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At least 199 records · Page 11

Grid-based minimization at scale: Feldman-Cousins corrections for SBN

We present a computational model for the construction of Feldman-Cousins (FC) corrections frequently used in High Energy Physics (HEP) analysis. The program contains a grid-based minimization and is written in C++. Our algorithms exploit vectorization through Eigen3, yielding a single-core speed-up of 350 compared to the original implementation, and achieve MPI data parallelism by using DIY. We demonstrate the application to scale very well at High Performance Computing (HPC) sites. We use HDF5 in conjunction with HighFive to write results of the calculation to file.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Topological Machine Learning Methods for Power System Responses to Contingencies: Preprint

While deep learning tools, coupled with the emerging machinery of topological data analysis, are proven to deliver various performance gains in a broad range of applications, from image classification to biosurveillance to blockchain fraud detection, their utility in areas of high societal importance such as power system modeling and, particularly, resilience quantification in the energy sector yet remain untapped. To provide fast acting synthetic regulation and contingency reserve services to the grid while having minimal disruptions on customer quality of service, we propose a new topologybased system that depends on neural network architecture for impact metrics classification and prediction in power systems. This novel topology-based system allows one to evaluate the impact of three power system contingency types, namely, in conjunction with transmission lines, transformers, and transmission lines combined with transformers. We show that the proposed new neural network architecture equipped with local topological measures facilitates both more accurate classification of unserved load as well as the amount of unserved load. In addition, we are able to learn complex relationships between electrical properties and local topological measurements on the simulated response to contingencies for NREL-SIIP power system.

graph theory↗

Dataset Repository for Investigating Suicide Risk Using Social and Environmental Determinants of Health

Suicide is frequently modeled as a function of genetics and environment, where the latter refers to factors other than direct biological consequences, such as air quality, financial level, social connectivity, transportation and food access, and homelessness status. According to the World Health Organization, clean air, a stable climate, adequate water, sanitation and hygiene, safe chemical use, radiation protection, healthy and safe workplaces, sound agricultural practices, health-supportive cities and built environments, and a preserved natural environment are all prerequisites for good health. Understanding the relationships between these determinants and mental health outcomes requires standardized data that can be included in healthcare programs and health outcome models. There is a wealth of publicly available data on social and environmental factors provided by various US organizations that can benefit the design of health care systems and public health interventions, as well as improve our comprehension of factors that impact health. Such information would not only help improve the understanding of individual and community risk but also identify new risk factors that have not previously been therapeutically targeted, especially in terms of their impact on mental health. However, curating and standardizing such datasets is challenging because they are often recorded at numerous geographical and temporal resolutions and with varying spatial and temporal granularities. To address this challenge, we launched an endeavor in conjunction with the Veterans Health Administration to collect publicly available socioeconomic and environmental determinants of health statistics in the US. In this manuscript, we describe a social and environmental determinants of health (SEDH) datasets repository, data curation documentation, and a pipeline framework for data generation; This effort started in 2020, when we began constructing a scalable pipeline to automate the download, extraction, preparation, analysis, and production of datasets. These datasets have been made available to the VHA and may be shared upon agreement with collaborating organizations.

60 APPLIED LIFE SCIENCES↗

Low-lying states and total internal partition sums of CH

The electronic structure and spin-orbit states of the CH radical have been systematically investigated using multi-reference configuration interaction (MRCI) and single-reference coupled-cluster (CC) methods. These calculations were performed in conjunction with large correlation-consistent basis sets of quadruple-, quintuple-, and sextuple-ζ quality. To achieve high accuracy, electronic energies for all states were extrapolated to the complete basis set (CBS) limit, enabling the detailed construction of potential energy curves and determination of reliable spectroscopic constants. Spin-orbit coupling effects were explicitly incorporated, and vibrational energy levels were computed via Numerov analysis. Furthermore, the resulting values exhibit good to excellent agreement with available experimental data. Dipole moment and transition dipole moment curves were evaluated to assess the opacity characteristics of CH, revealing that transitions such as Χ 2 Π (u′′ = 0) → Α 2 Δ (u′ = 0), Χ 2 Π (u′′ = 0) → Β 2 Σ − (u′ = 0), Χ 2 Π (u′′ = 0) → C 2 Σ + (u′ = 0), and Χ 2 Π (u′′ = 0) → D 2 Σ + (u′ = 3) are particularly probable. Finally, the total internal partition function sum (TIPS) of CH was computed over a broad temperature range (10–30,000 K) based on our high-accuracy ab initio results.

