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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Machine learning method for enforcing variable independence in background estimation with LHC data: ABCDisCoTEC

A novel solution is presented for the problem of estimating the backgrounds of a signal search using observed data while simultaneously maximizing the sensitivity of the search to the signal. The 'ABCD method' provides a reliable framework for background estimation by partitioning events into one signal-enhanced region (A) and three background-enhanced control regions (B, C, and D) via two smoothly varying, statistically independent variables. In practice, even slight correlations between the two variables can significantly undermine the method's performance. Thus, choosing appropriate variables by hand can present a formidable challenge, especially when background and signal differ only subtly. To address this issue, the ABCD with distance correlation (ABCDisCo) method was developed to construct two learned variables via a neural network trained to provide strong signal-background discrimination with small values of the distance correlation (DisCo) measure between the two learned variables. However, relying solely on minimizing the DisCo can result in learned variables that may not have distributions of background events that are smoothly varying and localized at extreme values, as necessary for the validity of the background estimation. The ABCDisCo training enhanced with closure (ABCDisCoTEC) method is introduced to solve this issue by directly minimizing the nonclosure, expressed as a dedicated differentiable loss term. This extended method is applied to a data set of proton-proton collisions at a center-of-mass energy of 13 TeV recorded by the CMS detector at the CERN Large Hadron Collider. Additionally, given the complexity of the minimization problem with constraints on multiple loss terms, the modified differential method of multipliers is applied and shown to greatly improve the stability and robustness of the ABCDisCoTEC method, compared to grid search hyperparameter optimization procedures.

Hayrapetyan, Aram [Yerevan Phys. Inst.]↗
NASA NTRS2000

Statistical Study of Auroral Kilometric Radiation Fine Structure Striations Observed by Polar

We have conducted a statistical survey of a semirandom sample of the auroral kilometric radiation (AKR) data observed by the plasma wave instrument wideband receiver on board the Polar spacecraft. We have determined that AKR fine structure patterns with very narrowband, negative drifting striations occur in approximately 6% of the high-resolution wideband spectrograms when AKR is present. Positive sloping striations are also observed, but at a much lower rate. More than 8200 AKR stripes have been scaled. The stripes are predominantly found in the 40 to 215-kHz frequency range and have a frequency extent of about 4 kHz and a duration of usually less than 2 s. The majority of the stripes have drift rates between -8 and -2 kHz/s, with a peak in the distribution between -6 and -4 kHz/s. There is also a much smaller group of striations with positive drift rates of up to about 5 or 6 kHz/s. We have further investigated the change of drift rate with frequency. Almost all striations are observed in the lowest two frequency bands of the wideband receiver (f < 215 kHz). There is an increase in the statistical drift rate with increasing frequency. The statistical slope of the striations increases with frequency from about -4.4 kHz/s at 75 kHz to about -5.7 kHz/s at 170 kHz. This frequency dependence of the drift rate is consistent, under certain conditions, with a production mechanism stimulated by an upward propagating electromagnetic ion cyclotron wave, as had been suggested earlier. However, such a changing drift rate is also compatible with a stimulated source region that propagates upward along the magnetic field line at the velocity of an ion beam accelerated by a local, upward directed electric field, as is typically observed in the auroral region. An explanation for this association is not apparent at this time.

Menietti, J. D.↗
NASA NTRS2008

Applications of Mars Global Reference Atmospheric Model (Mars-GRAM 2005) Supporting Mission Site Selection for Mars Science Laboratory

The Mars Global Reference Atmospheric Model (Mars-GRAM 2005) is an engineering level atmospheric model widely used for diverse mission applications. An overview is presented of Mars-GRAM 2005 and its new features. One new feature of Mars-GRAM 2005 is the 'auxiliary profile' option. In this option, an input file of temperature and density versus altitude is used to replace mean atmospheric values from Mars-GRAM's conventional (General Circulation Model) climatology. An auxiliary profile can be generated from any source of data or alternate model output. Auxiliary profiles for this study were produced from mesoscale model output (Southwest Research Institute's Mars Regional Atmospheric Modeling System (MRAMS) model and Oregon State University's Mars mesoscale model (MMM5)model) and a global Thermal Emission Spectrometer(TES) database. The global TES database has been specifically generated for purposes of making Mars-GRAM auxiliary profiles. This data base contains averages and standard deviations of temperature, density, and thermal wind components,averaged over 5-by-5 degree latitude-longitude bins and 15 degree L(s) bins, for each of three Mars years of TES nadir data. Results are presented using auxiliary profiles produced from the mesoscale model output and TES observed data for candidate Mars Science Laboratory (MSL) landing sites. Input parameters rpscale (for density perturbations) and rwscale (for wind perturbations) can be used to "recalibrate" Mars-GRAM perturbation magnitudes to better replicate observed or mesoscale model variability.

