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At least 1,531 records · Page 85

Promoting Sustainable Transportation Modes: A Systematic Review of Behavior-Change Strategies

In previous studies, many travel-behavior-change strategies often relied on single behavior determinants or psychological theories, overlooking the incorporation of sociopsychological theories for guidance in their design. Integrating these theories could offer consistent guidance for program developers and enhance intervention effectiveness. This paper systematically reviews interventions targeting travel-behavior change, with a focus on self-determination theory and its principles of satisfying individuals’ competence, autonomy, and relatedness needs for enacting change. Additionally, experiment design methods, including randomized controlled trials and quasi-experimental designs, are reviewed and discussed. Key findings highlight the effectiveness of personalized interventions and integrating feedback with goal-setting strategies. Given the limited direct references to sociopsychological theories in existing studies, we explore relevant sociopsychological theories applicable to travel-behavior-change programs to provide examples of how strategies could be designed based on them. This review contributes valuable insights into the development of strategies for changing travel behavior, offering a theoretical framework for researchers and practitioners to guide intervention design, experimentation, and evaluation. In conclusion, leveraging these theories not only facilitates reproducibility but also provides a standardized approach for transportation demand management program developers.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Opportunities for enhancing MLCommons efforts while leveraging insights from educational MLCommons earthquake benchmarks efforts

MLCommons is an effort to develop and improve the artificial intelligence (AI) ecosystem through benchmarks, public data sets, and research. It consists of members from start-ups, leading companies, academics, and non-profits from around the world. The goal is to make machine learning better for everyone. In order to increase participation by others, educational institutions provide valuable opportunities for engagement. In this article, we identify numerous insights obtained from different viewpoints as part of efforts to utilize high-performance computing (HPC) big data systems in existing education while developing and conducting science benchmarks for earthquake prediction. As this activity was conducted across multiple educational efforts, we project if and how it is possible to make such efforts available on a wider scale. This includes the integration of sophisticated benchmarks into courses and research activities at universities, exposing the students and researchers to topics that are otherwise typically not sufficiently covered in current course curricula as we witnessed from our practical experience across multiple organizations. As such, we have outlined the many lessons we learned throughout these efforts, culminating in the need for benchmark carpentry for scientists using advanced computational resources. The article also presents the analysis of an earthquake prediction code benchmark while focusing on the accuracy of the results and not only on the runtime; notedly, this benchmark was created as a result of our lessons learned. Energy traces were produced throughout these benchmarks, which are vital to analyzing the power expenditure within HPC environments. Additionally, one of the insights is that in the short time of the project with limited student availability, the activity was only possible by utilizing a benchmark runtime pipeline while developing and using software to generate jobs from the permutation of hyperparameters automatically. It integrates a templated job management framework for executing tasks and experiments based on hyperparameters while leveraging hybrid compute resources available at different institutions. The software is part of a collection called cloudmesh with its newly developed components, cloudmesh-ee (experiment executor) and cloudmesh-cc (compute coordinator).

58 GEOSCIENCES↗

Integrated Design of a Robust System for Inertial Fusion Energy

For inertial fusion energy (IFE) to be successful, designs need to work robustly including both target physics and engineering considerations. For a power plant to be reliable and have a high operating capacity factor, the integrated design of the target, driver, target fabrication, target injection system, and chamber all need to work together in way that is robust and repeatable to expected variations. One of the lesson’s learned from our experience at NIF is that designs that are sensitive have not performed as expected – even in single shot mode. The lesson’s learned from NIF should be folded into creating integrated designs for IFE and for evaluating the tradeoffs between the different parts of the IFE system. To do so, we propose using the NIF 1.3 MJ yield shot/design (N210808) as a starting point of a study of the feasibility of indirect drive designs for IFE. If the hohlraum inefficiency precludes indirect drive, the study would include direct drive or fast ignition versions of this design.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Diagnosing the sensitivity of grounding-line flux to changes in sub-ice-shelf melting

