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279 records · Page 16

Plasma Ignition and Combustion Stabilization Technology to Improve Flexible Operation, Reliability and Economics of an Existing Coal-Fired Boiler

GE Steam Power, Inc. (GE) proposed to improve reliability, flexibility, and economics of an existing coal-fired power plant by applying a new advanced technology developed by GE, a plasma-assisted pulverized fuel firing system. The objective of this program is to demonstrate the achievement of lower load by improved flame stabilization and therefore lower operating costs in a full-scale field installation at coal-fired electric utility. GE’s Plasma Ignition and Combustion Stabilization System is designed to operate continuously to support low load operation. With the plasma on, the flame will be attached and stable, removing the firing system as a limitation to low load operation. In addition, GE’s exclusively from ABENZ company licensed AC based technology has a 90+% system efficiency compared to all other systems at which are DC and operate with ~75% efficiency. Plant operating costs are lowered by eliminating use of expensive support fuel as well as the ability to operate at lower loads. The utilities’ ability to better match the demand curve will result in significant savings. Maintenance is lower for an AC system than a DC system as it operates at lower current. This eliminates the need for a demineralized cooling water system and provides longer electrode life which translates into both material and labor savings. It is the objective of GE to not only demonstrate the additional low load achievable with a plasma system after best achievable tuning, sensor and software approach has been exhausted, but also the increased stability of the flame at all loads with plasma assistance as well as cost savings at all low loads using plasma instead of oil. Upon successful completion of this project, GE will have sufficient field experience to rapidly deploy the Plasma Technology. The project objectives were achieved through the implementation of plasma ignitor technology at PacifiCorp Hunter Station Unit 3. A plasma ignitor system was retrofitted on ten wall-fired burners, Mill 3-4 combustion system. The Plasma Ignitors installed at Hunter proved that this GE technology is a direct and complete replacement for the original oil ignitors. The Hunter Unit 3 burner management system allows the plasma system to be used in all applications that originally required oil to be burned. This includes any time the Mill 3-4 is started or stopped for any reason including boiler starts, load changes, and low load support.

01 COAL, LIGNITE, AND PEAT↗

Acoustic-based monitoring and machine learning of component status for microreactor applications

This report provides a description and assessment of recent efforts to couple acoustic-based experimental measurements and characterization with machine learning models in order to enhance structural health monitoring capabilities for nuclear microreactors. With resilient embedded sensors in development by others supported by programs funded by the US Department of Energy’s Office of Nuclear Energy, the work described herein builds upon ongoing efforts to improve non-destructive testing technology that relates measured acoustic signatures to component stresses and/or structural defects, using a combination of new experimental measurements and machine learning architectures. The experimental procedure remained similar to that developed for the previous year’s demonstration of damage detection by the authors, with the same damaged sample tested under similar applied stress conditions. Notably, a new mounting fixture was designed and implemented to improve measurement consistency and a more sophisticated laser Doppler vibrometer was employed to make high-fidelity vibration measurements. Two nominally identical sets of training data were collected for each experimental setup to better understand the repeatability of the experiment and to better test the generality of trained neural network models. Additionally, we obtained new high-quality 3D mode shapes of the damaged test article at various stress and excitation levels, providing greater insights into the physical response of the sample during testing. Previously, we demonstrated that a machine learning model based on a convolutional neural network can predict structural details of an artificially introduced interface (intact, rough cut, smooth cut), and the applied torque level. In this study, we have transitioned to graph-based neural network architectures to better develop and test a flexible framework that is more suitable to being transferred away from controlled benchtop experiments and into more applied settings where less-structured data inputs may be expected. In general, performance testing of a graph neural network on frequency-domain representations of the data indicates strong and consistent identification of test conditions for datasets recorded on damaged components. With goals of predicting damage location and other changing experimental conditions using limited datasets, predictive models using a graph neural network architecture correctly predicted the applied torque level with an accuracy of 85% using only a single measurement point and predicted within one torque level in 95% of test windows. Predictions of damage location had limited success due to the symmetry and minimal number of the damage scenarios presented during model training. Results were ambiguous as to whether the model could detect the location of the artificial damage, or if it was instead learning the location of a given measurement point on the part and subsequently detecting which points were closest to the location of the damage. This finding will be factored into upcoming planned work on damaged graphite components, where new experimental tests with a larger number and variety of damage scenarios are expected to provide improved validation of recent developments in monitoring methodology.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Two-Stage Wildlife Event Classification for Edge Deployment

