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At least 793 records · Page 44
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Asymmetric loading of TnsE regulates Tn7 targeting of DNA replication structures

Abstract Tn7 transposable elements are known for their sophisticated target-site selection mechanisms. For the prototypical Tn7 element, dedicated transposon-encoded proteins direct insertions to either a conserved site in the chromosome or replicating DNA structures in conjugal plasmids, ensuring the vertical and horizontal spread of the element. While the pathway targeting the attTn7 site in the bacterial chromosome has been extensively studied, the pathway targeting DNA replication structures remains poorly understood. We have used an integrative structural biology approach to elucidate how the Tn7-encoded protein TnsE recognizes replication sites. Using native mass spectrometry, we found that TnsE forms 1:1 and 2:1 (TnsE:DNA) complexes on 3′-recessed DNA, with gain-of-function TnsE variants favoring the formation of 2:1 complexes. Structural characterization confirms that two TnsE molecules bind to DNA with the C-terminal domain of the protein recognizing duplex DNA, leaving the N-terminal domain to impose DNA substrate specificity and recruit the core transposition machinery. Collectively, our work is consistent with a model where TnsE-mediated target-site selection relies on the formation of an asymmetric TnsE:DNA complex to recruit the Tn7 transposase to DNA replication structures.

Biochemistry & Molecular Biology↗
DOE OSTI2026

Global metagenomics reveals plastid diversity and unexplored algal lineages

Photosynthetic organelles in eukaryotes originated through primary endosymbiosis with a cyanobacterium, an event that profoundly shaped the evolutionary landscape of the eukaryotic tree of life. Primary plastids in Archaeplastida, especially in cultivable plants and algae, contribute most to known plastid diversity. Secondary and higher-order endosymbiosis, involving eukaryotic hosts and algal endosymbionts, further spread photosynthesis among protists within the CASH lineages (Cryptophyta, Alveolata, Stramenopila, and Haptophyta). Despite various hypotheses explaining secondary plastid evolution and distribution, empirical support remains limited. Here, we employ cultivation-independent global metagenomics to expand plastid diversity and investigate plastid origins. We capture 1,027 plastid sequences, including 300 novel sequences belonging to previously unsequenced plastids and representing yet-to-be described microeukaryotes. This includes a new lineage that offers insights into plastid evolution in haptophytes and cryptophytes. Our results confirm that Archaeplastida plastids originate from an early branching cyanobacterial lineage closely related to Gloeomargaritales and identify the closest extant relative of Paulinella plastids. Additionally, our findings suggest two independent origins of secondary red-algal plastids, contributing to plastid diversity in CASH lineages and challenging the prevailing model of single secondary plastid origin. Our study highlights the importance of metagenomic data in uncovering biological diversity and advancing understanding of plastid relationships across photosynthetic eukaryotes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Cost effectiveness of preemptive school closures to mitigate pandemic influenza outbreaks of differing severity in the United States

Background: Nonpharmaceutical interventions (NPIs) may be considered as part of national pandemic preparedness as a first line defense against influenza pandemics. Preemptive school closures (PSCs) are an NPI reserved for severe pandemics and are highly effective in slowing influenza spread but have unintended consequences. Methods: We used results of simulated PSC impacts for a 1957-like pandemic (i.e., an influenza pandemic with a high case fatality rate) to estimate population health impacts and quantify PSC costs at the national level using three geographical scales, four closure durations, and three dismissal decision criteria (i.e., the number of cases detected to trigger closures). At the Chicago regional level, we also used results from simulated 1957-like, 1968-like, and 2009-like pandemics. Our net estimated economic impacts resulted from educational productivity costs plus loss of income associated with providing childcare during closures after netting out productivity gains from averted influenza illness based on the number of cases and deaths for each mitigation strategy. Results: For the 1957-like, national-level model, estimated net PSC costs and averted cases ranged from $\$7.5$ billion (2016 USD) averting 14.5 million cases for two-week, community-level closures to $\$97$ billion averting 47 million cases for 12-week, county-level closures. We found that 2-week school-by-school PSCs had the lowest cost per discounted life-year gained compared to county-wide or school district–wide closures for both the national and Chicago regional-level analyses of all pandemics. The feasibility of spatiotemporally precise triggering is questionable for most locales. Theoretically, this would be an attractive early option to allow more time to assess transmissibility and severity of a novel influenza virus. However, we also found that county-wide PSCs of longer durations (8 to 12 weeks) could avert the most cases (31–47 million) and deaths (105,000–156,000); however, the net cost would be considerably greater ($\$88$-$\$103$ billion net of averted illness costs) for the national-level, 1957-like analysis. Conclusions: We found that the net costs per death averted ($\$180,000$-$\$4.2$ million) for the national-level, 1957-like scenarios were generally less than the range of values recommended for regulatory impact analyses ($\$4.6$ to 15.0 million). This suggests that the economic benefits of national-level PSC strategies could exceed the costs of these interventions during future pandemics with highly transmissible strains with high case fatality rates. In contrast, the PSC outcomes for regional models of the 1968-like and 2009-like pandemics were less likely to be cost effective; more targeted and shorter duration closures would be recommended for these pandemics.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Designing high-performance superconductors with nanoparticle inclusions: Comparisons to strong pinning theory

