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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 145 records · Page 8

Transmission electron microscopy of ion irradiated ODS MA956 samples

Oxide dispersion strengthened (ODS) alloys are promising candidate materials for the next generation advanced nuclear reactors due to their superior irradiation resistance and mechanical properties. To better understand the effect of irradiation on MA956, it is essential to study higher dose (50-100 dpa) samples, so that the general trend of microstructural evolution and the resulting radiation-hardening can be deduced. Currently, ion irradiations are considered the only way to achieve doses beyond ~50 dpa in a practical time frame relevant to alloy and welding development programs. This dataset contains TEM characterization results of ODS MA956 samples that were ion irradiated under different conditions: Sample #5 (1.25 dpa at 190℃); Sample #9 (50 dpa at 190℃); Sample #15 (1.25dpa under 320℃); and Sample 17 (25 dpa at 320℃). TEM characterization focused on the irradiation induced defects (dislocation lines and loops) using the on-zone axis bright field STEM technique. These data were collected using a FEI Tecnai G2 F30 S/TEM at Microscopy and Characterization Suite (MaCS) at Center for Advanced Energy Studies (CAES), Idaho Falls, ID. This project (ion irradiation and TEM studies) was supported by the U.S. Department of Energy, Office of Nuclear Energy under DOE Idaho Operations Office Contract DE-AC07-05ID14517 as part of Nuclear Science User Facilities award #18-14784 (PI: Ramprashad Prabhakaran, PNNL).

Prabhakaran, Ramprashad↗

NSUF RTE completion report for 23-4780: Microstructural Defect Induced Thermal Conductivity Reduction in Uranium Nitride and Thorium Nitride

Uranium nitride (UN) is known to have a higher thermal conductivity than traditional oxide fuels, which could lead to a more efficient energy transport and lower local temperature during its lifetime. But the thermal transport performance of UN in extreme environments has not been systematic studied. This study investigated the irradiation induced microstructural defects in UN and the impacts on thermal conductivity. The samples were produced by spark plasma sintering at University of Texas-San Antonio (UTSA), Los Alamos National Laboratory (LANL), and Idaho National Laboratory (INL). Thermal conductivity of UN before and after 2MeV proton irradiation were measured by using laser metrology at INL in a temperature range of 77-295K. Thermal conductivity measurements in this wide, cryogenic temperature range is critical to understand the phonon scattering mechanisms between the thermal energy carrier, phonons, and different types of irradiation-induced defects. In order to ensure the measurements were conducted in the same grains and minimize the impact of the local heterogeneities, the measurement locations were highlighted by fiducial marks using the focused ion beam (FIB) with grain orientation identified using the electron backscatter diffraction (EBSD) at the Center of Advanced Energy Studies (CAES). Irradiation experiment was conducted at the Ion Beam Laboratory at Texas A&M University (TAMU). A total of 6 samples were irradiated with different irradiation doses and temperatures. After irradiation, the microstructure was characterized by using Transmission Electron Microscope (TEM) at CAES (also in the FIB marks).

36 - MATERIALS SCIENCE↗

microTrait: A Toolset for a Trait-Based Representation of Microbial Genomes

Remote sensing approaches have revolutionized the study of macroorganisms, allowing theories of population and community ecology to be tested across increasingly larger scales without much compromise in resolution of biological complexity. In microbial ecology, our remote window into the ecology of microorganisms is through the lens of genome sequencing. For microbial organisms, recent evidence from genomes recovered from metagenomic samples corroborate a highly complex view of their metabolic diversity and other associated traits which map into high physiological complexity. Regardless, during the first decades of this omics era, microbial ecological research has primarily focused on taxa and functional genes as ecological units, favoring breadth of coverage over resolution of biological complexity manifested as physiological diversity. Recently, the rate at which provisional draft genomes are generated has increased substantially, giving new insights into ecological processes and interactions. From a genotype perspective, the wide availability of genome-centric data requires new data synthesis approaches that place organismal genomes center stage in the study of environmental roles and functional performance. Extraction of ecologically relevant traits from microbial genomes will be essential to the future of microbial ecological research. Here, we present microTrait , a computational pipeline that infers and distills ecologically relevant traits from microbial genome sequences. microTrait maps a genome sequence into a trait space, including discrete and continuous traits, as well as simple and composite. Traits are inferred from genes and pathways representing energetic, resource acquisition, and stress tolerance mechanisms, while genome-wide signatures are used to infer composite, or life history, traits of microorganisms. This approach is extensible to any microbial habitat, although we provide initial examples of this approach with reference to soil microbiomes.

