Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “fleet operations”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 487 records · Page 27

Human-Centered and Explainable Artificial Intelligence in Nuclear Operations

Nuclear power plants in the United States are critical to the nation’s energy security, accounting for 20% of all electricity produced for the power grid. As energy needs grow, 100 gigawatts of additional nuclear power will be necessary by 2050, more than double the current capacity. Realizing this target requires cutting-edge technology like artificial intelligence (AI) and machine learning (ML) that can bring about significant increases in the level of automation. Human-centered AI (HCAI) is a combination of human-centered design (human factors, human-in-the-loop, etc.) with AI/ML to help produce an efficient and reliable system with full consideration for human engagement. This paper provides a comprehensive and novel discussion of HCAI considerations in nuclear power, introducing unique applications for the existing fleet as well as new advanced reactor designs. We include real-life use cases of AI applications to work management processes at nuclear power sites and highlight lessons learned for HCAI.

Hall, Anna↗

Innovative Advanced Hydrogen Mobile Fueler (Final Technical Report)

The US Department of Energy (DOE) funded a project to design, develop, deploy and analyze the economic viability of an innovative Advanced Hydrogen Mobile Fueler (AHMF). As part of the design activity the project team defined specifications based upon vehicle requirements and compliance with specific fueling performance criteria. The AHMF was originally designed to fuel 10-20 fuel cell vehicles (FCV) per day, consistent with the requirements of the H70 fueling category. The AHMF is able to operate without remote power connections, is modular for easy transport and deployment, and can provide expanded daily capacity and multi-day operations using delivered gaseous hydrogen. Toward the end of the project, due to request from the hydrogen industry and some necessary modifications of the AHMF, the system is now modified to fuel heavy duty vehicles. The project was conducted over two primary phases, each including several key tasks, subtasks, and project milestones. Phase 1 involved the design, development, and construction of the AHMF, moving from a conceptual design through to completion of assembly and testing. In addition to reviewing several different approaches, the team chose to take a conventional station design and modify it for mobile fueling. There were several innovative components included in the design. The high pressure storage was the first to achieve a US Department of Energy (DOE) Special Permit (SP 20391) to transport high pressure hydrogen (95 MPa) in a composite cylinder. The second novel system was a liquid nitrogen (LIN) cooling system with a compact heat exchanger. Without this change, the cooling system would not be able to fit into the AHMF. Phase 2 demonstrated the AHMF by fueling fuel cell buses at a fleet in Pomona, CA. The site was chosen because a temporary fueling solution was required while a fixed station was being installed. The existing permits for the fixed station and non-public access also was a determining factor. Over two months, the buses were fueled 320 times with over 5000 kg of hydrogen from tube trailers. Existing shore power was used, and the average electrical efficiency was 0.13 kWh/kg. The average liquid nitrogen (LIN) consumption was 90.68 scf/kg. The fueling and consumption data was provided to the National Renewable Energy Laboratory (NREL) for analysis. An economic analysis was performed and will be provided in a separate report. The project was successful, but not without challenges and lessons learned. The DOT special permit led the way for the use of high pressure, composite cylinders and is being by multiple other systems and applications. The pandemic along with time for the DOT special permit approval delayed the project for years. The team also believes that hydrogen mobile fueling has a use for the industry, especially during this upcoming phase of expansion. However, it does have its limitations due to high cost to build and operate, and the same permitting challenges as a fixed station. A fully capable system at the speeds and pressures of the AHMF may not be necessary for most applications and would help reduce the cost and increase storage capacity. The on-board generator can be easily replaced with shore power or the wide range of power generation solutions in the marketplace. One of the major results of the project was the development of new code language in National Fire Protection Agency (NFPA) 2 and the International Fire Code (IFC) for on-demand mobile fueling. This will provide guidance for Authorities Having Jurisdiction (AHJ) and user on how to permit temporary fueling sites across the nation.