One of the most promising routes for achieving high critical currents in superconductors is to incorporate dispersed, non-superconducting nanoparticles to control the dissipative motion of vortices. However, these inclusions reduce the overall superconducting volume and can strain the interlaying superconducting matrix, which can detrimentally reduce T c . Consequently, an optimal balance must be achieved between the nanoparticle density n p and size d. Determining this balance requires garnering a better understanding of vortex–nanoparticle interactions, described by strong pinning theory. Here, we map the dependence of the critical current on nanoparticle size and density in (Y 0.77 , Gd 0.23 )Ba 2 Cu 3 O 7-δ films in magnetic fields of up to 35 T and compare the trends to recent results from time-dependent Ginzburg–Landau simulations. We identify consistency between the field-dependent critical current J c (B) and expectations from strong pinning theory. Specifically, we find that J c ∝ B -α , where α decreases from 0.66 to 0.2 with increasing density of nanoparticles and increases roughly linearly with nanoparticle size d/ξ (normalized to the coherence length). At high fields, the critical current decays faster (~B -1 ), suggesting that each nanoparticle has captured a vortex. When nanoparticles capture more than one vortex, a small, high-field peak is expected in J c (B). Due to a spread in defect sizes, this novel peak effect remains unresolved here. Finally, we reveal that the dependence of the vortex creep rate S on nanoparticle size and density roughly mirrors that of α, and we compare our results to low-T nonlinearities in S(T) that are predicted by strong pinning theory.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Trap-Assisted Dopant Compensation Prevents Shunting in Poly-Si Passivating Interdigitated Back Contact Silicon Solar Cells

Using a trap-assisted compensation model, we explain why polycrystalline Si (poly-Si) passivating contacts are able to achieve low leakage current between the doped fingers of interdigitated back contact (IBC) monocrystalline Si solar cells despite mixing of boron and phosphorus dopants in the isolation region. The fill factor of IBC solar cells is strongly affected by the electrical isolation region between n- and p-type fingers, as this region is critical in minimizing shunting losses. During fabrication of monocrystalline Si solar cells with poly-Si passivating contacts, the intrinsic poly-Si isolation region inevitably gets contaminated with both p- and n-type dopants. Using dopant profiles measured with time-of-flight secondary ion mass spectrometry and scanning probe measurements of the isolation region, we demonstrate that despite the dopant spreading during cell processing, a well-compensated region between the doped fingers exists that prevents shunting. The trap-assisted dopant compensation mechanism significantly widens the compensated region to tens of microns, where the residual dopant densities are below the trap density. This enables a high-resistivity region, resulting in low shunt current. Using one-dimensional (1-D) finite element diode simulations, we identify the design parameters and experimental conditions under which a sufficiently resistive region can form. Furthermore, our measurements of 2-D local resistivity and work function maps across the isolation region using scanning spreading resistance microscopy and Kelvin probe force microscopy demonstrate the existence of a highly resistive, wide compensated region and confirm our proposed compensation mechanism. For our structures, this region is ~25 µm in width within a ~150 µm wide finger isolation region with nearly 3 orders of magnitude higher resistivity than the regions dominated by a single type of dopant.