Abstract. Using a numerical ice flow model, we study changes in ice shelf buttressing and grounding-line flux due to localized ice thickness perturbations, a proxy for localized changes in sub-ice-shelf melting. From our experiments, applied to idealized (MISMIP+) and realistic (Larsen C) ice shelf domains, we identify a correlation between a locally derived buttressing number on the ice shelf, based on the first principal stress, and changes in the integrated grounding-line flux. The origin of this correlation, however, remains elusive from the perspective of a theoretical or physically based understanding. This and the fact that the correlation is generally much poorer when applied to realistic ice shelf domains motivate us to seek an alternative approach for predicting changes in grounding-line flux. We therefore propose an adjoint-based method for calculating the sensitivity of the integrated grounding-line flux to local changes in ice shelf geometry. We show that the adjoint-based sensitivity is identical to that deduced from pointwise, diagnostic model perturbation experiments. Based on its much wider applicability and the significant computational savings, we propose that the adjoint-based method is ideally suited for assessing grounding-line flux sensitivity to changes in sub-ice-shelf melting.

54 ENVIRONMENTAL SCIENCES↗

Ion Traps and Packaging for Heterogenous Integration - Chimera

Microfabricated surface ion traps and silicon-based photonics are critical technologies for scaling quantum systems. Current ion trap architectures face scalability and integration challenges due to limitations in optical access, fabrication techniques, and material compatibility. State-of-the-art quantum computers and atomic clocks are investigating monolithic integration, which necessitates custom traps for each ion species and has not overcome the integration hurdles presented by merging these technologies. The Chimera (Ion Traps and Packaging for Heterogeneous Integration) project proposes a novel approach utilizing heterogeneous integration (HI) of ion traps and photonic circuits. This separation of components allows for flexibility in ion trap design and reduces fabrication compromises. The Chimera project specifically designed an ion trap to interface vertically with a separately fabricated waveguide chip and demonstrates the first steps to integrating them at the packaging level. The ion trap features a large area of removed silicon, allowing the photonics chip outputs closer to the ion trap, improving alignment and packaging processes. The alignment must be accurate to < 1 µm to ensure that the light from the waveguide can overlap with the trapping region. This fine alignment must also be maintained through an ultra-high vacuum bake, a critical step in preparing an ion trap experiment. By combining separate chips, we demonstrate a new path for scaling trapped ion technology that is less reliant on monolithic integration. We successfully fabricated a trap with a large area of oxide removed, resulting in a region thinned to about 40 µm, a key milestone toward successful integration.

42 ENGINEERING↗

Uniform Recalibration of Common Spectrophotometry Standard Stars onto the CALSPEC System Using the SuperNova Integral Field Spectrograph

Abstract We calibrate spectrophotometric optical spectra of 32 stars commonly used as standard stars, referenced to 14 stars already on the Hubble Space Telescope–based CALSPEC flux system. Observations of CALSPEC and non-CALSPEC stars were obtained with the SuperNova Integral Field Spectrograph over the wavelength range 3300–9400 Å as calibration for the Nearby Supernova Factory cosmology experiment. In total, this analysis used 4289 standard-star spectra taken on photometric nights. As a modern cosmology analysis, all presubmission methodological decisions were made with the flux scale and external comparison results blinded. The large number of spectra per star allows us to treat the wavelength-by-wavelength calibration for all nights simultaneously with a Bayesian hierarchical model, thereby enabling a consistent treatment of the Type Ia supernova cosmology analysis and the calibration on which it critically relies. We determine the typical per-observation repeatability (median 14 mmag for exposures ≳5 s), the Maunakea atmospheric transmission distribution (median dispersion of 7 mmag with uncertainty 1 mmag), and the scatter internal to our CALSPEC reference stars (median of 8 mmag). We also check our standards against literature filter photometry, finding generally good agreement over the full 12 mag range. Overall, the mean of our system is calibrated to the mean of CALSPEC at the level of ∼3 mmag. With our large number of observations, careful cross-checks, and 14 reference stars, our results are the best calibration yet achieved with an integral-field spectrograph, and among the best calibrated surveys.

