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At least 235 records · Page 13

Dispenser Reliability: Materials R&D. A Hydrogen Fueling Infrastructure Research and Station Technology (H2FIRST) Report

Dispensers are the top cause of maintenance events and down-time at hydrogen fueling stations. In an effort to help characterize and enable improvements in dispenser reliability, an extensive accelerated lifetime testing set-up was designed and built at NREL involving components typically part of dispensing operations at fueling stations. Device Under Test (DUTs) included different components such as normally open valves, normally closed valves, fueling nozzles, breakaways devices and filters. Conditions of testing included pressures, and flow rates similar to light duty fuel cell electric vehicles fueling at -40°C, and -20°C for thousands of cycles in hydrogen. Tested components (failed and non-failed) were disassembled at SNL and polymeric O-rings were carefully retrieved and cataloged for chemical and physical characterization. Data collected was compared to similar O-rings from unexposed or non-tested components for hydrogen effects, and failure modes. Degradation analyses, based on select polymer chemistries common across all component types, their location within components, visual assessment of damage coupled with strong hydrogen effects from chemical characterization, was completed and presented to NREL and DOE. Overall, the failure rate amongst the components was not as high as expected for the test conditions. Among the component types tested, breakaways were the most susceptible to damage under these test conditions, with fueling nozzles a close second. The proper combination of selection of the right polymer and optimum component design was found to make a strong difference in component reliability under severe dispenser operating conditions. Physical degradation of polymers, rather than chemical changes due to low temperature hydrogen exposure, is more prevalent as failure mode for these test conditions. The nature and the extent of the degradation was much less at -20°C as compared to -40°C. The damage and failure rates were higher at lower temperatures than at higher test temperatures. As expected, increasing the number of cycles at the lowest test temperature (-40°C) increased damage. This indicates that cycling at the low temperature of -40°C required by SAE J2601 can reduce component life in fuel dispensing operations

08 HYDROGEN↗

DUNE Offline Computing Conceptual Design Report

This document describes Offline Software and Computing for the Deep Underground Neutrino Experiment (DUNE) experiment, in particular, the conceptual design of the offline computing needed to accomplish its physics goals. Our emphasis in this document is the development of the computing infrastructure needed to acquire, catalog, reconstruct, simulate and analyze the data from the DUNE experiment and its prototypes. In this effort, we concentrate on developing the tools and systems that facilitate the development and deployment of advanced algorithms. Rather than prescribing particular algorithms, our goal is to provide resources that are flexible and accessible enough to support creative software solutions as HEP computing evolves and to provide computing that achieves the physics goals of the DUNE experiment.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Education for PV Modeling Professionals: Observations from the 2025 PVPMC Workshop

We surveyed professionals in the photovoltaic industry to understand interests in education and training for performance modeling of solar power systems. We found that most professionals are self-taught and rely on a variety of public sources of technical materials. Available formal education, such as courses or certification programs, either lacks detail or is focused on software user training. Responses indicate several opportunities to create public resources that would benefit professional learning for solar power system modeling: • Create a glossary of terms and common variable names. • Develop guidance on uncertainty analysis in the context of solar power systems modeling. • Assemble a catalog of available educational materials and data sources.

14 SOLAR ENERGY↗

Disequilibrium Chemistry in Exoplanet Atmospheres Observed with the Hubble Space Telescope

Literature on the theory of exoplanet atmospheric disequilibrium chemistry is rich, although its observational counterpart has yet to emerge beyond the hints provided by a few targets in dedicated studies. We report results from an uniform data reduction and analysis for a catalog of 62 Hubble Space Telescope exoplanet transit spectra where we assess the atmospheric model preference for disequilibrium chemistry (i.e., water vapor is not the dominant absorption spectral signature) over thermal equilibrium chemistry in a comparative planetology context. Where model preference assessment is possible, we find that disequilibrium occurs in about half of the atmospheres, indicating that disequilibrium processes play an important role in the composition of exoplanet atmospheres. While very hot atmospheres, over 1800 K, prefer equilibrium chemistry, we find a clustering of preference for disequilibrium in the 1200–1800 K temperature range. We suggest that UV-augmented thermochemistry may play a significant role for those atmospheres.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Probing the Connection between IceCube Neutrinos and MOJAVE AGN