14 SOLAR ENERGY↗
DOE OSTI2022

Modeling study of divertor particle and heat flux asymmetries for EAST H-mode discharges

The BOUT++ transport code is run to study the effects of plasma drifts on the divertor out-in asymmetries (DOIAs) of particle and heat fluxes and their decay widths for EAST lower single null H-mode discharges. The diamagnetic drift seems to have no effects on the DOIAs of total particle and heat fluxes due to its divergence-free nature. However, it could significantly increase the DOIAs of peak particle and heat fluxes and the flux decay widths. The E × B drift is found to induce a large plasma flow to the divertor region, enhancing the DOIAs of both total and peak particle and heat fluxes and the flux decay widths. Both the radial and poloidal components of the E × B drift are necessary in increasing the DOIAs, however, the radial E × B drift seems to play a more important role. The effects on the DOIAs caused by both diamagnetic and E × B drifts are reversed with the reverse of toroidal magnetic field. The heat flux decay width λ q and spreading width S q are important physical and engineering parameters for the divertors and could be obtained by fitting the heat flux profiles at divertor targets. The λ q at the outer target from the simulation case with all drifts could well match with the multi-machine scaling proposed by Eich and the DOIA of λ q is in reasonable agreement with the scaling proposed by Goldston.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Spatially varying seasonal modulation to tidal stream energy potential due to mixed tidal regimes in the Aleutian Islands, AK

We provide an assessment of the tidal stream energy resource of the Aleutian Islands, Alaska via a validated barotropic tidal numerical model of the region. Eight island passes are identified as energy “hotspots”. The annual mean kinetic energy fluxes, KEF , calculated at each pass vary from 1000 to 11,000 MW, while the annual available energy, AAE , varies from 5 to 42 MWh m −2 . Notable seasonal modulation to monthly power density averages and ranges are noted at some passes and not others. Seasonal adjustment is linked to the semi-annual solar declination cycle which enhances (dampens) diurnal (D 1 ) tidal amplitudes in summer/winter (spring/fall) as well as the time-varying phase lag between D 1 and semidiurnal (D 2 ) fortnightly tidal cycles. Annual variability in monthly mean power density scales with the tidal current form factor, F u , with the largest seasonal change occurring for F u > 1 (D 1 dominated tide). The spread in power density over a month is on average smaller for passes with mixed tides (F u = 1 ) than those with D 1 or D 2 dominance, as changes to fortnightly phase lag become influential to net power density ranges when tides are mixed. This study outlines overlooked, but relevant, long-term modulation to tidal streams in regions with mixed tides.

16 TIDAL AND WAVE POWER↗
DOE OSTI2023

Sensitivities of subgrid-scale physics schemes, meteorological forcing, and topographic radiation in atmosphere-through-bedrock integrated process models: a case study in the Upper Colorado River basin

Abstract. Mountain hydrology is controlled by interacting processes extending from the atmosphere through the bedrock. Integrated process models (IPMs), one of the main tools needed to interpret observations and refine conceptual models of the mountainous water cycle, require meteorological forcing that simulates the atmospheric process to predict hydroclimate then subsequently impacts surface–subsurface hydrology. Complex terrain and extreme spatial heterogeneity in mountainous environments drive uncertainty in several key considerations in IPM configurations and require further quantification and sensitivity analyses. Here, we present an IPM using the Weather Research and Forecasting (WRF) model which forces an integrated hydrologic model, ParFlow-CLM, implemented over a domain centered over the East River watershed (ERW), located in the Upper Colorado River basin (UCRB). The ERW is a heavily instrumented 300 km2 region in the headwaters of the UCRB near Crested Butte, CO, with a growing atmosphere-through-bedrock observation network. Through a series of experiments in the water year 2019 (WY19), we use four meteorological forcings derived from commonly used reanalysis datasets, three subgrid-scale physics scheme configurations in WRF, and two terrain shading options within WRF to test the relative importance of these experimental design choices for key hydrometeorological metrics including precipitation and snowpack, as well as evapotranspiration, groundwater storage, and discharge simulated by the ParFlow-CLM. Our hypothesis is that uncertainty from synoptic-scale forcings produces a much larger spread in surface–subsurface hydrologic fields than subgrid-scale physics scheme choice. Results reveal that the WRF subgrid-scale physics configuration leads to larger spatiotemporal variance in simulated hydrometeorological conditions, whereas variance across meteorological forcing with common subgrid-scale physics configurations is more spatiotemporally constrained. Despite reasonably simulating precipitation, a delay in simulated discharge peak is due to a systematic cold bias across WRF simulations, suggesting the need for bias correction. Discharge shows greater variance in response to the WRF simulations across subgrid-scale physics schemes (26 %) rather than meteorological forcing (6 %). The topographic radiation option has minor effects on the watershed-average hydrometeorological processes but adds profound spatial heterogeneity to local energy budgets (±30 W m−2 in shortwave radiation and 1 K air temperature differences in late summer). This is the first presentation of sensitivity analyses that provide support to help guide the scientific community to develop observational constraints on atmosphere-through-bedrock processes and their interactions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

