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Data-Enabled Fusion Technology (Final Scientific/Technical Report)

Advancing Scientific Understanding in Fusion Energy and Machine Learning This research represented a significant step forward in machine learning (ML) applications for fusion energy experiments. The project integrated advanced data-driven modeling, optimization techniques, and artificial intelligence to enhance the predictive capabilities and operational efficiency of plasma-based fusion systems. Specifically, tasks focused on ML-enhanced diagnostics, operator guidance tools, and predictive modeling helped improve the ability to interpret complex fusion experiments. Key areas of advancement included: 1) data-driven plasma control, i.e., using ML algorithms to optimize experimental conditions and classify plasma behaviors based on historical data; 2) spectroscopy and diagnostics, i.e., applying AI models to extract previously inaccessible insights from experimental spectroscopy data; and 3) configuration mapping and operator guidance, i.e., developing a predictive framework to assist scientists in identifying the most effective experimental parameters, reducing reliance on manual adjustments. By refining these ML-driven techniques, the project contributed to the broader scientific community’s understanding of plasma dynamics and fusion energy viability. Technical Effectiveness and Economic Feasibility The methods investigated demonstrated high technical effectiveness, as reflected in milestones assessing the predictive accuracy, performance, and optimization of fusion configurations. The development of an Operator Guidance Tool (OGT), for example, led to more precise control of plasma conditions by learning from experimental data and offering real-time adjustments. From an economic standpoint, DeFT provided: 1) the ability to reduce trial-and-error experimentation, which lowered operational costs; 2) improved data interpretation methods, which enabled more efficient resource allocation in large-scale fusion research projects; and 3) the automation of key diagnostic tasks, which reduced manual labor and human error, increasing overall efficiency. 13 The final assessments of predictive models and optimization strategies demonstrated that these approaches were scalable and could be implemented across multiple fusion energy research programs. Public Benefit and Societal Impact This project contributed directly to the broader goal of achieving sustainable and commercially viable fusion energy, which had profound implications for clean energy production and climate change mitigation. The integration of AI-driven solutions into fusion research: 1) sped up scientific discovery, accelerating progress towards achieving energy breakthroughs; 2) reduced the cost of experimentation, making fusion research more accessible; and 3) provided a framework for future AI applications in high-energy physics, benefiting adjacent fields like space exploration, material science, and renewable energy. Additionally, by fostering collaborations between AI researchers and plasma physicists, this project promoted interdisciplinary innovation that could lead to broader applications beyond fusion research.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Modeling and Analysis of a One-Third Scale Used Nuclear Fuel Package 30 cm Drop

This paper compares finite element models of used nuclear fuel package drop tests to actual test data recorded in a recent test campaign. In December of 2018, the US Department of Energy collaborated with Equipos Nucleares S.A, S.M.E (ENSA) and Bundesanstalt für Materialforschung und -prüfung (BAM) to perform 30 cm horizontal drop tests of a one-third scale model of the ENSA ENUN 32P dual-purpose used nuclear fuel package. The third-scale test package included a third-scale basket and simulated third-scale fuel assemblies that were instrumented with accelerometers to measure their individual impact responses. Two horizontal package drop tests were performed, one with the basket cells oriented parallel and perpendicular to the impact surface, and one with the basket rotated 45 degrees to change the relative orientation with the impact surface. This paper describes the modeling and analysis that supported the development of the test and instrumentation plan, such as which fuel assemblies should be instrumented and at what locations on each fuel assembly should the accelerometers be placed. Pre-test predictions based on finite element modelling are discussed, and a comparison against the actual test data is made. Post-test analysis and model refinement are also discussed, with the goal of identifying best practices and lessons learned. A separate paper by Kalinina et al., to be presented at this conference, more fully describes the test configuration and test results. This paper is focused on the numerical modeling that supported the test and the lessons learned about realistically modeling this type of physical test.