Karaoz, Ulas↗

Cosmology Large Angular Scale Surveyor (CLASS): 90 GHz Telescope Pointing, Beam Profile, Window Function, and Polarization Performance

The Cosmology Large Angular Scale Surveyor (CLASS) is a telescope array that observes the cosmic microwave background (CMB) over ∼75% of the sky from the Atacama Desert, Chile, at frequency bands centered near 40, 90, 150, and 220 GHz. CLASS measures the large angular scale CMB polarization to constrain the tensor-to-scalar ratio and the optical depth to last scattering. This paper presents the optical characterization of the 90 GHz telescope. Observations of the Moon establish the pointing while dedicated observations of Jupiter are used for beam calibration. The standard deviations of the pointing error in azimuth, elevation, and boresight angle are 1$^{'}_.$3, 2$^{'}_.$1, and 2$^{'}_.$0, respectively, over the first 3 yr of observations. This corresponds to a pointing uncertainty ∼7% of the beam’s full width at half-maximum (FWHM). The effective azimuthally symmetrized instrument 1D beam estimated at 90 GHz has an FWHM of 0$^°_.$620 ± 0$^°_.$003 and a solid angle of 138.7 ± 0.6(stats.) ± 1.1(sys.) μsr integrated to a radius of 4°. The corresponding beam window function drops to $b^2_ℓ$ = 0.93, 0.71, 0.14 at ℓ = 30, 100, 300, respectively. Far-sidelobes are studied using detector-centered intensity maps of the Moon and measured to be at a level of 10 −3 or below relative to the peak. The polarization angle of Tau A estimated from preliminary survey maps is 149°.6 ± 0°.2(stats.) in equatorial coordinates. The instrumental temperature-to-polarization (T → P) leakage fraction, inferred from per-detector demodulated Jupiter scan data, has a monopole component at the level of 1.7 × 10 −3 , a dipole component with an amplitude of 4.3 × 10 −3 , with no evidence of quadrupolar leakage.

79 ASTRONOMY AND ASTROPHYSICS↗

Carbon-nitrogen complex as an alternative to the 𝑇 center in Si

A first-principles study of a carbon-nitrogen (CN) impurity complex in silicon is presented as an isoelectronic alternative to the T center [(CCH) Si ]. The latter has been pursued for applications in quantum information science, yet its sensitivity to the presence of hydrogen is still problematic. Our proposed complex has no hydrogen, thereby eliminating this issue. First, we show that the CN complex is stable against decomposition into substitutional and interstitial defects. Next, we show that due to being isoelectronic to the T center, the CN complex has a similar electronic structure, and therefore could be used in similar applications. We assess several low-energy configurations of the CN complex, finding (CN) Si to be stable and have the largest Debye-Waller factor. We predict a zero-phonon line (ZPL) of 828 meV (in the telecom S-band) and a radiative lifetime of 4.2 μs, comparable to the T center. Due to the presence of a bound exciton, choice of the exchange-correlation functional and also supercell-size scaling of the ZPL and transition dipole moment require special scrutiny; we rigorously justify our extrapolation schemes that allow computing values in the dilute limit.

36 MATERIALS SCIENCE↗

WorkflowHub: a registry for computational workflows

The rising popularity of computational workflows is driven by the need for repetitive and scalable data processing, sharing of processing know-how, and transparent methods. As both combined records of analysis and descriptions of processing steps, workflows should be reproducible, reusable, adaptable, and available. Workflow sharing presents opportunities to reduce unnecessary reinvention, promote reuse, increase access to best practice analyses for non-experts, and increase productivity. In reality, workflows are scattered and difficult to find, in part due to the diversity of available workflow engines and ecosystems, and because workflow sharing is not yet part of research practice. WorkflowHub provides a unified registry for all computational workflows that links to community repositories, and supports both the workflow lifecycle and making workflows findable, accessible, interoperable, and reusable (FAIR). By interoperating with diverse platforms, services, and external registries, WorkflowHub adds value by supporting workflow sharing, explicitly assigning credit, enhancing FAIRness, and promoting workflows as scholarly artefacts. The registry has a global reach, with hundreds of research organisations involved, and more than 800 workflows registered.