74 ATOMIC AND MOLECULAR PHYSICS↗

DESI 2024 VI: cosmological constraints from the measurements of baryon acoustic oscillations

We present cosmological results from the measurement of baryon acoustic oscillations (BAO) in galaxy, quasar and Lyman-α forest tracers from the first year of observations from the Dark Energy Spectroscopic Instrument (DESI), to be released in the DESI Data Release 1. DESI BAO provide robust measurements of the transverse comoving distance and Hubble rate, or their combination, relative to the sound horizon, in seven redshift bins from over 6 million extragalactic objects in the redshift range 0.1 < z < 4.2. To mitigate confirmation bias, a blind analysis was implemented to measure the BAO scales. DESI BAO data alone are consistent with the standard flat ΛCDM cosmological model with a matter density Ω m =0.295±0.015. Paired with a baryon density prior from Big Bang Nucleosynthesis and the robustly measured acoustic angular scale from the cosmic microwave background (CMB), DESI requires H 0 =(68.52±0.62) km s -1 Mpc -1 . In conjunction with CMB anisotropies from Planck and CMB lensing data from Planck and ACT, we find Ω m =0.307± 0.005 and H 0 =(67.97±0.38) km s -1 Mpc -1 . Extending the baseline model with a constant dark energy equation of state parameter w, DESI BAO alone requirew=-0.99 +0.15 -0.13 . In models with a time-varying dark energy equation of state parametrised by w 0 and w a , combinations of DESI with CMB or with type Ia supernovae (SN Ia) individually prefer w 0 > -1 and w a < 0. This preference is 2.6σ for the DESI+CMB combination, and persists or grows when SN Ia are added in, giving results discrepant with the ΛCDM model at the 2.5σ, 3.5σ or 3.9σ levels for the addition of the Pantheon+, Union3, or DES-SN5YR supernova datasets respectively. For the flat ΛCDM model with the sum of neutrino mass ∑ m ν free, combining the DESI and CMB data yields an upper limit ∑ m ν < 0.072 (0.113) eV at 95% confidence for a ∑ m ν > 0 (∑ m ν > 0.059) eV prior. These neutrino-mass constraints are substantially relaxed if the background dynamics are allowed to deviate from flat ΛCDM.

79 ASTRONOMY AND ASTROPHYSICS↗

High Resolution Fission Fragment Spectroscopy with Superconducting Microcalorimeters

Sub-1 AMU mass determination is important for determining fission yields and neutron multiplicity, which are necessary inputs for fission models. Fission models can improve spent nuclear waste stream analysis and nuclear fuel burnup determination. Here, to achieve this goal, we have used superconducting microcalorimeter detectors to directly measure the energy of fission fragments from the spontaneous fission of 252 Cf. With a fiber coupled LED pulser setup we demonstrate that we can reach a relative energy resolution of 0.1% and better for photon pulses with energies above 60 MeV. This instrument, in conjunction with time-of-flight (TOF) measurement, would allow for sub-1 atomic mass unit (AMU) mass determination of fission fragments in a future beamline application.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Accumulative Roll Bonding of Alloy 2205 Duplex Steel and the Accompanying Impacts on Microstructure, Texture, and Mechanical Properties