Klymyshyn, Nicholas A.↗

NSUF 2016 Annual Report

The Nuclear Science User Facilities (NSUF) and its partner facilities represent a prototype laboratory that utilizes a distributed partnership, with each facility bringing exceptional capabilities to the relationship including reactors, beamlines, state-of-the-art instruments, hot cells, and equally important, expertise. These capabilities and people together create a nationwide infrastructure that allows the best ideas to be tested using the most advanced capabilities. Through the NSUF, researchers and their collaborators are building on current knowledge to better understand the complex behavior of materials and fuels in a nuclear reactor. The NSUF’s partnership program in 2016 included eight universities, one research and education consortium, three national laboratories, and one industry partner. The avenues opened through these partnerships facilitate cooperative research across the country, matching people with capabilities and students with mentors. The NSUF in 2016 included Idaho National Laboratory (INL) and the following institutions: • Argonne National Laboratory • Center for Advanced Energy Studies (a research and education consortium between Boise State University, INL, Idaho State University, University of Idaho, and University of Wyoming) • Illinois Institute of Technology • Massachusetts Institute of Technology • North Carolina State University • Oak Ridge National Laboratory • Pacific Northwest National Laboratory • Purdue University • University of California, Berkeley • University of Michigan • University of Nevada, Las Vegas • University of Wisconsin • Westinghouse Materials Center of Excellence. This report contains details on new capabilities brought into the NSUF in 2016, the evidence of the increasing research facilitated by the NSUF, and new tools and activities to propel nuclear research and development forward to meet energy reliability and security needs. Learn about the NSUF Nuclear Fuels and Materials Library and the Nuclear Energy Infrastructure Database, and how the robust NSUF website continues to evolve to support new tools. Read about how the NSUF supports Department of Energy (DOE) missions through efforts like the 2016 NSUF Ion Beam Options Workshop, which led to a prioritiza-tion of ion beam facilities according to their ability to support Department of Energy Office of Nuclear Energy (DOE-NE) missions.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Hierarchical Multi-agent Large Language Model Reasoning for Autonomous Heterogeneous Catalyst Discovery

Artificial intelligence is reshaping scientific exploration, but most methods automate procedural tasks without engaging in scientific reasoning, limiting autonomy in discovery. We demonstrate that hierarchical agentic large language model reasoning can efficiently drive simulation and scientific exploration. Across two chemical applications, CO adsorption on Cu surface transition metal adatoms and on M–N–C catalysts, reasoning-guided exploration reduces required atomistic simulations by up to 90% relative to heuristic or random selection. Comparisons across single-agent, multi-agent, and stochastic baselines show that hierarchical strategies yield more coherent and information-efficient search trajectories. Reasoning traces reveal chemically grounded decisions that cannot be explained by semantic bias or stochastic sampling. We realize these agentic reasoning strategies in Materials Agents for Simulation and Theory in Electronic-structure Reasoning (MASTER), a multimodal system that translates natural language into density functional theory workflows. Altogether, multi-agent collaboration accelerates heterogeneous catalyst discovery and marks a step toward more autonomous, reasoning-guided scientific exploration.

30 DIRECT ENERGY CONVERSION↗

Search for light long-lived particles decaying to displaced jets in proton–proton collisions at $\sqrt{s} = 13.6$ TeV

A search for light long-lived particles (LLPs) decaying to displaced jets is presented, using a data sample of proton–proton collisions at a center-of-mass energy of 13.6 TeV, corresponding to an integrated luminosity of 34.7 fb −1 , collected with the CMS detector at the CERN LHC in 2022. Novel trigger, reconstruction, and machine-learning techniques were developed for and employed in this search. After all selections, the observations are consistent with the background predictions. Limits are presented on the branching fraction of the Higgs boson to LLPs that subsequently decay to quark pairs or tau lepton pairs. An improvement by up to a factor of 10 is achieved over previous limits for models with LLP masses smaller than 60 GeV and proper decay lengths smaller than 1 m. The first constraints are placed on the fraternal twin Higgs (FTH) and folded supersymmetry (FSUSY) models, where the lower bounds on the top quark partner mass reach up to 350 GeV for the FTH model and 250 GeV for the FSUSY model.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

GHEP WIBT (Guidelines for Home Energy Professionals Weatherization Installer Badges Toolkit) [SWR-20-69]

The National Renewable Energy Laboratory (NREL) and the U.S. Department of Energy's (DOE) Weatherization Assistance Program (WAP) are collaborating with the home energy retrofit industry to support the development of skilled workers. The Installer Badges Toolkit provides a flexible, customizable, and voluntary approach to training and skills recognition for WAP implementers, utility programs, private-sector workers, and contractors. In Fiscal Year 2018, DOE, along with the Crew Leader scheme committee, determined the Retrofit Installer Technician (RIT) Job Task Analysis (JTA) could be eliminated and its tasks inserted in the Crew Leader JTA. The RIT tasks became the basis of the Installer Badges. The Badges Toolkit was updated in 2020 to add licensing and copyright agreements. Users must cite the copyright information when using or distributing copies of the Badges Toolkit in any way. The technical content has remained unchanged from previous versions of the Badges Toolkit. The Toolkit for home retrofits consists of 25 Badges, each representing different energy efficiency tasks that an installer could perform on a home. Each Badge defines the desired outcome, criteria to verify, applicable material requirements, and references to Standard Work Specifications (SWS) or other relevant standards. The Badges provide a consistent approach to training by ensuring that installers in different regions are learning the same skills nationwide. Organizations can also customize the Toolkit by choosing only those Badges that are relevant to their program. The Badges Toolkit includes five pieces: "How to Use the Badges Toolkit" provides a brief overview of how a Grantee, Subgrantee, or training provider may approach using the toolkit. The "Badges Toolkit: Worksheet" includes what to consider when determining whether and how to best incorporate the Badges into a weatherization assistance program. The "Crew Leader Job Task Analysis Spreadsheet" indicates how the Badges align with specific areas of the JTA. The "Installer Badges Passport" features separate pages for each Badge, which include places for the installer and the supervisor/trainer to record the number of times a task has been successfully completed. The "Installer Badges Verification Criteria" includes sample inspection checklists for each Badge. These can be modified as needed based on approved variance requests or more stringent requirements. They also provide a basis for consistent inspections and awarding of Badges. Note: All elements of the Badges Toolkit are designed for use by potential program implementers. They are not off-the-shelf products intended for immediate deployment. Program implementers must review and modify as needed, revise verification criteria to match local requirements, complete worksheets, and otherwise define the parameters of their own badging program.