97 MATHEMATICS AND COMPUTING↗

Alpha particle channeling in ITER

Alpha particle channeling, the attempt to extract energy from high-energy fusion alpha particles using a combination of high- and low-frequency waves introduced in the plasma with antennae, is studied using a guiding center code. We examine the effect of the combination of cooling caused by a cyclotron mode, particle diffusion due to Alfvén modes introduced for ash removal, the inclusion of microturbulent diffusion, and the slowing down of the alpha particles on electrons. Induced cooling is achieved with a cyclotron resonance, producing additional losses of particles above 3.5 MeV in an amount about equal to the prompt loss. The removal of the low-energy cooled particles by additional modes or by microturbulent diffusion is the hardest challenge for alpha channeling. The cooled alpha particles remain deep in the plasma center, so for this removal, the method used must be capable of providing transport from the plasma center to the edge without also causing losses of high-energy particles.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Performance assessment of a real water source heat pump within a hardware-in-the-loop (HIL) testing environment

Over the last decade, the global fight against climate change through electrification has led to an increase in research on building heating, ventilation, and air conditioning (HVAC) systems that utilize intelligent control algorithms to provide demand-side grid service while also maintaining the thermal comfort of building occupants. As the pivotal point between building electricity consumption and indoor thermal comfort, high-efficiency electrical vapor-compression heat pumps are at the center of these emerging studies, and various grid-interactive and occupant-comfort control algorithms have been developed for them. The impact of these algorithms on heat pump operation and performance when subjected to different weather conditions, building loads, and grid requests calls for investigation and verification via experimental testing with actual heat pumps integrated with real-time building and grid responses. This study introduces a Water-Source Heat Pump (WSHP) Hardware-in-The-Loop (HIL) Test Facility that is the first of its kind. This testbed utilizes a 2-ton variable speed water-to-air heat pump that is capable of interacting with a virtual environment currently comprised of an EnergyPlus (E+) building simulation, an agent-based occupant behavioral model, and a single U-tube ground-loop heat exchanger (GLHE) model. Detailed descriptions of the testbed’s physical design and operation, virtual environment, as well as their mutual communication is provided. An uncertainty analysis is also performed under manufacturer specified heating and cooling design conditions. This analysis shows that the total load across the WSHP’s demand side heat exchanger, i.e., the sum of its latent and sensible components, can be measured with a relative uncertainty of ± 10.4% and ± 3.6% in cooling and heating mode respectively. The WSHP’s coefficient of performance (COP) can be measured with relative uncertainties of ± 10.4% in cooling mode, and ± 3.7% in heating mode. A preliminary 24-h experimental demonstration is then performed utilizing the DOE prototype small commercial office building model in E+. The simulation takes place in Atlanta, GA on the date of 08/26/15 from 12:00 AM to 11:59 PM using TMY3 weather data. Here, the results from this demonstration show that over the course of this experiment the simulated outputs of zone dry-bulb temperature, zone humidity ratio, and WSHP inlet water temperature can be tracked by testbed emulators up to a root mean squared error (RMSE) of ± 0.27 °C, ± 0.376 g/kg, and ± 0.85 °C respectively. The WSHP’s dynamic behavioral characteristics and performance are also captured, and correspond well with the authors’ previous understanding of heat pump efficiency as a function of evaporator and condenser fluid inlet conditions respectively.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Empirically-calibrated H100 node power models for accurate AI training energy estimation

Accurately quantifying the energy use of artificial intelligence (AI) training is critical for infrastructure planning, carbon accounting, and sustainable data center operation, but few studies have directly measured the power consumption of production workloads on contemporary hardware. By combining empirical measurements from Brookhaven National Laboratory during AI training on 8-graphics-processing-unit H100 systems with open-source benchmarking data, we develop statistical models relating computational intensity to node-level power consumption. We measure the gap between manufacturer-rated thermal design power (TDP) and actual power demand during AI training. Our analysis reveals that even computationally intensive workloads operate at only 76% of the 10.2 kW TDP rating. Our architecture-specific model, calibrated to floating-point operations, predicts energy consumption with 11.4% mean absolute percentage error, significantly outperforming TDP-based approaches (27%–37% error). We identified distinct power signatures between transformer and convolutional neural network architectures, with transformers showing characteristic fluctuations that may impact grid stability. These results provide a measurement-grounded basis for improving AI training energy estimates, enabling more reliable infrastructure sizing, cost projections, and environmental impact assessments.

