuel assemblies used for power production at the North Anna nuclear power plant and shipped to Oak Ridge National Laboratory (ORNL) in 2016 for detailed non-destructive examination (NDE) and destructive examination (DE). The spent fuel rods were from 17×17 lattices and consist of four cladding types—Zirlo ® , M5 ® , Zircaloy-4, and low tin Zircaloy-4 (Zirc-4). These spent fuel rods are being tested to provide: (a) baseline characterization and mechanical property data that can be used as a comparison to fuel that was loaded into a modified TN-32B cask in November 2017, as part of the high-burnup confirmatory data project and (b) data applicable to high-burnup fuel rods (>45 GWd/MTU) currently stored and to be stored in the dry-cask fleet. The TN-32B cask is referred to as the “Demo” cask and is currently expected to be transported to a separate location and the internal contents inspected in approximately ten years. ORNL has completed the NDE of the twenty-five fuel rods. The purpose of this technical memorandum is to present a simplified summary of the first phase of destructive examinations and test conditions that will be used for communicating with various stakeholders. The destructive examinations will leverage the expertise and capabilities from multiple national laboratories for performing independent measurements of relevant data. Close coordination is required to ensure that all examinations follow well documented procedures and are performed so that measured data and characteristics can be readily compared. Pacific Northwest National Laboratory (PNNL) has published a detailed overview of the test program. ORNL and PNNL developed detailed draft test plans for testing to be performed at their facilities. ORNL and PNNL are in the process of refining these test plans to apply specifically to the testing described in this memorandum. Argonne National Laboratory (ANL) contributed to the ORNL test plan by describing tests to be conducted at ANL. Testing will be based on continuous learning. If a test produces results that are inconsistent with expectations or current trends, further testing will be paused until a path forward is established to understand the results and to identify follow-on testing.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Overview of the Regional Bio-Economy Model (RBEM)

Recent decarbonization goals and market pressures (nationally and internationally) have led airlines to commit to aggressive strategies to reduce carbon emissions in their fleet. To better understand possible regional evolution scenarios for SAF supply train, we have developed the Regional Biomass Energy Model (RBEM). RBEM is a dynamic model that can be used to create potential development scenarios for bioenergy fuels within a defined region. In this report, we describe the model and present illustrative results using the Chicago O'Hare Airport as an example.