Desai, Jal↗

Topics in Theoretical Physics

This award supported a broadly based research effort in theoretical particle physics, including research aimed at uncovering the laws of nature at short (subatomic) and long (cosmological) distances. These theoretical developments apply to experiments in laboratories such as CERN, the facility that operates the Large Hadron Collider outside Geneva, as well as to cosmological investigations done using telescopes and satellites. The results reported here apply to physics beyond the so-called Standard Model of particle physics; physics of high energy collisions such as those observed at the Large Hadron Collider; theoretical and mathematical tools and frameworks for describing the laws of nature at short distances; cosmology and astrophysics; and analytic and computational methods to solve theories of short distance physics. Some specific research accomplishments include + Theories of the electroweak interactions, the forces that give rise to many forms of radioactive decay; + Physics of the recently discovered Higgs boson. + Models and phenomenology of dark matter, the mysterious component of the universe, that has so far been detected only by its gravitational effects. + High energy particles in astrophysics and cosmology. + Algorithmic research and Computational methods for physics of and beyond the Standard Model. + Theory and applications of relativity and its possible limitations. + Topological effects in field theory and cosmology. + Conformally invariant systems and AdS/CFT. This award also supported significant training of students and postdoctoral fellows to lead the research effort in particle theory for the coming decades. These students and fellows worked closely with other members of the group as well as theoretical and experimental colleagues throughout the physics community. Many of the research projects funded by this grant arose in response to recently obtained experimental results in the areas of particle physics and cosmology. We describe a few of these below. Relativity is founded on a symmetry property of nature called "Lorentz Invariance". Like all symmetry properties, it is essential to determine precisely how symmetric nature actually is; that is, do the laws of nature fully respect the symmetry or is there room for tiny symmetry violating effects? An important consequence of Lorentz invariance is the existence of a universal limiting velocity for all physical particles. Light travels at this limiting velocity so it is frequently referred to as simply "the speed of light", but relativity requires that ALL particles travel more slowly than this speed. Once the Higgs particle was discovered in 2012 a natural question was whether or not this particle's speed was consistent with relativity. Although the speed of the Higgs particle is not measurable directly, Cohen has shown that, if the maximal speed of the Higgs particle was not precisely the same as the speed of light, then the Higgs would have some unusual properties. In some cases the Higgs would be unstable to some unusual decay modes; in other cases the interactions of the Higgs with other particles would change the properties of these other particles in ways that could be observed in so-called cosmic rays, very energetic particles (such as photons, protons and other atomic nuclei) coming from space. Once these particles hit the upper atmosphere they produce a "shower" of particles that can be seen by ground-based instruments. If the Higgs has a maximal speed that differs even a tiny bit from the speed of light these showers would look quite different from what is observed. In this way Cohen was able to establish that the Higgs travels with a maximal speed that cannot differ from the speed of light by more than one part in a thousand-trillion. This is by far the most precisely determined property of the Higgs particle. Cohen and Schmaltz reviewed evidence from the Large Hadron Collider (LHC), a particle physics experiment operating at the CERN laboratory near Geneva, for a new particle sometimes called a W'. This evidence included certain unexpected by-products in collisions of protons at very high energy. While the evidence was not significant enough to claim a discovery, it was sufficiently intriguing that many particle theorists worked to construct explanations for this signal. Cohen and Schmaltz were able to determine that such explanations are highly constrained by previous experiments involving collisions of very energetic particles. Nevertheless they were able to construct a theory that adequately explains the LHC data and remain consistent with prior experiments. Their explanation predicts the existence of yet another new particle, called a Z', with a mass slightly greater than that of the W'. This additional particle, if it exists, should be seen as more data is collected from the LHC. Amusingly, there is one collision by-product that has already been seen by the CMS experiment at the LHC that supports the existence of this new particle; however, it is not unlikely that this single event is a so-called "background" event, that is a somewhat atypical by-product of a conventional Standard Model process. This theory for the anomalous LHC data will either be confirmed or excluded with further data-taking at the LHC. The ratio of the number of electrons produced in bottom quark decays over the number of muons produced has been measured at the LHC. This ratio is interesting because it can be predicted very precisely from a basic property of the Standard Model: lepton universality. If lepton universality is correct, the ratio of electrons to muons is predicted to be equal to 1. The first measurements of this ratio find a value different from 1 with a statistical significance of about 3 standard deviations. Schmaltz and collaborator proposed a new extension of the Standard Model which