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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 199 records · Page 11

Results of a flow field survey conducted using the 0.0175 scale orbiter model 29-0 in AEDC VKF tunnel B during test OH52

Static pressure data and flow field surveys of the boundary layer and shock layer on the lower surface of a 0.0175 scale model of the space shuttle orbiter were obtained in a hypersonic wind tunnel. The tests were conducted at Mach number 7.9 and Reynolds number based on the model length of 1.3 x 1 million to simulate atmospheric entry. Twenty-six stations were surveyed at 30 and 35 degree angles of attack.

Herrera, B. J.↗

Statistical Modeling of Quiet Sonic Boom Community Response Survey Data

The existing ban on commercial supersonic flight overland is largely due to the effects of loud and startling sonic booms on communities. NASA is planning a nationwide campaign of community response surveys using the experimental X-59 Quiet SuperSonic Technology (X-59 QueSST) aircraft to understand how communities perceive the sounds of quiet supersonic flight. The X-59 community response survey data will be presented to noise regulators, who are considering replacing the ban with a noise-based certification limit so quiet supersonic vehicles can fly over land. In this document, we use pilot community response survey data to explore and assess multiple approaches to statistically model the dose-response relationship between single-event sonic boom sound exposure and human annoyance. The models have two primary functions—estimating two types of quantities that support setting regulations and experimental design of future surveys.

Jasme Lee↗

Cross-correlation of Dark Energy Survey Year 3 lensing data with ACT and Planck thermal Sunyaev-Zel’dovich effect observations. I. Measurements, systematics tests, and feedback model constraints

Here we present a tomographic measurement of the cross-correlation between thermal Sunyaev-Zel’dovich (TSZ) maps from Planck and the Atacama Cosmology Telescope and weak galaxy lensing shears measured during the first three years of observations of the Dark Energy Survey. This correlation is sensitive to the thermal energy in baryons over a wide redshift range and is therefore a powerful probe of astrophysical feedback. We detect the correlation at a statistical significance of 21σ, the highest significance to date. We examine the TSZ maps for potential contaminants, including cosmic infrared background and radio sources, finding that cosmic infrared background has a substantial impact on our measurements and must be taken into account in our analysis. We use the cross-correlation measurements to test different feedback models. In particular, we model the TSZ using several different pressure profile models calibrated against hydrodynamical simulations. Our analysis marginalizes over redshift uncertainties, shear calibration biases, and intrinsic alignment effects. We also marginalize over Ω m and σ 8 using Planck or DES priors. We find that the data prefer the model with a low amplitude of the pressure profile at small scales, compatible with a scenario with strong active galactic nuclei feedback and ejection of gas from the inner part of the halos. When using a more flexible model for the shear profile, constraints are weaker, and the data cannot discriminate between different baryonic prescriptions.

79 ASTRONOMY AND ASTROPHYSICS↗

Phase II Field Demonstration at Lansing Smith Generating Plant, Southport, Florida (Final Report)

The Final Technical Report: Field Test Design and Pressure Management Strategies for Phase II Field Demonstration of Optimal Pressure Control, Plume Management, and Produced Water Strategies presents the culmination of multi-year efforts under the U.S. Department of Energy’s Brine Extraction and Storage Test (BEST) program, led by EPRI in partnership with Gulf Power at the Plant Smith site near Panama City, Florida. The project was designed to evaluate and demonstrate the technical feasibility of managing subsurface pressures and fluid movement associated with large-scale CO₂ injection, using low-salinity water as a proxy fluid. Through a combination of field injection testing, reservoir modeling, and optimization studies, the research team developed and refined active and passive brine extraction strategies aimed at controlling injection-induced pressure buildup, mitigating risks of fault activation, and managing plume migration. The field demonstration incorporated a new injection well (TIW-2), a new monitoring/extraction well (TEMW-A), and an existing well (TIW-1) repurposed for passive pressure relief. Complementary geophysical monitoring was designed to track plume development and evaluate the effectiveness of pressure management strategies. The report details the integrated workflow encompassing wellfield development, regulatory permitting, model calibration, and survey design. It includes a comprehensive electromagnetic (EM) modeling and inversion study used to develop a cost-effective, time-lapse geophysical monitoring plan capable of imaging the evolving low-salinity plume within the highly saline Lower Tuscaloosa formation. Reservoir simulation results guided the design of the 17-month injection program and the timing of active extraction to maintain formation pressures below a hypothetical fault reactivation threshold. Supporting analyses evaluated potential injectivity risks related to clay fines migration and geochemical incompatibility, identifying practical mitigation measures such as salinity and pH control. The final design recommends a series of crosswell EM surveys—conducted before, during, and after injection—as the most effective and economical approach for plume imaging, supplemented by continuous downhole pressure and flow monitoring. Collectively, the study provides a field-ready framework for cost-effective pressure management and monitoring in support of future CO₂ storage projects.