79 ASTRONOMY AND ASTROPHYSICS↗

Evaluation of AI-enabled Digital Documented Safety Analysis

The National Reactor Innovation Center (NRIC) is leading a transformative initiative to accelerate advanced reactor deployment by fundamentally reimagining how nuclear safety basis documentation is developed, reviewed, and maintained. Traditional Documented Safety Analysis (DSA) processes for DOE-authorized facilities rely on static, document-centric workflows that consume significant time and resources, exemplified by recent major licensing efforts requiring hundreds of thousands of staff hours and millions of pages of documentation review. These conventional approaches create barriers to the rapid, cost-effective deployment of advanced reactors that America's future energy needs demand. NRIC's DOE Authorization Digital Transformation Project addresses these challenges through an innovative framework that integrates artificial intelligence (AI), digital engineering, and systems-based data management into a cohesive digital ecosystem. This white paper presents NRIC's methodology for evaluating AI-enabled document generation capabilities within this broader digital infrastructure, using the Demonstration of Microreactor Experiments (DOME) facility as a pilot case study. The evaluation will assess an AI tool's ability to generate a Preliminary Documented Safety Analysis (PDSA) through progressive integration stages—from standalone document processing to full digital thread connectivity—while maintaining rigorous verification, validation, and regulatory acceptance standards. By establishing dynamic, traceable connections between design data and safety documentation, NRIC's approach has the potential to reduce both document development time and regulatory review cycles by as much as 50%, while simultaneously improving accuracy, consistency, and traceability. This initiative represents a critical step toward establishing reusable digital infrastructure that reactor developers can leverage to accelerate their path from concept to commercial operation, directly supporting NRIC's mission to demonstrate and deploy advanced nuclear energy technologies.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗

Computational Estimation by Scientific Data Mining with Classical Methods to Automate Learning Strategies of Scientists

Experimental results are often plotted as 2-dimensional graphical plots (aka graphs) in scientific domains depicting dependent versus independent variables to aid visual analysis of processes. Repeatedly performing laboratory experiments consumes significant time and resources, motivating the need for computational estimation. The goals are to estimate the graph obtained in an experiment given its input conditions, and to estimate the conditions that would lead to a desired graph. Existing estimation approaches often do not meet accuracy and efficiency needs of targeted applications. We develop a computational estimation approach called AutoDomainMine that integrates clustering and classification over complex scientific data in a framework so as to automate classical learning methods of scientists. Knowledge discovered thereby from a database of existing experiments serves as the basis for estimation. Challenges include preserving domain semantics in clustering, finding matching strategies in classification, striking a good balance between elaboration and conciseness while displaying estimation results based on needs of targeted users, and deriving objective measures to capture subjective user interests. These and other challenges are addressed in this work. The AutoDomainMine approach is used to build a computational estimation system, rigorously evaluated with real data in Materials Science. Our evaluation confirms that AutoDomainMine provides desired accuracy and efficiency in computational estimation. It is extendable to other science and engineering domains as proved by adaptation of its sub-processes within fields such as Bioinformatics and Nanotechnology.

Computer Science↗

Study of charm hadronization with prompt $ {\Lambda}_{\textrm{c}}^{+} $ baryons in proton-proton and lead-lead collisions at $ \sqrt{s_{\textrm{NN}}} $ = 5.02 TeV

The production of prompt $ {\Lambda}_{\textrm{c}}^{+} $ baryons is measured via the exclusive decay channel $ {\Lambda}_{\textrm{c}}^{+}\to p{\textrm{K}}^{-}{\pi}^{+} $ at a center-of-mass energy per nucleon pair of 5.02 TeV, using proton-proton (pp) and lead-lead (PbPb) collision data collected by the CMS experiment at the CERN LHC. The pp and PbPb data were obtained in 2017 and 2018 with integrated luminosities of 252 and 0.607 nb$^{−1}$, respectively. The measurements are performed within the $ {\Lambda}_{\textrm{c}}^{+} $ rapidity interval |y| < 1 with transverse momentum (p$_{T}$) ranges of 3–30 and 6–40 GeV/c for pp and PbPb collisions, respectively. Compared to the yields in pp collisions scaled by the expected number of nucleon-nucleon interactions, the observed yields of $ {\Lambda}_{\textrm{c}}^{+} $ with p$_{T}$> 10 GeV/c are strongly suppressed in PbPb collisions. The level of suppression depends significantly on the collision centrality. The $ {\Lambda}_{\textrm{c}}^{+} $/D$^{0}$ production ratio is similar in PbPb and pp collisions at p$_{T}$> 10 GeV/c, suggesting that the coalescence process does not play a dominant role in prompt $ {\Lambda}_{\textrm{c}}^{+} $ baryon production at higher p$_{T}$.[graphic not available: see fulltext]