09 BIOMASS FUELS↗

Grid-Integrated Production of Fischer-Tropsch Synfuels from Nuclear Power

Idaho National Laboratory (INL) investigates the relative economic profitability of an integrated energy system (IES) coupling an NPP with a synfuel production process at selected case study locations across the United States. In the synfuel IES, a high-temperature steam electrolysis (HTSE) plant is thermally and electrically coupled with an NPP to produce zero-carbon hydrogen. The synthetic fuel is produced from this H 2 combined with a CO 2 supply using the reverse water gas shift process followed by the Fischer-Tropsch (FT) reaction. This analysis considers a system in which the CO 2 is sourced from regional CO 2 emitters via the construction and operation of pipeline-based CO 2 supply networks. Locating the FT plant at the same site as the NPP and HTSE plants enables the NPP to provide zero-carbon heat and power to the HTSE plant and zero-carbon power to the FT plant as well as avoid the requirement for long-distance H 2 product transport from the HTSE plant to the FT plant. Hydrogen storage is used to enable the NPP to dispatch power to the electrical grid (instead of the HTSE plant) when grid demand increases, thus enabling the FT plant to continue to operate in a steady-state production mode. The ability to cease hydrogen production for several hours within each day enables the NPP to provide power to the grid to balance the electricity market during peak periods and maximize revenues for the nuclear synfuel IES. The FT process design considered has a 99% carbon conversion efficiency. The use of nuclear energy and nuclear energy-derived hydrogen enables synfuel production to achieve this high level of carbon utilization. Additionally, the life-cycle carbon emissions of the nuclear-based synfuel production process are very low, with WTW emissions of approximately 25 gCO 2 e/MJ, including steam credits (generated from FT process excess heat), and approximately 7 gCO 2 e/MJ, if steam credits are excluded. This compares favorably with the WTW emissions of 90.5 gCO 2 e/MJ for a compression-ignition, direct injection (CIDI) vehicle with a fuel economy of 31.6 miles per gallon gasoline equivalent (MPGGE), using low-sulfur diesel produced using conventional petroleum production and refining processes. Several NPPs in various regions of the U.S. are considered as case study analyses. Supply locations and transportation via pipeline of the CO 2 feedstock to the NPP site are analyzed through the National Energy Technology Laboratory (NETL) CO 2 Transport Cost model. The team finds that the amount of CO 2 generated by different sectors is sufficient for the synfuel production process at all locations considered. The CO 2 transportation costs are functions of the distance of the source to the NPP location, the CO 2 capture cost at the source, and the quantity of CO 2 transported. Historical electricity prices for the NPP case study locations are collected and analyzed. Monthly average prices, price range, and duration of negative-price periods vary among these locations. For each location, an auto-regressive moving average (ARMA) model is trained on historical electricity price data. ARMA validation is done to ensure the synthetic price distributions represent one of historical prices with high fidelity. Synthetic time series from these ARMA models are used in a coupled dispatch and system optimization in the Holistic Energy Resource Optimization Network (HERON) to compute the differential net present value (NPV) of the IES. The team finds that this econometric is positive, ranging from $14M–1.3bn (2020) depending on the location. The optimal synfuel IES configuration to obtain this increase in NPV often maximizes the size of the synfuel production process with regards to the size of the NPP. However, the team shows that the NPP still plays a stabilizing role for the grid: In periods of high prices and high loads, more electricity from the NPP is sent to the grid. A high variability of electricity prices and extreme maximum prices tend to drive up electricity production. While it requires significant investment, the synfuel IES could increase the economic profitability for the existing fleet of LWRs across the country while still maintaining the grid stabilizer role of NPPs. During its lifetime, the main costs for the nuclear synfuel IES are the carbon feedstock transportation costs, followed by the capital expenses (CAPEX) and operation and maintenance (O&M) costs while the revenue comes first from the IRA H 2 production tax credit (PTC) and then from the sales of synfuel products. The profitability of the synfuel IES is most sensitive to the value of the hydrogen PTC and the synfuel products as well as the cost of the carbon feedstock, highlighting the importance of governmental incentives regarding hydrogen, carbon emissions, and synfuel in driving the deployment of future nuclear synfuel IESs.

08 HYDROGEN↗

FFTF Acceptance and Startup Testing for GAIN

The Fast Flux Test Facility (FFTF) is the most recent liquid metal reactor (LMR) to be designed, constructed, and operated by the U.S. Department of Energy (DOE). The 400-MWt sodium-cooled, fast-neutron flux reactor plant was designed for irradiation testing of nuclear reactor fuels and materials for liquid metal fast breeder reactors. Following the demise of the breeder reactor program in the United States, FFTF continued to play a key role in providing a test bed for demonstrating performance of advanced fuel designs and demonstrating operation, maintenance, and safety of advanced liquid metal reactors. FFTF operations ceased in April 1992 after a determination by DOE that no combination of proposed missions was financially feasible over a ten-year period. The reactor is currently deactivated and in a long-term surveillance and maintenance (S&M) mode. This report provides information on the extensive and rigorous process that was used to conduct turnover from construction followed by acceptance and startup testing of the FFTF. This paper is in support of the Gateway for Accelerated Innovation in Nuclear (GAIN), which provides the nuclear energy community with access to the technical, regulatory, and financial support necessary to move new or advanced nuclear reactor designs toward commercialization while ensuring the continued safe, reliable, and economic operation of the existing nuclear fleet. The information obtained from the design, startup, and operation of the FFTF provides valuable insight for follow-on reactor projects, such as the Versatile Test Reactor (VTR), in the areas of plant system and component design, component fabrication, fuel design and performance, prototype testing, site construction, reactor startup and operations, and reactor deactivation and decommissioning (D&D). The focus of this report is on the process used to startup the FFTF and to ensure that operations could be conducted efficiently and safely. A reference section is provided of documents detailing the successful turnover and testing process implemented for startup of the reactor and its supporting systems. The documents listed can be retrieved upon request and are believed useful for future reactor startup endeavors.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

