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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 613 records · Page 34
All sourcesNASA NTRSDOE OSTI
NASA NTRS2002

Spectroscopy of Low Mass X-Ray Binaries: New Insights into Accretion

This project is to observe two low mass X-ray binaries, chosen for their X-ray brightness, low column density, and diversity of accretion behavior. The high spectral resolution of the RGS, the broad energy range and tremendous collecting power of EPIC, and simultaneous optical monitoring with the OM are particularly well-suited to these studies. The second of two objects was not observed until September of 2002. Data analysis for the new observation is underway. over the next year we will: investigate the physical conditions of the emitting gas using emission and recombination line diagnostics to determine temperatures, densities, elemental abundances, and ionization structure; study the behavior of emission features as a function of binary orbit; and test and improve models of X-ray line emission developed by us over the past decade. We will gain insight on both the geometry of the accretion flow and on the evolutionary history of LMXBs.

Vrtilek, Saeqa Dil↗
NASA NTRS1995

Eclipse timings of the low-mass X-ray binary EXO 0748-676: Statistical arguments against orbital period changes

EXO 0748-676, an eclipsing low-mass X-ray binary, is one of only about four or five low-mass X-ray binaries for which orbital period evolution has been reported. We observed a single eclipse egress with ROSAT . The time of this egress is consistent with the apparent increase in P(sub orb) previously reported on the basis of EXOSAT and Ginga observations. Standard analysis, in which O-C (observed minus calculated) timing residuals are examined for deviations from a constant period, implicitly assume that the only uncertainty in each residual is measurement error and that these errors are independent. We argue that the variable eclipse durations and profiles observed in EXO 0748-676 imply that there is an additional source of uncertainty in timing measurements, that this uncertainty is intrinsic to the binary system, and that it is correlated from observation to observation with a variance which increases as a function of the number of binary cycles between observations. This intrinsic variability gives rise to spurious trends in O-C residuals which are misinterpreted as changes in the orbital period. We describe several statistics tests which can be used to test for the presence of intrinsic variability. We apply those statistical tests which are suitable to the EXO 0748-676 observations. The apparent changes in the orbital period of EXO 0748-676 can be completely accounted for by intrinsic variability with an rms variability of approximately 0.35 s per orbital cycle. The variability appears to be correlated from cycle-to-cycle on timescales of less than 1 yr. We suggest that the intrinsic variability is related to slow changes in either the source's X-ray luminosity or the structure of the companion star's atmosphere. We note that several other X-ray binaries and cataclysmic variables have previously reported orbital period changes which may also be due to intrinsic variability rather than orbital period evolution.

Hertz, Paul↗
NASA NTRS1990

Explicit relations in Bowen fluorescence - Applications to nebulae, the sun, Scorpius X-1, and laboratory plasmas

A general analysis of the fluorescent process is described which emphasizes the differing roles of escape probabilities in one-component and two-component gases, and the existence of discrete fluorescent saturation regimes. Explicit formulas are obtained and discussed for astrophysical Bowen fluorescence, as a concrete example, with applications to planetary nebulae, the solar atmosphere and the X-ray binary Sco X-1. An expression is also provided and evaluated for the profile overlap integral involved in the pumping process. A preliminary conclusion is deduced that densities in the fluorescent line-emitting regions of nebular sources may be higher than those derived from forbidden line ratios. The analysis is extended to a proposed laboratory investigation which would exploit the possibility of controlling the determining factors in the fluorescent process, i.e., O III/He II abundance ratio, optical depth, and photoexciting radiation field.

Kastner, S. O.↗
DOE OSTI2024

EGS Collab Experiment 2: Microseismic Monitoring

This dataset contains continuous seismic waveform data recorded during stimulation and thermal circulation tests for the Enhanced Geothermal Systems (EGS) Collab Experiment #2, conducted from February to September 2022 at the Sanford Underground Research Facility in Lead, South Dakota. This experiment aimed to study and validate models of geothermal systems by injecting high-pressure fluids into rock formations 1200-1500 meters below the surface, inducing microseismic events. The seismic monitoring system included 16 three-component accelerometers and a 24-channel hydrophone array, installed in boreholes surrounding the test area. Data were recorded at high sampling rates using a continuous waveform recording system to monitor seismic activity in real time. The dataset contains the raw data stored in binary format, with files named based on timestamps, and includes calibration certificates for some sensors to facilitate corrections to real units. Users are strongly advised to consult the accompanying detailed report, which outlines the experimental setup, sensor specifications, installation procedures, and data processing methods. The report also describes important nuances, such as the hardware filters on hydrophones, sensor calibration details, and the naming conventions for the recorded data. Proper use of this dataset may require familiarity with seismic data analysis tools, such as the Obspy Python package, and an understanding of the SEED naming conventions used for channel identification.