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Higher Efficiency, Demand Flexible Refrigerator with On-Demand Micro-Vibrational De-icing Technology

Refrigerator technology has advanced significantly over the last couple of decades. Today’s refrigerators use only about 25% of the energy that was required to power models built in 1975. Even as they continually improve efficiency to meet standards, refrigerators have increased in size by almost 20%, added energy-consuming features such as through-the-door ice, and provide more benefits than ever before. However, a few challenges and technology gaps are preventing further improvement of the demand responsiveness and efficiency of the refrigerators. One of the major technology gaps in existing refrigerators is their outdated de-icing process. When the evaporator generates frost, an old-fashioned resistive heating element melts the ice. Most refrigerators have a timed defrost cycle, rather than an active system that could monitor the state of the frost. In these systems, not only is the precious electricity used at its least efficient form of conversion (direct conversion of electricity to heat), but also all the latent heat associated with the ice is wasted during the melting process. On top of that, the refrigerator needs to work harder to pull the temperature down after defrosting, and, last but not least, the food quality is severely impacted by the temperature swings during the defrost cycle. According to a study, the EU alone wastes 89 million tons of food in the supply chain every year. Any temperature swing during defrosting (about 6F according to Emerson for low-temperature cases) can negatively impact the shelf life of meat and other products for multiple days. All these issues can happen during the peak demand time of the electric grid. Unlike the conventional systems, the proposed novel advanced micro-vibrational deicing process uses no heat for defrosting. Instead, it uses the micro vibrations generated by a piezoelectric or vibration-generating module to mechanically break ice from the heat exchanger almost instantaneously. The project titled “Higher Efficiency, Demand Flexible Refrigerator with On-Demand Micro-Vibrational De-icing Technology, performed by Ultrasonic Technology Solutions, LLC (UTS) of Knoxville, TN, in collaboration with Emerson (now Copeland), represents the final phase of a multi-year effort funded under the U.S. Department of Energy’s Building Technologies Office (BTO) BENEFIT FOA 2020. Initiated on October 1, 2021, and completed after a nine-month no-cost extension ending September 30, 2025, this project aimed to develop and validate a novel micro-vibrational mechanical defrosting system, achieving more than 25% improvement in defrosting energy efficiency over conventional baseline defrosting technologies. Over sixteen quarters, the project advanced from fundamental ice-mechanical characterization and prototype development to full-scale system integration and validation. Initial efforts established project management infrastructure and characterized ice adhesion properties, followed by the design and fabrication of early aluminum-based prototypes for resonance frequency testing. Subsequent quarters saw rapid technical progression, including the identification of optimal piezoelectric and motor-based vibration mechanisms, the demonstration of effective de-icing over 6x6-inch aluminum surfaces. The team achieved its Go/No-Go milestone by exceeding the 25% energy-efficiency improvement target—reaching up to 3,340% under optimized conditions—and later confirmed that motor-driven systems offered superior performance and energy efficiency compared to piezoelectric alternatives. Continued refinement led to the development of amplifier systems on printed circuit boards, improved control and instrumentation hardware, and integration into full-scale heat exchanger (HX) prototypes at both UTS and Copeland facilities. Multiple vibration-mounting studies and frost-growth experiments guided mechanical optimization and noise-mitigation strategies, achieving a 17.5 dB reduction in sound pressure level and verifying robust mechanical performance. Advanced analyses, including modal and harmonic simulations, established a quantitative understanding of vibrational behavior and de-icing efficiency across >1000 cm² systems. The final project phase successfully demonstrated scalable integration within reach-in and chest freezer prototypes, confirmed >25% efficiency improvements in large-area systems, and completed a comprehensive business model and scale-up strategy identifying electric defrost systems as the primary beachhead market. The culmination of this DOE-supported effort establishes micro-vibrational defrosting as a viable, high-efficiency, low-noise, and demand-flexible de-icing technology, paving the way for commercial deployment and broader application in next-generation refrigeration systems.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Control And Optimization Modular Modeling Application For Nuclear Deployment