On-the-Fly Energy Condensation for Whole-Core Multiphysics Simulations

As the nuclear energy industry considers ways to achieve improved economics in the current fleet of light-water reactors (LWRs), one possible approach is to operate each cycle longer. This causes a greater portion of the fuel to be burned and reduces the frequency of outages, which ultimately reduces the cost to operate the reactor. However, this also leads to higher burnup fuels than have traditionally been allowed in these reactors. There are concerns about integrity of high-burnup (HBu) fuel, especially during accident conditions such as loss-of-coolant accidents (LOCAs), as shown by Capps et al. To investigate these concerns, advanced modeling and simulation capabilities are under development to determine the susceptibility of HBu fuel to fuel fragmentation, relocation, and dispersion (FFRD). Improvements have previously been made to fuel performance capabilities to model these phenomena more accurately; multiphysics simulations have also been conducted to determine the power and burnup histories of the HBu fuel, which are needed as inputs to the fuel performance calculations. Most recently, new statistical approaches have been developed to identify a subset of fuel rods that have greater FFRD susceptibility, reducing the total number of fuel performance simulations required.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Assessment of Sodium Fast Reactor Specific Consensus Standards and Recommendations for Future Regulatory Development for Standards Activities

The U.S. has designed, constructed, and operated several sodium fast reactors (SFRs). To support these efforts and to document best practices, activities associated with the development of standards and consensus standards were carried out, however, the vast majority of those SFR standards are currently in a withdrawn or inactive status. Consensus standards are useful during design and licensing of reactors, as is evident in the current nuclear power generation fleet. Consensus standards provide certainty and predictability between stakeholders during licensing and other regulatory interactions. These standards offer guidance, reflect expert positions, and establish effective practices for a wide range of topics. Consensus standards are developed by committees with representation from a broad cross-section of industry, organizations, professional societies, and government agencies. However, most existing consensus standards applicable to nuclear power plants were developed specifically for light-water reactor (LWR) designs and may not adequately address specific advanced non-LWR design topics such as those related to SFRs.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Light Water Sustainability Program: Optimizing Information Automation Using a New Method Based on System-Theoretic Process Analysis

This report describes the interim progress for research supporting the design and optimization of information automation systems for nuclear power plants. Much of the domestic nuclear fleet is currently focused on modernizing technologies and processes, including transitioning toward digitalization in the control room and elsewhere throughout the plant, along with a greater use of automation, artificial intelligence, robotics, and other emerging technologies. While there are significant opportunities to apply these technologies toward greater plant safety, efficiency, and overall cost-effectiveness, optimizing their design and avoiding potential safety and performance risks depends on ensuring that human-performance-related organizational and technical design issues are identified and addressed. This report describes modeling tools and techniques, based on sociotechnical system theory, to support these design goals and their application in the current research effort. The report is intended for senior nuclear energy stakeholders, including regulators, corporate management, and senior plant management. We have developed and employed a method to design an optimized information automation ecosystem (IAE) based on the systems-theoretic constructs underlying sociotechnical systems theory in general and the Systems-Theoretic Accident Modeling and Processes (STAMP) approach in particular. We argue that an IAE can be modeled as an interactive information control system whose behavior can be understood in terms of dynamic control and feedback relationships amongst the system’s technical and organizational components. Up to this point, we have employed a Causal Analysis based on STAMP (CAST) technique to examine a performance- and safety-related incident at an industry partner’s plant that involved the unintentional activation of an emergency diesel generator. This analysis provided insight into the behavior of the plant’s current information control structure within the context of a specific, significant event. Our ongoing analysis is focused on identifying near-term process improvements and longer-term design requirements for an optimized IAE system. The latter analyses will employ a second STAMP-derived technique, System-Theoretic Process Analysis (STPA). STPA is a useful modeling tool for generating and analyzing actual or potential information control structures. Finally, we have begun modeling plantwide organizational relationships and processes. Organizational system modeling will supplement our CAST and STPA findings and provide a basis for mapping out a plantwide information control architecture. CAST analysis findings indicate an important underlying contributor to the incident under investigation, and a significant risk to information automation system performance, was perceived schedule pressure, which exposed weaknesses in interdepartmental coordination between and within responsible plant organizations and challenged the resilience of established plant processes, until a human caused the initiating event. These findings are discussed in terms of their risk to overall system performance and their implications for information automation system resilience and brittleness. We present two preliminary information automation models. The proactive issue resolution model is a test case of an information automation concept with significant near-term potential for application and subsequent reduction in significant plant events. The IAE model is a more general representation of a broader, plantwide information automation system. From our results, we have generated a set of preliminary system-level requirements and safety constraints. These requirements will be further developed over the remainder of our project in collaboration with nuclear industry subject matter experts and specialists in the technical systems under consideration. Additionally, we will continue to pursue the system analyses initiated in the first part of our effort, with a particular emphasis on STPA as the main tool to identify weak or weakening control structures that affect the resilience of organizations and programs. Our intent is to broaden the scope of the analysis from an individual use case to a related set of use cases (e.g., maintenance tasks, compliance tasks) with similar human-system performance challenges. This will enable more generalized findings to refine the Proactive Issue Resolution and IAE models, as well as their system-level requirements and safety constraints. We will use organizational system modeling analyses to supplement STPA findings and model development. We conclude the report with a set of summary recommendations and an initial draft list of system-level requirements and safety constraints for optimized information automation systems.

