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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 1,531 records · Page 85

Extrapolation of Type Ia Supernova Spectra into the Near-infrared Using Principal Component Analysis

Abstract We present a method of extrapolating the spectroscopic behavior of Type Ia supernovae (SNe Ia) in the near-infrared (NIR) wavelength regime up to 2.30 μ m using optical spectroscopy. Such a process is useful for accurately estimating K-corrections and other photometric quantities of SNe Ia in the NIR. A principal component analysis is performed on data consisting of Carnegie Supernova Project I & II optical and NIR FIRE spectra to produce models capable of making these extrapolations. This method differs from previous spectral template methods by not parameterizing models strictly by photometric light-curve properties of SNe Ia, allowing for more flexibility of the resulting extrapolated NIR flux. A difference of around −3.1% to −2.7% in the total integrated NIR flux between these extrapolations and the observations is seen here for most test cases including Branch core-normal and shallow-silicon subtypes. However, larger deviations from the observation are found for other tests, likely due to the limited high-velocity and broad-line SNe Ia in the training sample. Maximum-light principal components are shown to allow for spectroscopic predictions of the color-stretch light-curve parameter, s BV , within approximately ±0.1 units of the value measured with photometry. We also show these results compare well with NIR templates, although in most cases the templates are marginally more fitting to observations, illustrating a need for more concurrent optical+NIR spectroscopic observations to truly understand the diversity of SNe Ia in the NIR.

Astronomy & Astrophysics↗

Production of Radioactive 22 Na in Core-collapse Supernovae: The Ne-E(L) Component in Presolar Grains and Its Possible Consequences on Supernova Observations

Presolar graphite grains carry the isotopic signatures of their parent stars. A significant fraction of presolar graphites show isotopic abundance anomalies relative to solar for elements such as O, Si, Mg, and Ca, which are compatible with nucleosynthesis in core-collapse supernovae (CCSNe). Therefore, they must have condensed from CCSN ejecta before the formation of the Sun. Their most puzzling abundance signature is the 22 Ne-enriched component Ne-E(L), interpreted as the effect of the radioactive decay of 22 Na (T 1/2 = 2.6 yr). Previous works have shown that if H is ingested into the He shell and not fully destroyed before the explosion, the CCSN shock in the He-shell material produces large amounts of 22 Na. Here we focus on such CCSN models, showing a radioactive 26 Al production compatible with grain measurements, and analyze the conditions of 22Na nucleosynthesis. In these models, 22 Na is mostly made in the He shell, with a total ejected mass varying between 2.6 × 10 −3 M ⊙ and 1.9 × 10 −6 M ⊙ . We show that such 22 Na may already impact the CCSN light curve 500 days after the explosion, and at later stages it can be the main source powering the CCSN light curve for up to a few years before 44 Ti decay becomes dominant. Based on the CCSN yields above, the 1274.53 keV γ-ray flux due to 22 Na decay could be observable for years after the first CCSN light is detected, depending on the distance. This makes CCSNe possible sites to detect a 22 Na γ-ray signature consistently with the Ne-E(L) component found in presolar graphites. Finally, we discuss the potential contribution from 22 Na decay to the Galactic positron annihilation rate.

79 ASTRONOMY AND ASTROPHYSICS↗

BICEP/Keck. XX. Component-separated Maps of the Polarized Cosmic Microwave Background and Thermal Dust Emission Using Planck and BICEP/Keck Observations through the 2018 Observing Season

We present component-separated polarization maps of the cosmic microwave background (CMB) and Galactic thermal dust emission, derived using data from the BICEP/Keck experiments through the 2018 observing season and Planck. By employing a maximum-likelihood method that utilizes observing matrices, we produce unbiased maps of the CMB and dust signals. We outline the computational challenges and demonstrate an efficient implementation of the component map estimator. We show methods to compute and characterize power spectra of these maps, opening up an alternative way to infer the tensor-to-scalar ratio from our data. We compare the results of this map-based separation method with the baseline BICEP/Keck analysis. Our analysis demonstrates consistency between the two methods, finding an 84% correlation between the pipelines.

cosmic inflation↗

Bayesian Component Separation for DESI LAE Automated Spectroscopic Redshifts and Photometric Targeting

Lyα emitters (LAEs) are valuable high-redshift cosmological probes traditionally identified using specialized narrowband photometric surveys. In ground-based spectroscopy, it can be difficult to distinguish the sharp LAE peak from residual sky emission lines using automated methods, leading to misclassified redshifts. We present a Bayesian spectral component separation technique to automatically determine spectroscopic redshifts for LAEs while marginalizing over sky residuals. We use visually inspected spectra of LAEs obtained using the Dark Energy Spectroscopic Instrument (DESI) to create a data-driven prior and can determine redshift by jointly inferring sky residual, LAE, and residual components for each individual spectrum. We demonstrate this method on 881 spectroscopically observed z = 2–4 DESI LAE candidate spectra and determine their redshifts with >90% accuracy when validated against visually inspected redshifts. Using the Δχ$^{2}$ value from our pipeline as a proxy for detection confidence, we then explore potential survey design choices and implications for targeting LAEs with medium-band photometry. This method allows for scalability and accuracy in determining redshifts from DESI spectra, and the results provide recommendations for LAE targeting in anticipation of future high-redshift spectroscopic surveys.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Disentangling the Hadronic Components in NGC 1068