A deep learning-based direct forecasting of CO 2 plume migration

Accurate and timely forecasts of CO 2 plume evolution in geological reservoirs are crucial for CO 2 migration detection, leakage risk assessment, and operation decision support. Conventional forecasting usually adopts a two-step strategy, first calibrating reservoir model parameters against observations using iterative inverse modeling (or history matching) and then applying the calibrated model for predictions. This method impedes real-time forecasts due to the heavy computational demand in inverse modeling and may suffer from poor prediction accuracy because of the limited observation data. In this work, we propose a deep learning-based latent space mapping framework to forecast CO 2 plume migration directly by avoiding the inverse modeling. We first use the convolutional autoencoder to map the high-dimensional complex plume extents onto low-dimensional latent space. Next, we use neural networks to learn the relationship between the observation variables and the prediction latent variables. And then for given observation data, we infer the prediction values directly. This one-step direct forecasting is computationally efficient which requires a few number of parallelizable reservoir simulations and it can provide accurate predictions with limited observations by learning the observation-prediction relationship in the reduced dimension. Therefore, our proposed method enables an in-time forecast of dynamic CO 2 plume distributions. In this work, we demonstrate the effectiveness and accuracy of our method in predicting the CO 2 plume migration using four metrics such as plume area, centroid movement distance, and plume spreading in the primary and secondary directions. And the spatio-temporal evolution patterns of plume migration under diverse geological complexities are also accurately quantified.

15 GEOTHERMAL ENERGY↗
DOE OSTI2020

Radiation damage and dose limits in serial synchrotron crystallography at cryo- and room temperatures

Radiation damage limits the accuracy of macromolecular structures in X-ray crystallography. Cryogenic (cryo-) cooling reduces the global radiation damage rate and, therefore, became the method of choice over the past decades. The recent advent of serial crystallography, which spreads the absorbed energy over many crystals, thereby reducing damage, has rendered room temperature (RT) data collection more practical and also extendable to microcrystals, both enabling and requiring the study of specific and global radiation damage at RT. Here, we performed sequential serial raster-scanning crystallography using a microfocused synchrotron beam that allowed for the collection of two series of 40 and 90 full datasets at 2- and 1.9-Å resolution at a dose rate of 40.3 MGy/s on hen egg white lysozyme (HEWL) crystals at RT and cryotemperature, respectively. The diffraction intensity halved its initial value at average doses ( D 1/2 ) of 0.57 and 15.3 MGy at RT and 100 K, respectively. Specific radiation damage at RT was observed at disulfide bonds but not at acidic residues, increasing and then apparently reversing, a peculiar behavior that can be modeled by accounting for differential diffraction intensity decay due to the nonuniform illumination by the X-ray beam. Specific damage to disulfide bonds is evident early on at RT and proceeds at a fivefold higher rate than global damage. The decay modeling suggests it is advisable not to exceed a dose of 0.38 MGy per dataset in static and time-resolved synchrotron crystallography experiments at RT. This rough yardstick might change for proteins other than HEWL and at resolutions other than 2 Å.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Joint Analysis of the Epidemic Evolution and Human Mobility During the First Wave of COVID-19 in Spain: Retrospective Study