The purpose of the COMMAND code is to provide a flexible, scalable tool for use in developing, integrating, and testing the technologies necessary for achieving autonomous operations of advanced nuclear reactors. The code enables users to efficiently implement custom simulations and experiments by combining key methods from different software modules. These modules are focused on: modeling and simulation tools, such as nuclear simulation tools used for high-fidelity modeling (e.g., Reactor Excursion and Leak Analysis Program [RELAP5-3D] and Monte Carlo N-Particle [MCNP]); machine learning and optimization tools (e.g., anomaly detection and data-driven modeling techniques); advanced control in its digital, high-performance, and supervisory control forms (e.g., proportional integral derivative (PID) control and model predictive control (MPC); and integration with hardware through industrial communication protocols. To ensure flexibility and scalability, COMMAND was designed to be both modular—the software “pieces” all inherit from generic building blocks and can be combined and connected to create complicated simulations—and high performing—designed for parallel processing, enabling simulations and experiments to take advantage of multi-core computers, servers, and nodes. The code is written in the Python programming language due to the language's popularity, active community, and open-source and cross-platform nature. Maintaining consistency with other simulation tools used within the nuclear energy community, users implement simulations and experiments through text input files, which define components, parameters, connections, etc., through lines of text. Given that COMMAND is written in Python, these input files are native Python scripts, and so use the standard Python structure and formatting. This also enables users to take advantage of Python's extensive package library to develop custom capabilities for their specific use cases.

Faber, Jacob [Idaho National Laboratory (INL), Ida↗

Is there a Perfect D and D Plan - 20100

Problems with many Deactivation and Demolition (D and D) projects arise not necessarily from the technical difficulty of the actions required in a given facility, but rather from lack of integration of the stove piped planning efforts; engineering, operations, environmental, radiological, human resources, etc. This paper will cover Polestar Technical Service, Inc. (Polestar) systems engineering approach to D and D planning based on the company's experience over the past 27 years. This systematic, four-pronged approach to planning is applicable to any D and D project and addresses several diverse topics in a cohesive and integrated manner. The four areas to be discussed are project scope, requirements, facility end state, work force and base operations. This approach progresses a facility through the typical DOE life-cycle from operations, through deactivation, into surveillance and maintenance (S and M) and to eventual demolition and site remediation. To achieve a final end state the approach brings together the efforts associated with identifying and managing the right set of requirements, detailing the scope of work, establishing the baseline, redefining the work processes, aligning the workforce resources with the work processes, and maintaining the base operations activities as the project progresses through the various life-cycle stages. Getting these building blocks right provides a solid framework for executing any D and D project. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Development of Corrosion Resistant Coatings for Structural Materials for Liquid Fueled Molten Salts Reactors Applications (Final Report)