01 COAL, LIGNITE, AND PEAT↗

Comparing Automated Posterior Estimation Techniques for Modeling Strong Lenses In Ground-based Survey Data

Current and future ground-based cosmological surveys, such as the Dark Energy Survey (DES), and the Vera Rubin Observatory Legacy Survey of Space and Time (LSST), are predicted to discover thousands to tens of thousands of strong gravitational lenses. The large number of strong lenses discoverable in future surveys will make strong lensing a highly competitive and complementary cosmic probe. However, conventional lens modeling techniques are unable to scale up to the sheer number of lenses that will be discovered through upcoming surveys. Therefore, the use of automated lens analysis techniques is necessary. We demonstrate that machine learning methods can be used to automate the inference of informative model posteriors of strong lensing systems in ground-based surveys with credible uncertainty estimation. We present two Simulation-Based Inference (SBI) approaches for lens parameter estimation of galaxy-galaxy lenses. We demonstrate applications of Neural Posteriors Estima tors (NPEs) and Bayesian Neural Network (BNNs) to automate the inference of a 12-parameter lensing system for DES-like ground-based imaging data. We apply a suite of diagnostics (e.g., posterior coverage and SBC) to validate the performance of our methods. We find that NPEs outperform the BNN, producing posterior distributions that are for the most part both more accurate and more precise; in particular, several source-light model parameters are systematically biased in the BNN implementation.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Primary energy release

The physical processes by which the magnetic energy of a solar active region is converted to other forms of energy in the appearance of a solar flare are discussed. Observations of the secondary manifestations of flare energy release, such as thermal plasmas and energetic particle emissions, are presented, with particular attention given to the temporal variations of flare radiation, the various forms of energy release, flare energy density, flare locations and sizes, energy distributions and H alpha, hard X-ray and microwave burst events. Current models of the primary energy release process are surveyed, and the models of Spicer (1976, 1977), which explains rapid flare energy release in terms of multiple tearing modes causing reconnection in sheared magnetic fields, and Uchida and Sakurai (1976, 1978), which attributes primary energy release to dynamic collapse caused by the interchange instability of the neutral sheet, are examined in detail.

Kahler, S.↗

Toward a CFD nose-to-tail capability - Hypersonic unsteady Navier-Stokes code validation

Computational fluid dynamics (CFD) research for hypersonic flows presents new problems in code validation because of the added complexity of the physical models. This paper surveys code validation procedures applicable to hypersonic flow models that include real gas effects. The current status of hypersonic CFD flow analysis is assessed with the Compressible Navier-Stokes (CNS) code as a case study. The methods of code validation discussed to beyond comparison with experimental data to include comparisons with other codes and formulations, component analyses, and estimation of numerical errors. Current results indicate that predicting hypersonic flows of perfect gases and equilibrium air are well in hand. Pressure, shock location, and integrated quantities are relatively easy to predict accurately, while surface quantities such as heat transfer are more sensitive to the solution procedure. Modeling transition to turbulence needs refinement, though preliminary results are promising.

Edwards, Thomas A.↗

A semblance measure for model comparison

Algorithmic and computational advances have made it possible that geophysical survey and earth model design can be aided by many systematic trial inverse-modelling runs with synthetic data. Such may, for example, come up in machine-learning approaches. Automated image appraisal pertaining to such applications will involve common statistical tests for goodness-of-data fit as a primary evaluation method. However, solution non-uniqueness may render multiple images equivalent in terms of their data fit, requiring secondary categorizers. A logical choice for classifying synthetic-imaging results quantifies the goodness of model fit where a known reference model replaces the observational input. The task of model intercomparison in terms of measuring the resemblance to the reference model poses challenges to common distance-based metrics like root mean square error and mean absolute error. First, distance-based metrics can introduce spurious contributions when smooth models with fuzzy target contours are to be compared against a sharp reference. Second, large differences due to parameter-estimation overshoots can dominate distance metrics. Here, we propose a remedy that is referred to as semblance and is based on the idea of logistic functions, where a binary-dependent variable adds non-zero or zero accumulation terms for the, respectively, passing or failing of preset target thresholds. This classifying approach is amenable to an objective where model feature recognition is primary. Numerical comparisons to distance-based metrics provide evidence for the advantages of the semblance in view of this objective. Geophysical imaging in conjunction with machine-learning is seen as a benefitting upcoming application area.