Camera-based wildlife monitoring is often overwhelmed by non-target triggers and slowed by manual review or cloud-dependent inference, which can prevent timely intervention for high stakes human–wildlife conflicts. Our key contribution is a deployable, fully offline edge vision sensor that achieves near-real-time, highly accurate wildlife event classification by combining detector-based empty-image suppression with a lightweight classifier trained with a staged transfer-learning curriculum. Specifically, Stage 1 uses a pretrained You Only Look Once (YOLO)-family detector for permissive animal localization and empty-trigger suppression, and Stage 2 uses a lightweight EfficientNet-based binary classifier to confirm puma on detector crops and gate downstream actions. Our design is robust to low-quality nighttime monochrome imagery (motion blur, low contrast, illumination artifacts, and partial-body captures) and operates using commercially available components in connectivity-limited settings. In field deployments running since May 2025, end-to-end latency from camera trigger to action command is approximately 4 s. Ablation studies using a dataset of labeled wildlife images (pumas, not pumas) show that the two-stage approach substantially reduces false alarms in identifying pumas relative to a full-image classifier while maintaining high recall. On the held-out test set (N = 1434 events), the proposed two-stage cascade achieves precision 0.983, recall 0.975, F1 0.979, accuracy 0.986, and balanced accuracy 0.983, with only 8 false positives and 12 false negatives. The system can be easily adapted for other species, as demonstrated by rapid retraining of the second stage to classify ringtails. Downstream responses (e.g., notifications and optional audio/light outputs) provide flexible actuation capabilities that can be configured to support intervention.

58 GEOSCIENCES↗

Even Higher-Level Synthesis: An Exploration of AI Hardware Accelerators using HLS4ML

With the rise of artificial intelligence, the popularization of deep learning, and a constantly evolving industry, the demand for flexible and efficient tools has never been greater. As algorithms grow more complex, their runtime and energy consumption increase exponentially. Customized hardware accelerators, long used for specific mathematical operations, remain essential for managing modern applications' computational and power demands. Hardware accelerators can speed up complex computations by orders of magnitude, but their manual design and verification processes are often challenging and time-consuming. High-Level Synthesis (HLS) provides a solution by transforming high-level algorithm descriptions, typically written in C++ or SystemC, into synthesizable RTL suitable for hardware implementation. This approach reduces development time for RTL engineers while offering flexibility beyond what traditional handwritten RTL can provide. We extended this capability to the machine-learning domain with the open-source framework hls4ml, which allows neural networks trained in Python frameworks like Tensorflow or PyTorch to be synthesized into efficient hardware representations for the traditional FPGA and ASIC flows. This breakthrough addresses the growing need for reduced design turnaround and easy verification of ML hardware accelerators with low latency and power efficiency constraints. During this tutorial, we will demonstrate how Python complements HLS by simplifying the ML design process, bridging the gap between software and hardware development. Attendees will explore how we translate neural networks modeled in Python into fixed-point C++ models suitable for HLS workflows. We will dive into strategies like Value-Range Analysis and Quantization-Aware Training, which optimize these designs for deployment and evaluate their accuracy, power consumption, and energy efficiency. To exemplify these concepts, experts from Fermilab will share their experiences applying this technology to high-energy physics experiments, where real-time, low-latency processing is critical. Over the years, Fermilab engineers have demonstrated how deep neural networks, optimized for hardware using hls4ml, can meet the stringent requirements of trigger systems at the CERN Large Hadron Collider. These systems rely on rapid decision-making to process immense data volumes while retaining only the most relevant events for further analysis. The application of hls4ml has also been extended to innovative technologies like smart pixel arrays. These smart pixels integrate ML inference capabilities directly into sensor devices, enabling localized data processing at the pixel level. This approach drastically reduces the need to transmit raw data to external processing units, significantly decreasing power consumption and latency. By embedding neural networks within the pixel architecture, the smart pixels can identify and prioritize relevant data in real time, providing a highly efficient solution for edge computing in scenarios such as particle detectors and imaging systems. Fermilab's work highlights the potential of hardware-accelerated ML in scenarios where both speed and power efficiency are mission-critical. Through this tutorial, attendees will gain valuable insights into the challenges and solutions of deploying ML in hardware. Understanding how HLS and hls4ml streamline the development of neural network-based hardware accelerators is fundamental for the industry's future. Participants will learn how these technologies are shaping the future of AI and scientific computing.