can explain the new data. In addition, Schmaltz and collaborators proposed several new measurements of ratios of decay rates which can confirm or rule out the surprising results from the earlier LHC data. The most recent and precise measurements of the cosmic microwave background from the Planck satellite, from a combination of measurements of the dark matter distribution in the universe, and from a measurement of the expansion rate of the universe today show some disagreement when interpreted in terms of the so-called LambdaCDM model. Schmaltz and collaborators proposed an alternative model to LambdaCDM in which the usual cold dark matter is replaced by a new ``dark sector". This sector consists of a cold dark matter particle which interacts with a newly postulated dark radiation component of the universe. The dark radiation can help explain the discrepancy in measurements of the expansion rate, and the dark matter interactions subtly modify the clumping of dark matter at large scales, thus potentially explaining both kinds of tensions in the data. In two publications Schmaltz described the new model and then performed a precision comparison of the predictions of the model with all currently available cosmological data. The results favor the new model at the level of three standard deviations with current data. Quantum Field Theory (QFT) is the language we use to describe quantum systems which are consistent with Einstein’s theory of Special Relativity. In particular, the requirement of Einstein’s theory that signals not travel faster than the speed of light constrains the types of interactions which particles can engage in. One consequence of relativity is that these interactions cannot preserve particle number. The stronger the interactions, the more severe the particle number violation in a given Relativistic QFT. When particle number violation is strong, it becomes very difficult to adequately parameterize the quantum wave function (which characterizes the state of a quantum system). For example, though we can formulate the QFT which describes the strong force as a set of interactions between quark and gluon particles, we have no clear idea how to express the proton state in terms of these quarks and gluons. This is because the proton, though a bound state of quarks and gluons, is not a state of a fixed number of particles due to strong interactions. Yet, understanding the proton state is very important in order to theoretically predict the reaction rates observed at the LHC in Geneva, which is a proton-proton collider. Katz has formulated a new approach to QFT, which among other things offers a way to adequately approximate the quantum wave function of a bound state at strong coupling. The approximation scheme is related to the fact that any sensible QFT (including that of the strong interactions) is at short distances approximately self-similar upon rescaling of space and time. It turns out that keeping track of the response upon this rescaling is important in efficiently parameterizing the state. Katz and collaborators have used this observation to approximate the state of the proton in toy versions of the strong force. In the late 60s Sheldon Glashow, Abdus Salam and Steven Weinberg (1979 Nobel Prize awardees) proposed a theory unifying weak and electromagnetic interaction which assumed the existence of new particles, the W and Z bosons. The W and Z bosons were eventually detected in high-energy collision in a particle accelerator at CERN, and the recent discovery of the Higgs meson at the Large Hadron Collider (LHC), always at CERN, completed the picture. However, deep theoretical considerations indicate that the theory by Glashow, Weinberg and Salam, often referred to as "the standard model" cannot be the whole story: the existence of new particles and new interactions at yet higher energies is widely anticipated. The experiments at the LHC are looking for these, while theorists, like Brower, Rebbi and collaborators, are investigating models for these new interactions. Working in a large national collaboration with access to the most powerful DOE computers Brower, Rebbi and colleagues have been using calculational techniques, similar to those successfully employed for many years to investigate the interactions among quarks in nucleons, to study theories that can describe the expected "beyond the standard model" (BSM) interactions. Their results, which include also a model for dark matter, have been published in several refereed papers in prestigious journals. Various ideas in topologically interesting field theories predict hypothetical objects such as fractional charges and Majorana excitations. However, such fascinating objects have not been seen in particle physics. Nevertheless, these objects demonstrate possible phenomena that quantum field theory can support. Pi used condensed matter physics as a laboratory to study possible realizations and observable effects of these objects predicted by quantum field theory. In recent times there has developed considerable interest among condensed matter field theorists in precisely the same geometrical and topological structures, which were first discovered in particle physics field theories. From particle physicists' point of view, this is an interesting development, since condensed matter provides an arena in which one can concretely realize particle physics ideas. Moreover, particle physicists can learn new ideas from condensed matter physics. Higgs phenomenon is precisely an important particle physics realization of condensed matter ideas. In contrast to the small distance characterizing condensed matter systems, field theory also describes large distance physics characterizing cosmology. Pi worked on various geometrical effects in the standard theory of cosmology, viz general relativity.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