15 GEOTHERMAL ENERGY↗
DOE OSTI2023

Direct analysis of the broad-line SN 2019ein: connection with the core-normal SN 2011fe

Type Ia supernovae (SNe Ia) are important cosmological probes and contributors to galactic nucleosynthesis, particularly of the iron group elements. To improve both their reliability as cosmological probes and to understand galactic chemical evolution, it is vital to understand the binary progenitor system and explosion mechanism. The classification of SNe Ia into Branch groups has led to some understanding of the similarities and differences among the varieties of observed SNe Ia. Branch groups are defined by the pseudo-equivalent widths of the two prominent Si ii lines, leading to four distinct groups: core-normal (CN), shallow-silicon, cool, and broad-line (BL). However, partly due to small sample size, little work has been done on the BL group. We perform direct spectral analysis on the pre-maximum spectra of the BL SN 2019ein, comparing and contrasting to the CN SN 2011fe. Both SN 2019ein and SN 2011fe were first observed spectroscopically within 2 d of discovery, allowing us to follow the spectroscopic evolution of both SNe in detail. We find that the optical depths of the primary features of both the CN and BL SNe are very similar, except that there is a Doppler shift between them. We further examine the BL group and show that for nine objects with pre-maximum spectra in the range (–6)–(–2) d with respect to B-maximum all the emission peaks of the Si ii λ6355 line of BL are blueshifted pre-maximum, suggesting a possible classification criterion.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Comprehensive characterization of protein–protein interactions perturbed by disease mutations

Technological and computational advances in genomics and interactomics have made it possible to identify how disease mutations perturb protein–protein interaction (PPI) networks within human cells. Here, we show that disease-associated germline variants are significantly enriched in sequences encoding PPI interfaces compared to variants identified in healthy participants from the projects 1000 Genomes and ExAC. Somatic missense mutations are also significantly enriched in PPI interfaces compared to noninterfaces in 10,861 tumor exomes. We computationally identified 470 putative oncoPPIs in a pan-cancer analysis and demonstrate that oncoPPIs are highly correlated with patient survival and drug resistance/sensitivity. Further, we experimentally validate the network effects of 13 oncoPPIs using a systematic binary interaction assay, and also demonstrate the functional consequences of two of these on tumor cell growth. In summary, this human interactome network framework provides a powerful tool for prioritization of alleles with PPI-perturbing mutations to inform pathobiological mechanism- and genotype-based therapeutic discovery.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Isoscaling and nuclear reaction dynamics

Isoscaling parameters α and β have been explored as a function of breakup angle in binary excited projectile-like fragment decays produced in collisions of 70 Zn+ 70 Zn and 64 Zn+ 64 Zn at 35 MeV per nucleon. In this analysis, focus was placed on isoscaling the second heaviest fragment with 4 ≤ Z L ≤ 8 emitted from the excited projectile-like fragment in events that contained a heavy fragment with Z H ≥ 12. The breakup orientation θ prox was defined as the angle between the heavy and light fragments’ center-of-mass velocity and the fragment pairs’ relative velocity. Breakups between 0° < θ prox ≤ 80° have been shown to be dominated by dynamical contributions, while break-up angles of θ prox > 100° are predominantly statistical. Historically, isoscaling has often been understood and applied in a statistical context, assuming that the fragments are produced after statistical equilibrium is achieved. Finally, studying isoscaling parameters as a function of θ prox reveals the sensitivity of α and β to the mechanism of fragment production.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

Leaf-scale carbon assimilation simulated by the multi-assumption architecture & testbed for process sensitivity analysis