Newkirk, Alex C↗

Jet suppression and azimuthal anisotropy from RHIC to LHC

Azimuthal anisotropies of high- p T particles produced in heavy-ion collisions are understood as an effect of a geometrical selection bias. Particles oriented in the direction in which the QCD medium formed in these collisions is shorter suffer less energy loss, and thus, are over-represented in the final ensemble compared to those oriented in the direction in which the medium is longer. In this work we present the first semianalytical predictions, including propagation through a realistic, hydrodynamical background, of the elliptic azimuthal anisotropy for jets, obtaining a quantitative agreement with available experimental data as a function of the jet p T , its cone size R , and the collisions centrality. Jets are multipartonic, extended objects and their energy loss is sensitive to substructure fluctuations. This sensitivity is determined by the physics of color coherence that relates to the ability of the medium to resolve those partonic fluctuations. Specifically, color dipoles with an angular separation smaller than a critical angle, θ c , are not resolved by the medium and they effectively act as a coherent source of energy loss. We find that elliptic jet azimuthal anisotropy has a specially strong dependence on coherence physics due to the marked length dependence of θ c . By combining our predictions for the collision systems and center-of-mass energies studied at RHIC and the LHC, covering a wide range of typical values of θ c , we show that the relative size of elliptic jet azimuthal anisotropies for jets with different cone sizes R follows a universal trend that indicates a transition from a coherent regime of jet quenching to a decoherent regime. These results suggest a way forward to reveal the role played by the physics of jet color decoherence in probing deconfined QCD matter. Published by the American Physical Society 2024

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Measurement of the e + e − → p p ¯ π 0 cross section at s = 2.1000 − 3.0800 GeV

The process e + e − → p p ¯ π 0 is studied at 20 center-of-mass energies ranging from 2.1000 to 3.0800 GeV using 636.8 pb − 1 of data collected with the BESIII detector operating at the BEPCII collider. The Born cross sections for e + e − → p p ¯ π 0 are measured with high precision. Since the lowest center-of-mass energy, 2.1000 GeV, is less than 90 MeV above the p p ¯ π 0 energy threshold, we can probe the threshold behavior for this reaction. However, no anomalous threshold enhancement is found in the cross sections for e + e − → p p ¯ π 0 . Published by the American Physical Society 2024

Astronomy & Astrophysics↗

Measurements of ${\mathrm{p}} {\mathrm{p}} \rightarrow {\mathrm{Z}} {\mathrm{Z}} $ production cross sections and constraints on anomalous triple gauge couplings at $\sqrt{s} = 13\,\text {TeV} $

The production of Z boson pairs in proton–proton (${\mathrm{p}} {\mathrm{p}} $) collisions, ${{\mathrm{p}} {\mathrm{p}} \rightarrow ({\mathrm{Z}}/\gamma ^*)({\mathrm{Z}}/\gamma ^*) \rightarrow 2\ell 2\ell '}$, where ${\ell ,\ell ' = {\mathrm{e}}}$ or ${{\upmu }}$, is studied at a center-of-mass energy of 13$\,\text {TeV}$ with the CMS detector at the CERN LHC. The data sample corresponds to an integrated luminosity of 137$\,\text {fb}^{-1}$, collected during 2016–2018. The ${\mathrm{Z}} {\mathrm{Z}} $ production cross section, $\sigma _{\text {tot}} ({\mathrm{p}} {\mathrm{p}} \rightarrow {\mathrm{Z}} {\mathrm{Z}} ) = 17.4 \pm 0.3 \,\text {(stat)} \pm 0.5 \,\text {(syst)} \pm 0.4 \,\text {(theo)} \pm 0.3 \,\text {(lumi)} \text { pb} $, measured for events with two pairs of opposite-sign, same-flavor leptons produced in the mass region ${60< m_{\ell ^+\ell ^-} < 120\,\text {GeV}}$ is consistent with standard model predictions. Differential cross sections are also measured and agree with theoretical predictions. The invariant mass distribution of the four-lepton system is used to set limits on anomalous ${\mathrm{Z}} {\mathrm{Z}} {\mathrm{Z}} $ and ${{\mathrm{Z}} {\mathrm{Z}} \gamma }$ couplings.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Chemistry of the thermal water samples of the Camas Prairie area in Idaho, USA