The mechanical and microstructural evolution of Alloy 2205 during severe plastic deformation is examined in this study. A combination of accumulative roll bonding (ARB) and cold rolling results in the successful formation of a nanograined dual-phase microstructure of austenite and ferrite with some transformed martensite. Severe deformation to cumulative reductions of 80.5, 92.5, 95, and 97 pct were performed. Microscopy indicates that grain dimensions in the sheet normal direction is less than 100 nm for reductions ≥ 92.5 pct. Shear banding is observed at reductions ≥ 95 pct while twinning is only observed at reductions < 92.5 pct. Neutron diffraction measurements indicated the presence of martensite for reductions ≥ 95 pct at ~ 8 pct volume fraction. Taken in conjunction, it appears that during initial ARB processing, both slip and twinning are active plastic mechanisms. As twinning becomes exhausted, martensitic transformation, slip, and intermittent shear banding account for the active plasticity mechanisms. Material hardness saturates at 92.5 pct reduction, with a maximum hardness of 45 HRC. Sub-sized tensile testing confirms this approximate hardness with measurements indicating a UTS of ~ 1440 MPa. Texture analysis of crystal orientation distributions in the plate normal direction suggest an approximate Kurdjumov–Sachs orientation relationship at all reductions above 80 pct indicating stability of the orientation relationship at high strains. The intragranular structure develops a fine scale sub-grain content with increasing deformation, resulting in a continual evolution of texture up to and including 97 pct reduction. The final structure presents strong components of Goss and rotated cube texture in both the austenite and ferrite. In this body of work we aim to compare ARB of an industrially relevant FCC/BCC system (Alloy 2205) to historical model FCC/BCC systems such as Cu/Nb.

36 MATERIALS SCIENCE↗

Conditioning the Surface and Bulk of High-Nickel Cathodes with a Nb Coating: An In Situ X-ray Study

Surface coating is commonly employed by industries to improve the cycling and thermal stability of high-nickel (Ni) transition metal (TM) layered cathodes for their practical use in lithium-ion batteries. Niobium (Nb) coating or substitution has been shown to be effective in stabilizing LiNi 0.8 Mn 0.1 Co 0.1 O 2 (NMC811) cathodes; in addition, the electrochemical performance of the final products varies depending on the postprocessing. In this follow-up study, we use in situ synchrotron X-ray diffraction to investigate the kinetic processes and the involved structural evolution in Nb-coated NMC811 upon heat treatment. Furthermore, quantitative structure analysis reveals thermally driven concurrent changes in the bulk and surface, in particular, the phase evolution of the coating layer and Nb/TM interdiffusion that facilitates penetration of Nb into the bulk and particle growth at the increased temperatures. Findings from this study highlight the new opportunities for the intended control of the structure and surface properties of high-Ni cathodes through surface coating in conjunction with postprocessing.

36 MATERIALS SCIENCE↗

Deep Direct-Use Geothermal Feasibility Study for Hawthorne NV

The Hawthorne Nevada, deep direct-use geothermal study is a two-year effort funded by the U.S. Department of Energy to determine the techno-economic feasibility of implementing a large-scale, direct-use facility for the Hawthorne Army Depot (HAD) and the public facilities of the city of Hawthorne and Mineral County. The approach links a production side analysis (PSA) and a demand side analysis (DSA) into a whole-system analysis (WSA) to provide an integrated assessment of the resource and the probability of delivering economically viable direct-use energy to Hawthorne. Hawthorne, Nevada is in the western part of the Basin and Range province and has been the focus of geothermal investigations for over 40 years. Over the last 15 years, several studies completed by the U.S. Navy Geothermal Program Office (GPO) in conjunction with industry professionals quantified the existence of several low temperature geothermal prospects, the most promising of which is called Prospect A. The promise of Prospect A is based on drilling and flow testing that produced ~100 °C water at flow rates of up to 31 l/s (500 gallons per minute). Measured productivity indexes range from 40-85 l/s/MPa, suggesting a warm and productive heat source. Despite the promise of the resource, uncertainties in its spatial extent and long-term sustainability mean that techno-economic analyses must include probabilities of the sustainability of the resource under different operating scenarios. Here, the PSA is conducted by integrating a wide range of disparate data to estimate lognormal P90, P50, and P10 resource capacities. These capacities are used as input to a thermal-hydrologic (T-H) model to estimate thermal drawdown for each capacity estimate for several different DSA scenarios. Using a systems-based approach, the WSA links the dynamic T-H simulations of the PSA/DSA combinations with the techno-economic model GEOPHIRES to account for both the temporal dynamics and uncertainties in the system to produce probabilistic distributions of several performance metrics including the levelized cost of heat (LCOH) and the return on investment (ROI). This report is the final delivery for the project and documents the study's activities and results.