Di Guglielmo, Giuseppe [Fermilab]↗

Measurement placement in electric power transmission and distribution grids: Review of concepts, methods, and research needs

Sensing and measurement systems are quintessential to the safe and reliable operation of electric power grids. Their strategic placement is of ultimate importance because it is not economically viable to install measurement systems on every node and branch of a power grid, though they need to be monitored. An overwhelming number of strategies have been developed to meet oftentimes multiple conflicting objectives. The prime challenge in formulating the problem lies in developing a heuristic or an optimisation model that, though mathematically tractable and constrained in cost, leads to trustworthy technical solutions. Further, large-scale, long-term deployments pose additional challenges because the boundary conditions change as technologies evolve. For instance, the advent of new technologies in sensing and measurement, as well as in communications and networking, might impact the cost and performance of available solutions and shift initially set conditions. Also, the placement strategies developed for transmission grids might not be suitable for distribution grids, and vice versa, because of unique characteristics; therefore, the strategies need to be flexible, to a certain extent, because no two power grids are alike. Despite the extensive literature on the present topic, the focus of published works tends to be on a specific subject, such as the optimal placement of measurements to ensure observability in transmission grids. There is a dearth of work providing a comprehensive picture for developing optimal placement strategies. Because of the ongoing efforts on the modernisation of electric power grids, there is a need to consolidate the status quo while exposing its limitations to inform policymakers, industry stakeholders, and researchers on the research-and-development needs to push the boundaries for innovation. Accordingly, this paper first reviews the state-of-the-art considering both transmission and distribution grids. Then, it consolidates the key factors to be considered in the problem formulation. Finally, it provides a set of perspectives on the measurement placement problem, and it concludes with future research directions.