08 HYDROGEN↗

Utility and Industry Perceptions of Control Room Modernization Over the Last 10 Years

Within the current United States (U.S.) nuclear power fleet, main control room modernization (CRM) is an important step towards cost savings. In recent decades, plants have been engaged in upgrades to varying degrees. This process requires a nuanced, balanced, and timely approach that ensures continued safety and long-term sustainability. In 2012 a survey was issued to individuals from the nuclear industry to learn their perspectives on a range of CRM issues. The survey targeted the benefits and challenges for utilities undertaking this process, including the main drivers and barriers to technology upgrades, regulatory compliance, and the effects these factors have on concepts of operations, strategic approaches, and staffing. In 2022, the survey was issued again to understand whether CRM perceptions had changed in the last 10 years. Our findings identify changes in industry thinking from a decade ago. Here we reveal perspective shifts that represent increased optimism and, in some instances, increased doubt regarding the opportunities and challenges inherent in CRM and implementation. We also report nuanced differences in CRM perspectives between utility and surrounding nuclear industry respondents.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Phase 1: Duke Energy Zero Emission Resource Integration Study (ZERIS); Phase 2: Carbon-Free Resource Integration Study for Duke Energy (Final Report)

Phase 1: This statement of work makes up Phase 1 of a larger effort. During this Phase 1 effort, NREL will work with Duke Energy to analyze the impacts of integrating significant amounts of new solar power into the Duke Energy power system under a variety of different penetrations scenarios, with a maximum of ten (10) full scenarios examined. The existing fleet, particularly the nuclear generation, will be considered in the quantitative assessments and discussions. Duke Energy is looking to quantify how much solar generation its system can handle. NREL will work with Duke Energy to quantify solar potential, identify likely integration challenges and possible opportunities for wind, storage, demand side resources and other technologies. Phase 2: This Statement of Work consists of a follow-up effort (Phase 2) to a recently completed Phase 1 modeling effort. During Phase 2, NREL will work closely with Duke Energy to analyze the impacts of integrating significant amounts of variable generation resources (wind and solar) and storage into Duke Energy's system in the Carolinas. The existing fleet, particularly nuclear generation, will be considered in the quantitative assessment and discussions. This Statement of Work also includes an extension to Phase II of the Carbon-Free Resource Integration Study for Duke Energy. In this extension, NREL will work closely with Duke Energy to extend the production cost analysis developed in Phase II to 2018 weather and load data for Duke Energy's territory. This extension leverages the modeling tools and datasets developed as part of Phase II. The analysis will compare results from Phase II (using 2012 weather and load) with 2018 results to assess system operations with increased penetration of renewables and storage. Simplifying assumptions will be made for modeling Duke Energy's neighbors in the production cost model.

14 SOLAR ENERGY↗

Launch Alaska Transportation and Energy Accelerator (LATEA)

The Launch Alaska Transportation and Energy Accelerator (LATEA), funded through the U.S. Department of Energy Office of Technology Commercialization’s Energy Program for Innovation Clusters (EPIC),advanced deployment of innovative and efficient transportation and energy technology in Alaska from October 2021 through June 2025. The project was designed to leverage Launch Alaska’s accelerator model to identify, recruit, and support transportation technology companies with novel solutions to market needs while building the stakeholder networks, demonstration opportunities, and institutional capacity necessary to accelerate commercialization in one of the most challenging operating environments in the United States.

08 HYDROGEN↗

Severe Accident Phenomena: A Comparison Among the NuScale SMR, Other Advanced LWR Designs, and Operating LWRs

During a severe accident in a nuclear reactor, there are a number of phenomenological events which can present a challenge to containment integrity. These include the generation and combustion of hydrogen, energetic fuel-coolant interactions, thermal attack of fission product barriers, core-concrete interactions, direct containment heating, and gradual overpressurization. The advanced design of the NuScale small modular reactor has resulted in the reduced likelihood and severity of severe accident challenges to containment. This paper discusses the features of the NuScale design that reduce the likelihood of occurrence of these severe accident phenomena, and discusses the ability of containment to survive in the unlikely event that they do occur. Here, the impact of severe accident phenomena for the NuScale design is compared and contrasted against other advanced light water reactors, such as AP1000 and ESBWR, as well as the existing fleet, using information from publicly available documents.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Dynamic Probabilistic Risk Assessment Based Response Surface Approach for FLEX and Accident Tolerant Fuels for Medium Break LOCA Spectrum

