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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 1,567 records · Page 87
All sourcesNASA NTRSDOE OSTI
NASA NTRS1988

Tidal dissipation, surface heat flow, and figure of viscoelastic models of Io

The deformation of Io, the tidal dissipation rate, and its interior spatial distribution are investigated by means of numerical simulations based on (1) a three-layer model (with dissipation in the mantle) or (2) a four-layer model (with dissipation in the asthenosphere). The mathematical derivation of the models is outlined; the selection of the input-parameter values is explained; the results are presented in extensive graphs and contour maps; and the constraints imposed on the models by observational data on the hot-spot distribution, tidal deformation, and gravity field are discussed in detail. It is found that both dissipation mechanisms may play a role on Io: model (2) is better able to explain the concentration of hot spots near the equator, while the presence of a large hot spot near the south pole (if confirmed by observations) would favor model (1).

Segatz, M.↗
NASA NTRS2021

Oklahoma Health and Air Quality: Mapping Air Quality Using NASA Earth Observations to Investigate Recent Increases in Ozone Concentrations

Tropospheric ozone (O3) is formed by anthropogenic pollutants interacting with sunlight and is considered harmful to human health in high concentrations. In the summer of 2018, the Oklahoma Department of Environmental Quality (DEQ) measured unexpected spikes in O3 in Seiling, Oklahoma, with concentrations exceeding those measured in bustling Oklahoma City and Tulsa. The DEQ tracks air quality using ground monitors and does not utilize Earth observation data in its monitoring or analysis. This project used remotely sensed data to investigate these2018 air quality anomalies, identifying possible causes. We analyzed atmospheric data from Terra and Aqua Moderate Resolution Imaging Spectroradiometer (MODIS), and Sentinel-5P Tropospheric Ozone Monitoring Instrument (TROPOMI) in conjunction with ground-based measurements of tropospheric ozone (O3), nitrogen dioxide (NO2), methane (CH4), carbon monoxide (CO), formaldehyde (HCHO) and aerosol optical depth (AOD). We compared Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model simulations and Earth observation visualizations to pinpoint ozone spike causes. We also generated models to identify contributing factors to variations in ground ozone concentrations in our study area. The results point to a variety of ozone spike causes, primarily from outside of the state, and support the placement of additionalNO2, O3, and CO monitors to the southeast of Seiling. These analyses can help guide the placement of future monitors in the ground monitoring network and inform air quality regulations in Oklahoma.

Carolina Rosales↗
DOE OSTI2025

Jipole: A Differentiable ipole-based Code for Radiative Transfer in Curved Spacetimes

Recent imaging of supermassive black holes by the Event Horizon Telescope has relied on exhaustive parameter-space searches, matching observations to large, precomputed libraries of theoretical models. As observational data become increasingly precise, the limitations of this computationally expensive approach grow more acute, creating a pressing need for more efficient methods. In this work, we present Jipole, an automatically differentiable (AD), ipole-based code for radiative transfer in curved spacetimes, designed to compute image gradients with respect to underlying model parameters. These gradients quantify how parameter changes—such as the black hole’s spin or the observer’s inclination—affect the image, enabling more efficient parameter estimation and reducing the number of required images. We validate Jipole against ipole in two analytical tests and then compare pixelwise intensity derivatives from AD with those from finite-difference methods. We then demonstrate the utility of these gradients by performing parameter recovery for an analytical model in three increasingly complex cases for the injected image: ideal, blurred, and blurred with added noise. In most cases, high-accuracy fits are obtained in only a few optimization steps, failing only in cases with extremely low signal-to-noise ratios. These results highlight the potential of AD-based methods to accelerate robust, high-fidelity model-data comparisons in current and future black hole imaging efforts.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Assessing observational constraints on dark energy

Observational constraints on time-varying dark energy (e.g., quintessence) are commonly presented on a w 0 –w a plot that assumes the equation of state of dark energy strictly satisfies w(z) = w 0 + w a z/(1 + z) as a function of the redshift z. Recent observations favor a sector of the w 0 –w a plane in which w 0 > –1 and w 0 + w a < –1, suggesting that the equation of state underwent a transition from violating the null energy condition (NEC) at large z to obeying it at small z. In this paper, we demonstrate that this impression is misleading by showing that simple quintessence models satisfying the NEC for all z predict an observational preference for the same sector. We also find that quintessence models that best fit observational data can predict a value for the dark energy equation of state at present that is significantly different from the best-fit value of w 0 obtained assuming the parameterization above. In addition, the analysis reveals an approximate degeneracy of the w 0 –w a parameterization that explains the eccentricity and orientation of the likelihood contours presented in recent observational studies.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