24 POWER TRANSMISSION AND DISTRIBUTION↗

A Cybersecurity Threat Profile for a Connected Lighting System

In anticipation of improved energy performance and cost savings, cities and building owners are increasingly considering “smart lighting initiatives” that aim to convert their collection of simple luminaires (i.e., lighting fixtures) into an intelligent connected lighting system (CLS) capable of remotely monitoring energy consumption and fault conditions, and possibly implementing adaptive lighting schemes. The U.S. Department of Energy (DOE) has set an national goal of tripling the energy efficiency and demand flexibility of the buildings sector by 2030, relative to 2020 levels 1. It is forecast that connected lighting systems can contribute to that goal by delivering 125 TWh of annual energy savings by 2035 2, equivalent to the annual output of 50 typical (500 MW) power plants. However, these energy savings and the DOE goal are put at significant risk if connected technologies are not adopted due to real or perceived cybersecurity concerns. Connected IoT devices such as these have historically been rife with vulnerabilities which sometimes put security considerations secondary to functionality and operability. What are the cybersecurity threats that will impact these systems, as formerly banal luminaires transition into intelligent connected devices that collect information about themselves, their surrounding environment, and possibly us? In this paper we analyze a threat profile performed on a fault-detection use case for streetlights. A threat profile establishes security requirements, justifies security measures, yields actionable controls, and effectively communicates risk to stakeholders. This effort provides critical information for making threat-based decisions to increase security at a reasonable cost, and can effectively be used by development teams, software architects, and managers to make cybersecurity a part of their ongoing culture of awareness, training, and prevention. This leads to more secure systems and better-understood security. On-premise, cloud, and hybrid architectures with different authentication mechanisms were modeled and later categorized using the Microsoft STRIDE framework. An analysis of the recommended controls for each threat was performed to determine which controls could and should be put in place by manufacturers or third-party suppliers, and which controls need to be left up the end-user to implement. Fifty-seven threats were identified. Among our key findings: (1) 65% (37/57) of the threats did not involve the luminaires, but rather the other components needed to communicate with and manage them; (2) 63% (36/57) of the threats could have been mitigated through manufacturer-implemented defensive techniques or “controls”; and (3) 23% (13/57) of the threats were dependent on the network configuration. Recommendations based on the results of this work are made to key stakeholder groups. Notably, lighting technology developers are advised to address all threats that can be reasonably controlled with baked-in technology solutions (e.g., encryption or authentication controls), and employ some form of secure supply chain management and tracking where other parts (e.g., sensors, microprocessors) of a luminaire must also be built and manufactured with the proper security controls in place. Developers should also review threats involving assets not developed in-house to understand how connectivity with other devices will affect their product during system operation and determine if a compensating control for a defense-in-depth strategy will be needed. Finally, those interested in deploying CLS should compare the differences between cloud and on-premise models to determine which is more suitable for their needs and the abilities of their security team.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Subtask 1.5 – CO2 Injection Monitoring with an Optimized Scalable, Automated, Semipermanent Seismic Array

The scalable, automated, semipermanent seismic array (SASSA) method is a flexible and relatively cost-effective surface geophysical method for regular time-lapse monitoring of the movement of injected carbon dioxide (CO2) in a reservoir for CO2 enhanced oil recovery (EOR) or geologic CO2 storage operations. It has the advantages of a low-environmental-footprint while monitoring regions of a reservoir from the surface without the need for a regular grid distribution of receivers. Automated data collection is possible. As only time-lapse amplitude changes at the reservoir level due to CO2 movement within the reservoir are monitored, the turnaround time to deliver results from the SASSA method can be short, without the need for long, time-consuming data-processing workflows. As data is collected and processed, incremental information can be provided to the field operator. The Energy & Environmental Research Center (EERC) conducted a SASSA field test from September 2018 to November 2020 in a portion of the Bell Creek Field in Montana, which implemented new CO2 EOR field activities during the study period. Lessons learned from a proof-of-concept study were incorporated to improve the data quality of the SASSA method and demonstrate the viability of the technology. The EERC implemented several enhancements to improve data quality, including 1) an iterative survey design, which allowed placing the receivers in strategic locations where the movement of the CO2 in the reservoir could be tracked with minimum interference by the cultural noise in the study area; 2) the use of powerful seismic sources in the form of surface orbital vibrators, and 3) data acquisition during optimal periods. History-matched reservoir simulation was performed to predict gas saturation and pressure response induced by CO2 injection in the study area. The results were compared with the SASSA-measured responses to CO2 injection as a partial validation technique. A match between the two methods was observed for most of the SASSA points predicted to have intersected a CO2 saturation change. The validated results provide confidence that the SASSA method can be used independently as a CO2 saturation monitoring technique. As data are collected and processed, incremental information can be provided to the field operator. The critical components of the SASSA workflow for a successful application of the method are the following: Iterative survey design with information about CO2 injection activities from the oilfield operator. A detailed CO2 injection plan is the key driver to select the strategic monitoring location of the SASSA sensors. After this information is incorporated in the initial distribution of sources and receivers in the study area, high-resolution satellite images are used to identify ground locations not affected by cultural noise sources, such as power lines, pipelines/flow lines, or roadways. In the next iteration of the survey design, a scouting trip to the study area is needed to understand more details of the noise sources identified in the previous step and the intensity of the field activities that can also generate noise during the monitoring. Integrating the information from the scouting trip into the survey design to select the optimum source and receiver locations is the final step. Noise attenuation. The variety of noise types during seismic monitoring of an oil field is enormous. Tailored noise characterization and processing at a node-by-node level can enhance the performance and sensitivity of the SASSA technique. Future advancements that could improve the efficiency and application of the SASSA technology include: Gaining a better understanding of the noise field produced by the seismic source to aid the choice of receiver location. Surface noise from the source can overwhelm the small signal changes due to CO2 that the SASSA method measures. Improved data-processing workflow to automatically analyze and adapt to dynamic noise conditions associated with industrial settings. This subtask was funded through the EERC–DOE Joint Program on Research and Development for Fossil Energy-Related Resources Cooperative Agreement No. DE- FE0024233.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Westinghouse Accident Tolerant Fuel Phase 2B with Higher Enriched and Higher Burnup Add-On Project Final Technical Report Deliverable Volume 1

