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At least 415 records · Page 23

SAM Two-Phase Flow Model Development and Applications for Operational Transients in Advanced Reactors

As advanced nuclear technologies continue to develop, the need for the flexible operation and generation of these advanced reactors becomes necessary to maximize economic potential. As large-scale experiments are not always feasible, modeling and simulations of advanced reactors play a crucial role in design optimization and analysis. The SAM (System Analysis Module) code developed at Argonne National Laboratory is a state-of-the-art system-level thermal-hydraulic code aimed at simulating advanced reactor systems. Recent code developments have implemented two-phase flow modeling using the homogeneous equilibrium model, and a new steam generator component has been developed to utilize the two-phase flow implementation. In addition to verification tests, a load-following simulation was performed to model a realistic load-following transient in a proposed integrated system consisting of a conceptual advanced reactor known as the Advanced Burner Test Reactor (ABTR) and thermal energy storage (TES) tanks. The integrated system model uses two large TES tanks designed for sodium and a model helical coil steam generator to simulate the operational load-following transient. The flow rates of the feedwater and secondary loops are regulated to meet a prescribed steam generator load consistent with the electricity demand over a 24-h period. In conclusion, the results found the ABTR system was able to maintain stable reactor conditions and primary- and secondary-side characteristics over the course of the load-following transient.

Advanced Burner Test Reactor (ABTR)↗

Real-time plasma monitoring framework for advanced plasma control and ML-research in DIII-D

Real-time and adaptive plasma control is crucial for robust tokamak operation, requiring sensitivity and tolerance measurements of the plasma state. This paper presents the implementation of an integrated real-time plasma monitoring framework on the DIII-D tokamak to support advanced control approaches, including machine-learning (ML) methods. The system is built on the SHIELD framework, a high-performance modular architecture that provides a unified pipeline for integrating diverse diagnostics. The framework leverages high-bandwidth digitizers, fast numerical processing, and deterministic, low-latency interconnects to stream high-fidelity data from diagnostics such as electron cyclotron emission (ECE), beam emission spectroscopy (BES), CO interferometers, and a visible tangential divertor camera (TangTV). The system’s validity is demonstrated through direct comparisons of real-time and offline data. Furthermore, we present two key applications of the developed plasma monitoring system with ML-based plasma control strategies, including real-time divertor detachment and active Alfvén Eigenmode control. As a result, this work presents a robust and scalable approach for integrating high-frequency, multidimensional diagnostics into advanced control algorithms for future fusion devices.

AI/ML↗

(U) A Code System for Cross-Section Uncertainty Propagation for PARTISN

A rudimentary code system has been developed for propagating neutron cross-section uncertainties to response uncertainties using the PARTISN multigroup discrete-ordinates neutron transport code. The code system uses the first-order sandwich rule with sensitivities computed using SENSMG and covariances computed using NJOY. Databases of reaction cross sections and covariances using ENDF/B-VIII.0 data in the LANL standard 30-group structure have been precalculated. The final uncertainty in a k eff example problem compares well with the result from TOFFEE, a similar code that propagates neutron cross-section uncertainties to response uncertainties using the MCNP6 Monte Carlo neutron transport code. Presently, neither code system propagates uncertainties in $\overline{v}$, $\overline{μ}$, or χ, and neither code system propagates nuclide-nuclide covariances

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Development and performance of high-temperature superconducting CORC ® cables with CFD REBCO tapes

Abstract Increasing the normal zone propagation velocity (NZPV) in superconducting cables based on rare earth barium copper oxide (REBCO) tapes is expected to cause a paradigm shift by enabling the development of faster and more reliable quench detection systems to mitigate the development of destructive hot spots. Furthermore, a higher NZPV is beneficial in terms of fault current limitation capabilities by accelerating the homogenization of the quench in superconducting power devices. One way envisioned to increase the NZPV of cables based on REBCO tapes is the current flow diverter (CFD) concept. A Conductor on Round Core (CORC ® ) cable made with CFD REBCO tapes, called CFD CORC ® cable, and a CORC ® cable made with regular REBCO tapes, were fabricated and tested. The critical current of the CFD and regular CORC ® cables were obtained at temperatures ranging from 67 to 77 K in self-field. Measurements showed that the NZPV was increased by a factor of 4–4.5 in the case of the CFD CORC ® cable. Furthermore, the results suggest that the NZPV depends only on the applied current, similar to what has been observed previously on single REBCO tapes. These results demonstrate the successful integration of CFD REBCO tapes in CORC ® cables, without compromising their superconducting properties or their enhanced NZPV. The possibility of enhancing the NZPV of REBCO-based cables could facilitate quench detection, which remains an important issue in HTS magnet applications. This advancement also holds promise for the fault current limitation functionality of CORC ® cables.