Raw and processed output from the Multi-Assumption Architecture & Testbed (MAAT, https://github.com/walkeranthonyp/MAAT, tag: v1.2.1_walker2020; Walker et al., 2018). The dataset contains leaf-scale carbon assimilation data from three MAAT simulations and their post-processing and plotting scripts. Simulation 1, labelled "FvC_4proc_proc," is a four-process, process sensitivity analysis (Dai et al., 2017) of carbon assimilation based on the Farquhar et al. (1980) photosynthesis model, and its variant proposed by Collatz et al. (1991). Simulation 2, labelled "FvC_4proc_salt," is a 14 parameter sensitivity analysis (Saltelli et al., 2010) of carbon assimilation based on the Farquhar and Collatz photosynthesis models. Simulation 3, labelled "FvC," is a factorial combination of the alternative process representations and parameter values presented in those original papers across a factorial combination of incident photosynthetically active radiation (50-2000 µmol m-2 s-1, in increments of 50) and atmospheric CO2 concentration (50-1500 µmol m-2 s-1, in increments of 50). Additional scripts/functions for post-processing and plotting are part of the MAAT repository. These data were generated to evaluate and compare the Farquhar and Collatz models of leaf-scale photosynthesis across a range of CO2 and incident light conditions. Analysis of results can be found in Walker et al. (2020). This dataset is comprised of R scripts to process data and produce figures; .RDS files, a binary format specific to R and read with the 'readRDS' function, to store raw MAAT output; R and bash scripts (.bs) that help to run a MAAT simulation, .XML files that are output from MAAT describing a run, and .csv files which contain the calculated sensitivity indexes published in Walker et al. (2020).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Process Image Analysis using Big Data, Machine Learning, and Computer Vision

The development of algorithms for machine learning and data analysis for the 3013 MIS corrosion surveillance program is a collaborative effort by SRNL, USC and GT. For corrosion detection, LCM image data is extracted from large binary files, with software written to convert the data to physical attributes (i.e. height, color and grayscale values; all as functions of a location in a plane projection). The user interface for the software permits selective downloading of binary data and interrogation of attributes. User input thresholds are used to flag attributes of interest. Machine learning algorithms, developed for this application, are used to determine whether the features are the result of corrosion. To address the fundamental mechanisms of corrosion, machine learning algorithms are being developed to derive interatomic potential force-fields from ab-initio DFT calculations. The goal is to apply molecular modeling on a large enough scale to guide the design of resistant materials.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2021

Neural Network Approaches for Mobile Spectroscopic Gamma-Ray Source Detection

Artificial neural networks (ANNs) for performing spectroscopic gamma-ray source identification have been previously introduced, primarily for applications in controlled laboratory settings. To understand the utility of these methods in scenarios and environments more relevant to nuclear safety and security, this work examines the use of ANNs for mobile detection, which involves highly variable gamma-ray background, low signal-to-noise ratio measurements, and low false alarm rates. Simulated data from a 2” × 4” × 16” NaI(Tl) detector are used in this work for demonstrating these concepts, and the minimum detectable activity (MDA) is used as a performance metric in assessing model performance.In addition to examining simultaneous detection and identification, binary spectral anomaly detection using autoencoders is introduced in this work, and benchmarked using detection methods based on Non-negative Matrix Factorization (NMF) and Principal Component Analysis (PCA). On average, the autoencoder provides a 12% and 23% improvement over NMF- and PCA-based detection methods, respectively. Additionally, source identification using ANNs is extended to leverage temporal dynamics by means of recurrent neural networks, and these time-dependent models outperform their time-independent counterparts by 17% for the analysis examined here. The paper concludes with a discussion on tradeoffs between the ANN-based approaches and the benchmark methods examined here.

Bilton, Kyle J. (ORCID:0000000184553689)↗
NASA NTRS1989

Correlation between X-ray flux and rotational acceleration in Vela X-1

The results of a search for correlations between X-ray flux and angular acceleration for the accreting binary pulsar Vela X-1 are presented. Results are based on data obtained with the Hakucho satellite during the interval 1982 to 1984. In undertaking this correlation analysis, it was necessary to modify the usual statistical method to deal with conditions imposed by generally unavoidable satellite observing constraints, most notably a mismatch in sampling between the two variables. The results are suggestive of a correlation between flux and the absolute value of the angular acceleration, at a significance level of 96 percent. The implications of the methods and results for future observations and analysis are discussed.