The recent detection of high-energy neutrinos by IceCube in the direction of the nearby Seyfert/starburst galaxy NGC 1068 implies that radio-quiet active galactic nuclei can accelerate cosmic-ray ions. Dedicated multimessenger analyses suggest that the interaction of these high-energy ions with ambient gas or photons happens in a region of the galaxy that is highly opaque for GeV–TeV gamma rays. Otherwise, the GeV–TeV emission would violate existing constraints provided by the Fermi Large Area Telescope (LAT) and the Major Atmospheric Gamma Imaging Cherenkov. The conditions of high optical depth are realized near the central supermassive black hole (SMBH). At the same time, the GeV emission detected by the Fermi LAT is likely related to the galaxy’s sustained star formation activity. In this work, we derive a 20 MeV–1 TeV spectrum of NGC 1068 using 14 yr of Fermi LAT observations. We find that the starburst hadronic component is responsible for NGC 1068's emission above ~500 MeV. However, below this energy, an additional component is required. In the 20–500 MeV range, the Fermi LAT data are consistent with hadronic emission initiated by non-thermal ions interacting with gas or photons in the vicinity of the central SMBH. This highlights the importance of the MeV band to discover hidden cosmic-ray accelerators.

79 ASTRONOMY AND ASTROPHYSICS↗

Phase partitioning and volatility of secondary organic aerosol components formed from α-pinene ozonolysis and OH oxidation: the importance of accretion products and other low volatility compounds

We measured a large suite of gas- and particle-phase multi-functional organic compounds with a Filter Inlet for Gases and AEROsols (FIGAERO) coupled to a high-resolution time-of-flight chemical ionization mass spectrometer (HR-ToF-CIMS) developed at the University of Washington. The instrument was deployed on environmental simulation chambers to study monoterpene oxidation as a secondary organic aerosol (SOA) source. We focus here on results from experiments utilizing an ionization method most selective towards acids (acetate negative ion proton transfer), but our conclusions are based on more general physical and chemical properties of the SOA. Hundreds of compounds were observed in both gas and particle phases, the latter being detected by temperature-programmed thermal desorption of collected particles. Particulate organic compounds detected by the FIGAERO–HR-ToF-CIMS are highly correlated with, and explain at least 25–50 % of, the organic aerosol mass measured by an Aerodyne aerosol mass spectrometer (AMS). Reproducible multi-modal structures in the thermograms for individual compounds of a given elemental composition reveal a significant SOA mass contribution from high molecular weight organics and/or oligomers (i.e., multi-phase accretion reaction products). Approximately 50 % of the HR-ToF-CIMS particle-phase mass is associated with compounds having effective vapor pressures 4 or more orders of magnitude lower than commonly measured monoterpene oxidation products. The relative importance of these accretion-type and other extremely low volatility products appears to vary with photochemical conditions. We present a desorption-temperature-based framework for apportionment of thermogram signals into volatility bins. The volatility-based apportionment greatly improves agreement between measured and modeled gas-particle partitioning for select major and minor components of the SOA, consistent with thermal decomposition during desorption causing the conversion of lower volatility components into the detected higher volatility compounds.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Model bias in simulating major chemical components of PM 2.5 in China

High concentrations of PM 2.5 (particulate matter with an aerodynamic diameter less than 2.5 µm) in China have caused severe visibility degradation. Accurate simulations of PM 2.5 and its chemical components are essential for evaluating the effectiveness of pollution control strategies and the health and climate impacts of air pollution. In this study, we compared the GEOS-Chem model simulations with comprehensive datasets for organic aerosol (OA), sulfate, nitrate, and ammonium in China. Model results are evaluated spatially and temporally against observations. The new OA scheme with a simplified secondary organic aerosol (SOA) parameterization significantly improves the OA simulations in polluted urban areas, highlighting the important contributions of anthropogenic SOA from semivolatile and intermediate-volatility organic compounds. The model underestimates sulfate and overestimates nitrate for most of the sites throughout the year. More significant underestimation of sulfate occurs in winter, while the overestimation of nitrate is extremely large in summer. The model is unable to capture some of the main features in the diurnal pattern of the PM 2.5 chemical components, suggesting inaccuracies in the presented processes. Potential model adjustments that may lead to a better representation of the boundary layer height, the precursor emissions, hydroxyl radical concentrations, the heterogeneous formation of sulfate and nitrate, and the wet deposition of nitric acid and nitrate have been tested in the sensitivity analysis. The results show that uncertainties in chemistry perhaps dominate the model biases. The proper implementation of heterogeneous sulfate formation and the good estimates of the concentrations of sulfur dioxide, hydroxyl radical, and aerosol liquid water are essential for the improvement of the sulfate simulation. The update of the heterogeneous uptake coefficient of nitrogen dioxide significantly reduces the modeled concentrations of nitrate. However, the large overestimation of nitrate concentrations remains in summer for all tested cases. The possible bias in the chemical production and the wet deposition of nitrate cannot fully explain the model overestimation of nitrate, suggesting issues related to the atmospheric removal of nitric acid and nitrate. A better understanding of the atmospheric nitrogen budget, in particular, the role of the photolysis of particulate nitrate, is needed for future model developments. Moreover, the results suggest that the remaining underestimation of OA in the model is associated with the underrepresented production of SOA.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Assessment of the ParFlow–CLM CONUS 1.0 integrated hydrologic model: evaluation of hyper-resolution water balance components across the contiguous United States