Background The initial wave of the COVID-19 pandemic placed a tremendous strain on health care systems worldwide. To mitigate the spread of the virus, many countries implemented stringent nonpharmaceutical interventions (NPIs), which significantly altered human behavior both before and after their enactment. Despite these efforts, a precise assessment of the impact and efficacy of these NPIs, as well as the extent of human behavioral changes, remained elusive. Objective In this study, we conducted a retrospective analysis of the initial wave of COVID-19 in Spain to better comprehend the influence of NPIs and their interaction with human behavior. Such investigations are vital for devising future mitigation strategies to combat COVID-19 and enhance epidemic preparedness more broadly. Methods We used a combination of national and regional retrospective analyses of pandemic incidence alongside large-scale mobility data to assess the impact and timing of government-implemented NPIs in combating COVID-19. Additionally, we compared these findings with a model-based inference of hospitalizations and fatalities. This model-based approach enabled us to construct counterfactual scenarios that gauged the consequences of delayed initiation of epidemic response measures. Results Our analysis demonstrated that the pre–national lockdown epidemic response, encompassing regional measures and heightened individual awareness, significantly contributed to reducing the disease burden in Spain. The mobility data indicated that people adjusted their behavior in response to the regional epidemiological situation before the nationwide lockdown was implemented. Counterfactual scenarios suggested that without this early epidemic response, there would have been an estimated 45,400 (95% CI 37,400-58,000) fatalities and 182,600 (95% CI 150,400-233,800) hospitalizations compared to the reported figures of 27,800 fatalities and 107,600 hospitalizations, respectively. Conclusions Our findings underscore the significance of self-implemented prevention measures by the population and regional NPIs before the national lockdown in Spain. The study also emphasizes the necessity for prompt and precise data quantification prior to enacting enforced measures. This highlights the critical interplay between NPIs, epidemic progression, and human behavior. This interdependence presents a challenge in predicting the impact of NPIs before they are implemented.

Public, Environmental & Occupational Health↗
DOE OSTI2025

Modeling the microplastic distribution along the Delaware River Estuary: Accumulation patterns and hydrodynamic influences

Microplastic pollution is an escalating environmental concern, particularly in densely populated estuary regions, where it poses significant threats to aquatic life and human health. The dispersion patterns of microplastic particles along estuaries are influenced and complicated by multiple environmental factors such as river flow, tidal mixing, salt intrusion, and estuarine circulation. This study examines the accumulation and dispersion patterns by modeling three typical classes of microplastics in the Delaware River Estuary: synthetic fibers, sinking plastic films, and rising plastic pellets. Our findings reveal specific areas with high microplastic accumulation for each type. Notably, the upper estuary regions exhibit significant retention of rising microplastics, associated with a region with reduced along-thalweg velocities downstream of Trenton, NJ and upstream of Philadelphia, PA. Conversely, synthetic fibers and sinking plastic films accumulate in the flow convergence zone near the bottom salinity front, typically downstream of Philadelphia. All of the microplastic accumulation hot spot locations are controlled by the balance of river discharge and salinity intrusions. During the dry season, microplastic accumulation hot spots shift upstream in the estuary, whereas in the wet season, the strong river discharge pushes them downstream. Furthermore, on the other hand, tidal mixing, settling, and resuspension processes strongly impact the spreading of microplastics along the river.

Delaware River Estuary↗
DOE OSTI2025

Evidence for large baryonic feedback at low and intermediate redshifts from kinematic Sunyaev-Zel’dovich observations with ACT and DESI photometric galaxies

Recent advances in cosmological observations have provided an unprecedented opportunity to investigate the distribution of baryons relative to the underlying matter. In this work, we show that the gas is more extended than the dark matter, and the amount of baryonic feedback at $z \lesssim 1$ disfavors low-feedback models such as that of state-of-the-art hydrodynamical simulation IllustrisTNG compared with high-feedback models such as that of the original Illustris simulation. This has important implications for bridging the gap between theory and observations and understanding galaxy formation and evolution. Furthermore, a better grasp of the baryon-dark matter link is critical to future cosmological analyses, which are currently impeded by our limited knowledge of baryonic feedback. Here, we measure the kinematic Sunyaev-Zel'dovich (kSZ) effect from the Atacama Cosmology Telescope (ACT), stacked on the luminous red galaxy (LRG) sample of the Dark Energy Spectroscopic Instrument (DESI) imaging survey. This is the first analysis to use photometric redshifts for reconstructing galaxy velocities. Due to the large number of galaxies comprising the DESI imaging survey, this is the highest signal-to-noise stacked kSZ measurement to date: we detect the signal at 13$σ$, finding strong evidence that the gas is more spread out than the dark matter, as well as a preference for larger feedback compared to some commonly used state-of-the-art hydrodynamical simulations. Here, our work opens up the possibility of recalibrating large hydrodynamical simulations using the kSZ effect. In addition, our findings highlight the importance of properly accounting for baryonic feedback with future surveys such as LSST through direct probes such as the kSZ, and shed light on long-standing enigmas in astrophysics, such as the “missing baryon” problem.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