Calculation of primordial abundances of light nuclei including a heavy sterile neutrino

We include the coupling of a heavy sterile neutrino with active neutrinos in the calculation of primordial abundances of light-nuclei. We calculate neutrino distribution functions and primordial abundances, as functions depending on a renormalization of the sterile neutrino distribution function (a), the sterile neutrino mass (m{sub s}) and the mixing angle (φ). Using the observable data, we set constrains on these parameters, which have the values 0a < 0.4, sin{sup 2} φ ≈ 0.12−0.39 and 0m{sub s} < 7 keV at 1σ level, for a fixed value of the baryon to photon ratio. When the baryon to photon ratio is allowed to vary, its extracted value is in agreement with the values constrained by Planck observations and by the Wilkinson Microwave Anisotropy Probe (WMAP). It is found that the anomaly in the abundance of {sup 7}Li persists, in spite of the inclusion of a heavy sterile neutrino.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2014

Guide to Using the WIND Toolkit Validation Code

In response to the U.S. Department of Energy's goal of using 20% wind energy by 2030, the Wind Integration National Dataset (WIND) Toolkit was created to provide information on wind speed, wind direction, temperature, surface air pressure, and air density on more than 126,000 locations across the United States from 2007 to 2013. The numerical weather prediction model output, gridded at 2-km and at a 5-minute resolution, was further converted to detail the wind power production time series of existing and potential wind facility sites. For users of the dataset it is important that the information presented in the WIND Toolkit is accurate and that errors are known, as then corrective steps can be taken. Therefore, we provide validation code written in R that will be made public to provide users with tools to validate data of their own locations. Validation is based on statistical analyses of wind speed, using error metrics such as bias, root-mean-square error, centered root-mean-square error, mean absolute error, and percent error. Plots of diurnal cycles, annual cycles, wind roses, histograms of wind speed, and quantile-quantile plots are created to visualize how well observational data compares to model data. Ideally, validation will confirm beneficial locations to utilize wind energy and encourage regional wind integration studies using the WIND Toolkit.

17 WIND ENERGY↗
DOE OSTI2023

First Impressions: Early-time Classification of Supernovae Using Host-galaxy Information and Shallow Learning

Substantial effort has been devoted to the characterization of transient phenomena from photometric information. Automated approaches to this problem have taken advantage of complete phase coverage of an event, limiting their use for triggering rapid follow-up of ongoing phenomena. In this work, we introduce a neural network with a single recurrent layer designed explicitly for early photometric classification of supernovae (SNe). Our algorithm leverages transfer learning to account for model misspecification, host-galaxy photometry to solve the data-scarcity problem soon after discovery, and a custom weighted loss to prioritize accurate early classification. We first train our algorithm using state-of-the-art transient and host-galaxy simulations, then adapt its weights and validate it on the spectroscopically confirmed SNe Ia, SNe II, and SNe Ib/c from the Zwicky Transient Facility Bright Transient Survey. On observed data, our method achieves an overall accuracy of 82% ± 2% within 3 days of an event’s discovery, and an accuracy of 87% ± 5% within 30 days of discovery. At both early and late phases, our method achieves comparable or superior results to the leading classification algorithms with a simpler network architecture. These results help pave the way for rapid photometric and spectroscopic follow-up of scientifically valuable transients discovered in massive synoptic surveys.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

A Strong Gravitational Lens Is Worth a Thousand Dark Matter Halos: Inference on Small-scale Structure Using Sequential Methods