99 GENERAL AND MISCELLANEOUS↗

Transition Core Modeling for Extended Enrichment & Accident-Tolerant Fuels Using Polaris/PARCS

Commercial light water reactor (LWR) operators and fuel vendors are currently interested in increasing the low-enriched uranium (LEU) fuel enrichments from the current limit of 5.0 $^w/_o$ $^{235}U$ up to 10 $^ w/_o$ $^{235}U$ (referred to as "LEU+") in their current fleets; they are also interested in using accident-tolerant fuel (ATF) with both LEU and LEU+ fuel. This report aims to identify modeling challenges and accuracy concerns in transition core analysis using the SCALE Polaris lattice physics code and U.S. Nuclear Regulatory Commission core simulator PARCS. At the time this study was started, no publicly available LEU+ core designs existed for boiling water reactor (BWR) or pressurized water reactor (PWR) systems. Therefore, fuel lattices were shuffled within a multi-assembly model to mimic neutronically challenging lattice combinations seen in transition cores, such as a fresh LEU+ lattice next to depleted LEU lattices. In addition to multi-assembly models, whole-core BWR transition core calculations were performed for ATF and LEU+ fuel using an existing Hatch-1 Cycle 3 core model. A whole-core BWR model was chosen due to the more heterogeneous core designs compared to those for a PWR core. Since the original core is an old checkerboard core design and no core or fuel design optimization was performed for the modeled fuel types, these core calculations were intended only to provide: (1) Comparisons of core characteristics of interest, such as the pin power distributions and peaking factors, Doppler temperature coefficients (DTCs), and control blade worths (CBWs) under challenging core designs, (2) Identification of reactor physics challenges in modeling LEU+ and ATF cores, and (3) A stress test for the Polaris/PARCS two-step modeling approach, including characterization of the relative accuracy for predicting characteristics of interest such as pin power distributions.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Microstructural Simulation of Ion-Irradiated Natural Rocks and Minerals

This report details the contribution of Oak Ridge National Laboratory to the Nuclear Energy University Program (NEUP) project, "Rapid Characterization of Concrete Mineralogy using Multi-Scale Tools" led by the University of Illinois at Urbana-Champaign. To support the subsequent license renewal (SLR) of the US nuclear power plants (NPPs) fleet, the performance of concrete-forming aggregates against neutron irradiation needs to be assessed. Ion irradiation is proposed as a rapid, cost-effective surrogate method to full neutron irradiation testing. To complement the characterization of ion-irradiated rock specimens, ORNL has run finite-elements and fast-Fourier transform (FFT-based) simulations using the codes MARS and Microstructure-Oriented Scientific Analysis of Irradiated Concrete (MOSAIC). The main conclusion of this analysis is that the apparent post–ion-irradiation step-height underestimates the accumulated free radiation-induced volumetric expansion (RIVE) in the ion-implanted depth by about 15% at full amorphization and about 25% toward the beginning of the ion irradiation experiment. The discrepancy is explained by the fact that the step height is proportional to the sum of the RIVE (i.e., one third of the RIVE) and the irradiation-assisted plastic strains in the vertical direction (lower than two thirds of the RIVE). Because of the large lateral compressive stresses caused by the restraining effect of the unirradiated substrate, the stress field in the mineral grains and at the grain boundary (GB) in the ion-implanted layer is much different than the comparable stress field occurring during neutron irradiation. Hence, the mismatch RIVE causing cracks in the rock-forming minerals leads to different cracking patterns. Ion irradiation continues to be used as a rapid technique to assess the RIVE potential of rocks.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Packetized Energy Management: Coordinating Transmission and Distribution (Final Report)