Active galactic nuclei (AGN) are prime candidate sources of the high-energy, astrophysical neutrinos detected by IceCube. This is demonstrated by the real-time multimessenger detection of the blazar TXS 0506+056 and the recent evidence of neutrino emission from NGC 1068 from a separate time-averaged study. However, the production mechanism of the astrophysical neutrinos in AGN is not well established, which can be resolved via correlation studies with photon observations. For neutrinos produced due to photohadronic interactions in AGN, in addition to a correlation of neutrinos with high-energy photons, there would also be a correlation of neutrinos with photons emitted at radio wavelengths. In this work, we perform an in-depth stacking study of the correlation between 15 GHz radio observations of AGN reported in the MOJAVE XV catalog, and 10 yr of neutrino data from IceCube. We also use a time-dependent approach, which improves the statistical power of the stacking analysis. No significant correlation was found for both analyses, and upper limits are reported. When compared to the IceCube diffuse flux, at 100 TeV and for a spectral index of 2.5, the upper limits derived are ~3% and ~9% for the time-averaged and time-dependent cases, respectively.

79 ASTRONOMY AND ASTROPHYSICS↗

Status of DUNE Offline Computing

We summarize the status of Deep Underground Neutrino Experiment (DUNE) Offline Software and Computing program. We describe plans for the computing infrastructure needed to acquire, catalog, reconstruct, simulate and analyze the data from the DUNE experiment and its prototypes in pursuit of the experiment's physics goals of precision measurements of neutrino oscillation parameters, detection of astrophysical neutrinos, measurement of neutrino interaction properties and searches for physics beyond the Standard Model. In contrast to traditional HEP computational problems, DUNE's Liquid Argon Time Projection Chamber data consist of simple but very large (many GB) data objects which share many characteristics with astrophysical images. We have successfully reconstructed and simulated data from 4% prototype detector runs at CERN. The data volume from the full DUNE detector, when it starts commissioning late in this decade will present memory management challenges in conventional processing but significant opportunities to use advances in machine learning and pattern recognition as a frontier user of High Performance Computing facilities capable of massively parallel processing. Our goal is to develop infrastructure resources that are flexible and accessible enough to support creative software solutions as HEP computing evolves.

43 PARTICLE ACCELERATORS↗

Identification of Galaxy Shreds in Large Photometric Catalogs Using Convolutional Neural Networks

Contamination from galaxy fragments, identified as sources, is a major issue in large photometric galaxy catalogs. In this paper, we prove that this problem can be easily addressed with computer vision techniques. We use image cutouts to train a convolutional neural network (CNN) to identify cataloged sources that are in reality just star-formation regions and/or shreds of larger galaxies. The CNN reaches an accuracy ~98% on our testing data sets. We apply this CNN to galaxy catalogs from three among the largest surveys available today: the Sloan Digital Sky Survey, the DESI Legacy Imaging Surveys, and the Panoramic Survey Telescope and Rapid Response System Survey. We find that, even when strict selection criteria are used, all catalogs still show a ~5% level of contamination from galaxy shreds. Our CNN gives a simple yet effective solution to clean galaxy catalogs from these contaminants.

79 ASTRONOMY AND ASTROPHYSICS↗

BASS. XXV. DR2 Broad-line-based Black Hole Mass Estimates and Biases from Obscuration