WM26 Paper Multi-Robot Collaboration for Hazardous Environments

Hazardous nuclear and industrial facilities are rarely designed for robots. Work in these domains demand precise manipulation and robust mobility in cluttered, constrained spaces where off-the-shelf platforms struggle and “one-size-fits-all” machines become costly and complex. Idaho National Laboratory (INL) is developing an autonomous, multi-robot inspection system that coordinates task-specific platforms rather than relying on a single omni-tool robot. An electric truck serves as a power and compute hub for a custom manipulator co-developed with Florida International University (FIU), a commercial mini crawler, a pan–tilt–zoom camera, and a Nexxis Argus LiDAR mapping system. Working in concert, these robots generate spatial, radiation, and temperature maps of the pit environments at the Hanford Waste Tank Farms. These systems will capture visual records and environmental telemetry to allow for analysis post inspection. The system architecture uses Robot Operating System 2 (ROS 2) for publish/subscribe integration, NVIDIA Isaac Sim and Unity for simulation and visualization, and algorithms such as NVBlox to fuse data into unified 3D overlays. This robot-agnostic approach reduces operator burden by enabling autonomy across heterogeneous platforms and lets each robot be used where it is strongest. Having autonomous functions means operators don’t have to fully control multiple different components. The ease of use could allow for more widespread adoption of advanced robotics at waste management sites that see continued use. By coordinating simpler, purpose-built mechanisms, the approach lowers design and manufacturing complexity, reduces capital risk in contaminated settings, and improves controllability for complex inspection and manipulation tasks. We present the architecture, early results, and lessons learned from building and deploying this coordinated multi-robot system, with the goal of accelerating safe, cost-effective adoption of advanced robotics at waste-management sites.

42 - ENGINEERING↗

Managing Knowledge Over Time for Supporting Radioactive Waste Geological Disposal Project Development - 19028

Projects designed to define, build, operate and monitor radioactive waste disposal solutions require the transmission of knowledge over several decades and the preservation of memory over several centuries. This is particularly acute for the geological disposal project 'Cigeo' led by the French national radioactive waste management agency (Andra) as far as the requirements in terms of reversibility lead to the choice of an incremental design that allows to integrate learning resulting from continuous improvement of knowledge. For instance, for robustness purposes, Cigeo is designed on the basis of currently proven technologies, but its step-by-step construction in successive stages must make it possible to integrate improvements derived from the scientific and technical progress as well as from experience feedback from its exploitation. In the field of industrial activity, a significant proportion of the knowledge and skills implemented by employees of a company are not known or even identified by the human resources organization or the mid-management staff. This is mainly due to the fact that (i) the organized knowledge-sharing is often based on documentary tools but little on social modalities and (ii) the organization of knowledge is mostly cross-cutting to the managerial lines. To overcome this bias, a global and integrated approach to knowledge management is currently the focus of Andra's specific efforts. Cross-disciplinary groups and close intergenerational links positioned throughout the life of the projects aim specifically at continuous and participative knowledge sharing, capitalization and transmission. Then, devices aiming at systematic dissemination of and access to knowledge support experience feedback and provide unified collaboration, traceability and decision-support at all scales. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

A Mechanistic Reliability Assessment of RVACS and Metal Fuel Inherent Reactivity Feedbacks

GE Hitachi Nuclear Energy (GEH) and Argonne National Laboratory (Argonne) participated in a two year collaboration to modernize and update the probabilistic risk assessment (PRA) for the PRISM sodium fast reactor. At a high level, the primary outcome of the project was the development of a next-generation PRA that is intended to enable risk-informed prioritization of safety- and reliability-focused research and development. A central Argonne task during this project was a reliability assessment of passive safety systems, which included the Reactor Vessel Auxiliary Cooling System (RVACS) and the inherent reactivity feedbacks of the metal fuel core. Both systems were examined utilizing a methodology derived from the Reliability Method for Passive Safety Functions (RMPS), with an emphasis on developing success criteria based on mechanistic system modeling while also maintaining consistency with the Fuel Damage Categories (FDCs) of the mechanistic source term assessment. This paper provides an overview of the reliability analyses of both systems, including highlights of the FMEAs, the construction of best-estimate models, uncertain parameter screening and propagation, and the quantification of system failure probability. In particular, special focus is given to the methodologies to perform the analysis of uncertainty propagation and the determination of the likelihood of violating FDC limits. Additionally, important lessons learned are also reviewed, such as optimal sampling methodologies for the discovery of low likelihood failure events and strategies for the combined treatment of aleatory and epistemic uncertainties.