After the Fukushima Daiichi Accident, the safety features such as accident tolerant fuel (ATF) and diverse and flexible coping strategies (FLEX) for existing nuclear fleets are being investigated by the US Department of Energy under the Light Water Reactor Sustainability Program. This research is being conducted to quantify the risk-benefit of these safety features. Dynamic probabilistic risk assessment (DPRA)-based response-surface approach has been presented to quantify the FLEX and ATF benefits by estimating the risk associated with each option. ATFs with multilayered silicon carbide (SiC), iron-chromium-aluminum, and chromium-coated zirconium cladding were considered in this study. While these ATF candidates perform better than the current zirconium cladding (Zr), they may introduce additional failure modes in some operating conditions. The fuel failure analysis modules (FAMs) were developed to investigate ATF performance. The dynamic risk assessments were performed using RAVEN, a DPRA tool, coupled with RELAP5 and FAMs. A cumulative distribution function-based index provided a mean of comparing the benefits of safety enhancements. For medium break loss of coolant accidents, FLEX operational timing window for each fuel type was estimated. Among these ATF candidates, SiC-type ATF was the most beneficial candidate for an increased safety margin than Zr-based fuel and was found to complement FLEX strategies in terms of risk and coping time.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Energy and Emission Prediction for Mixed-Vehicle Transit Fleets Using Multi-task and Inductive Transfer Learning

Public transit agencies are focused on making their fixed-line bus systems more energy efficient by introducing electric (EV) and hybrid (HV) vehicles to their fleets. However, because of the high upfront cost of these vehicles, most agencies are tasked with managing a mixed-fleet of internal combustion vehicles (ICEVs), EVs, and HVs. In managing mixed-fleets, agencies require accurate predictions of energy use for optimizing the assignment of vehicles to transit routes, scheduling charging, and ensuring that emission standards are met. The current state-of-the-art is to develop separate neural network models to predict energy consumption for each vehicle class. Although different vehicle classes’ energy consumption depends on a varied set of covariates, we hypothesize that there are broader generalizable patterns that govern energy consumption and emissions. In this paper, we seek to extract these patterns to aid learning to address two problems faced by transit agencies. First, in the case of a transit agency which operates many ICEVs, HVs, and EVs, we use multi-task learning (MTL) to improve accuracy of forecasting energy consumption. Second, in the case where there is a significant variation in vehicles in each category, we use inductive transfer learning (ITL) to improve predictive accuracy for vehicle class models with insufficient data. As this work is to be deployed by our partner agency, we also provide an online pipeline for joining the various sensor streams for fixed-line transit energy prediction. Here, we find that our approach outperforms vehicle-specific baselines in both the MTL and ITL settings.

97 MATHEMATICS AND COMPUTING↗

Climate Vulnerability Assessment and Resilience Planning for Idaho National Laboratory