58 GEOSCIENCES↗

Parameterization of Aerosol Sinks in Chemical Transport Models

The modelers point of view is that the aerosol problem is one of sources, evolution, and sinks. Relative to evolution and sink processes, enormous attention is given to the problem of aerosols sources, whether inventory based (e.g., fossil fuel emissions) or dynamic (e.g., dust, sea salt, biomass burning). On the other hand, aerosol losses in models are a major factor in controlling the aerosol distribution and lifetime. Here we shine some light on how aerosol sinks are treated in modern chemical transport models. We discuss the mechanisms of dry and wet loss processes and the parameterizations for those processes in a single model (GEOS-5). We survey the literature of other modeling studies. We additionally compare the budgets of aerosol losses in several of the ICAP models.

Colarco, Peter↗

Assessment of Higher-Order RANS Closures in a Decelerated Planar Wall-Bounded Turbulent Flow

A reference DNS database is presented, which includes third- and fourth-order moment budgets for unstrained and strained planar channel flow. Existing RANS closure models for third- and fourth-order terms are surveyed, and new model ideas are introduced. The various models are then compared with the DNS data term by term using a priori testing of the higher-order budgets of turbulence transport, velocity-pressure-gradient, and dissipation for both the unstrained and strained databases. Generally, the models for the velocity-pressure-gradient terms are most in need of improvement.

Jeyapaul, Elbert↗

How deep is your soil? Quantifying and spatially analyzing understudied deep soil in the United States

Deep soil is largely understudied and important in understanding biogeochemical processes in soil. Here, understudied soil is defined as the difference between soil studied to a known depth and the estimated bedrock depth. To understand more about deep soil, the understudied soil in the US was quantified and spatially analyzed using soil survey data and model estimates of bedrock depth. An equation was derived to find understudied soil using the dataset parameters “max lower depth studied”, “depth to bedrock”, and “likelihood of bedrock in the top 200 cm”. The survey data and bedrock model revealed that soil has been studied to an average depth of 1-2 meters, and the average depth to bedrock is 20 meters. Soil data density in the soil surveys was greatest in the West Coast, Midwest, and areas historically managed for agricultural, while the non-contiguous US and interior West were underrepresented. The soil had been studied deeper than the estimated soil depth in 455 out of 56,889 observation points concentrated in Alaska, California, Texas, Florida, Puerto Rico, and the US Virgin Islands. To understand the diversity and any taxonomic bias of the global soil data available, soil order was compared to US-based National Resource Conservation Service percentages and it was found that Oxisols, Alfisols, Ultisols, Andisols, and Histosols were overrepresented while Gelisols, Aridisols, Vertisols, Entisols, and Spodosols are underrepresented. Soil depth is important in exploring the complexity of biogeochemical processes that take place in soil.

Bedrock↗

Dynamical models of highly flattened oblate elliptical galaxies with De Vaucouleurs' surface-brightness profiles

Two surveys of dynamical models of E6 elliptical galaxies were constructed with de Vaucouleurs'surface-brightness distributions. One set of models has a constant mass-to-light ratio. The other set consists of models embedded in oblate isothermal gravitational potentials. In both sets, the observed axis ratio of the models is 0.55 when viewed edge-on. When viewed edge-on, it is possible to construct models in either potential that have velocity-dispersion profiles that increase or decrease with radius along either or both principal axes. The observational data seem to indicate that dispersion profiles decrease or remain constant as function of radius. The most surprising result of this work is that in order for a model to have velocity-dispersion profiles that decrease with radius out to 1.5 r(e) along both principal axes, it must be dominated by fairly thin-walled tube orbits at large radii. This is very different from the spherical case, where radial orbits dominate at large radii.

Fillmore, James A.↗

Registratiom of TM data to digital elevation models

Several problems arise when attempting to register LANDSAT thematic mapper data to U.S. B Geological Survey digital elevation models (DEMs). The TM data are currently available only in a rotated variant of the Space Oblique Mercator (SOM) map projection. Geometric transforms are thus; required to access TM data in the geodetic coordinates used by the DEMs. Due to positional errors in the TM data, these transforms require some sort of external control. The spatial resolution of TM data exceeds that of the most commonly DEM data. Oversampling DEM data to TM resolution introduces systematic noise. Common terrain processing algorithms (e.g., close computation) compound this problem by acting as high-pass filters.

Source record↗

Registering Thematic Mapper imagery to digital elevation models

The problems encountered when attempting to register Landsat Thematic Mapper (TM) data to U.S. geological survey digital elevation models (DEMs) are examined. It is shown that TM and DEM data are not available in the same map projection, necessitating geometric transformation of one of the data type, that the TM data are not accurately located in their nominal projection, and that TM data have higher resolution than most DEM data, but oversampling the DEM data to TM resolution introduces systematic noise. Further work needed in this area is discussed.