Abstract. Recent advancements in computational efficiency and Earth system modeling have awarded hydrologists with increasingly high-resolution models of terrestrial hydrology, which are paramount to understanding and predicting complex fluxes of moisture and energy. Continental-scale hydrologic simulations are, in particular, of interest to the hydrologic community for numerous societal, scientific, and operational benefits. The coupled hydrology–land surface model ParFlow–CLM configured over the continental United States (PFCONUS) has been employed in previous literature to study scale-dependent connections between water table depth, topography, recharge, and evapotranspiration, as well as to explore impacts of anthropogenic aquifer depletion to the water and energy balance. These studies have allowed for an unprecedented process-based understanding of the continental water cycle at high resolution. Here, we provide the most comprehensive evaluation of PFCONUS version 1.0 (PFCONUSv1) performance to date by comparing numerous modeled water balance components with thousands of in situ observations and several remote sensing products and using a range of statistical performance metrics for evaluation. PFCONUSv1 comparisons with these datasets are a promising indicator of model fidelity and ability to reproduce the continental-scale water balance at high resolution. Areas for improvement are identified, such as a positive streamflow bias at gauges in the eastern Great Plains, a shallow water table bias over many areas of the model domain, and low bias in seasonal total water storage amplitude, especially for the Ohio, Missouri, and Arkansas River basins. We discuss several potential sources for model bias and suggest that minimizing error in topographic processing and meteorological forcing would considerably improve model performance. Results here provide a benchmark and guidance for further PFCONUS model development, and they highlight the importance of concurrently evaluating all hydrologic components and fluxes to provide a multivariate, holistic validation of the complete modeled water balance.

O'Neill, Mary M. F. (ORCID:0000000221455165)↗

Data and figures for "Integrated modeling of boron powder injection for real-time plasma-facing component conditioning"

This dataset contains raw and processed data, as well as supplementary figures used in the paper titled "Integrated modeling of boron powder injection for real-time plasma-facing component conditioning." The data includes simulation results for boron transport and deposition in DIII-D tokamak scenarios, and processed plots. It provides insights into the effects of boron powder injection on plasma-facing component conditioning and surface composition.

ablative particle injection↗

A PSCAD Library Component Featuring a Reduced-Order IBR Model for EMT-Based Fault Studies

This paper presents a fully implemented inverter reduce-order-model (ROM) in an EMT simulation (PSCAD) library component for direct user utilization in protection studies. The developed inverter ROM has the following features: Equivalent to a full IBR inverter model with positive- and negative-sequence current formulation and representation A python script is developed to fully automate this process, including training data generation, ROM parameter training, updating parameters, and model verification and validation. With this PSCAD ROM library component, protection engineers can utilize a trustworthy, accurate ROM for protection studies in an easy-to-use and streamlined manner.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Hand tool bends component leads accurately

Hand-operated die set bends, without damage, electrical component leads to perfectly match holes in printed circuit board. This tool speeds up printed circuit fabrication and reduces the number of component rejections.

Source record↗

Novel probe simplifies electronic component testing

Test probe, in conjunction with standard equipment, tests axial-lead electronic components in their original packages. The probe can be modified to test any electronic component with automatic or nonautomatic equipment.

Syner, W. F.↗

Fixture aids soldering of electronic components on circuit board

Spring clamp fixture holds small electronic components in a desired position while they are being soldered on a circuit board. The spring clamp is clipped on the edge of the circuit board and an adjustable spring-steel boom holds components against the board. The felt pad at the end of the boom is replaced with different attachments for other holding tasks.

Ross, M. H.↗

Body-fitted harness provides safe and easy component handling

Body-fitted restraint harness enables workers to safely and conveniently handle critical components during their installation or removal. Since the harness supports the components, the worker is able to maneuver through restricted areas with his hands free. It is easily put on, adjusted, and removed, or comfortably worn without interfering with normal activities.

Miller, E. G.↗

Semiautomatic device tests components with biaxial leads

Semiautomatic device with a four-terminal network tests quantities of components having biaxial leads. The four-terminal network permits the testing of components in different environments. This device is easily modified for completely automatic operation.

Marshall, T. C.↗