Strong gravitational lenses are a singular probe of the Universe’s small-scale structure—they are sensitive to the gravitational effects of low-mass (<10 10 M ⊙ ) halos even without a luminous counterpart. Recent strong-lensing analyses of dark matter structure rely on simulation-based inference (SBI). Modern SBI methods, which leverage neural networks as density estimators, have shown promise in extracting the halo-population signal. However, it is unclear whether the constraints from these models are limited by the methodology or the data. In this study, we introduce an accelerator-optimized simulation pipeline that can generate lens images with realistic subhalo populations in milliseconds. Leveraging this simulator, we identify the main limitation of our fiducial SBI analysis: training set size. We then adopt a sequential neural posterior estimation (SNPE) approach, allowing us to refine the training distribution to align with the observed data. Using only one-fifth as many mock Hubble Space Telescope images, SNPE matches the constraints on the low-mass halo population produced by our best nonsequential model. Our experiments suggest that an over 3 order-of-magnitude increase in training set size and GPU hours would be required to achieve an equivalent result without sequential methods. While the full potential of the existing lens sample remains to be explored, the notable improvement in constraining power enabled by our sequential approach highlights that current constraints are limited primarily by methodology and not the data itself. Moreover, our results emphasize the need to treat training set generation and model optimization as interconnected stages of any cosmological analysis using SBI.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1991

Observational tests of convective core overshooting in stars of intermediate to high mass in the Galaxy

This study presents the results of 14 tests for the presence of convective overshooting in large convecting stellar cores for stars with masses of 4-17 solar masses which are members of detached close binary systems and of open clusters in the Galaxy. A large body of theoretical and observational data is scrutinized and subjected to averaging in order to minimize accidental and systematic errors. A conservative upper limit of d/HP less than 0.4 is found from at least four tests, as well as a tighter upper limit of d/HP less than 0.2 from one good test that is subject to only mild restrictions and is based on the maximum observed effective temperature of evolved blue supergiants. It is concluded that any current uncertainty about the distance scale for these stars is unimportant in conducting the present tests for convective core overshooting. The correct effective temperature scale for the B0.5-B2 stars is almost certainly close to one of the proposed hot scales.

Stothers, Richard B.↗
NASA NTRS2014

Regional Distribution Models with Lack of Proximate Predictors: Africanized Honeybees Expanding North

Species distribution models have often been hampered by poor local species data, reliance on coarse-scale climate predictors and the assumption that species-environment relationships, even with non-proximate predictors, are consistent across geographical space. Yet locally accurate maps of invasive species, such as the Africanized honeybee (AHB) in North America, are needed to support conservation efforts. Current AHB range maps are relatively coarse and are inconsistent with observed data. Our aim was to improve distribution maps using more proximate predictors (phenology) and using regional models rather than one across the entire range of interest to explore potential differences in drivers.

PRedictors↗
DOE OSTI2023

Using long‐term data from a whole ecosystem warming experiment to identify best spring and autumn phenology models

Abstract Predicting vegetation phenology in response to changing environmental factors is key in understanding feedbacks between the biosphere and the climate system. Experimental approaches extending the temperature range beyond historic climate variability provide a unique opportunity to identify model structures that are best suited to predicting phenological changes under future climate scenarios. Here, we model spring and autumn phenological transition dates obtained from digital repeat photography in a boreal Picea ‐ Sphagnum bog in response to a gradient of whole ecosystem warming manipulations of up to +9°C, using five years of observational data. In spring, seven equally best‐performing models for Larix utilized the accumulation of growing degree days as a common driver for temperature forcing. For Picea , the best two models were sequential models requiring winter chilling before spring forcing temperature is accumulated. In shrub, parallel models with chilling and forcing requirements occurring simultaneously were identified as the best models. Autumn models were substantially improved when a CO 2 parameter was included. Overall, the combination of experimental manipulations and multiple years of observations combined with variation in weather provided the framework to rule out a large number of candidate models and to identify best spring and autumn models for each plant functional type.

Schädel, Christina↗
NASA NTRS1999

Sensitivity of Temperature Profiles Retrieved from Mars Global Surveyor Thermal Emission Spectrometer (MGS/TES) Observations to the GSFC Synthetic Mars Model Atmosphere

Part of the task of interpreting IR spectral features observed by MGS/TES due to surface minerals requires distinguishing those IR signatures from atmospheric signatures of gas and dust. Surface-atmosphere separation for MGS/TES depends on knowledge of the retrieved temperature profile. In turn, the temperature retrieval Erom the observed data depends on molecular parameters including 15 micron CO2 line shape or line intensities which contribute to defining the Mars synthetic radiative transfer model. Using a simple isothermal, homogeneous single layer model of Pinnock and Shine, we find the ratio of (the error in degrees Kelvin of the retrieved temperature profile) to (the percentage error in the absorption coefficient) (deg K/percent) to be 0.4 at 200K. This ratio at 150K and 250K is 0.2 and 0.6, respectively. A more refined model, incorporating observed MGS/TES retrieved temperature profiles, the TES instrumental resolution and the most recent molecular modelling, will yield an improved knowledge of this error sensitivity. We present results of such a sensitivity study to determine the dependence of temperature profiles inverted from MGS/TES on these and other molecular parameters. This work was supported in part by NASA's Mars Data Analysis Program.