Grabaskas, David↗

Effectiveness and predictability of in-network storage cache for Scientific Workflows

Large scientific collaborations often have multiple scientists accessing the same set of files while doing different analyses, which create repeated accesses to the large amounts of shared data located far away. These data accesses have long latency due to distance and occupy the limited bandwidth available over the wide-area network. To reduce the wide-area network traffic and the data access latency, regional data storage caches have been installed as a new networking service. To study the effectiveness of such a cache system in scientific applications, we examine the Southern California Petabyte Scale Cache for a high-energy physics experiment. By examining about 3TB of operational logs, we show that this cache removed 67.6% of file requests from the wide-area network and reduced the traffic volume on wide-area network by 12. 3TB (or 35.4%) an average day. The reduction in the traffic volume (35.4%) is less than the reduction in file counts (67.6%) because the larger files are less likely to be reused. Due to this difference in data access patterns, the cache system has implemented a policy to avoid evicting smaller files when processing larger files. We also build a machine learning model to study the predictability of the cache behavior. Tests show that this model is able to accurately predict the cache accesses, cache misses, and network throughput, making the model useful for future studies on resource provisioning and planning.

Sim, Caitlin↗

Converged Computing: A Best of Both Worlds of High-Performance Computing and Cloud

Collaboration between Cloud and High Performance Computing (HPC) communities has accelerated in the last half decade. A common goal to run batch workloads combined with a desire for reproducibility, automation, and optimization has led to successful projects that range from container technologies to workload management and security. This span of current and future work defines a novel “Converged Computing” paradigm that aims to combine the best of both worlds, both from a technological and cultural standpoint. Furthermore, in this Special Issue, we review common themes in the space, showcasing current work and encouraging a continued effort toward innovative ideas that will enable the next generations of scientific discovery.

97 MATHEMATICS AND COMPUTING↗

The GIF Proliferation Resistance and Physical Protection Methodology Applied to Gen IV System Designs: Some Reflections

The Generation Four International Forum (GIF) formed a proliferation resistance and physical protection (PR&PP) Working Group (PRPPWG) to develop a methodology to evaluate the six GIF reactor technologies. The PRPPWG developed the methodology through a series of development and demonstration case studies, using a hypothetical “Example Sodium Fast Reactor” (ESFR). The ESFR assessment enabled testing of the full methodology on a complete nuclear energy system and many insights were gained from the process. The PRPPWG, in collaboration with representatives of the GIF System Steering Committees/provisional Steering Committees (SSCs/pSSCs) for each of the six GIF reactor technologies, analyzed the PR&PP aspects of the six reactor technologies. The outcome of this activity is documented in a joint PRPPWG and SSCs/pSSCs report made publicly available in 2011, highlighting the analysis performed and its main outcomes. Currently, the PRPPWG and the six GIF SSCs/pSSCs are in the process of repeating the exercise, based on the current status of the six GIF system design concepts, taking into account the designs’ evolution since 2011. In line with Safeguards by Design concept, whilst during the first exercise the level of detail of the design options enabled only a high-level evaluation of the systems’ proliferation resistance, the early design stage allowed designers to introduce modifications for improving the systems’ performance. With the designs’ current level of detail, the opportunity for proposing modifications diminishes, whilst at the same time increasing the opportunity to inform the safeguards R&D community on potential R&D needs to meet safeguardability issues. The paper will first summarize the main concepts behind the PR&PP evaluation methodology. It will then summarize the main outcomes and lessons learned, as in the current white papers on the PR aspects of the six GIF design concepts, and will finally describe the ongoing activity to update them.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

Savannah River National Laboratory Collaborative Innovation Pilot Team - 17560

The Collaborative Innovation (COIN) program was established by the Savannah River National Laboratory (SRNL) in March 2016. The goal of the SRNL COIN program is to identify innovative options to significantly reduce program and project risks (improve safety, reduce schedule and cost) of high priority Department of Energy Environmental Management, National Nuclear Security Administration, and Nuclear Energy missions. The COIN Advisory Board selected as the target outcome of the first COIN effort a 50% improvement to the Savannah River Site (SRS) H-Canyon spent nuclear fuel (SNF) processing 'baseline,' or current plan, as defined in the SRS Nuclear Materials Planning Roadmap. A small team of SRNL and Savannah River Nuclear Solutions personnel with pertinent experience and expertise was co-located and largely sequestered for eight weeks to identify improvements to H-Canyon processing of SNF. Following the process defined in the SRNL COIN Charter, the COIN Pilot Team analyzed the baseline for processing SNF through H Canyon; generated alternative ideas; tested seemingly viable ideas by reaching out to other subject-matter experts; and identified options for consideration for implementation by the COIN Advisory Board. The COIN Pilot produced a number of important outcomes, including important lessons learned for subsequent COIN efforts. The two principal outcomes are these: 1. The COIN Pilot Team conducted a comprehensive examination of the individual unit operations, the integrated system, and external interfaces to produce a timeline of H-Canyon processing and sampling times that had not previously existed. The general timeline served as the baseline from which the Pilot Team identified processing improvements. In addition, the timeline has already been employed in other planning efforts. 2. The COIN Pilot Team determined that innovations to the H-Canyon Dissolving unit operation alone could increase the number of SNF bundles processed through H Canyon by the target of 50%, but with little margin for error. To ensure that the gains in throughput in the Dissolving unit operation would be maintained throughout the facility, the Pilot Team identified four additional improvements to create greater efficiency and flexibility in downstream H-Canyon unit operations. The COIN Pilot Team's innovations reduce the processing time of a single batch of SNF through H Canyon from about 70 days to about 50 days. This talk will review the COIN process and the results of the pilot of the process. (authors)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