Ben Saâd, Haïfa (ORCID:0000000216205364)↗

Towards Sustainable Post-Exascale Leadership Computing

As computing systems approach the limits of traditional silicon technology, the diminishing returns in performance per watt present a significant barrier to sustaining growth in HPC. From a large-scale scientific supercomputing facility point of view, we propose a multifaceted strategy toward specialized hardware and architectures that are optimized for energy efficiency in specific applications. We also emphasize the need for integrating energy-aware practices across all levels of HPC, from system design and software development to operational policies. We discuss strategic opportunities such as the adoption of application-specific accelerators, the development of energy-efficient algorithms, and the implementation of data-driven operational analytics. Our goal is to develop a comprehensive roadmap ensuring that future leadership systems at OLCF can meet scientific demands while operating within stringent energy budgets, thereby supporting sustainable computing growth.

Shin, Woong↗

FPGA-Based Spill Regulation System for the Muon Delivery Ring at Fermilab

The Muon to Electron Experiment (Mu2e) requires a uniform beam profile from the Muon Delivery Ring to meet their experimental needs. A specialized Spill Regulation System (SRS) has been developed to help achieve consistent spill uniformity. The system is based on a custom-designed carrier board featuring an Arria 10 SoC, capable of executing real-time feedback control. The FPGA processes beam pulses of approximately 200 ns every 1.695 $μ$s, allowing for continuous monitoring of the extracted spill intensity through fast bunch integration. The system directly controls three quadrupole magnets, which work in conjunction with sextupole magnets to achieve third-order resonant extraction. Furthermore, the board interfaces with Fermilab's Accelerator Control Network (ACNET), enabling operators to modify spill regulation settings in real-time via the control network while providing diagnostic waveforms. These waveforms help operators monitor the process and fine-tune the feedback mechanisms. This paper presents an overview of the board's architecture and its initial progress toward regulating beam extraction. This initial version of the regulation system aims to evaluate baseline performance to inform future system improvements.

Berlioz, J. R. [Fermilab]↗

Systems Engineering and Analysis in Support of a US Federal Staging Facility for UNF

The US Department of Energy Office of Nuclear Energy (DOE-NE) Office of Spent Fuel and High-Level Waste Disposition is examining a set of system options and conducting supporting analyses to inform the development of an integrated waste management system, which may include one or more federal staging facilities (FSFs) for used nuclear fuel (UNF ) sited using a collaborative siting process. This paper focuses on the ongoing activities in two systems engineering and analysis work areas: (1) data and tools development, validation, and maintenance and (2) systems engineering execution. Within the first work area, the STANDARDS 5.0 UNF data and analysis tool, formerly known as UNF-ST&DARDS, is being developed as a foundational resource to assist in the management of UNF data. It has the key capability to model UNF throughout the entire back end of the fuel cycle. STANDARDS also includes several compatible analysis tools for the time-dependent characterization of UNF and related systems by interfacing with the SCALE code system for nuclear analysis and COBRA-SFS for thermal analysis. Also, within the data and tools area is the Next Generation System Analysis Model (NGSAM), which is an agent-based simulation software tool expressly designed to be capable of modeling the waste management system, including the transportation of UNF to and from a FSF. NGSAM has been developed to enable informed decision-making by providing the capability to analyze various potential system options for the management of UNF and high-level radioactive waste. Finally, in the systems engineering execution area, the team has begun to apply a disciplined systems engineering approach at the system level along with supporting analysis to guide the development of the FSF project requirements (including associated transportation infrastructure). Systems engineering principles and practices and their adaptation/application to design and development activities will ensure that the waste management system is effectively implemented as work proceeds. Other activities include investigating the implications of changes in various assumptions and parameters related to waste management systems, such as UNF acceptance rates, receipt logic, facility capacities and capabilities, use of standardized canisters, and different assumed facility operation start dates. Keywords: federal staging facility (FSF), used nuclear fuel (UNF), integrated waste management (IWM) system, Next Generation System Analysis Model (NGSAM), STANDARDS, systems engineering