Idaho National Laboratory’s (INL’s) mission is to discover, demonstrate, and secure innovative nuclear energy solutions, other clean energy options, and critical infrastructure. This INL’s Climate Vulnerability Assessment and Resilience Plan (VARP) was developed to enable and sustain that mission while ensuring the viability of operations considering expected climate change impacts. The VARP was developed according to the narrative requirements from the “Vulnerability Assessment and Resilience Planning Guidance, Version 1.2” document issued in February 2022. A prescribed process was used to identify mission-critical systems and components, determine historical and expected climate impacts, and develop resilient solutions. Experts from across INL, including operations staff, researchers, and climate scientists supplied input to the process. Analyses of climate modeling sources revealed that under scenarios of higher and lower greenhouse gas emissions (Representative Concentration Pathway (RCP) 4.5 and RCP 8.5), INL anticipates an increase in climate hazards, including drought, heat waves, wildfire, and precipitation. Increased frequency and duration of climatic hazards forecasts high impacts on certain mission-critical asset and infrastructure types. Utilizing the VARP Risk Assessment Tool, projected high climate hazard impacts across multiple asset and infrastructure types at the INL include energy generation and distribution systems, Site buildings, specialized or mission-critical equipment, and transportation and fleet infrastructure. Some of these mission-critical asset and infrastructure types maintain high adaptive capacity to climatic changes; however, others may need additional adaptive capacity to withstand increased frequency and duration of climate hazards. INL identified close to 300 resilient solutions that were consolidated into 11 solution categories to be tracked in the Department of Energy Sustainability Dashboard. The identified solutions are a starting point for future project development and analysis. These data are intended to inform decision makers on climate issues and potential solutions across INL and associated communities. The VARP is not intended to be a budget tool or project decision document on its own, but rather one of many tools used by decision makers to establish resilient priorities. This initial document provides the framework and foundation to resilient solutions. In the coming years, each solution needs to be fully developed, costed, and prioritized based on mission-critical risk and funding priorities.

54 ENVIRONMENTAL SCIENCES↗

Hourly Load Profile Dataset for Electric Transit Bus Depots in the United States

Transit buses operate primarily in dense urban areas, where nearby populations face increased exposure to fine particulates, nitrogen oxides, and other harmful pollutants. Electrifying transit buses presents a clear opportunity to reduce greenhouse gas emissions and improve urban air quality. However, widespread adoption may pose significant energy and infrastructure challenges, which can be mitigated through proactive planning and investment. This report presents a robust modeling framework and an initial estimation of the hourly electricity demand at transit bus depots across the United States. The resulting depot-level dataset, available at data.nrel.gov/submissions/282, provides valuable insights for infrastructure planning and electricity demand forecasting, supporting the scalable electrification of transit bus fleets nationwide.

33 ADVANCED PROPULSION SYSTEMS↗

Wind Turbine Maintenance Costs: Assessing the Potential of Gear Oil Improvements

Wind turbine operations & maintenance (O&M) costs constitute a sizable portion of total energy cost for wind power. There are many components in a utility-scale wind turbine that need to be lubricated with either oil or grease. This study uses gearbox oil as an example and assesses how lubricant technology improvements may impact wind turbine power production and levelized cost of energy. Using the modeling tools (i.e., WOMBAT, reV, and SAM) developed at National Renewable Energy Laboratory and lubrication oil technology scenarios defined based on inputs provided by ExxonMobil and industry stakeholders, we quantify the potential for increasing energy production and reducing maintenance costs across the current and future U.S. fleet of wind turbines as a result of improvements in lubrication technologies. The modeled improvements reduce the median levelized cost of energy by 1-2% across the U.S. fleet. Cumulative saving from gear oil technology improvements in 2050 for U.S. fleet is estimated to be approximately $6 billion. Extending the lubricant replacement interval has a larger impact on total cost and energy production than reducing lubricant cost.

costs↗

Leak detection in a subcritical boiler

Thermal power plants experience cycling duty leading to the fatigue of the boiler and heat exchanger tubes. As a result, tube failures occur frequently in coal fired fleets leading to forced outages. Furthermore, because the tube leaks have been the major source of unwanted shutdowns and the number of outages is increasing, present work focuses on the detection and isolation of the leak in a subcritical boiler based upon the process data from a commercial coalfired power plant. The mass balance equation around the steam drum was analyzed using timeseries data collected from a 300 MW power plant. The ratio of the feed water mass flow rate to the steam mass flow rate was defined as a key parameter for detecting leaks. The difference in slope between the feedwater and steam mass flow rate during the normal and faulty operations was established as the upper control limit for real time monitoring. To reduce false alarm rates that arise when raw signal is directly compared against the threshold due to common process fluctuations, an optimal filter was derived for smoothing. It was found that the optimal filter reacted much more quickly to process changes than an exponential moving average filter, around 8 h earlier on average. Occurrence of relatively high false alarm rates even in the filtered responses was related to the cycling of the boiler from the base load condition. Variable threshold was established to keep false alarm rates to the minimum while maintaining the leak detection rate. Finally, the leak was located at the economizer and this could readily be isolated by investigating the magnitude of the mass flow rates ratio and the temperature at the economizer outlet.