Maguire, William C.↗
DOE OSTI2014

Short gamma-ray burst formation rate from BATSE data using E{sub p} -L{sub p} correlation and the minimum gravitational-wave event rate of a coalescing compact binary

Using 72 short gamma-ray bursts (SGRBs) with well determined spectral data observed by BATSE, we determine their redshift and luminosity by applying the E{sub p} -L{sub p} correlation for SGRBs found by Tsutsui et al. For 53 SGRBs with an observed flux brighter than 4 × 10{sup –6} erg cm{sup –2} s{sup –1}, the cumulative redshift distribution up to z = 1 agrees well with that of 22 Swift SGRBs. This suggests that the redshift determination by the E{sub p} -L{sub p} correlation for SGRBs works well. The minimum event rate at z = 0 is estimated as R{sub on−axis}{sup min}=6.3{sub −3.9}{sup +3.1}× 10{sup −10} events Mpc{sup −3} yr{sup −1}, so that the minimum beaming angle is 0.°6-7.°8 assuming a merging rate of 10{sup –7}- 4 × 10{sup –6} events Mpc{sup –3} yr{sup –1} suggested from the binary pulsar data. Interestingly, this angle is consistent with that for SGRB 130603B of ∼4°-8°. On the other hand, if we assume a beaming angle of ∼6° suggested from four SGRBs with the observed beaming angle value, then the minimum event rate including off-axis SGRBs is estimated as R{sub all}{sup min}=1.15{sub −0.66}{sup +0.56} × 10{sup −7} events Mpc{sup −3} yr{sup −1}. If SGRBs are induced by the coalescence of binary neutron stars (NSs) and/or black holes (BHs), then this event rate leads to a minimum gravitational-wave detection rate of 3.8{sub −2.2}{sup +1.8} (146{sub −83}{sup +71}) events yr{sup −1} for an NS-NS (NS-BH) binary, respectively, by a worldwide network with KAGRA, advanced-LIGO, advanced-VIRGO, and GEO.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

On the eigenvector bias of Fourier feature networks: From regression to solving multi-scale PDEs with physics-informed neural networks

Physics-informed neural networks (PINNs) are demonstrating remarkable promise in integrating physical models with gappy and noisy observational data, but they still struggle in cases where the target functions to be approximated exhibit high-frequency or multi-scale features. Here in this work we investigate this limitation through the lens of Neural Tangent Kernel (NTK) theory and elucidate how PINNs are biased towards learning functions along the dominant eigen-directions of their limiting NTK. Using this observation, we construct novel architectures that employ spatio-temporal and multi-scale random Fourier features, and justify how such coordinate embedding layers can lead to robust and accurate PINN models. Numerical examples are presented for several challenging cases where conventional PINN models fail, including wave propagation and reaction–diffusion dynamics, illustrating how the proposed methods can be used to effectively tackle both forward and inverse problems involving partial differential equations with multi-scale behavior.

42 ENGINEERING↗
DOE OSTI2024

Synchronization of the Recent Decline of East African Long Rains and Northwestern Eurasian Warming

Abstract The East African March–April–May (MAM, “long rains”) precipitation decline in recent decades remains a puzzle marked by various proposed large‐scale drivers. Here, the interannual variability of the long rains and their recent drying trend are examined using global model simulations and observations. Comparison of a control simulation and re‐initialized simulations in which land‐surface feedback is suppressed shows that much of the long rains deficit experienced between 1980 and 2014 is synchronized with the warming of the Northwestern Eurasian landmass. In agreement with the modeling results, multiple observational data sets reveal a strong negative correlation between MAM mean East African rainfall amount and the surface temperature over Northwestern Eurasia. Idealized simulations further indicate that warming in Northwestern Eurasia weakens the regional Hadley Cell and diverts the monsoonal transport of moisture away from Eastern Africa toward Europe and southern Africa, highlighting the role of remote land surface warming on the observed precipitation decline.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2014