The effect of terrain-influenced winds on fire spread in QUIC-Fire

Here in this manuscript, we describe the implementation of the terrain-following version of QUIC-URB into QUIC-Fire and a demonstration of the impacts of terrain-influenced winds on QUIC-Fire-simulated fire spread. No changes to the underlying QUIC-Fire fire spread algorithm were made other than what was required to correctly account for the inclusion of terrain. This paper summarizes simulations used to understand how the QUIC-URB terrain-influenced winds affect upslope fire behavior without additional changes to the QUIC-Fire fire spread algorithm. Previously published FIRETEC results are compared to simulation results from the modified QUIC-Fire (incorporating terrain-influenced winds) that use the same topographies and fuels. QUIC-Fire results showed overall similar behaviors in terms of how the topographies affected fire shapes and trends in spread rates. Due to the terrain-following version of QUIC-URB being unable to generate flow separations at the crest of hills, fire spread rates in these regions across all non-flat topographies were over-predicted when compared to FIRETEC. Lateral fire growth showed similar trends with FIRETEC between topographies but did not capture the increase in spread due to a diagonal interface between grassland and forested fuel regions in the test domain. These simulations suggest possible refinements that are necessary to improve QUIC-Fire and thus guide ongoing efforts related to: how flame tilt angle is accounted for, the incorporation of non-local drag effects, and the inclusion of the wake-eddy parameterizations that are used in QUIC-URB.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

S 5 : Probing the Milky Way and Magellanic Clouds potentials with the 6D map of the Orphan–Chenab stream

We present a 6D map of the Orphan–Chenab (OC) stream by combining the data from Southern Stellar Stream Spectroscopic Survey (S 5 ) and Gaia. We reconstruct the proper motion, radial velocity, distance, on-sky track, and stellar density along the stream with spline models. The stream has a total luminosity of M V = -8.2 and metallicity of [Fe/H] = -1.9, similar to classical Milky Way (MW) satellites like Draco. The stream shows drastic changes in its physical width varying from 200 pc to 1kpc, but a constant line-of-sight velocity dispersion of 5 km s -1 . Despite the large apparent variation in the stellar number density along the stream, the flow rate of stars along the stream is remarkably constant. We model the 6D stream track by a Lagrange-point stripping method with a flexible MW potential in the presence of a moving extended Large Magellanic Cloud (LMC). This allows us to constrain the mass profile of the MW within the distance range 15.6 < r < 55∙5 kpc, with the best measured enclosed mass of (2.85 ± 0.1) X 10 11 M ⊙ within 32.4 kpc. Our stream measurements are highly sensitive to the LMC mass profile with the most precise measurement of its enclosed mass made at 32.8 kpc, 7.02 ± 0.9) X 10 11 M ⊙ . We also detect that the LMC dark matter halo extends to at least 53 kpc. The fitting of the OC stream allows us to constrain the past LMC trajectory and the degree of dynamical friction it experienced. We demonstrate that the stars in the OC stream show large energy and angular momentum spreads caused by LMC perturbation.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Cavern Leaching Monitoring CY18 And CY19