The GIF Proliferation Resistance and Physical Proection Methodology Applied to GEN IV System Designs: An Update

The Generation IV International Forum (GIF) formed a proliferation resistance and physical protection (PR&PP) Working Group (PRPPWG) to develop a methodology to evaluate the six GIF reactor technologies. The PRPPWG developed the methodology through a series of development and demonstration case studies and many insights were gained from the process. The PRPPWG, in collaboration with representatives of the GIF System Steering Committees/provisional Steering Committees (SSCs/pSSCs) for each of the six GIF reactor technologies, analyzed and evaluated the PR&PP aspects of the six reactor technologies. The outcome of this activity is documented in a joint PRPPWG and SSCs/pSSCs report made publicly available in 2011, highlighting the analysis performed and its main outcomes. Currently, the PRPPWG and the six GIF SSCs/pSSCs are in the process of repeating the exercise, based on the status of the six GIF system design concepts, considering the designs’ evolution since 2011. In line with the PR&PP by Design concept, whilst during the first exercise the level of detail of the design options enabled only a high-level evaluation of the systems’ proliferation resistance, the early design stage allowed designers to introduce modifications for improving the systems’ performance. With the designs’ current level of development, the opportunity for proposing modifications diminishes, whilst at the same time increasing the opportunity to inform the safeguards R&D community on potential R&D needs to meet safeguardability issues. The paper will first summarize the main concepts behind the PR&PP evaluation methodology. It will then present the main outcomes and lessons learned as in the current white papers on the PR aspects of the six GIF design concepts and will finally describe the ongoing activity to update them within a PR&PP-by-Design context.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

Demonstrating Advanced Nuclear Energy Solutions for Net Zero

Background/Objectives. The aggressive goals being set by nation states, communities, and private industry for decarbonization of grid electricity, industrial heat sources, and transportation around the world are imperative to mitigating the devastating effects that we are seeing from climate change. Although many of these goals focus on accomplishments by 2035 or 2050, the decisions that we make today won’t just impact the landscape of energy systems for the next 20 or 30 years—they will shape the world’s environment for centuries to come. That means that we can’t just focus on technologies that will get us to 2050, but technologies that will withstand our energy demands over that long-ranging future. Success will require us to utilize all of the clean energy resources that we have available to meet demands for electricity, heat, and steam, and we will need energy carriers such as hydrogen that do not emit additional greenhouse gases at the point of use. Nuclear energy, ranging from technologies in service today to advanced, higher temperature and modular systems that will be in service this decade, will provide a robust complement to renewable energy resources that operate variably. Researchers across the U.S. Department of Energy laboratory complex are working to advance multiple aspects of these clean energy solutions, with many focusing on integrated energy system solutions that leverage all available clean energy assets to meet wide-ranging energy demands. Approach/Activities. Nuclear energy is a proven, zero-emission option during operation that can provide consistent, dispatchable power to meet electricity demands while also providing high-quality heat that can meet energy demands beyond the electricity sector. Energy system design should seek to maximize these assets. As a dispatchable energy source with a small land utilization footprint, nuclear energy can be collocated with renewable resources, and the smaller systems that will be deployed this decade (ranging from a few megawatts to hundreds of megawatts) can be installed right where that energy is needed. Integrated nuclear and renewable systems will enhance power grid reliability and resilience, and they will help stabilize the grid through their increasingly flexible operation. Licensing, installation, and broad adoption of these advanced nuclear energy systems are expected to progress significantly in the 2020s, but this may be longer than desired by some stakeholders wishing to implement impactful clean energy decisions today. However, one must recall that nuclear energy systems will operate for 80 or more years, as is being demonstrated by current fleet nuclear systems. The nuclear community is extremely thorough in reviewing these systems with regard to safety and security; these efforts ensure that the deployed systems will continue to provide reliable, resilient energy over that operational lifetime. That investment of time up front will ensure that we can support energy demands over the centuries to come. While advanced nuclear technologies move through this process, communities and private industry may choose to install renewable generation systems that can later be coupled to the complementary nuclear systems as they become available—thus moving closer to the net zero goals in the near term. Choosing technologies and deployment configurations that allow small modular nuclear powerhouses to be added to these “energy parks” as they become available will ensure that advanced technologies can be readily adopted to support growing demands for clean energy. Results/Lessons Learned. The primary focus of integrated energy systems (IES) research is to assess the technical and economic potential of novel multi-input, multioutput solutions that are expected to enhance energy system flexibility, reliability, and resilience as we pursue a clean energy transition. Various energy applications and product streams beyond electricity are being evaluated, ranging from generation of potable water to production of hydrogen, fertilizers, synthetic fuels, and various chemicals. In early FY23 Idaho National Laboratory (INL) will commission thermal energy generation systems that emulate nuclear fission energy input using electric heating and will allow for integrated system testing with thermal energy storage, hydrogen production via high temperature electrolysis (HTE), and power systems hardware to demonstrate operation of a clean energy park within a microgrid or larger grid infrastructure, supporting up to 450 kW of heat input via electric heating and demonstrating operation of HTE systems at the multi-hundred kW scale. This presentation will highlight the wide array of RD&D being conducted at INL and partner laboratories to develop and deploy nuclear and renewable-based IES that will be key to achieving our net zero goals, including both computational and experimental demonstrations. By working with key collaborators in industry, analytical st