42 ENGINEERING↗

Supercritical Carbon Dioxide Primary Power Large-Scale Pilot Plant

The United States electrical power generation fleet encompasses a wide range of technologies, ranging from traditional combustion-based power generation, to nuclear power, to renewable energy. While the distribution of these assets continues to shift due to economic and regulatory influences, coal combustion continues to be a key part of the US energy portfolio. Despite the relative maturity of coal combustion technology, improvements in overall fuel-to-power efficiency and generation flexibility are still possible and will improve both the economic and environmental factors of coal combustion. Echogen Power Systems proposes to lead a world-class team including the University of Missouri, Electric Power Research Institute and Louis Perry Associates in the design, construction and operation of a 10MWe coal-fired supercritical carbon dioxide (sCO 2 ) large-scale pilot. This transformational technology uses sCO 2 as a working fluid instead of water to achieve high thermodynamic efficiencies that can significantly exceed advanced steam-Rankine cycles. Further, the compact nature of sCO 2 turbomachinery offers capital cost and footprint advantages, and the low maintenance of a water-free power cycle can significantly reduce operation and maintenance (O&M) costs over conventional steam-Rankine systems. Recent integration studies of sCO 2 with coal combustion power plants highlight the significant improvements in plant efficiency that sCO 2 can offer relative to even advanced steam Rankine cycles. At commercial scales, coal-sCO 2 plant net efficiency is predicted to be 39-44.0% (HHV), or 10-20% higher output than conventional steam-Rankine systems, which will significantly improve the competitiveness of coal-fired generation. This proposal builds upon projects previously funded by the Department of Energy, including DE-FE0025959 (High-Efficiency Thermal Integration of Closed Supercritical CO 2 Brayton Power Cycles with Oxy-Fired Heaters) and DE-NE0008470 (Conceptual Design for sCO 2 Power Cycle Test Facility). An appropriately-scaled and properly designed and operated pilot project is essential to overcome the natural risk-aversion of the power generation industry and project financing community. The 10 MWe coal-fired sCO 2 pilot power plant proposed herein will reduce the technical and economic risk of this transformational technology, enabling commercial deployment at the conclusion of the project. For the second phase of this project, Echogen lead a team that completed and refined the pilot system conceptual system and key component designs resulting in the completion of a front-end-engineering-design (FEED) study, completed the NEPA review process, completed the permitting process for construction and operation, refined the techno-economic analysis of the proposed system at commercial scale and received commitments for Phase III cost share. The end result of the program will be to demonstrate the technical and economic superiority of the sCO 2 power cycle for coal-fired operation. Major risk elements will have been retired with sufficient operation at high power to enable the power generation industry to move forward with the first commercial deployment of this transformational system.

01 COAL, LIGNITE, AND PEAT↗

Safe Operations at Roadway Junctions: Intelligent Roadway Infrastructure as Functional Interlocking