Joseph, Robert↗

The Systems of Radiological Protection for Ionizing and Non-Ionizing Radiation

This paper summarizes the presentations and panel discussion held at Plenary Session 1 of the 16th IRPA International Congress/69th Health Physics Society Annual Meeting, in Orlando, FL, in July 2024. Plenary Session 1 discussed the basics of the systems of radiological protection (RP) for ionizing radiation (IR) and non-ionizing radiation (NIR) and included five presentations and a panel discussion. Rodney Croft, Chair of the International Commission on Non-Ionizing Radiation Protection (ICNIRP), delivered the first presentation. Croft introduced the System of RP for NIR and provided an overview of ICNIRP’s coverage and current areas of work. Werner Rühm, Chair of the International Commission on Radiological Protection (ICRP), delivered the second presentation. He gave an overview of the System of RP for IR and covered the key principles of justification, optimization, and dose limitation, including the current plans of ICRP toward the envisaged revision of the System of RP. The third speaker, Sigurður Magnús Magnússon, from the International Radiation Protection Association (IRPA), provided the perspective of the RP professionals on the development of the Systems of RP for IR and NIR. Emilie van Deventer, from the World Health Organization (WHO), presented WHO’s views of both Systems of RP and discussed the relevant current activities of WHO with regard to IR and NIR. Kathryn Higley, President of the National Council on Radiation Protection and Measurements (NCRP), delivered the final presentation. Higley outlined the history of NCRP, the differences between ICRP and NCRP, and discussed the role of the NCRP in the System of RP, including NCRP’s role to analyze mechanisms of interaction of NIR with biological systems, including humans. The session concluded with a fruitful panel discussion, where the audience had the opportunity to ask the five invited speakers questions.

61 RADIATION PROTECTION AND DOSIMETRY↗

AutoCSM

A template system-of-systems modeling approach for automating the development, deployment, and integration of cooling system models (CSMs) for supercomputing facilities within the ExaDigiT framework. AutoCSM is a Python-based framework to assist in CSM developers in accelerating the creation and deployment of system-level thermal-hydraulic CSMs. The intention is for this tool specifically to help standardize digital twin workflows for ExaDigiT. However, this tool can be used independent of ExaDigiT (and even other systems besides CSMs).

Greenwood, MichaelScott [Oak Ridge National Labora↗

Laser Powder Directed Energy Deposition of Steels for Nuclear Applications

This comprehensive investigation examines the structure–property relationships in two nuclear alloy systems—Alloy 709 (A709) austenitic stainless steel and Grade 92 (G-92) ferritic/martensitic (F/M) steel—manufactured via directed energy deposition (DED) for sodium-cooled fast reactor applications. This study establishes the fundamental mechanisms for controlling microstructures for optimizing the mechanical performance of additively manufactured nuclear materials through systematic heat treatment optimization and multiscale characterization. As-deposited A709 steel develops a complex multiscale strengthening architecture consisting of a fine cellular solidification structure with diameter of 2-3 µm within10–50 µm grains, elevated dislocation densities from rapid thermal cycling, and grain boundary precipitates that activate concurrent Hall–Petch, dislocation, and precipitation hardening mechanisms to achieve exceptional properties [yield strength (YS): 603 MPa, ultimate tensile strength (UTS): 844 MPa, Vickers hardness: 220 HV] that achieve a 44% superior strength compared to that of the wrought material. Heat treatments produce different results. Solution annealing (SA) dissolves the cellular structure and reduces the hardness to 190 HV. Precipitation treatment (PT) keeps the cellular structure but adds carbides, allowing the hardness to reach 205 HV. The best approach combines both treatments (SA+PT) and creates uniform precipitate distributions with M 23 C 6 carbides at the grain boundaries and MX carbonitrides in the matrix, achieving a hardness of 195 HV. However, directional differences persist, with a 12%–15% strength variation between orientations due to the inherited layered microstructural architecture that survives aggressive heat treatment. While tensile testing at 550°C demonstrates 40%–50% thermal softening with dynamic strain aging, DED A709 steel still maintains a 71% higher YS than that of the wrought material. Ion irradiation studies (100–400 dpa) of DED A709 steel reveal progressive radiation damage with increasing void density and radiation-induced segregation causing nickel enrichment and chromium depletion, which will ultimately compromise mechanical properties. As-deposited G-92 exhibits exceptional strength (UTS: 1650–1700 MPa, 430 HV) through a complex microstructure containing both ferrite and martensite phases, a high geometrically necessary dislocation (GND) density (17.04×10 14 /m 2 ), and fine carbides. Heat treatments create distinct changes. Normalizing produces fresh martensite with the highest hardness (460 HV) and an increased GND density (20.23×10 14 /m 2 ). Tempering develops dual precipitation systems and reduces the hardness to 290 HV. The optimal approach uses sequential normalizing plus tempering, achieving balanced properties with the lowest hardness (250 HV) and a reduced GND density (11.01×10 14 /m 2 ). A processing-dependent anisotropy is observed: horizontal specimens achieve superior ductile behavior, while vertical specimens exhibit brittle failure. A tempering heat treatment successfully mitigates this anisotropic behavior by transforming the hard martensitic as-deposited structure into tempered martensite enabling both horizontal and vertical specimens to exhibit similar stress–strain characteristics with visible necking behavior. Remarkably, testing at 550°C reveals a reversal in the anisotropy, where as-deposited specimens achieve near isotropy with superior thermal stability (a 15%–20% strength reduction), while tempered specimens develop an orientation dependence with a 25%–30% strength reduction. Both alloy systems demonstrate that DED processing creates specimens with a superior strength through refined microstructural features, though with distinct strengthening mechanisms—austenitic through cellular structures and precipitates versus F/M through phase transformations and precipitates. Heat treatment optimization requires alloy-specific approaches, with A709 benefiting from controlled precipitation while G-92 requires careful phase transformation control. The results show that DED manufacturing can produce nuclear materials with exceptional performance, but directional effects and temperature-dependent behavior must be carefully considered for reactor component design and qualification.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Synthesis of Correct Digital Controller Models from Specifications by Model Transformation (21-0320)