08 HYDROGEN↗

Multi-scale visual analysis of time-varying electrocorticography data via clustering of brain regions

There exists a need for effective and easy-to-use software tools supporting the analysis of complex Electrocorticography (ECoG) data. Understanding how epileptic seizures develop or identifying diagnostic indicators for neurological diseases require the in-depth analysis of neural activity data from ECoG. Such data is multi-scale and is of high spatio-temporal resolution. Comprehensive analysis of this data should be supported by interactive visual analysis methods that allow a scientist to understand functional patterns at varying levels of granularity and comprehend its time-varying behavior. We introduce a novel multi-scale visual analysis system, ECoG ClusterFlow, for the detailed exploration of ECoG data. Our system detects and visualizes dynamic high-level structures, such as communities, derived from the time-varying connectivity network. The system supports two major views: 1) an overview summarizing the evolution of clusters over time and 2) an electrode view using hierarchical glyph-based design to visualize the propagation of clusters in their spatial, anatomical context. We present case studies that were performed in collaboration with neuroscientists and neurosurgeons using simulated and recorded epileptic seizure data to demonstrate our system's effectiveness. ECoG ClusterFlow supports the comparison of spatio-temporal patterns for specific time intervals and allows a user to utilize various clustering algorithms. Neuroscientists can identify the site of seizure genesis and its spatial progression during various the stages of a seizure. Our system serves as a fast and powerful means for the generation of preliminary hypotheses that can be used as a basis for subsequent application of rigorous statistical methods, with the ultimate goal being the clinical treatment of epileptogenic zones.

60 APPLIED LIFE SCIENCES↗

Late-Stage Research Development and Demonstration Sub-activities Updates – FY24 Q3

Oak Ridge National Laboratory (ORNL), in collaboration with the Pacific Northwest National Laboratory (PNNL), the National Renewable Energy Laboratory (NREL), the Lawrence Berkeley National Laboratory (LBNL), and the Hummingbird Firm (a specialized consulting firm focused on promoting diversity, equity, and inclusion considerations), has initiated a national initiative known as the Heat Pump (HP) and Heat Pump Water Heater (HPWH) Field Validation Partnership. This effort involves active participation from numerous critical entities involved in research and market transformation within the field. The ORNL team is responsible for leading Late-Stage Research Development and Demonstration (LSRDD) among the four different topics. The overall outcomes of this project will be: (1) A structured Field Validation Partnership between DOE, the national labs, research, implementation, and market transformation organizations. This will result in unique way to coordinate field validation plans and collect relevant data from around the country into the HP and HPWH Field Validation Database. (2) The Field Validation Partnership will result in a continuous stream of information between DOE and the major industry players in the space of HPs and HPWHs. If desired, DOE could use this information to inform roadmaps related to HP and HPWH market adoption and research going forward. (3) The structure of this Partnership provides a mechanism for sharing lessons learned directly between Late-Stage RD&D, Building Integration Barriers, Regional Market and Policy and Workforce Development efforts. The result will be training content that is well-reviewed by the Partnership which will lead to a workforce that meets the industry’s quality and workforce supply demands. (4) The structure of this Partnership also provides an opportunity for regions to share lessons learned on policy and market transformation with each other through the Market and Policy core Committee. This report includes an update in Late-Stage Research Development and Demonstration.

99 GENERAL AND MISCELLANEOUS↗