We present measurements of broad emission lines and virial estimates of supermassive black hole masses (M BH ) for a large sample of ultrahard X-ray-selected active galactic nuclei (AGNs) as part of the second data release of the BAT AGN Spectroscopic Survey (BASS/DR2). Our catalog includes M BH estimates for a total of 689 AGNs, determined from the Hα, Hβ, Mg II λ2798, and/or C IV λ1549 broad emission lines. The core sample includes a total of 512 AGNs drawn from the 70 month Swift/BAT all-sky catalog. We also provide measurements for 177 additional AGNs that are drawn from deeper Swift/BAT survey data. We study the links between M BH estimates and line-of-sight obscuration measured from X-ray spectral analysis. We find that broad Hα emission lines in obscured AGNs ($\mathrm{log}({N}_{{\rm{H}}}/{\mathrm{cm}}^{-2})\gt 22.0$) are on average a factor of ${8.0}_{-2.4}^{+4.1}$ weaker relative to ultrahard X-ray emission and about ${35}_{-12}^{\,+7}$% narrower than those in unobscured sources (i.e., $\mathrm{log}({N}_{{\rm{H}}}/{\mathrm{cm}}^{-2})\lt 21.5$). This indicates that the innermost part of the broad-line region is preferentially absorbed. Consequently, current single-epoch M BH prescriptions result in severely underestimated (>1 dex) masses for Type 1.9 sources (AGNs with broad Hα but no broad Hβ) and/or sources with $\mathrm{log}({N}_{{\rm{H}}}/{\mathrm{cm}}^{-2})\gtrsim 22.0$. We provide simple multiplicative corrections for the observed luminosity and width of the broad Hα component (L[bHα] and FWHM[bHα]) in such sources to account for this effect and to (partially) remedy M BH estimates for Type 1.9 objects. As a key ingredient of BASS/DR2, our work provides the community with the data needed to further study powerful AGNs in the low-redshift universe.

79 ASTRONOMY AND ASTROPHYSICS↗

Measuring Young Stars in Space and Time. I. The Photometric Catalog and Extinction Properties of N44

In order to better understand the role of high-mass stellar feedback in regulating star formation in giant molecular clouds, we carried out a Hubble Space Telescope (HST) Treasury Program Measuring Young Stars in Space and Time (MYSST) targeting the star-forming complex N44 in the Large Magellanic Cloud (LMC). Using the F555W and F814W broadband filters of both the ACS and WFC3/UVIS, we built a photometric catalog of 461,684 stars down to m {sub F555W} ≃ 29 mag and m {sub F814W} ≃ 28 mag, corresponding to the magnitude of an unreddened 1 Myr pre-main-sequence star of ≈ 0.09 M {sub ☉} at the LMC distance. In this first paper we describe the observing strategy of MYSST and the data reduction procedure and present the photometric catalog. We identify multiple young stellar populations tracing the gaseous rim of N44's superbubble, together with various contaminants belonging to the LMC field population. We also determine the reddening properties from the slope of the elongated red clump (RC) feature by applying the machine-learning algorithm RANSAC, and we select a set of upper-main-sequence stars as primary probes to build an extinction map, deriving a relatively modest median extinction A {sub F555W} ≃ 0.77 mag. The same procedure applied to the RC provides A {sub F555W} ≃ 0.68 mag.

47 OTHER INSTRUMENTATION↗

Kinematic Sunyaev-Zel’dovich effect with ACT, DES, and BOSS: A novel hybrid estimator

The kinematic and thermal Sunyaev-Zel’dovich (kSZ and tSZ) effects probe the abundance and thermodynamics of ionized gas in galaxies and clusters. We present a new hybrid estimator to measure the kSZ effect by combining cosmic microwave background temperature anisotropy maps with photometric and spectroscopic optical survey data. The method interpolates a velocity reconstruction from a spectroscopic catalog at the positions of objects in a photometric catalog, which makes it possible to leverage the high number density of the photometric catalog and the precision of the spectroscopic survey. Combining this hybrid kSZ estimator with a measurement of the tSZ effect simultaneously constrains the density and temperature of free electrons in the photometrically selected galaxies. Using the 1000 deg 2 of overlap between the Atacama Cosmology Telescope (ACT) Data Release 5, the first three years of data from the Dark Energy Survey (DES), and the Baryon Oscillation Spectroscopic Survey (BOSS) Data Release 12, we detect the kSZ signal at 4.8 σ and reject the null (no-kSZ) hypothesis at 5.1 σ . This corresponds to 2.0 σ per 100,000 photometric objects with a velocity field based on a spectroscopic survey with 1 / 5 th the density of the photometric catalog. For comparison, a recent ACT analysis using exclusively spectroscopic data from BOSS measured the kSZ signal at 2.1 σ per 100,000 objects. Our derived constraints on the thermodynamic properties of the galaxy halos are consistent with previous measurements. With future surveys, such as the Dark Energy Spectroscopic Instrument and the Rubin Observatory Legacy Survey of Space and Time, we expect that this hybrid estimator could result in measurements with significantly better signal-to-noise than those that rely on spectroscopic data alone.