Justh, Hilary L.↗
NASA NTRS2011

MODIS Aerosol Optical Depth Bias Adjustment Using Machine Learning Algorithms

To monitor the earth atmosphere and its surface changes, satellite based instruments collect continuous data. While some of the data is directly used, some others such as aerosol properties are indirectly retrieved from the observation data. While retrieved variables (RV) form very powerful products, they don't come without obstacles. Different satellite viewing geometries, calibration issues, dynamically changing atmospheric and earth surface conditions, together with complex interactions between observed entities and their environment affect them greatly. This results in random and systematic errors in the final products.

Albayrak, Arif↗
NASA NTRSDate not supplied

High School Citizen Scientists Use AI/ML to Predict Intra-Ocular Pressure From Gene Expression Data for Spaceflown Mice

Artificial Intelligence (AI) and Machine Learning (ML) have increasingly become pivotal in biological and biomedical research, largely due to the culture of open data sharing and its associated benefits. The methodologies inherent in AI/ML are particularly adept at identifying and forecasting biological phenotypes from the vast amounts of data generated by next-generation sequencing technologies. These techniques offer substantial promise for advancing research in space biosciences and for the development of automated systems for monitoring space health. Nevertheless, there are crucial aspects to consider when training, validating, and testing machine learning models in both biological research and clinical contexts. It is essential that Open Science principles, including data sharing and the availability of open-source code, are complemented by high-quality, publicly accessible training resources. These resources should focus on best practices and include modules based on real-world scientific cases and data to ensure that future AI/ML practitioners gain practical experience with genuine problems. Addressing this knowledge gap, we have designed, developed, and delivered both interactive and self-paced training programs for citizen scientists worldwide, enabling them to utilize AI/ML for space biology research. This initiative was made possible through generous funding from a Transformation to Open Science Training grant. The interactive training sessions, conducted this summer, utilized AI/ML techniques to analyze data from the Open Science Data Repository, specifically targeting the effects of spaceflight on ocular structure and function. The dataset OSD-583, from the Rodent Research 9 mission, provides experimental data detailing the ocular responses of mice subjected to a 35-day spaceflight, compared with ground control counterparts. Using OSD-583 as observational data, our summer training participants applied AI/ML methods to predict intraocular pressure from RNA-seq data and identify the genes most predictive of the observed responses. Further analysis through pathway enrichment and gene set enrichment revealed that these genes are involved in molecular and cellular processes contributing to retinal degeneration.

James Casaletto↗
NASA NTRS2016

Soil Moisture Active Passive Mission L4_C Data Product Assessment (Version 2 Validated Release)

The SMAP satellite was successfully launched January 31st 2015, and began acquiring Earth observation data following in-orbit sensor calibration. Global data products derived from the SMAP L-band microwave measurements include Level 1 calibrated and geolocated radiometric brightness temperatures, Level 23 surface soil moisture and freezethaw geophysical retrievals mapped to a fixed Earth grid, and model enhanced Level 4 data products for surface to root zone soil moisture and terrestrial carbon (CO2) fluxes. The post-launch SMAP mission CalVal Phase had two primary objectives for each science product team: 1) calibrate, verify, and improve the performance of the science algorithms, and 2) validate accuracies of the science data products as specified in the L1 science requirements. This report provides analysis and assessment of the SMAP Level 4 Carbon (L4_C) product pertaining to the validated release. The L4_C validated product release effectively replaces an earlier L4_C beta-product release (Kimball et al. 2015). The validated release described in this report incorporates a longer data record and benefits from algorithm and CalVal refinements acquired during the SMAP post-launch CalVal intensive period. The SMAP L4_C algorithms utilize a terrestrial carbon flux model informed by SMAP soil moisture inputs along with optical remote sensing (e.g. MODIS) vegetation indices and other ancillary biophysical data to estimate global daily net ecosystem CO2 exchange (NEE) and component carbon fluxes for vegetation gross primary production (GPP) and ecosystem respiration (Reco). Other L4_C product elements include surface (10 cm depth) soil organic carbon (SOC) stocks and associated environmental constraints to these processes, including soil moisture and landscape freeze/thaw (FT) controls on GPP and respiration (Kimball et al. 2012). The L4_C product encapsulates SMAP carbon cycle science objectives by: 1) providing a direct link between terrestrial carbon fluxes and underlying FT and soil moisture constraints to these processes, 2) documenting primary connections between terrestrial water, energy and carbon cycles, and 3) improving understanding of terrestrial carbon sink activity in northern ecosystems. There are no L1 science requirements for the L4_C product; however self-imposed requirements have been established focusing on NEE as the primary product field for validation, and on demonstrating L4_C accuracy and success in meeting product science requirements (Jackson et al. 2012). The other L4_C product fields also have strong utility for carbon science applications; however, analysis of these other fields is considered secondary relative to primary validation activities focusing on NEE. The L4_C targeted accuracy requirements are to meet or exceed a mean unbiased accuracy (ubRMSE) for NEE of 1.6 g C/sq m/d or 30 g C/sq m/yr, emphasizing northern (45N) boreal and arctic ecosystems; this is similar to the estimated accuracy level of in situ tower eddy covariance measurement-based observations (Baldocchi 2008).