15 GEOTHERMAL ENERGY↗

Kinetic equilibrium reconstructions of plasmas in the MAST database and preparation for reconstruction of the first plasmas in MAST upgrade

Reconstructions of plasma equilibria using magnetic sensors were routine during operation of the Mega Ampere Spherical Tokamak (MAST) device, but reconstructions using kinetic profiles were not. These are necessary for stability and disruption analysis of the MAST database, as well as for operation in the upgrade to the device, MAST-U. The three-dimensional (3D) code VALEN is used to determine eddy currents in the 3D vessel structures for vacuum coil test shots, which are then mapped to effective resistances in the two-dimensional vessel groupings in the EFIT equilibrium reconstruction code to be used in conjunction with nearby loop voltage measurements for estimated currents in the structures during reconstruction. Kinetic equilibrium reconstructions with EFIT, using all available magnetic sensors as well as Thomson scattering measurements of electron temperature and density, charge exchange recombination spectroscopy measurements of ion temperature, and internal magnetic field pitch angle measurements from a motional Stark effect (MSE) diagnostic are performed for a large database of MAST discharges. Excellent convergence errors are obtained for the portions of the discharges where the stored energy was not too low, and it is found that reconstructions performed with temperature and density measurements but without MSE data usually already match the pitch angle measurements well. A database of 275 kinetic equilibria is used to test the ideal MHD stability calculation capability for MAST. In conclusion, the necessary changes to conducting structure in VALEN, and diagnostic setup in EFIT have been completed for the upgrade from MAST to MAST-U, enabling kinetic reconstructions to commence from the first plasma discharges of the upgraded device.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Results from the Advanced Scintillator Compton Telescope (ASCOT) Balloon Payload

The Advanced Scintillator Compton Telescope (ASCOT) is a medium-energy gamma-ray Compton telescope flown on NASA’s high-altitude scientific balloon from Palestine, TX on 5th July 2018. It uses commercially available highperformance scintillators like Cerium Bromide (CeBr3) and p-terphenyl along with compact readout devices - silicon photomultipliers (SiPMs) - for an improved instrument response. ASCOT was built to address the existing need for observations in the gamma-ray energy range of 0.4 - 20 MeV. Operating stably throughout the mission, it reached an altitude of 120,000 ft and observed the Crab Nebula at MeV energies for ~5 hours. Built on the legacy of COMPTEL (onboard CGRO), along with the hardware advancement ASCOT also makes use of the Time-of-Flight (ToF) background rejection technique for effective imaging. Presented here is the Energy and ToF calibrated flight data with optimal data cuts (Earth Horizon Cut, Pulse Shape Discrimination Cut). The growth curves generated using this data from 5 to 100 g/cm2 of residual atmosphere in conjunction with the Monte Carlo simulations of the instrument response have been used to obtain the Cosmic Diffuse Gamma-ray (CDG) flux value of (1.28 ± 0.37)×10 -5 photons/cm 2 /s/sr/keV for 0.4 – 0.7 MeV energy range. The 3σ upper limit for CDG flux is 1.8×10-5 photons/cm 2 /s/sr/keV for 0.7-1.5 MeV and 2×10-6 photons/cm2/s/sr/keV for 1.5-2.5 MeV. The analysis of the Crab Nebula from flight observation is underway

79 ASTRONOMY AND ASTROPHYSICS↗

Advancing Solar Innovation for Low and Moderate-Income Households (Final Technical Report)