Deeter, J. E.↗
NASA NTRS1989

An upper limit on the high-energy gamma-ray emission of Vela X-1

The possibility of high-energy gamma-ray emission from the X-ray binary Vela X-1 was investigated by analyzing the COS-B satellite observations, using the COS-B X-ray detector for a phase coherent analysis in the search of rotational periodicity. The rotational upper limit is compared to the X-ray, TeV, and PeV fluxes reported by Chodil et al. (1967), North et al. (1984), and Protheroe et al. (1984), respectively. It was found that, under certain conditions, the upper limit determined here is not inconsistent with the reports of TeV and PeV emission.

Mattox, J. R.↗
NASA NTRS1991

Search for TeV emission from 4U 0115 + 63

While previous studies of the X-ray binary 4U 0115+63 suggest it to be a steady, TeV gamma-ray emitter, with pulses at the 3.6-sec neutron-star period, the present analysis of data obtained on 60 nights over a 4-yr period with an imaging gamma-ray telescope has uncovered no indication of TeV signals. The derived upper limit of 1 x 10 to the -11th/sq-cm sec, for gamma-rays of energy above 0.7 TeV, is noted to be significantly below the previously reported fluxes.

Macomb, D. J.↗
NASA NTRS2000

Effect of Melt Convection at Various Gravity Levels and Orientations on the Forces Acting on a Large Spherical Particle in the Vicinity of a Solidification Interface

Numerical modeling was Undertaken to analyze the influence of both radial and axial thermal gradients on convection patterns and velocities claiming solidification of pure Al and an Al-4 wt% Cu alloy. The objective of the numerical task was to predict the influence of convective velocity on an insoluble particle near a solid/liquid (s/l) interface. These predictions were then be used to define the minimum gravity level (q) required to investigate the fundamental physics of interactions between a particle and a s/l interface. This is an ongoing NASA founded flight experiment entitled "particle engulfment and pushing by solidifying interfaces (PEP)". Steady-state calculations were performed for different gravity levels and orientations with respect to the gravity vector The furnace configuration used in this analysis is the quench module insert (QMI-1) proposed for the Material Science Research Facility (MSRF) on board the International Space Station (ISS). The general model of binary alloy solidification was based on the finite element code FIDAP. At a low g level of 10(exp -4) g(sub o) (g(sub o) = 9.8 m/square s) maximum melt convection was obtained for an orientation of 90 deg. Calculations showed that even for this worst case orientation the dominant forces acting on the particle are the fundamental drag and interfacial forces.

Bune, Andris V.↗
NASA NTRS2001

Characteristics of AVIRIS Band Measurements in Desert Agroecosystems in the Area of Blythe, California: Studies of Cotton Spectra - 1

Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data from Blythe, California, were acquired in June 1997 to study agricultural spectra from different crops and to identify crops in other areas with similar environmental factors and similar spectral properties. The main objectives of this study are: (1) to compare the spectral and radiometric characteristics of AVIRIS data from agriculture crops with ground spectra measured by a FieldSpec ASD spectrometer; (2) to explore the use of AVIRIS spectral images for identifying agricultural crops; (3) to study the spectral expression of environmental factors on selected crops; and (4) to build a spectral library for the crops that were studied. A long-term goal is to extend the spectral library for different vegetation or crops in different stages of growth. To support our study, on July 18 and 19, 2000, we collected spectra using the FieldSpec spectrometer from selected fields with different crops in the Blythe area of California (longitude 114 deg 33.28 W and latitude 33 deg 25.42 N to longitude 1140 44.53 W and latitude 33 deg 39.77 N). These crops were cotton in different stages of growth, varieties of grass pure or mixed, Sudan grass, Bermuda grass, Teff grass, and alfalfa. Some of the fields were treated with different types of irrigation (i.e., wet to dry conditions). Additional parameters were studied such as the soil water content (WC), pH, and organic matter (OM). The results of this study showed that for crops known to be similar, there is a significant correlation between the spectra that were collected by AVIRIS in 1997 and spectra measured by the FieldSpec (registered) spectrometer in 2000. This correlation allowed development of a spectral library to be used in ENVI-IDL analysis software. This library was used successfully to identify different crops. Furthermore, using IDL algorithms of Spectral Angle Mapper classification (SAM), spectral feature fitting (SFF) and spectral binary encoding (SPE) showed that there is excellent agreement between the predicted and the actual crop type (i.e., the correlation is between 85-90% match). Further use of the AVIRIS images can be of a value to crop identification or crop yield for commercial use.