Cal/Val↗
NASA NTRS1993

Compositional and textural information from the dual inversion of visible, near and thermal infrared remotely sensed data

A technique is presented that allows extraction of compositional and textural information from visible, near and thermal infrared remotely sensed data. Using a library of both emissivity and reflectance spectra, endmember abundances and endmember thermal inertias are extracted from AVIRIS (Airborne Visible and Infrared Imaging Spectrometer) and TIMS (Thermal Infrared Mapping Spectrometer) data over Lunar Crater Volcanic Field, Nevada, using a dual inversion. The inversion technique is motivated by upcoming Mars Observer data and the need for separation of composition and texture parameters from sub pixel mixtures of bedrock and dust. The model employed offers the opportunity to extract compositional and textural information for a variety of endmembers within a given pixel. Geologic inferences concerning grain size, abundance, and source of endmembers can be made directly from the inverted data. These parameters are of direct relevance to Mars exploration, both for Mars Observer and for follow-on missions.

Brackett, Robert A.↗
DOE OSTI2025

Validation of the DESI 2024 Lyman alpha forest BAL masking strategy

Broad absorption line quasars (BALs) exhibit blueshifted absorption relative to a number of their prominent broad emission features. These absorption features can contribute to quasar redshift errors and add absorption to the Lyman-α (Lyα) forest that is unrelated to large-scale structure. We present a detailed analysis of the impact of BALs on the Baryon Acoustic Oscillation (BAO) results with the Lyα forest from the first year of data from the Dark Energy Spectroscopic Instrument (DESI). The baseline strategy for the first year analysis is to mask all pixels associated with all BAL absorption features that fall within the wavelength region used to measure the forest. We explore a range of alternate masking strategies and demonstrate that these changes have minimal impact on the BAO measurements with both DESI data and synthetic data. This includes when we mask the BAL features associated with emission lines outside of the forest region to minimize their contribution to redshift errors. We identify differences in the properties of BALs in the synthetic datasets relative to the observational data, as well as use the synthetic observations to characterize the completeness of the BAL identification algorithm, and demonstrate that incompleteness and differences in the BALs between real and synthetic data also do not impact the BAO results for the Lyα forest.

Lyman alpha forest↗
DOE OSTI2018

Neoclassical Diffusion of Radiation-Belt Electrons Across Very Low L -shells

In the presence of drift-shell splitting intrinsic to the IGRF magnetic field model, pitch-angle scattering from Coulomb collisions experienced by radiation-belt electrons in the upper atmosphere and ionosphere produces extra radial diffusion, a form of neoclassical diffusion. The strength of the neoclassical radial diffusion at L < 1.2 exceeds that expected there from radial-diffusion mechanisms traditionally considered, and decreases with increasing L-shell. In this study we construct a numerical model for this coupled (radial and pitch-angle) collisional diffusion process and apply it to simulate raw count-rate data observed aboard the Gemini spacecraft for several years after the 1962 Starfish nuclear detonation. The data show apparent lifetimes 10-100 times as long as would have been expected from collisional pitch-angle diffusion and Coulomb drag alone. Our model reproduces apparent lifetimes for >0.5-MeV electrons in the region 1.14 < L < 1.26 to within a factor of two (comparable to the uncertainty quoted for the observations). We conclude that neoclassical radial diffusion (resulting from drift-shell splitting intrinsic to IGRF's azimuthal asymmetries) mitigates the decay expected from collisional pitch-angle diffusion and inelastic energy loss alone and thus contributes importantly to the long apparent lifetimes observed at these low L-shells.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Preference for a pressure-induced 3D structure after 1T-HfSe 2