The project Packetized Energy Management (PEM): Coordinating Transmission and Distribution was part of the ARPA-E NODES program from 2015 to 2023. The high-level goal of the project was to develop and demonstrate novel, scalable, and impactful technologies related to the coordination of networked distributed energy resources (DERs). By demonstrating responsive means by which fleets of DERs could be coordinated to enhance grid operation and reliability, the U.S. could accelerate renewable integration and electrification efforts and meet decarbonization goals.

25 ENERGY STORAGE↗

Explainable Artificial Intelligence Technology for Predictive Maintenance

The domestic nuclear power plant fleet has relied on labor-intensive and time-consuming preventive maintenance programs, thus driving up operation and maintenance costs to achieve high-capacity factors. Artificial intelligence and machine learning can help simplify complex problems, such as diagnosing equipment degradation, to enable more effective decision-making. Benefits will be felt not only within existing analog and digital instrumentation and control, but also work processes, the integration of people with technology, and most importantly, the business case. Together, these hold promise to make nuclear power more efficient and reduce costs associated with operation and maintenance. While the artificial intelligence and machine learning technologies hold significant promise in the nuclear industry, there are challenges or barriers to their adoption. This report outlines the those different machine learning adoption barriers (categorized as historical, technical, economic, regulatory, and user) that the industry must overcome to realize the full benefits of artificial intelligence and machine learning capabilities for long-term economic sustainability. This report also provides solutions for some of these barriers by focusing on improving the explainability of machine learning to encourage trust from the end-user. Trust and explainability are essential to machine learning adoption. This report focuses on research-developed solutions to some of these barriers while analyzing a non-safety-related system, namely the circulating water system. This system frequently experiences waterbox fouling which our models preemptively diagnoses then explains to the operator how those conclusions were reached. This report presents and discusses the inherent trade-off between machine learning performance (in terms of accuracy) and explainability, where highly accurate machine learning methods (such as deep-learning) are the least explainable, and the most explainable methods (such as decision trees) are the least accurate. In addition, explainability of artificial intelligence techniques in terms of transparency and post-hoc metrics are discussed. This report outlines the importance of data novelty and value of new information in evaluating both the explainability and trustworthiness. Novelty detection helps to establish consistency or inconsistency of the new data with respect to the training data. On the other hand, value of information could be a part of the user-centric visualization recommendation system that request additional information to be collected, thereby strengthening the machine learning outcomes. During this project, a copyrighted user-centric visualization that aligns with a human-in-the-loop approach was developed. The user-centric visualization presents different levels of information and can be tailored as per user credentials to gain user confidence. One of the salient features of the user-centric visualization is it presents machine learning methods with explainability metrics. A simplified version of the user-centric visualization was presented to 32 users with varying levels of machine learning expertise. Feedback was solicited to test the hypothesis that the app contained sufficient explainability and that the users would trust the algorithm. Overall, the app was positively received, and the hypothesis was supported. This report discusses the trust-but-verify framework – a potential approach to build user trust artificial intelligence. The framework discusses trust from the human level to artificial intelligence level. The fundamental premise of the trust but verify framework is derived from an observation of nuclear safety culture (i.e., nuclear power plant personnel do not rely on a singular source of data to make a decision). This also ties back to the user-centric visualization that presents different levels of information to achieve both explainability and trustworthiness of artificial intelligence. Even so, the adoption of artificial intelligence and machine learning in the nuclear industry faces additional barriers, namely regulatory and stakeholder readiness. To overcome these challenges, new solutions must gain regulatory approval and cater to stakeholder needs. The Nuclear Regulatory Committee has a 5-year strategic plan which prepares them for reviewing artificial intelligence technologies in licensee submissions. Early and frequent engagement with the regulator is encouraged. Additionally, artificial intelligence solutions should incorporate human-in-the-loop considerations and offer explainability. Stakeholders must prepare by hiring or training staff to adapt to advancing technology in everyday plant tasks.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