The design of high consequence controllers (in weapons systems, autonomy, etc.) that do what they are supposed to do is a significant challenge. Testing simply does not come close to meeting the requirements for assurance. Today circuit designers at Sandia (and elsewhere) typically capture the core behavior of their components using state models in tools such as STATEFLOW. They then check that their models meet certain requirements (e.g. “The system bus must not deadlock” or “both traffic lights at an intersection must not be green at the same time”) using tools called model checkers. If the model checker returns “yes” then the property is guaranteed to be satisfied by the model. However, there are several drawbacks to this industry practice: (1) there is a lot of detail to get right, this is particularly challenging when there are multiple components requiring complex coordination (2) any errors returned by the model checker have to be traced back through the design and fixed, necessitating rework, (3) there are severe scalability problems with this approach, particularly when dealing with concurrency. All this places high demands on the designers who now face not only an accelerated schedule but also controllers of increasing complexity. This report describes a new and fundamentally different approach to the construction of safety-critical digital controllers. Instead of directly constructing a complete model and then trying to verify it, the designer can start with an initial abstract (think “sketch”) model plus the requirements, from which a correct concrete model is automatically synthesized. There is no need for post-hoc verification of required functional properties. Having tool to carry this out will significantly impact the nation’s ability to ensure the safety of high-consequence digital systems. The approach has been implemented in a prototype tool, along with a suite of examples, including ones that reflect actual problems faced by designers. Our approach operates on a variant of Statecharts developed at Sandia called Qspecs. Statecharts are a widely used formalism for developing concurrent reactive systems, supporting scalability through allowing state models containing composite states, which are the serial or parallel composition of substates which can themselves contain statecharts. Statecharts enable an incremental style of development, in which states are progressively refined to incorporate greater detail in an incremental model of software development. Our approach formulates a set of constraints from the structure of the models and the requirements and propagates these constraints to a fixpoint. The solution to the constraints is an inductive invariant along with guards on the transitions. We also show how our approach extends to implementation refinement, decomposition, composition, and elaboration. We currently handle safety requirements written in LTL (Linear Temporal Logic)

42 ENGINEERING↗

Machine learning modeling and model predictive control of a closed-circuit reverse osmosis system

Closed-circuit reverse osmosis (CCRO) offers a flexible and energy-efficient alternative to conventional reverse osmosis by operating in a semi-batch mode that recycles brine, enabling higher recovery rates and reduced specific energy consumption (SEC). However, developing accurate, system-level dynamic models for CCRO remains challenging due to its nonlinear, multi-phase operation and sensitivity to variable feed water conditions. Traditional modeling approaches, such as NARMAX (nonlinear autoregressive moving average with exogenous inputs), often struggle to generalize across varying inlet feed concentrations, necessitating frequent parameter re-estimation and limiting their utility for real-time control applications. To address these limitations, we developed a long short-term memory (LSTM) neural network model trained on an extensive experimental data set from a CCRO pilot plant. The model accepts three inputs, feed flow rate, recirculation flow rate, and initial feed conductivity, and predicts three key outputs: reject conductivity, feed pump power draw, and recirculation pump power draw. We validated the LSTM model against experimental data, demonstrating its ability to distinguish between different feed conductivities and adapt to variable flow rates. Subsequently, we incorporated the LSTM model within a nonlinear model predictive control (MPC) scheme and conducted closed-loop simulations to optimize the integrated SEC (iSEC). In conclusion, the results project up to a 6% reduction in iSEC by using MPC to optimize performance over the entire experiment duration, without requiring any random excitation for data collection or parameter re-estimation.