The Westinghouse Electric Company LLC (Westinghouse) accident tolerant fuel (ATF) program funded by Westinghouse and the US Department of Energy (DOE) utilized chromium (Cr) coated zirconium alloy cladding with doped UO 2 (ADOPT(TM)) and uranium silicide (U 3 Si 2 ) high density/high thermal conductivity fuel for its lead test rod (LTR) program with irradiation beginning in 2019. ADOPT is a Cr 2 O 3 +Al 2 O 3 doped UO 2 pellet with increased oxidation resistance and density, and increased resistance to fission gas release. Due to the issues with U 3 Si 2 fuel reaction in pressurized water reactor (PWR) environments, uranium nitride (U 15 N) has been substituted for U 3 Si 2 as a long-term fuel option. Cr coated cladding with ADOPT fuel is the near-term Westinghouse EnCore fuel product. The long-term EnCore ® fuel product is SiGA ® SiC/SiC composite cladding with high density/high thermal conductivity UN fuel. In 2020, the higher burnup and higher enriched and (HBHE) program was integrated into the ATF program. The objective of this expanded program is to extend ATF burnups to at least 75 MWd/kgU to economically facilitate 24-month cycles in PWRs. The ATF program now includes ADOPT fuel with enrichments >5% 235 U. Over the past several years, Westinghouse has tested the Cr coated zirconium (Zr) and silicon carbide (SiC) claddings in Westinghouse Churchill autoclaves and the Massachusetts Institute of Technology (MIT) reactor. Additionally, the Cr coated cladding has been tested in the Advanced Test Reactor (ATR) at Idaho National Laboratory (INL) and in LTR programs at the Doel 4 and Bryon 2 commercial reactors. High temperature tests at the state-of-the-art Westinghouse facilities in Churchill, PA and at Karlsruhe Institute of Technology (KIT) have been carried out to determine the time and temperature limits for the Cr coated zirconium claddings. These tests indicate that Cr coated Zr cladding can take temperatures up to about 1500°C for short periods of time without becoming totally oxidized. The main issue is the formation of the Cr-Zr eutectic at 1333°C resulting in the migration of this eutectic inward with the formation of ZrCr 2 which rapidly oxidizes to ZrO 2 on the outside of the tube. The Cr coated Zr cladding also delays the bursting of the tube, reduces the burst area, and reduces hydriding and embrittlement of the Zr which is a major benefit for reducing fuel fragmentation, redistribution, and dispersal (FFRD), the major licensing issue faced by HBHE. The manufacturing parameters for the SiC have been found to have a significant effect on the corrosion rate of the SiC in light water reactor (LWR) conditions and significant improvements have been made in the yield, quality, and oxidation resistance of the SiC cladding by identifying and tightening manufacturing process parameters. Current autoclave results for SiC composite claddings indicate that a corrosion rate of fewer than 2 micrometers per year can be achieved which meets corrosion requirements under normal operating conditions. High temperature steam oxidation tests at the state-of-the-art Westinghouse facilities in Churchill, PA and at Karlsruhe Institute of Technology (KIT) have been carried and determined that SiC cladding can withstand temperatures up to about 1800°C to 1900°C before excessive corrosion reactions begin, and that the SiC will not balloon and burst. ADOPT fuel pellets were incorporated into the Westinghouse ATF program because of their increased density and oxidation resistance. A topical report supporting the use of ADOPT pellets has been submitted to the NRC and will be approved shortly. ADOPT pellets have been a product in Europe for over 15 years. The additives work to make larger grain sizes which appear to reduce fission gas release during transients as well as increase the density of the pellet. Fuel rod and assembly design in preparation for the lead test rod (LTR) and lead test assembly (LTA) programs is underway as well as licensing efforts with the Nuclear Regulatory Commission (NRC). Finally, accident analyses coupled with economic