The overarching goal of this project was to deepen the understanding of the social and economic aspects of solar adoption, with a specific eye towards any pathways or barriers that could be identified that directly impact low and moderate-income households. Specific objectives included (1) identifying and assessing significant non-economic barriers that complicate the ability of LMI households to adopt and benefit from solar, even under scenarios with low economic barriers; (2) assessing the differential ability of groups to benefit from solar adoption based on their ability to invest in different solar innovations; (3) explaining why some LMI communities nonetheless experience significantly higher rates of solar adoption and benefit than others; (4) developing a methodological model for generating data addressing key issues to the project; and (5) designing and developing an interactive web portal that aggregates existing datasets, provides researchers trend analysis capabilities, standardizes project protocols for other states and communities; provides the opportunities for researchers using the same protocol in other communities to upload their results; and engages with the general public by providing them the ability to upload their own perspectives and stories of solar technology adoption. Through a common framework for conducting semi-structured field interviews. In partnership with cooperative extension services, in conjunction with survey research and the aggregation of existing solar adoption datasets, this study has identified that currently ,there is a strong values alignment and knowledge access challenge that continues to affect solar adoption. Participants in this study – many of whom are either low or moderate-income and/or live in underserved rural communities do not believe solar is an option where they live or believe solar is appropriate for their lifestyle. This perception challenge is further exacerbated by the absolute dearth of adopters in most communities and a total lack of local marketing for solar energy. What marketing that does exist is geared towards audiences other than those in the participant's community, reinforcing a perception that 22% of survey respondents (n = 1,551) have: that solar energy is not meant for them and their community. Overcoming these serious human challenges pertaining to knowledge and marketing are critical to reducing the customer acquisition costs incurred amongst LMI communities and especially those in rural America where the opportunities solar provides to increase local energy resilience, security, all while engaging in personal stewardship of the planet could align with local values. Community-Based Social Marketing, built in partnership with community leaders and geared towards meeting local visions of ideal life, is a near term opportunity to bridge the gap between local priorities and national market and policy imperatives for solar while moving towards the administration's goals for renewable energy as part of a just and equitable decarbonization program. The tools and methods developed for this study can serve as a template for identifying other specific local challenges for solar adoption in other state, and provide the opportunity for a common data framework for understanding system-wide trends and barriers to achieving uptake of residential solar in communities that may, ultimately, benefit the most from the technology.

14 SOLAR ENERGY↗

Emissions Characterization for Ammonia Fuel Blends in an Enclosed Swirl-Stabilized Diffusion Burner

This study investigates ammonia flames using the enclosed Sydney swirl burner (ESSB), focusing on detailed global emissions measurements. Emissions were measured via Fourier-transform-infrared (FTIR) spectrometer, utilizing a heated, long-path absorption cell. Hot, wet measurements of pertinent species were collected, and concentrations were determined via lineshape fitting in conjunction with the HITRAN database. Results show that partially cracked ammonia compositions yield lower emissions compared to pure NH3/H2, and small amounts of NH3 addition to CH4-containing fuel blends exhibit high levels of NOx and CO, with measurable HCN and unburnt CH4. Equilibrium calculations suggest trade-offs between chemical timescale, heat loss, and mixing. Future work will explore emissions sampling procedures and expand analysis using chemical reactor network modelling.

ammonia combustion↗

Analysis on the Preliminary Gap Conductance Test with Single Primary Heat Extraction and Removal Emulator

Microreactor is a type of nuclear reactor that is intended to produce thermal energy from the micro and integrated design. Among various microreactor roadmaps, microreactor with heat pipes is one of the promising designs that under active development. At Idaho National Laboratory (INL) and supported by the Department of Energy (DOE) Microreactor Program (MRP), a Single Primary Heat Extraction and Removal Emulator (SPHERE) was developed. The main purpose of SPHRE is to understand thermal performance of heat pipe in the conjunction of heat source without using nuclear material. The heat pipe used in the SPHERE has sodium as a working fluid, with Argon gas in the vapor region, thus this heat pipe is variable conductance heat pipe (VCHP). The volume of non-condensable gas changes with power and elapsed time, so the area covered by non-condensable gas changes. This gives an effect that passively controls the cooling capability of condenser section. This preliminary experiment was intended to perform a gap conductance experiment that reveals heat transfer characteristics of gas at the gap around the heat pipe. However, there are not many experimental data that deals with heat transfer of the gas at the gap around heat pipe. In this research, the preliminary experimental result regarding to the heat pipe performance with different composition of gas at the gap, level of power is presented. The experimental data will be used for the validation study of SOCKEYE as a future plan.