AOI 3 Life Modelling of Critical Steam Cycle Components in Coal-Fueled Power Plants

Microstructural damage accumulation models have been used to produce calibrated life estimation models for a DR22/P22 steel wye-block welds, and a Jethete stainless steel turbine blade (bucket). The calibrated life estimation models will aid the power plant operator in determining optimal maintenance and operation schedules based upon historical operational data as well as current, or future operation schemes. The impact of this project will enable existing coal-fueled power plants to operate safely for longer periods of time and at higher efficiencies, thereby reducing the economic and environmental impact of the existing coal power plant fleet. Testing, characterization, and modelling indicates that the operating life of P22 pipelines and their welds are dominated by fatigue damage mechanisms. Specifically, fatigue is of no concern in these materials when operating under realistic conditions manifesting in the main steam piping of coal-fueled power plants. However, if a low-temperature overload ever occurs during operation, fatigue will manifest as a damage mechanism of interest. Primary impact provided by the completion of this work is in the manifestation of a detailed ABAQUS solid model providing accurate boundary conditions to enable the prediction of operational stresses and strains. The completed plant solid model, in conjunction with the calibrated fatigue and creep life models provide definitive confirmation that creep is the dominant damage mechanism during operational conditions. Jethete life modelling has been completed by the manifestation of a material-specific, and temperature-specific, Kitagowa diagram. The Kitagowa diagram provides maintenance and operation decision making with scientifically-based go/no-go support based upon the crack-like features that have been identified by use of inspection.

01 COAL, LIGNITE, AND PEAT↗

Biodiesel Handling and Use Guide: Sixth Edition

This document serves as background and a guide for those who blend, distribute, and/or use biodiesel and biodiesel blends. It provides basic information on the proper and safe use of biodiesel in compression ignition engines, home heating oil systems, boilers, and other applications. This guide is intended to help users, fleets, blenders, distributors, and others understand handling and use of biodiesel and biodiesel blends. Information on the environmental benefits of biodiesel is also provided.

09 BIOMASS FUELS↗

U.S. Hydropower Market Report 2023

This is the fourth complete edition of the U.S. Hydropower Market Report (the previous editions, published in 2015, 2018, and 2021, are available here). In intervening years between publishing the full report, updated data are also summarized and released and can be found at the Oak Ridge National Laboratory HydroSource website. This report combines data from public and commercial sources and research findings from other U.S. Department of Energy (DOE) R&D projects to provide a comprehensive picture of developments in the U.S. hydropower and pumped storage hydropower (PSH) fleet and industry trends. Prior to the first Hydropower Market Report being published, there was a noted lack of publicly available and easily accessible information about hydropower in the United States and other important trends affecting this important sector of the energy industry. New and valuable types of information are constantly being developed as part of DOE research activities and, in a rapidly evolving energy industry, it is important that these data be made available in a predictable and consistent manner for use by all different types of stakeholders and decision-makers.

13 HYDRO ENERGY↗

Assessment of Core Physics Characteristics of Extended Enrichment and Higher Burnup LWR Fuels using the Polaris/PARCS Two-Step Approach (Vol. 2: BWR Fuel)

Nuclear fuel vendors and utilities are currently investigating changes to fuel contents and fuel designs for more economical and safer reactor operations. Extending cycle lengths beyond 18-month cycles for pressurized water reactors (PWRs) and 24-month cycles for boiling water reactors (BWRs) requires extending fuel enrichments beyond the current 5 wt % 235U limit. Therefore, low-enriched uranium plus (LEU+) fuel is expected to be used in current light-water reactor fleets in the near term. LEU+ is a subset of high-assay low-enriched uranium (HALEU) and is a term to describe fuel enrichments above 5% up to 10%. A series of studies were conducted at Oak Ridge National Laboratory (ORNL) to compare low-enriched uranium (LEU) with LEU+ fuel with respect to isotopic fuel content, lattice parameters, and core physics to identify any challenges in operation, storage, and transportation.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