evaluations for both operating savings as well as fuel savings have been initiated. Modular Accident Analysis Program 5 (MAAP5) calculations indicate that both Cr coated cladding and SiC composite cladding can increase the time to fuel rod loss of geometry for up to two hours longer than current Zr based cladding in a station blackout scenario. This additional time is due to the much higher oxidation resistance of the SiC and Cr coated cladding. These two hours can be used to implement additional response options instituted through the Diverse and Flexible Mitigation Capability (FLEX) program by reactor operators. Both ATF cladding options also reduce hydrogen production which dramatically reduces primary system and containment pressure and the risk of fission product release beyond containment in the unlikely event of an accident. The lower pressure in the system allows more time to feed cooling water to the core, resulting in the avoidance of fuel melting. The coping time is extended indefinitely if the modest water flow provided by FLEX continues. Experimental work on methods to rapidly fabricate SiC composite structures with high density and reduce the fabrication price of SiC fibers while maintaining a high level of performance is needed. Methods for mitigating or stopping the Cr-Zr eutectic are also needed to further improve the oxidation resistance of Cr coated Zr. Minimal (<1%) swelling of U 3 Si 2 and subsequent fission gas release has been demonstrated up to 20 MWd/kgU. Irradiation experiments with U 3 Si 2 fuel in ATR to determine these properties at 40 MWd/kgU were completed but post irradiation examinations were not done since U 3 Si 2 has been replaced by UN. UN has three issues that are being addressed. The first is increasing the oxidation resistance so that there is not excessive reaction up to ~1500°C. While UN increases the pellet density and additives to the UN postponed the temperature at which rapid oxidation occurred by ~100°C to 200°C, this is not enough, and pellet coating options are now being pursued. The second is developing a method to manufacture that does not require the multi-step process of UF 6 to UO 2 to UC to UN. Efforts are underway looking at UF 6 to UN 2 to UN and UF 6 to UF 4 to UN 2 to UN reactions. Finally, an economically acceptable process for potentially enriching the 15 N content of the nitrogen used to make UN to >95% 15N was identified though not experimentally validated. In addition to the work supported by the DOE, research and testing activities are being carried on in a world-wide effort funded by many countries such as Sweden, United Kingdom, Belgium, Netherlands, Spain, Germany, Japan, and France. This work is being facilitated through the Westinghouse led Collaboration for Advanced Research on Accident Tolerant Fuel (CARAT) program. Annual meetings were organized in 2018 and 2019 by Westinghouse as a venue for presentation of this work and to provide for the cross-fertilization of ideas among the many outstanding researchers in the ATF area. No meetings were held in 2020 and 2021 due to the COVID-19 related restrictions on traveling and gatherings. Since SiC, coated cladding, and high-density fuel options are not currently used in the nuclear industry; support from the government and industry members is needed to further the significant effort of setting new standards. The same is true for the Nuclear Regulatory Commission (NRC) which must review and approve the commercial use of these new fuels since all current regulations are oriented toward Zr/UO 2 fuel. Several meetings have been held with the NRC to generate a fast-track approach to licensing ATF using a combination of atomic modeling, in-rod sensors, and in-reactor testing. This approach was memorialized in an “Accelerated Fuel Qualification White Paper” prepared by the Accelerated Fuel Qualification Working Group lead by General Atomics.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Westinghouse Accident Tolerant Fuel Phase 2B with Higher Enriched and Higher Burnup Add-On Project Final Technical Report Deliverable Volume 2