79 ASTRONOMY AND ASTROPHYSICS↗

Galaxy Clusters Selected via the Sunyaev-Zel'dovich Effect in 5 year data from the SPT-3G Main Survey

We report a new galaxy cluster catalog, selected using the thermal Sunyaev-Zel'dovich (SZ) effect, from 5 years of observations of the SPT-3G Main field. Drawn from arcminute-resolution data with white noise levels of 3.2, 2.5, and 8.9 $μ$K-arcmin at 95, 150, and 220 GHz, respectively, the sample consists of 8,892 cluster candidates detected above significance $ξ=4$, with an expected purity of $>82\%$ (4,480 at $ξ\ge5$ with purity $>99\%$). Using optical and infrared data we have confirmed 7,190 candidates as clusters. The sample spans a mass range $7.9 \times 10^{13}M_\odot/h_{70}< M_\textrm{500c} < 1.6 \times 10^{15}M_\odot/h_{70}$ with a median mass of $1.65 \times 10^{14}M_\odot/h_{70}$, and a redshift range of $0.0371$ and 271 at $z>1.5$. Compared to previous SZ cluster samples from South Pole Telescope and Atacama Cosmology Telescope data, the SPT-3G sample is highly consistent in mass and redshift but is significantly deeper, with per-cluster detection signal-to-noise 2-4 times higher and a cluster density of 4.5 confirmed clusters/deg$^2$. We cross match with eRASS1 cluster and point source catalogs, finding 1,279 and 1,319 matches, respectively. The SPT and eROSITA cluster mass estimates are in relatively good agreement. We perform a series of validation checks using both internal data splits and comparisons to external samples. These tests show increasing correlated (dusty) emission with redshift, with a $\sim17\times$ larger 220 GHz temperature increment for clusters at $z\sim1.5$ than $z\sim0.25$, but only weak evidence for correlated synchrotron emission. Finally, a number of clusters are flagged as candidate strong gravitational lenses.

Bleem, L. E. [Argonne (main); Chicago U., KICP; Ch↗

Improved Earthquake Source Parameters with 3D Wavespeed Models in California and Nevada

Seismic tomography harnesses earthquake data to explore the inaccessible structure of the Earth. Adjoint waveform tomography (AWT), a method of seismic tomography, updates the tomographic model by optimizing the fit between observed earthquake data and synthetic waveforms. The synthetic data are calculated by solving the wave equation through a given 3D model. An important requirement to calculating synthetics is the source information (location, centroid time, depth, and moment tensor). Errors in source information affect the quality of the synthetics produced, which in turn can limit how structure can be inferred in the AWT workflow. Here, to test the effect of updating source information, we used MTTime (Chiang, 2020), a time-domain full-waveform moment tensor inversion code, to calculate the moment tensors and depths of 118 earthquakes that occurred in California and Nevada over a 20-yr period. We calculated 3D Green’s functions using a 3D seismic wavespeed model of California and Nevada (Doody et al., 2023b). We show that the inverted solutions provide better waveform fits than the Global Centroid Moment Tensor catalog and increase usable, well-correlated data by up to 7%. Therefore, we argue that recalculating source parameters should be considered in AWT workflows, particularly for smaller magnitude events (⁠M w > 5.0).