42 ENGINEERING↗

Machine learning enabling high-throughput and remote operations at large-scale user facilities

Imaging, scattering, and spectroscopy are fundamental in understanding and discovering new functional materials. Contemporary innovations in automation and experimental techniques have led to these measurements being performed much faster and with higher resolution, thus producing vast amounts of data for analysis. These innovations are particularly pronounced at user facilities and synchrotron light sources. Machine learning (ML) methods are regularly developed to process and interpret large datasets in real-time with measurements. However, there remain conceptual barriers to entry for the facility general user community, whom often lack expertise in ML, and technical barriers for deploying ML models. Herein, we demonstrate a variety of archetypal ML models for on-the-fly analysis at multiple beamlines at the National Synchrotron Light Source II (NSLS-II). We describe these examples instructively, with a focus on integrating the models into existing experimental workflows, such that the reader can easily include their own ML techniques into experiments at NSLS-II or facilities with a common infrastructure. The framework presented here shows how with little effort, diverse ML models operate in conjunction with feedback loops via integration into the existing Bluesky Suite for experimental orchestration and data management.

36 MATERIALS SCIENCE↗

Full-field quantitative visualization of shock-driven pore collapse and failure modes in PMMA

The dynamic collapse of pores under shock loading is thought to be directly related to hot spot generation and material failure, which is critical to the performance of porous energetic and structural materials. However, the shock compression response of porous materials at the local, individual pore scale is not well understood. This study examines, quantitatively, the collapse phenomenon of a single spherical void in PMMA at shock stresses ranging from 0.4 to 1.0 GPa. Using a newly developed internal digital image correlation technique in conjunction with plate impact experiments, full-field quantitative deformation measurements are conducted in the material surrounding the collapsing pore for the first time. The experimental results reveal two failure mode transitions as shock stress is increased: (i) the first in situ evidence of shear localization via adiabatic shear banding and (ii) dynamic fracture initiation at the pore surface. Numerical simulations using thermo-viscoplastic dynamic finite element analysis provide insights into the formation of adiabatic shear bands (ASBs) and stresses at which failure mode transitions occur. Further numerical and theoretical modeling indicates the dynamic fracture to occur along the weakened material inside an adiabatic shear band. Finally, analysis of the evolution of pore asymmetry and models for ASB spacing elucidate the mechanisms for the shear band initiation sites, and elastostatic theory explains the experimentally observed ASB and fracture paths based on the directions of maximum shear.

42 ENGINEERING↗

Cell Dancoff-based embedded self-shielding capability for doubly heterogeneous particulate fuels in SCALE/Polaris

Polaris is a two-dimensional (2D) transport lattice physics capability in the SCALE code system for light-water reactor (LWR) analysis. SCALE/Polaris is being extended to treat doubly heterogeneous particulate fuels in LWRs with accident-tolerant fuels and prismatic high-temperature gas-cooled reactor (HTGR) fuel. Recently, a Dancoff-based Wigner-Seitz approximation capability based on the embedded self-shielding method (DWA-ESSM) was implemented into Polaris for efficient computation. A new double heterogeneity treatment capability based on DWA-ESSM in conjunction with the Hebert's collision probability method for double heterogeneity was developed and implemented for Polaris. The new capability was verified by performing benchmark calculations for the prismatic HTGR fuel compact problems with various design parameters through a code-to-code comparison between the Polaris and continuous-energy Monte Carlo results. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Persistent Acoustic Sensing for Monitoring A Reactor Facility

Measurements over the past few years, taking place within the Multi-Informatics for Nuclear Operations Scenarios project, show that infrasound and low-frequency acoustic monitoring can detect, and often quantify, activities that occur on-site at the High Flux Isotope Reactor. Observable activities include: crane translation, lifting, and lowering; differentiation between loaded and unloaded crane operations; access door opening and closing; vehicle operations; and cooling tower fan operations. Advanced data analytic and spectral feature extraction methods can be used to interpret selected signatures to reach a deeper understanding of different reactor activities. These measurements are being conducted using a network of smartphones that continuously operate in conjunction with cloud-based architectures. A recent addition to the system is the development and deployment of a real-time, cloud-based analytic framework that supports near-real-time alarming which can facilitate tip-and-cue protocols. This paper presents recent research in this area including the use of low-frequency acoustics to tip-off transfer operations and cue a more comprehensive analysis by other sensor networks.

42 ENGINEERING↗