The Westinghouse Electric Company LLC (Westinghouse) accident tolerant fuel (ATF) program funded by Westinghouse and the US Department of Energy (DOE) utilized chromium (Cr) coated zirconium alloy cladding with doped UO 2 (ADOPT(TM)) and uranium silicide (U 3 Si 2 ) high density/high thermal conductivity fuel for its lead test rod (LTR) program with irradiation beginning in 2019. ADOPT is a Cr 2 O 3 +Al 2 O 3 doped UO 2 pellet with increased oxidation resistance and density, and increased resistance to fission gas release. Due to the issues with U 3 Si 2 fuel reaction in pressurized water reactor (PWR) environments, uranium nitride (U 15 N) has been substituted for U 3 Si 2 as a long-term fuel option. Cr coated cladding with ADOPT fuel is the near-term Westinghouse EnCore ® fuel product. The long-term EnCore fuel product is SiGA ® SiC/SiC composite cladding with high density/high thermal conductivity UN fuel. In 2020, the higher burnup and higher enriched and (HBHE) program was integrated into the ATF program. The objective of this expanded program is to extend ATF burnups to at least 75 MWd/kgU to economically facilitate 24-month cycles in PWRs. The ATF program now includes ADOPT fuel with enrichments >5% 235 U. Over the past several years, Westinghouse has tested the Cr coated zirconium (Zr) and silicon carbide (SiC) claddings in Westinghouse Churchill autoclaves and the Massachusetts Institute of Technology (MIT) reactor. Additionally, the Cr coated cladding has been tested in the Advanced Test Reactor (ATR) at Idaho National Laboratory (INL) and in LTR programs at the Doel 4 and Bryon 2 commercial reactors. High temperature tests at the state-of-the-art Westinghouse facilities in Churchill, PA and at Karlsruhe Institute of Technology (KIT) have been carried out to determine the time and temperature limits for the Cr coated zirconium claddings. These tests indicate that Cr coated Zr cladding can take temperatures up to about 1500°C for short periods of time without becoming totally oxidized. The main issue is the formation of the Cr-Zr eutectic at 1333°C resulting in the migration of this eutectic inward with the formation of ZrCr 2 which rapidly oxidizes to ZrO 2 on the outside of the tube. The Cr coated Zr cladding also delays the bursting of the tube, reduces the burst area, and reduces hydriding and embrittlement of the Zr which is a major benefit for reducing fuel fragmentation, redistribution, and dispersal (FFRD), the major licensing issue faced by HBHE. The manufacturing parameters for the SiC have been found to have a significant effect on the corrosion rate of the SiC in light water reactor (LWR) conditions and significant improvements have been made in the yield, quality, and oxidation resistance of the SiC cladding by identifying and tightening manufacturing process parameters. Current autoclave results for SiC composite claddings indicate that a corrosion rate of fewer than 2 micrometers per year can be achieved which meets corrosion requirements under normal operating conditions. High temperature steam oxidation tests at the state-of-the-art Westinghouse facilities in Churchill, PA and at Karlsruhe Institute of Technology (KIT) have been carried and determined that SiC cladding can withstand temperatures up to about 1800°C to 1900°C before excessive corrosion reactions begin, and that the SiC will not balloon and burst. ADOPT fuel pellets were incorporated into the Westinghouse ATF program because of their increased density and oxidation resistance. A topical report supporting the use of ADOPT pellets has been submitted to the NRC and will be approved shortly. ADOPT pellets have been a product in Europe for over 15 years. The additives work to make larger grain sizes which appear to reduce fission gas release during transients as well as increase the density of the pellet. Fuel rod and assembly design in preparation for the lead test rod (LTR) and lead test assembly (LTA) programs is underway as well as licensing efforts with the Nuclear Regulatory