Current structural alloys, code certified for the MSRs temperature ranges, contain high levels of chromium, making them highly susceptible to molten halide salt corrosion. One potential solution to circumvent the need for code certification of novel alloys, which is expensive and time consuming, is to design claddings that will protect the underlying code certified materials from corrosion damage during operation. In this work, we examined the corrosion of Ni and Cu electroplated, Ni and CuNi weld overlay, Mo-laser clad, and carburized claddings on SS316H for use in molten salt reactor environments. After characterization of the cladded materials (Task 1), static corrosion tests were used to assess corrosion resistance of the claddings in typical molten fluoride salts (Task 2). The corrosion tests were performed in molten FLiNaK at 700°C up to 1000 hours. Pre- and post-corrosion Scanning Electron Microscopy (SEM), energy-dispersive-spectroscopy (EDS), Transmission Electron Microscopy (TEM), X-ray Diffraction (XRD) and glow-discharge-optical-emission-spectroscopy (GDOES) were performed on cladding cross-sections and surfaces to evaluate degradation. The Cu and Ni electroplated samples, as well as the carburized samples, showed excellent corrosion resistance relative to the bare SS316H. To assess high temperature cladding stability, ageing experiments were performed at temperatures up to 900 C in inert atmosphere for the electroplated and carburized samples and a diffusion model was developed to predict long term cladding behavior (Task 3). It was found that the Cu cladding was basically insensitive to the high temperature ageing, except for small secondary phases forming at the interface. On the other hand, the Ni electroplated cladding experienced significant interdiffusion. Nevertheless, the gain in corrosion resistance for a 100μm Ni electroplated cladding is phenomenal, with more than 50% reduction in chromium dissolution from the substrate material for the first 15 years of salt exposure at 700°C. To assess radiation resistance and phase stability, high-temperature 4MeV Ni heavy ion irradiation was performed across the cladding/substrate interface up to 50 displacement-per-atom (DPA) at 500°C and 700°C to assess the phase stability and irradiation behaviors of the electroplated systems (Task 4). The Ni and Cu electroplated systems did not experience void swelling at the contrary to the SS316H substrate due to their nanocrystalline nature. Some level of recrystallization was observed in the cladding, as well as radiation induced segregation and enhanced diffusion. The interface acted as a potent sink for point defects with the presence of a void denuded zone. The mechanical properties of the claddings were assessed using thermal shock, micro-indentation, nano-indentation, and four-point bend testing experiments (Task 5). These experiments were performed on the claddings in as-received, corroded, irradiated, and thermally aged states to determine the effects of typical molten salt reactor environments on cladding integrity. No significant mass loss was observed after repeated thermal shocks. While the electroplated samples softened after high-temperature ageing, irradiation hardening compensate this effect, such that there is little different with the as-received materials. The results of these experiments suggest that the electroplated (copper/nickel) show the greatest promise for application in molten salt reactor development. These claddings prevented any chromium dissolution from occurring during the static corrosion experiments. Additionally, they demonstrated favorable properties for high temperature diffusion, phase stability, interfacial mechanical properties, and irradiation resistance. Weld-overlay cladding are also of great interest and could reach properties similar to the electroplated samples upon optimization (especially with multiple weld passes). The carburized SS316H showed excellent behavior as well, but more work needs to be done to assess their long-term stability. Finally, the Mo-laser clad system was not pursued further due to the manufacturing challenges. It is also worth noting that the Ni cladding systems should behave relatively well in terms of weldability since the Ni-weld overlay microstructure and associated corrosion rate are sound. While the NiCu weld-overlay has even lower corrosion rates than the Ni-weld overlay, more studies on welding of Cu-electroplated systems are necessary since Cu clusters are known to embrittle steels.

36 MATERIALS SCIENCE↗

Strategy and performance of the CMS long-lived particle trigger program in proton-proton collisions at $\sqrt{s}$ = 13.6 TeV

In the physics program of the CMS experiment during the CERN LHC Run 3, which started in 2022, the long-lived particle triggers have been improved and extended to expand the scope of the corresponding searches. These dedicated triggers and their performance are described in this paper, using several theoretical benchmark models that extend the standard model of particle physics. The results are based on proton-proton collision data collected with the CMS detector during 2022$-$2024 at a center-of-mass energy of 13.6 TeV, corresponding to integrated luminosities of up to 123 fb$^{-1}$.

FOS: Physical sciences↗

RESCue Model (RESCue Experiment and Model) [SWR-24-84]