Desalination↗

RF Digitizer for EIC LLRF

With the shutdown of Relativisitc Heavy Ion Collider (RHIC) in FY26, the former RHIC facility will be upgraded to the new Electron-Ion Collider (EIC). An RF Digitizer for the EIC LLRF system has been developed and tested on a RHIC 197 MHz cavity in Q2 2026 for a baseline per formance. Firmware and software has been developed and validated during the 197 MHz cavity test. Preliminary data from the cavity test shows phase noise performance signifi cantly better than the RHIC LLRF system.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Project Development of an Electrochemical Denitration and Caustic Generation System for HLW Pretreatment at Hanford - 26350

An engineering-scale electrochemical processing skid is proposed to perform the denitration of Hanford tank waste, which would help to mitigate a key process concern with the direct feed processing of the Hanford Tank Waste Treatment and Immobilization Plant (WTP). The reduction of nitrates and organic compounds in the waste feed will directly reduce hazardous NOx and ammonia gases generated during the vitrification process, which in turn will aid in addressing potential regulatory and safety challenges associated with processing large volumes of tank waste. This paper highlights the past legacy work, project layout, accomplishments from Phase 1 and research and development envisioned for Phase 2. An innovative electrochemical denitration and caustic generation (EDCGe) process was demonstrated for the pretreatment of tank waste at the Savannah River Site (SRS) in the early 2000s. The denitration electrolyzer, off-gas abatement system, and caustic generator electrolyzer are being developed with the intent that the denitration electrolyzer will convert nitrate and nitrite anions to nitrogen gas while also yielding other gaseous byproducts, which may include N2O, NH3, VOCs, and H2. The gaseous byproducts will be managed via a tandem off-gas catalyst-bed treatment system. The caustic generation electrolyzer will recycle NaOH from the feed to produce a clean caustic stream for use within the batching tanks at Hanford, aiding in the preparation of waste for WTP. The reduction in hazardous emissions and improved waste treatment processes provides a robust solution for nuclear waste management, contributing to environmental safety and regulatory compliance. The EDCGe technology is being adapted, modified, and updated for the preparation of the Direct Feed-High Level Waste (DF-HLW) flowsheet at Hanford. Phase 1 demonstrated a bench-scale proof-of-concept for reactions involving the denitration electrolyzer and gas phase abatement of ammonia. The electrochemical technology is drawing on the scientific outcomes that were reported in the legacy work. The results from Phase 1 demonstrated the viability of the EDCGe system in reducing the nitrogen species of simple non-radioactive waste simulants. Commercially available alloys used as electrode materials and membranes are being studied for the denitration and caustic generation electrolyzers. The continuation of this project holds promise for broader applications, such as energy-efficient ammonia production, and contributes significant advancements in nuclear waste management. Additional material discovery has been investigated into ceramic Na super ion conductive (NaSICON) materials and off-gas abatement catalyst discovery. NaSICON is of interest for selective transport of Na within the electrolyzers to make a clean caustic stream. Future integration and optimization efforts, informed by Phase 1 results and ongoing research, will continue to drive advancements in nuclear waste management technology. The technology developed for the EDCGe treatment of tank waste will also have broader potential to inform other fields, such as energy-efficient ammonia production, as well as ammonia abatement catalysis through the lessons learned in electrochemical nitrate reduction. The applications and benefits of this research extend beyond Hanford and the Savannah River Site, supported by a collaborative team of scientists and engineers from national labs, academia, and industry, ensuring a comprehensive approach to solving complex waste treatment challenges. The team is leveraging advanced electrochemical technologies, machine learning, novel catalysts tailored for gaseous nitrogen species, and cutting-edge reactor systems to enhance the process efficiency and effectiveness of the denitration process.