The U.S. Strategic Petroleum Reserve (SPR) is a crude oil storage system run by the U.S. Department of Energy (DOE). The reserve consists of 60 active storage caverns spread across four sites in Louisiana and Texas, near the Gulf of Mexico. Beginning in 2016, the SPR began executing U.S. congressionally mandated oil sales. The configuration of the reserve, with a total capacity of greater than 700 MMB, requires raw water to be used instead of saturated brine for oil withdrawals such as for sales. All sales will produce leaching within the caverns used for oil delivery. Thirty-six caverns had a combined total of over 29 MMB of water injected from CY18-CY19 for mandatory sales. Leaching effects were monitored in these caverns to understand how the sales operations may impact the long-term integrity of the caverns. While frequent sonars are the best way to monitor changes in cavern shape, they can be resource intensive for the number of caverns involved in sales and exchanges. An intermediate option is to model the leaching effects and see if any concerning features develop. The leaching effects were modeled here using the Sandia Solution Mining Code (SANSMIC). The results indicate that leaching induced features are not of concern in the majority of the caverns, 32 of 36. Four caverns, BH-107, BH-108, BH-114 and WH-114 have features that may grow with additional leaching and should be monitored as leaching continues in those caverns. Six caverns had post sale sonars which were compared with SANSMIC results. SANSMIC was able to capture the leaching well. A deviation in the SANSMIC and sonar cavern shapes was observed near the cavern floor in caverns with significant floor rise, a process not captured by SANSMIC. These results suggest SANSMIC is a useful tool for monitoring changes in cavern shape due to leaching effects related to sales and exchanges.

02 PETROLEUM↗
DOE OSTI2021

The Red Supergiant Content of M31 and M33

We identify red supergiants (RSGs) in our spiral neighbors M31 and M33 using near-IR (NIR) photometry complete to a luminosity limit of logL/L{sub ⊙}=4.0. Our archival survey data cover 5 deg{sup 2} of M31, and 3 deg{sup 2} for M33, and are likely spatially complete for these massive stars. Gaia is used to remove foreground stars, after which the RSGs can be separated from asymptotic giant branch (AGB) stars in the color–magnitude diagram. The photometry is used to derive effective temperatures and bolometric luminosities via MARCS stellar atmosphere models. The resulting H-R diagrams show superb agreement with the evolutionary tracks of the Geneva evolutionary group. Our census includes 6400 RSGs in M31 and 2850 RSGs in M33 within their Holmberg radii; by contrast, only a few hundred RSGs are known so far in the Milky Way. Our catalog serves as the basis for a study of the RSG binary frequency being published separately, as well as future studies relating to the evolution of massive stars. Here we use the matches between the NIR-selected RSGs and their optical counterparts to show that the apparent similarity in the reddening of OB stars in M31 and M33 is the result of Malmquist bias; the average extinction in M31 is likely higher than that of M33. As expected, the distribution of RSGs follows that of the spiral arms, while the much older AGB population is more uniformly spread across each galaxy’s disk.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Determining Stellar Elemental Abundances from DESI Spectra with the Data-driven Payne

Abstract Stellar abundances for a large number of stars provide key information for the study of Galactic formation history. Large spectroscopic surveys such as the Dark Energy Spectroscopic Instrument (DESI) and LAMOST take median-to-low-resolution (R≲ 5000) spectra in the full optical wavelength range for millions of stars. However, the line-blending effect in these spectra causes great challenges for elemental abundance determination. Here we employDD-Payne, a data-driven method regularized by differential spectra from stellar physical models, to the DESI early data release spectra for stellar abundance determination. Our implementation delivers 15 labels, including effective temperatureT eff , surface gravity log g , microturbulence velocityv mic , and the abundances for 12 individual elements, namely C, N, O, Mg, Al, Si, Ca, Ti, Cr, Mn, Fe, and Ni. Given a spectral signal-to-noise ratio of 100 per pixel, the internal precisions of the label estimates are about 20 K forT eff , 0.05 dex for log g , and 0.05 dex for most elemental abundances. These results agree with the theoretical limits from the Crámer–Rao bound calculation within a factor of 2. The majority of the accreted halo stars contributed by the Gaia–Enceladus–Sausage are discernible from the disk and in situ halo populations in the resultant [Mg/Fe]–[Fe/H] and [Al/Fe]–[Fe/H] abundance spaces. We also provide distance and orbital parameters for the sample stars, which spread over a distance out to ∼100 kpc. The DESI sample has a significantly higher fraction of distant (or metal-poor) stars than the other existing spectroscopic surveys, making it a powerful data set for studying the Galactic outskirts. The catalog is publicly available.

Astronomy & Astrophysics↗