Commission (NRC). Finally, accident analyses coupled with economic evaluations for both operating savings as well as fuel savings have been initiated. Modular Accident Analysis Program 5 (MAAP5) calculations indicate that both Cr coated cladding and SiC composite cladding can increase the time to fuel rod loss of geometry for up to two hours longer than current Zr based cladding in a station blackout scenario. This additional time is due to the much higher oxidation resistance of the SiC and Cr coated cladding. These two hours can be used to implement additional response options instituted through the Diverse and Flexible Mitigation Capability (FLEX) program by reactor operators. Both ATF cladding options also reduce hydrogen production which dramatically reduces primary system and containment pressure and the risk of fission product release beyond containment in the unlikely event of an accident. The lower pressure in the system allows more time to feed cooling water to the core, resulting in the avoidance of fuel melting. The coping time is extended indefinitely if the modest water flow provided by FLEX continues. Experimental work on methods to rapidly fabricate SiC composite structures with high density and reduce the fabrication price of SiC fibers while maintaining a high level of performance is needed. Methods for mitigating or stopping the Cr-Zr eutectic are also needed to further improve the oxidation resistance of Cr coated Zr. Minimal (<1%) swelling of U 3 Si 2 and subsequent fission gas release has been demonstrated up to 20 MWd/kgU. Irradiation experiments with U 3 Si 2 fuel in ATR to determine these properties at 40 MWd/kgU were completed but post irradiation examinations were not done since U 3 Si 2 has been replaced by UN. UN has three issues that are being addressed. The first is increasing the oxidation resistance so that there is not excessive reaction up to ~1500°C. While UN increases the pellet density and additives to the UN postponed the temperature at which rapid oxidation occurred by ~100°C to 200°C, this is not enough, and pellet coating options are now being pursued. The second is developing a method to manufacture that does not require the multi-step process of UF 6 to UO 2 to UC to UN. Efforts are underway looking at UF 6 to UN 2 to UN and UF 6 to UF 4 to UN 2 to UN reactions. Finally, an economically acceptable process for potentially enriching the 15 N content of the nitrogen used to make UN to >95% 15 N was identified though not experimentally validated. In addition to the work supported by the DOE, research and testing activities are being carried on in a world-wide effort funded by many countries such as Sweden, United Kingdom, Belgium, Netherlands, Spain, Germany, Japan, and France. This work is being facilitated through the Westinghouse led Collaboration for Advanced Research on Accident Tolerant Fuel (CARAT) program. Annual meetings were organized in 2018 and 2019 by Westinghouse as a venue for presentation of this work and to provide for the cross-fertilization of ideas among the many outstanding researchers in the ATF area. No meetings were held in 2020 and 2021 due to the COVID-19 related restrictions on traveling and gatherings. Since SiC, coated cladding, and high-density fuel options are not currently used in the nuclear industry; support from the government and industry members is needed to further the significant effort of setting new standards. The same is true for the Nuclear Regulatory Commission (NRC) which must review and approve the commercial use of these new fuels since all current regulations are oriented toward Zr/UO 2 fuel. Several meetings have been held with the NRC to generate a fast-track approach to licensing ATF using a combination of atomic modeling, in-rod sensors, and in-reactor testing. This approach was memorialized in an “Accelerated Fuel Qualification White Paper” prepared by the Accelerated Fuel Qualification Working Group lead by General Atomics.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