58 GEOSCIENCES↗

The Gaia–Kepler Stellar Properties Catalog. I. Homogeneous Fundamental Properties for 186,301 Kepler Stars

An accurate and precise Kepler Stellar Properties Catalog is essential for the interpretation of the Kepler exoplanet survey results. Previous Kepler Stellar Properties Catalogs have focused on reporting the best-available parameters for each star, but this has required combining data from a variety of heterogeneous sources. We present the Gaia–Kepler Stellar Properties Catalog, a set of stellar properties of 186,301 Kepler stars, homogeneously derived from isochrones and broadband photometry, Gaia Data Release 2 parallaxes, and spectroscopic metallicities, where available. Our photometric effective temperatures, derived from g to K{sub s} colors, are calibrated on stars with interferometric angular diameters. Median catalog uncertainties are 112 K for T{sub eff}, 0.05 dex for log g, 4% for R{sub ⋆}, 7% for M{sub ⋆}, 13% for ρ{sub ⋆}, 10% for L{sub ⋆}, and 56% for stellar age. These precise constraints on stellar properties for this sample of stars will allow unprecedented investigations into trends in stellar and exoplanet properties as a function of stellar mass and age. In addition, our homogeneous parameter determinations will permit more accurate calculations of planet occurrence and trends with stellar properties.

79 ASTRONOMY AND ASTROPHYSICS↗

Vera C. Rubin Observatory Prompt Products

Data products produced by prompt and daily processing of images obtained in the Legacy Survey of Space and Time. These include realtime alerts sent to community alert brokers, newly-discovered Solar System Objects reported to the Minor Planet Center, processed visit and difference images, and source catalogs. Prompt Products are not a static single data release but continually grow throughout the ten-year LSST survey.

79 ASTRONOMY AND ASTROPHYSICS↗

Vera C. Rubin Observatory Prompt Products: alert packets data

Data products produced by prompt and daily processing of images obtained in the Legacy Survey of Space and Time. These include realtime alerts sent to community alert brokers, newly-discovered Solar System Objects reported to the Minor Planet Center, processed visit and difference images, and source catalogs. Prompt Products are not a static single data release but continually grow throughout the ten-year LSST survey. This dataset is a subset of the full data release consisting of a dataset named alert packets. This dataset contains measurements for 5-sigma sources detected in difference images that were issued to the community brokers.

79 ASTRONOMY AND ASTROPHYSICS↗

A Co-design Framework for Online Data Analysis and Reduction

Science applications preparing for the exascale era are increasingly exploring in situ computations comprising of simulation-analysis-reduction pipelines coupled in-memory. Efficient composition and execution of such complex pipelines for a target platform is a codesign process that evaluates the impact and tradeoffs of various application- and system-specific parameters. In this article, we describe a toolset for automating performance studies of composed HPC applications that perform online data reduction and analysis. We describe Cheetah, a new framework for composing parametric studies on coupled applications, and Savanna, a runtime engine for orchestrating and executing campaigns of codesign experiments. Furthermore, this toolset facilitates understanding the impact of various factors such as process placement, synchronicity of algorithms, and storage versus compute requirements for online analysis of large data. Ultimately, we aim to create a catalog of performance results that can help scientists understand tradeoffs when designing next-generation simulations that make use of online processing techniques. We illustrate the design of Cheetah and Savanna, and present application examples that use this framework to conduct codesign studies on small clusters as well as leadership class supercomputers.

97 MATHEMATICS AND COMPUTING↗

The Sensitivity of GPz Estimates of Photo-z Posterior PDFs to Realistically Complex Training Set Imperfections

The accurate estimation of photometric redshifts is crucial to many upcoming galaxy surveys, for example, the Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST). Almost all Rubin extragalactic and cosmological science requires accurate and precise calculation of photometric redshifts; many diverse approaches to this problem are currently in the process of being developed, validated, and tested. In this work, we use the photometric redshift code GPz to examine two realistically complex training set imperfections scenarios for machine learning based photometric redshift calculation: (i) where the spectroscopic training set has a very different distribution in color–magnitude space to the test set, and (ii) where the effect of emission line confusion causes a fraction of the training spectroscopic sample to not have the true redshift. By evaluating the sensitivity of GPz to a range of increasingly severe imperfections, with a range of metrics (both of photo-z point estimates as well as posterior probability distribution functions, PDFs), we quantify the degree to which predictions get worse with higher degrees of degradation. In particular, we find that there is a substantial drop-off in photo-z quality when line-confusion goes above ~1%, and sample incompleteness below a redshift of 1.5, for an experimental setup using data from the Buzzard Flock synthetic sky catalogs.

79 ASTRONOMY AND ASTROPHYSICS↗