Hanna, Safwat H. Shakir↗
NASA NTRS2016

Search for Transient Gravitational Waves in Coincidence with Short-Duration Radio Transients During 2007-2013

We present an archival search for transient gravitational-wave bursts in coincidence with 27 single-pulse triggers from Green Bank Telescope pulsar surveys, using the LIGO (Laser Interferometer Gravitational Wave Observatory), Virgo (Variability of Solar Irradiance and Gravity Oscillations) and GEO (German-UK Interferometric Detector) interferometer network. We also discuss a check for gravitational-wave signals in coincidence with Parkes fast radio bursts using similar methods. Data analyzed in these searches were collected between 2007 and 2013. Possible sources of emission of both short-duration radio signals and transient gravitational-wave emission include star quakes on neutron stars, binary coalescence of neutron stars, and cosmic string cusps. While no evidence for gravitational-wave emission in coincidence with these radio transients was found, the current analysis serves as a prototype for similar future searches using more sensitive second-generation interferometers.

Abbott, B. P.↗
NASA NTRS2016

Faint-Source-Star Planetary Microlensing: The Discovery of the Cold Gas-Giant Planet OGLE-2014-BLG-0676Lb

We report the discovery of a planet OGLE-2014-BLG-0676Lb via gravitational microlensing. Observations for the lensing event were made by the following groups: Microlensing Observations in Astrophysics; Optical Gravitational Lensing Experiment; Wise Observatory; RoboNETLas Cumbres Observatory Global Telescope; Microlensing Network for the Detection of Small Terrestrial Exoplanets; and -FUN. All analyses of the light-curve data favoura lens system comprising a planetary mass orbiting a host star. The most-favoured binary lens model has a mass ratio between the two lens masses of (4.78 +/- 0.13) 10(exp -3). Subject to some important assumptions, a Bayesian probability density analysis suggests the lens system comprises a 3.09(+1.02/-1.12) MJ planet orbiting a 0.62(+0.20/-0.22) solar mass host star at a deprojected orbital separation of 4.40(+2.16/-1.46) au. The distance to the lens system is 2.22(+0.96/-0.83) kpc. Planet OGLE-2014-BLG-0676Lb provides additional data to the growing number of cool planets discover redusing gravitational microlensing against which planetary formation theories may be tested. Most of the light in the baseline of this event is expected to come from the lens and thus high-resolution imaging observations could confirm our planetary model interpretation.

OGLE-2014-BLG-0676Lb↗
DOE OSTI2022

BFSVBF (BatFinder Smart Video BioFilter) [SWR-22-87] and Multi-class BatFinder Smart Video BioFilter Keras

Bats are notoriously difficult to study, therefore, identifying specific behavioral trends and the precise environmental conditions at the time of collision requires a monitoring solution that can reliably collect relevant data. To date, thermal infrared video surveillance has been extensively applied to study bats and has proven to be a powerful yet cumbersome tool. Current analytical approaches are time consuming because data processing data has not been fully automated. In the past, steps have been taken to record avian and bat activity in conjunction with complicated image processing techniques that separate species from other moving objects within the field of view (i.e. clouds and portions of the wind turbine). Once the videos are collected, the post-processing does not allow real time monitoring and identification, leading to a delay in both studying the behavior of these species and determining the effectiveness of any impact reduction strategy being studied. Moreover, object identification capability is lacking, thus limiting the usefulness of video data. To resolve these issues, we are using open source computer vision and machine learning techniques allowing for automatic detection of objects in real-time with the ability to correlate these objects with environmental variables and recording the flight paths of each object. The code has gone through five rounds of development with images used to train the models. This advancement allows for automated real-time data collection, identification, and tracking, thereby eliminating the need for long and tedious post-analysis processing of the videos. We will discuss the two open source and publicly available machine learning models developed within this scope of this work: 1) a binary model with a 97.5% accuracy in identifying the difference between an object and an empty scene, including wind turbine and clouds; and 2) a multiple classification model with the capability of identifying the type of object detected: bats (90% accuracy), birds (83% accuracy), insects (69% accuracy) and non-biological (99% accuracy).

Yarbrough, John↗