Extensive crystal structure prediction searches provide evidence of two 3D structures with orthorhombic (Immm) and monoclinic (C2/m) space groups as reasonable candidates for the first pressure-induced phase of 1T-HfSe 2 . Our candidates are compared with two recent proposals that keep the 2D nature of the ambient conditions phase and display hexagonal (P6 3 /mmc) and monoclinic (C2/m) symmetry, although the latter has a different structure than our proposed C2/m phase. Both of these 2D-like structures are discarded based on simple thermodynamic and kinetic arguments that can be extended to explain the pressure-induced polymorphic sequence of other transition metal dichalcogenides. The computed observables of our orthorhombic phase are fully consistent with the experimental structural and Raman data observed at low and high-pressure.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Community detection in hypergraphs via mutual information maximization

Abstract The hypergraph community detection problem seeks to identify groups of related vertices in hypergraph data. We propose an information-theoretic hypergraph community detection algorithm which compresses the observed data in terms of community labels and community-edge intersections. This algorithm can also be viewed as maximum-likelihood inference in a degree-corrected microcanonical stochastic blockmodel. We perform the compression/inference step via simulated annealing. Unlike several recent algorithms based on canonical models, our microcanonical algorithm does not require inference of statistical parameters such as vertex degrees or pairwise group connection rates. Through synthetic experiments, we find that our algorithm succeeds down to recently-conjectured thresholds for sparse random hypergraphs. We also find competitive performance in cluster recovery tasks on several hypergraph data sets.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

A TEST OF THE FORMATION MECHANISM OF THE BROAD LINE REGION IN ACTIVE GALACTIC NUCLEI

The origin of the broad line region (BLR) in active galaxies remains unknown. It seems to be related to the underlying accretion disk, but an efficient mechanism is required to raise the material from the disk surface without giving signatures of the outflow that are too strong in the case of the low ionization lines. We discuss in detail two proposed mechanisms: (1) radiation pressure acting on dust in the disk atmosphere creating a failed wind and (2) the gravitational instability of the underlying disk. We compare the predicted location of the inner radius of the BLR in those two scenarios with the observed position obtained from the reverberation studies of several active galaxies. The failed dusty outflow model well represents the observational data while the predictions of the self-gravitational instability are not consistent with observations. The issue that remains is why do we not see any imprints of the underlying disk instability in the BLR properties.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1973

On the identifiability of linear dynamical systems

Consider the situation in which the unknown parameters of a stationary linear system may be parametrized by a set of unknown parameters. The question thus arises of when such a set of parameters can be uniquely identified on the basis of observed data. This problem is considered here both in the case of input and output observations and in the case of output observations in the presence of a white noise input. Conditions for local identifiability are derived for both situations and a sufficient condition for global identifiability is given for the former situation, i.e., when simultaneous input and output observations are available.

Glover, K.↗
NASA NTRS1985

Anomalous increase of solar anisotropy above 150GV in 1981-1983

An analysis was carried out of the observed data with Nagoya (surface). Misato (34mwe) and Sakashita (80mwe) multidirectional muon telescope, for the solar activity maximum period of 1978-1983. These data respond to primaries extending over the median rigidity range 60GV to 600GV. The observed amplitude at Sakashita station in 1981-1983 increased, especially in 1982; the amplitude is twice as large as that in 1978-1980, when those at Nagoya and Misato stations are nearly the same as those in 1978-1980. Uni-directional anisotropy is derived by the best fit method by assuming the flat rigidity spectrum with the upper cutoff rigidity Pu. The value of Pu obtained is 270GV in 1981-1983 and 150GV in 1978-1980.