This dataset includes chemistry of geothermal water samples of the Camas Prairie area in Idaho. The samples included in this dataset were collected over the period of 2016-2019. Collection/analysis of new water samples and compilation of existing water chemistry database were conducted for Snake River Play Fairway Project. All chemical analysis of the samples were conducted in the Analytical Laboratory at the Center of Advanced Energy Studies (unless otherwise indicated) in Idaho Falls, Idaho. Isotope analysis were conducted in analytical/isotope measurement labs at Lawrence Berkeley National Laboratory, Utah State University, and University of Utah.

15 GEOTHERMAL ENERGY↗

PARETO 0.5.0 Release

PARETO 0.5.0 Release. Highlights: Treatment Center Modeling - New case study with desalination, clean brine, and evaporation treatment technologies - New option to reduce disposal capacity due to Seismic Response Areas (SRA) - New option to consider water sharing outside of system General Updates - New features for Sankey Diagram visualization (multiple regions, filtered time periods) - Introduce badges to README.md - Convert documentation to ASCII LaTeX - Code cleaning and maintenance - Correct strategic model documentation typo - Update and format treatment demo input spreadsheet Bug Fixes - Fix water quality operational model results printing bug - Piping and trucking variables are now built only over defined arcs instead of all possible connections - Revise pipeline expansion cost constraints, ensure that all pipelines built incur cost

PARETO,PARETO-UI,PSE,Process Systems Engineering,P↗

JIRIAF: JLAB Integrated Research Infrastructure Acros Facilities

The JIRIAF project aims to combine geographically diverse computing facilities into an integrated science infrastructure. This project starts by dynamically evaluating temporarily unallocated or idled compute resources from multiple providers. These resources are integrated to handle additional workloads without affecting local running jobs. This paper describes our approach to launch best-effort batch tasks which exploit these underutilized resources. Our system measures the real-time behavior of jobs running on a machine and learns to distinguish typical performance from outliers. Unsupervised ML techniques are used to analyze hardware-level performance measures, followed by a real-time cross-correlation analysis to determine which applications cause performance degradation. We then ameliorate bad behavior by throttling these processes. We demonstrate that problematic performance interference can be detected and acted on, which makes it possible to continue to share resources between applications and simultaneously maintain high utilization levels in a computing cluster. We relocate the CLAS12 data processing workflow to a remote data center for a case study, preventing file migration and temporal data persistency.

Lawrence, David↗

Williston Basin Carbon Ore, Rare Earth, and Critical Minerals (CORE-CM) Program

The U.S. Department of Energy’s Office of Fossil Energy awarded 13 CORE-CM programs as part of the CORE-CM Initiative, designed to develop the technology and upstream and midstream supply chains to extract rare-earth elements (REEs) and critical minerals (CMs) from the nation’s coal supplies. The intent is to catalyze regional economic growth and job creation while strengthening the use of domestic resources. The Williston Basin CORE-CM Program aims to drive the expansion and transformation of coal and coal-based resource usage within the Williston Basin to produce REEs, CMs, and nonfuel carbon-based products (CBPs). The work constitutes Phase 1 of a long-term program. The objectives of Phase 1 are to identify the existing knowledge base and gaps and to develop a series of assessments/plans, including an initial basinal assessment; a characterization and data acquisition plan; a waste stream reuse plan; a basinal strategies assessment for infrastructure, industries, and business; a technology assessment, development, and field testing plan; a technology innovation center plan(s); and a stakeholder outreach and education plan. The goal of this project is to initiate the development of a new industry in the resource-rich Williston Basin that will catalyze economic growth and job creation through a coalition team of private industry, university, and state, local, and federal government entities. A coalition team of nearly 30 private industry, university, and state, local, and federal government partners was formed for this program. Partners include the University of North Dakota Energy & Environmental Research Center, Institute for Energy Studies, and Nistler College; North Dakota State University; Montana Tech University; Pacific Northwest National Laboratory; Critical Materials Institute; North Dakota Geological Survey; South Dakota Geological Survey; U.S. Geological Survey; North American Coal Corporation; BNI Energy; Basin Electric Power Cooperative; Minnkota Power Cooperative; and many more.

Kay, John P.↗