Rodene, Dylan [Savannah River National Laboratory ↗

Microreactor Automated Control System - Digital Twin Models and Advanced Control Systems Updates

Automation of control systems is expected to be important in the economic and safe operation of microreactors. Therefore, there is a need to develop and demonstrate automated control for microreactors, along with the development of testbeds for this purpose. This report provides updates on the status of a nonnuclear microreactor automated control system (MACS)—a real-time, hardware-in-the-loop testbed for non-nuclear testing of microreactor control system automation. A real-time hardware-in-the-loop testbed incorporates the realistic dynamics of physical systems into control system development and testing. The collaborative effort between Oak Ridge National Laboratory (ORNL) and Idaho National Laboratory (INL) resulted in the development of a prototypic microreactor plant-level digital twin that includes the reactor and a balance of plant system. Advanced control strategies were incorporated to demonstrate testing of control automation solutions. The gRPC communication protocol, which was implemented in the hardware-in-the-loop testbed by INL, was coupled to a digital twin model developed using the TRANsient Simulation Framework of Reconfigurable Models (TRANSFORM) library in Modelica. This digital twin simulation was tested with the ViBRANT hardware for realistic feedback and visual representation of control action in real time. A modular Python client structure was developed to manage functional mock-up unit-based simulation and real-time gRPC communication. Hardware-in-the-loop testing indicated that the modeled reactor—a natural-convection, molten-salt coolant loop configuration—responds well to control of drum positioning for modulation of reactor core power, as well as system-level control and downstream demand changes. Ongoing research is focused on integrating additional control algorithms that utilize data from newly included sensors within the MACS hardware testbed, as well as demonstrating and assessing the performance of the different automated control algorithms on multiple additional operational scenarios.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DEVELOPMENT OF AN INTEGRATED SECURITY AND SAFETY MONITORING SYSTEM FOR SPENT NUCLEAR FUEL AND HIGH-LEVEL WASTE TRANSPORTATION

This paper provides an overview of the progress to date, and discussion of the path forward, related to designing, fabricating, and testing an integrated security and safety monitoring system (ISSMS) for railcars used to transport spent nuclear fuel (SNF) and high-level radioactive waste (HLW) in the United States. The system will comply with the US Department of Energy’s (DOE) Order 460.2B “Departmental Materials Transportation Management” and the Association of American Railroads’ (AAR) standard S-2043 “Performance Specification for Trains Used to Carry High-level Radioactive Material” [1] developed specifically for railcars used to transport high-level radioactive material (HLRM). DOE is in the process of developing and testing an ISSMS that will satisfy both DOE requirements and AAR standards. DOE has already developed railcar designs for transportation of HLRM. In 2024, DOE’s Atlas railcar project completed the design, fabrication and testing of three railcar types: transportation cask-carrying, buffer, and security escort, resulting in AAR conditional approval to operate on freight rail networks in North America. DOE decided to combine the required security and safety systems into one system, and this combined system is the subject of the current effort. DOE is developing and proposes to implement the ISSMS for these railcars as part of the build out of the railcar fleet. DOE began planning for development of the ISSMS in February 2020. The project is divided into seven phases starting with conceptual design and continuing through production design, as shown in Figure 1. An earlier version of the system was tested as part of the Atlas railcar consist demonstration test run in 2023. This paper describes the design features and system testing using the Atlas project railcars, and laboratory testing completed to date. The paper will also describe the activities planned to support the DOE project to ship the High Burn-Up Research Cask (HBRC) in 2027.

Schultze, Michael [ORNL] (ORCID:0000000283205671)↗

Reference Shapefiles and Pre-trained Random Forest Classification Models for Detecting Aufeis on the North Slope of Alaska in Landsat Imagery

This dataset provides shapefiles and trained machine learning models used for aufeis detection at four sites on the North Slope of Alaska. It includes reference data for evaluating Landsat-based detection methods, supporting research on remote sensing approaches for identifying aufeis. The ReferenceData folder contains ArcGIS shapefiles of semi-automated land cover classifications for 217 Landsat Collection 2 images, categorizing pixels into six classes: aufeis, snow, ground, none, water, and cloud. The SiteBuffers.zip file includes 10-kilometer buffer shapefiles defining regions of interest around four aufeis fields (Canning21, FH1, Firth, and Kuparuk), used to test three detection techniques. Additionally, the TrainedRFModels folder contains six pre-trained Scikit-Learn Random Forest classifiers (100 trees, max depth = 30) designed to predict aufeis presence in Landsat Collection 2 Surface Reflectance images using Red, Blue, SWIR2, NDVI, and NDWI bands. This dataset supports the development and validation of remote sensing methods for mapping aufeis in Arctic environments.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research.The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska.Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