Ueno, H.↗
NASA NTRS1986

Comparative energetics of the observed and simulated global circulation during the special observing periods of FGGE

Energetics of the observed and simulated global circulation are evaluated in the zonal spectral domain for the special observing periods of FGGE. The study utilizes GLA analyses of FGGE observational data and parallel simulation experiments. There are noticeable differences in energy transformations between the observation and simulation during SOP-1. These include the baroclinic conversion C(n) by the zonal mean motion and short-wave disturbances, and the nonlinear wave-wave interaction L(n) at the long and short waves. The energy transformations of the short-wave disturbances are much more intense in the simulated circulation than in the observation. However, good agreement is noted in the conversion and dissipation of kinetic energy in the large- and cyclone-wave range n = 1-10. Spectral distributions of global energy transformations at the long- and cyclone-wave range indicate that the SOP-2 simulation agrees more closely with the observed fields than the SOP-1 simulation. Other pertinent points of energetics diagnosis are also included in the discussion.

Kung, E. C.↗
NASA NTRS2007

An Integrated High Resolution Hydrometeorological Modeling Testbed using LIS and WRF

Scientists have made great strides in modeling physical processes that represent various weather and climate phenomena. Many modeling systems that represent the major earth system components (the atmosphere, land surface, and ocean) have been developed over the years. However, developing advanced Earth system applications that integrates these independently developed modeling systems have remained a daunting task due to limitations in computer hardware and software. Recently, efforts such as the Earth System Modeling Ramework (ESMF) and Assistance for Land Modeling Activities (ALMA) have focused on developing standards, guidelines, and computational support for coupling earth system model components. In this article, the development of a coupled land-atmosphere hydrometeorological modeling system that adopts these community interoperability standards, is described. The land component is represented by the Land Information System (LIS), developed by scientists at the NASA Goddard Space Flight Center. The Weather Research and Forecasting (WRF) model, a mesoscale numerical weather prediction system, is used as the atmospheric component. LIS includes several community land surface models that can be executed at spatial scales as fine as 1km. The data management capabilities in LIS enable the direct use of high resolution satellite and observation data for modeling. Similarly, WRF includes several parameterizations and schemes for modeling radiation, microphysics, PBL and other processes. Thus the integrated LIS-WRF system facilitates several multi-model studies of land-atmosphere coupling that can be used to advance earth system studies.

Kumar, Sujay V.↗
NASA NTRSDate not supplied

Combining Disparate Measures of Metabolic Rate During Simulated Spacewalks

Scientists from NASA's Extravehicular Activities (EVA) Physiology Systems and Performance Project help design space suits for future missions, during which astronauts are expected to perform EVA activities on the Lunar or Martian surface. During an EVA, an astronaut's integrated metabolic rate is used to predict how much longer the activity can continue and still provide a safe margin of remaining consumables. For EVAs in the Apollo era, NASA physicians monitored live data feeds of heart rate, O 2 consumption, and liquid cooled garment (LCG) temperatures, which were subjectively combined or compared to produce an estimate of metabolic rate. But these multiple data feeds sometimes provided conflicting estimates of metabolic rate, making real-time calculations of remaining time difficult for physician/monitors. Currently, designs planned for the Constellation Program EVAs utilize an automated, but largely heuristic methodology for incorporating the above three measurements, plus an additional one - CO 2 production, ignoring data that appears in conflict; however a more rigorous model-based approach is desirable. In this study, we show how principal axis factor analysis, in combination with OLS regression and LOWESS smoothing can be used to estimate metabolic rate as a data-driven weighted average of heart rate, O 2 consumption, LCG temperature data, and CO 2 production. Preliminary results suggest less sensitivity to occasional spikes in observed data feeds, and reasonable within-subject reproducibility when applied to subsequent tasks. These methods do not require physician monitoring and as such can be automated in the electronic components of future space suits. With additional validation, our models show promise for increasing astronaut safety, while reducing the need for and potential errors associated with human monitoring of multiple systems.

Alan H Feiveson↗
NASA NTRS2016

Virtual Collections: An Earth Science Data Curation Service

The role of Earth science data centers has traditionally been to maintain central archives that serve openly available Earth observation data. However, in order to ensure data are as useful as possible to a diverse user community, Earth science data centers must move beyond simply serving as an archive to offering innovative data services to user communities. A virtual collection, the end product of a curation activity that searches, selects, and synthesizes diffuse data and information resources around a specific topic or event, is a data curation service that improves the discoverability, accessibility, and usability of Earth science data and also supports the needs of unanticipated users. Virtual collections minimize the amount of the time and effort needed to begin research by maximizing certainty of reward and by providing a trustworthy source of data for unanticipated users. This presentation will define a virtual collection in the context of an Earth science data center and will highlight a virtual collection case study created at the Global Hydrology Resource Center data center.

Data↗