Automated vehicle (AV) technology is quickly maturing, and the corresponding infrastructure systems that evaluate traffic and communicate to vehicles requires sophisticated sensing and perception technologies, referred to as intelligent roadway infrastructure (IRI), to complement emerging AV capabilities. IRI provides signals to vehicles, indicating right-of-way for vehicles and communicating to approaching AVs that no other vehicle is failing to yield. This capability, denoted as safety-affirmative signaling, provides a green light or a green arrow as appropriate and affirms through communication links to connected vehicles when it is safe to proceed. About 36% of collisions occur at intersections, with most occurring upon left turns (22.2%) or crossing over (12.6%), and only a small percentage (1.2%) while turning right at an intersection. Of all intersection crashes about half (52.5%) of those vehicles were traveling through a signalized intersection 2. Safety-affirmative signaling would guarantee safety of AV fleet vehicles, by providing the interlocking principle, a term from automated train control that only allows progression through a railway intersection after affirming no opportunity for a crash exists. IRI through safety-affirmative signaling would bring performance and safety to complex roadway intersections where AV transit fleet service is most needed, as well as safety benefits to traditional, non-automated vehicles and vulnerable road users. The implementation of IRI has functional, programmatic, and technical challenges. Research work performed at the National Renewable Energy Laboratory (NREL) in an integrative approach encapsulating these themes, and termed infrastructure perception and control (IPC) is motivated by improved performance (travel time), improved safety (reduced collisions), and improved energy efficiency (less fuel burned and minimized production of greenhouse gases). IPC is intended not only for roadway and intersection applications but also in extension to inform complementary buildings and grid systems to enable better co-management, as vehicles and their charging needs become increasingly integrated into the built environment. The NREL IPC project presents an open-source framework, architecture, and supporting technology to implement IRI, addressing critical issues such as fusion of data, reliability, standardization of data interfaces, and confidence of detection. The framework is informed by previous experience in U.S. Department of Defense research technology, specifically in the use of radar to detect, identify, and track aerial threats. These principles combined with multi-sensor fusion provides for a complete digital twin with known and measurable confidence and accuracy from which safety-affirmative signaling can be developed and deployed.

ADVANCED PROPULSION SYSTEMS,MATHEMATICS AND COMPUT↗

PreMevE‐MEO: Predicting Ultra‐Relativistic Electrons Using Observations From GPS Satellites

Abstract Ultra‐relativistic electrons with energies greater than or equal to two megaelectron‐volt (MeV) pose a major radiation threat to spaceborne electronics, and thus specifying those highly energetic electrons has a significant meaning to space weather communities. Here we report the latest progress in developing our predictive model for MeV electrons in the outer radiation belt. The new version, primarily driven by electron measurements made along medium‐Earth‐orbits (MEO), is called PREdictive MEV Electron (PreMevE)‐MEO model that nowcasts ultra‐relativistic electron flux distributions across the whole outer belt. Model inputs include >2 MeV electron fluxes observed in MEOs by a fleet of GPS satellites as well as electrons measured by one Los Alamos satellite in the geosynchronous orbit. We developed an innovative Sparse Multi‐Inputs Latent Ensemble NETwork (SmileNet) which combines convolutional neural networks with transformers, and we used long‐term in situ electron data from NASA's Van Allen Probes mission to train, validate, optimize, and test the model. It is shown that PreMevE‐MEO can provide hourly nowcasts with high model performance efficiency and high correlation with observations. This prototype PreMevE‐MEO model demonstrates the feasibility of making high‐fidelity predictions driven by observations from longstanding space infrastructure in MEO, thus has great potential of growing into an invaluable space weather operational warning tool.

79 ASTRONOMY AND ASTROPHYSICS↗

Autonomie Simulation Datasets in Support of U.S. DOT-NHTSA Advanced Vehicle Technology Research

Understanding how new vehicle technologies affect fuel economy and energy use is critical to the regulatory work performed by the U.S. Department of Transportation’s National Highway Traffic Safety Administration (NHTSA), which sets Corporate Average Fuel Economy (CAFE) standards under the Energy Policy and Conservation Act of 1975. In order to support this work, Argonne National Laboratory uses Autonomie, a full-vehicle simulation tool, to evaluate advanced powertrain architectures and their effects on vehicle energy consumption and performance. A wide range of vehicle classes has been assessed (i.e., internal combustion engine vehicles, hybrid electric vehicles, plug-in hybrid electric vehicles, battery-electric vehicles, and fuel cell electric vehicles), as well as the effects of various technology improvements such as lightweighting, aerodynamic refinements, and low-rolling-resistance tires. Simulations have been run across multiple drive cycles to capture fuel and electricity use under realistic operating conditions. The resulting datasets include detailed vehicle-level results, model assumptions, and validation reports, all of which have been made publicly available through NHTSA in support of the 2023 notice of proposed rulemaking covering light-duty vehicles for model years 2027 to 2035. These data are critical to stakeholders working in fuel economy regulation, vehicle technology assessment, and energy policy analysis.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Advanced Ultra-Supercritical Component Test (ComTest) Project for 760*C Steam Conditions