Dynamical evolution of viscous disks around be stars. II. Polarimetry

Be stars exhibit variability for a great number of observables. Putting the pieces of the disk dynamics together is not an easy task and requires arduous modeling before achieving a good fit to the observational data. In order to guide the modeling process and make it more efficient, it is very instructive to investigate reference dynamical cases. This paper focuses on continuum polarimetric quantities and is the second of a series that aims to demonstrate the capacity of deriving the dynamical history and fundamental parameters of a classical Be star through follow-up of various observables. After a detailed study of the different opacities at play in the formation of polarized spectra, we investigate predictions of polarimetric observables in the continuum for different dynamical scenarios. Our models are based on a coupling of a hydrodynamic viscous decretion simulations in a disk and a three-dimensional non-LTE radiative transfer code. Through introduction of the polarization color diagram (PCD), we show that certain combinations of polarimetric observables exhibit features that are characteristic of a mass-loss history. This diagram also enables estimates of fundamental parameters such as the inclination angle, disk density scale, and the α viscous diffusion parameter. We present the PCD as a powerful diagnosis tool to track the dynamical phases of a Be star, such as disk build-up, dissipation, periodic, and episodic outbursts. Finally, we confront our models with observations of four Be stars that exhibited long-term polarimetric activity.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Identification of Blue Horizontal Branch Stars with Multimodal Fusion

Blue Horizontal Branch stars (BHBs) are ideal tracers to probe the global structure of the milky Way (MW), and the increased size of the BHB star sample could be helpful to accurately calculate the MW's enclosed mass and kinematics. Large survey telescopes have produced an increasing number of astronomical images and spectra. However, traditional methods of identifying BHBs are limited in dealing with the large scale of astronomical data. A fast and efficient way of identifying BHBs can provide a more significant sample for further analysis and research. Therefore, in order to fully use the various data observed and further improve the identification accuracy of BHBs, we have innovatively proposed and implemented a Bi-level attention mechanism-based Transformer multimodal fusion model, called Bi-level Attention in the Transformer with Multimodality (BATMM). The model consists of a spectrum encoder, an image encoder, and a Transformer multimodal fusion module. The Transformer enables the effective fusion of data from two modalities, namely image and spectrum, by using the proposed Bi-level attention mechanism, including cross-attention and self-attention. As a result, the information from the different modalities complements each other, thus improving the accuracy of the identification of BHBs. The experimental results show that the F1 score of the proposed BATMM is 94.78%, which is 21.77% and 2.76% higher than the image and spectral unimodality, respectively. It is therefore demonstrated that higher identification accuracy of BHBs can be achieved by means of using data from multiple modalities and employing an efficient data fusion strategy.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1995

On Ba(+) production in the CRIT 2 experiment

Analysis of partical data from the CRIT 2 experiment, studying Alfven's critical ionization velocity (CIV) effect, shows that the density of newly created ions (presumably Ba(+) from the shaped-charge beam) is consistent with the increase in total plasma density measured by the independent RF plasma probe on board (Swenson et al., 1990) at the most active time period. We model this ion production using the measured electron flux data and the neutral barium model of Stenbaek-Nielsen et al. (1990a). To identify the main source mechanisms which may contribute most to the barium ionization, a simple model for the barium ion density at the payload location is developed based on Liouvilles theorem. We estimate that the electron impact ionization is responsible for 90% of the barium ion production observed by CRIT 2 in the first release and up to 45% in the second release. By employing a two-state approximation calculation (Rapp and Francis, 1962), the Ba-O(+) charge exchange cross section is found to range from about 2.0 X 10(exp -17) sq cm at a velocity of 4 km/s to 2.0 X 10(exp -15) sq cm at a velocity of 20 km/s. This result suggests that the Ba-O(+) charge exchange is probably dominant among all the non-CIV ionization processes. By considering the charge exchange process in our density model, the barrium ion densities are calculated for the two releases on CRIT II. The comparison between the model results and the observed data is found to be resonably consistent if the cross sections, as calculated above, are multiplied by 0.3 for the first release and 1.0 for the second release. Our result suggests that the charge exchange process could be the most important non-CIV ionization mechanism in the CRIT II experiment and it should be considered carefully case by case in CIV experiments.

Liou, K.↗