The Renewable Energy and Storage Cybersecurity Research (RESCue) project is a collaborative effort aimed at securing the rapidly growing deployment of transmission-connected hybrid renewable energy systems, consisting of a combination of wind, solar, and/or energy storage equipment, against escalating cyber threats. This project brings together major original equipment manufacturers (OEMs) of wind, solar, and energy storage, along with major asset owners and DOE National Laboratories, to collectively identify cyber threats, assess risks, and develop robust cybersecurity strategies and solutions. The development of hybrid reference architectures has provided comprehensive blueprints for the secure design and integration of hybrid renewable energy systems, accounting for their unique characteristics and interdependencies. Additionally, NREL has created a cyber-resilient design framework that integrates cybersecurity considerations from the start of the system lifecycle, ensuring security is "baked in" from the initial design phase. The research thrusts for the project included (i) development of hybrid reference architectures and (ii) a cyber-resilient design framework for hybrid energy systems. The reference architectures has provided comprehensive blueprints for the secure design and integration of hybrid renewable energy systems, accounting for their unique characteristics and interdependencies. Additionally, NREL has created a cyber-resilient design framework that integrates cybersecurity considerations from the start of the system lifecycle, ensuring security is "baked in" from the initial design phase. A demonstration experiment was developed for one of the architectures using NREL's Cyber Range resources. This experiment configuration, deployable using open-source tools, is provided here in this repository. Additional models were developed for the wind and solar architectures as well, however the configurations for only the Energy Storage scenario are provided here: https://www.nrel.gov/docs/fy24osti/89921.pdf

Hasandka, Adarsh↗

Resolved resonance region evaluations of n+ 206,207,208 Pb for fast spectrum applications

Resolved resonance region evaluations of the major isotopes of natural lead, 206 Pb, 207 Pb, 208 Pb, have been per formed to support the development of Generation IV reactors. In this study, validation of nuclear data for lead fast reactors was performed with simulations of shielding benchmarks, integral critical benchmarks, and quasi-differential scattering measurements. Sensitivity analyses of these systems showed that elastic scattering reactions above 100 keV were the dominant reactions driving system performance. The resolved resonance regions (RRRs) of the lead isotopes extend past 100 keV, making the RRR an ideal starting point to evaluate lead cross sections. Since the R-matrix requires knowledge of bound, distant, and observed resonances, it was necessary to evaluate from 10 -5 eV up to the respective limit of the RRR. The 208 Pb RRR evaluation was extended to 1.5 MeV in order to obtain resonance parameters used to calculate new elastic scattering angular distributions up to 1.5 MeV. Resonance parameter uncertainties and covariance were generated using the R-matrix code SAMMY. The new RRR parameters show a direct improvement to the scattering kernel below 1.5 MeV which in turn greatly improves fast critical experiments over ENDF/B-VIII.0.

206Pb↗

Perturbative analysis of low-frequency instabilities in high-field ST40 experiments

Abstract Linear and nonlinear perturbative analyses of low-frequency instabilities are presented for ST40 spherical torus high field plasmas, with simultaneous neutral beam heating due to two tangential sources at 25 keV and 55 keV. Initial plasma profiles on which the TRANSP and NUBEAM codes were based were obtained using an integrated analysis of several diagnostics including line-of-sight integrated and volume average measurements, as well as limited profile information from a charge-exchange-recombination spectrometer. Magnetohydrodynamics (MHD) analysis using the NOVA/NOVA-K codes suggests that the modes in the experiments are core-localized n = 1 eigenmodes with mixed acoustic and electromagnetic Alfvénic polarization. The global transport combined with the perturbative mode analysis indicates that there is greater tendency for bursty chirping response as the level of background micro-turbulence decreases in time and those predictions are shown to be consistent with the experimental data. This finding is interpreted in terms of the suppression of coherent phase-space structures that support chirping when the resonant fast ion dynamics is dominated by frequent stochastic, orbit-decorrelating events.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Measurement of the CKM angle γ with B ± → D[K ∓ π ± π ± π ∓ ]h ± decays using a binned phase-space approach

The CKM angle γ is determined from CP-violating observables measured in B ± → D[K ∓ π ± π ± π ∓ ]h ± , (h = K, π) decays, where the measurements are performed in bins of the decay phase-space of the D meson. Using proton-proton collision data collected by the LHCb experiment at centre-of-mass energies of 7, 8 and 13 TeV, corresponding to a total integrated luminosity of 9 fb –1 , γ is determined to be $\gamma ={\left(54.8\begin{array}{c}+6.0\\ {}-5.8\end{array}\begin{array}{c}+0.6\\ {}-0.6\end{array}\begin{array}{c}+6.7\\ {}-4.3\end{array}\right)}^{\circ },$ where the first uncertainty is statistical, the second systematic and the third from the external inputs on the coherence factors and strong phases of the D-meson decays.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