ComTest is a $27M Department of Energy-funded project. Phase I, which began in November 2015, served to identify the technology gaps, as well as the scope and cost of required testing. Phase II, which was awarded in December 2018, includes an advanced manufacturing effort to complete U.S. based supply chain development for full commercial scale (800-850 MWe) AUSC components made of nickel-based alloys, components operating at up to 760°C. Completion of Phase II scheduled for September 30, 2021. Strategic Objectives of U.S. AUSC Project include: Power Plant Efficiency Improvements –Develop cost-effective, reliable technologies to improve the efficiency of new and existing high-temperature advanced generation power plants. Close gaps to achieve readiness for commercial scale demonstration of Advanced Ultra-Supercritical (AUSC) technology. Fabricate full-scale versions of key nickel-based alloy components. Validate capabilities of US supply chain for cost certainty. Support cross-cutting high-temperature generation technologies. Obtain ASME Code approval for new materials, components and processes. Increase power plant steam temperatures for higher cycle efficiency (Note: Average efficiency of US coal-fired fleet = 33% HHV; A-USC plant efficiency over 47% HHV at 1,400°F (760°C) steam temperature).

fireside corrosion↗

Charpy Impact Characterization of Surveillance Specimens Harvested from Palisades High Fluence A-60 Capsule

Located on the shores of Lake Michigan, the Palisades Nuclear Generating Station (PNGS) was a nuclear power plant that operated in Covert Township, Michigan. The plant had a single pressurized water reactor that produced electricity for the region. The PNGS was shut down in 2022 after more than four decades of service. The PNGS included in its surveillance program a surveillance capsule, designated A-60, containing specimens of a weld metal with nickel content of about 1.36 wt% and copper content of about 0.25 wt%. The capsule was removed from its surveillance position in early 1995 and has been resident in the spent fuel pool since that time. This capsule was irradiated to a fluence of 1.96×10 20 n/cm 2 (E>1MeV) that is equivalent for more than 150 effective full power years (EFPYs) for the US reactor pressure vessel (RPV) fleet. The material is also of special interest because of its very high nickel content and potential for development of NiMnSi (nickel-manganese-silicon) precipitates. Combination of very high fluence and very high Ni and Cu content makes the material in this capsule of great interest as benchmark for currently developing embrittlement trend curves (ETC) aiming to predict embrittlement at high fluences. Multi-year efforts by the Light Water Reactor Sustainability (LWRS) Program personnel from the Materials Research Pathway (MRP) to harvest this capsule finally succeeded in 2023. As a result, the Westinghouse Electric Company (WEC) through contract with Oak Ridge National Laboratory (ORNL) came to PNGS site, retrieved the A-60 capsule, brought it to WEC Churchill hot cell facility, opened the capsule and sent all surveillance specimens in the capsule to ORNL for future characterization by July 2023. Total of 9 tensile and 48 Charpy specimens were inventoried in the ORNL hot cells. Testing plan has been developed based on available specimens. It includes hardness, tensile, Charpy impact, Mini-CT fracture toughness testing, in-situ thermal annealing, and microstructural characterization, including Atom Probe Tomography (APT). Charpy impact testing has been completed and results are presented in this report. Moreover, negotiations with Pressurized Water Reactors Owners Group (PWROG) and Westinghouse resulted in Westinghouse donating to ORNL a piece of archive weld and base metal such that unirradiated characterization of these materials can be performed as part of this project. Comparison of measured hardening and embrittlement has been performed and data are compared to available large database.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