Frew, J.↗

Modeling the structure of H I in the galactic disk

For comparison with a detailed H I survey, we calculated models for the H I intensity distribution, T(B)(l, b, v), for a 18 x 12 deg region in the disk of the Galaxy toward l = 205 deg. In one class of models, neutral hydrogen is in the form of clouds, while in the other class of models it is a continuous medium with holes whose sizes are typical of supernova remnants and superbubbles. The cloud models are a poor representation of the data in that the amplitude fluctuations are dissimilar and the continuity of the H I observations is not reproduced. A continuous H I medium with holes provides a much better match to the data, and the best-fit models suggest that the filling factor for the H I is 20-50 percent.

Bregman, Joel N.↗

Soil microbiome predictability increases with spatial and taxonomic scale

Soil microorganisms shape ecosystem function, yet it remains an open question whether we can predict the composition of the soil microbiome in places before observing it. Furthermore, it is unclear whether the predictability of microbial life exhibits taxonomic- and spatial-scale dependence, as it does for macrobiological communities. Here, we leverage multiple large-scale soil microbiome surveys to develop predictive models of bacterial and fungal community composition in soil, then test these models against independent soil microbial community surveys from across the continental United States. We find remark- able scale dependence in community predictability. The predictability of bacterial and fungal communities increases with the spatial scale of observation, and fungal predictability increases with taxonomic scale. These patterns suggest that there is an increasing importance of deterministic versus stochastic processes with scale, consistent with findings in plant and animal communities, suggesting a general scaling relationship across biology. Biogeochemical functional groups and high-level taxonomic groups of microorganisms were equally predictable, indicating that traits and taxonomy are both powerful lenses for understanding soil communities. Here, by focusing on out-of-sample prediction, these findings suggest an emerging generality in our understanding of the soil microbiome, and that this understanding is fundamentally scale dependent

Biogeography↗

The Completed SDSS-IV extended Baryon Oscillation Spectroscopic Survey: exploring the halo occupation distribution model for emission line galaxies

We study the modelling of the halo occupation distribution (HOD) for the eBOSS DR16 emission line galaxies (ELGs). Motivated by previous theoretical and observational studies, we consider different physical effects that can change how ELGs populate haloes. We explore the shape of the average HOD, the fraction of satellite galaxies, their probability distribution function (PDF), and their density and velocity profiles. Our baseline HOD shape was fitted to a semi-analytical model of galaxy formation and evolution, with a decaying occupation of central ELGs at high halo masses. We consider Poisson and sub/super-Poissonian PDFs for satellite assignment. We model both Navarro–Frenk–White and particle profiles for satellite positions, also allowing for decreased concentrations. We model velocities with the virial theorem and particle velocity distributions. Additionally, we introduce a velocity bias and a net infall velocity. We study how these choices impact the clustering statistics while keeping the number density and bias fixed to that from eBOSS ELGs. The projected correlation function, w p , captures most of the effects from the PDF and satellites profile. The quadrupole, ξ 2 , captures most of the effects coming from the velocity profile. We find that the impact of the mean HOD shape is subdominant relative to the rest of choices. Here, we fit the clustering of the eBOSS DR16 ELG data under different combinations of the above assumptions. The catalogues presented here have been analysed in companion papers, showing that eBOSS RSD+BAO measurements are insensitive to the details of galaxy physics considered here. These catalogues are made publicly available.

79 ASTRONOMY AND ASTROPHYSICS↗

LISA Galactic binaries in the Roman Galactic Bulge Time-Domain Survey

ABSTRACT Short-period Galactic white dwarf binaries detectable by Laser Interferometer Space Antenna are the only guaranteed persistent sources for multimessenger gravitational-wave astronomy. Large-scale surveys in the 2020s present an opportunity to conduct preparatory science campaigns to maximize the science yield from future multimessenger targets. The Nancy Grace Roman Space Telescope Galactic Bulge Time-Domain Survey will (in its Reference Survey design) image seven fields in the Galactic Bulge approximately 40 000 times each. Although the Reference Survey cadence is optimized for detecting exoplanets via microlensing, it is also capable of detecting short-period white dwarf binaries. In this paper, we present forecasts for the number of detached short-period binaries the Roman Galactic Bulge Time-Domain Survey will discover and the implications for the design of electromagnetic surveys. Although population models are highly uncertain, we find a high probability that the baseline survey will detect of the order of ∼5 detached white dwarf binaries. The Reference Survey would also have a ${\gtrsim} 20\,{\rm per\,cent}$ chance of detecting several known benchmark white dwarf binaries at the distance of the Galactic Bulge.

Astronomy & Astrophysics↗