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At least 433 records · Page 24
All sourcesNASA NTRSDOE OSTI
NASA NTRS2021

Constraining particle acceleration in Sgr A? with simultaneous GRAVITY, Spitzer, NuSTAR, and Chandra observations

We report the time-resolved spectral analysis of a bright near-infrared and moderate X-ray flare of Sgr A⋆. We obtained light curves in the M, K, and H bands in the mid- and near-infrared and in the 2 − 8 keV and 2 − 70 keV bands in the X-ray. The observed spectral slope in the near-infrared band is νLν ∝ ν0.5 ± 0.2; the spectral slope observed in the X-ray band is νLν ∝ ν−0.7 ± 0.5. Using a fast numerical implementation of a synchrotron sphere with a constant radius, magnetic field, and electron density (i.e., a one-zone model), we tested various synchrotron and synchrotron self-Compton scenarios. The observed near-infrared brightness and X-ray faintness, together with the observed spectral slopes, pose challenges for all models explored. We rule out a scenario in which the near-infrared emission is synchrotron emission and the X-ray emission is synchrotron self-Compton. Two realizations of the one-zone model can explain the observed flare and its temporal correlation: one-zone model in which the near-infrared and X-ray luminosity are produced by synchrotron self-Compton and a model in which the luminosity stems from a cooled synchrotron spectrum. Both models can describe the mean spectral energy distribution (SED) and temporal evolution similarly well. In order to describe the mean SED, both models require specific values of the maximum Lorentz factor γmax, which differ by roughly two orders of magnitude. The synchrotron self-Compton model suggests that electrons are accelerated to γmax ∼ 500, while cooled synchrotron model requires acceleration up to γmax ∼ 5 × 104. The synchrotron self-Compton scenario requires electron densities of 1010 cm−3 that are much larger than typical ambient densities in the accretion flow. Furthermore, it requires a variation of the particle density that is inconsistent with the average mass-flow rate inferred from polarization measurements and can therefore only be realized in an extraordinary accretion event. In contrast, assuming a source size of 1 RS, the cooled synchrotron scenario can be realized with densities and magnetic fields comparable with the ambient accretion flow. For both models, the temporal evolution is regulated through the maximum acceleration factor γmax, implying that sustained particle acceleration is required to explain at least a part of the temporal evolution of the flare.

R. Abuter↗
DOE OSTI2023

Machine Learning 5G Attack Detection in Programmable Logic

Machine learning-assisted network security may significantly contribute to securing 5G components. However, machine learning network security inference speeds generally require tens to hundreds of milliseconds thereby introducing significant latency in 5G operations. The inference latency can be reduced by deploying the machine learning model to programmable logic in a field programmable gate array (FPGA) at the cost of a small loss in accuracy. In order to quantify this loss, as well as to establish baseline performance inference speeds for programmable logic implementations, this work explores an autoencoder and a ß-variational autoencoder deployed on two different FPGA evaluation boards and compares accuracy and performance against an NVIDIA A100 GPU implementation. A publicly available 5G dataset containing 10 types of attacks along with normal traffic is introduced as part of the evaluation.

97 MATHEMATICS AND COMPUTING↗
NASA NTRSDate not supplied

Use of Design of Experiments and Rule-Based Inference in Determining Neural Network Architectures for Loss of Control Detection

In this work, we describe methods for selecting the neural network architectures and input spaces to implement belief state inference on generic commercial transport aircraft. First, we highlight a case study on the planning, execution, and analysis of a set of experiments to determine the configurations of a conditional variational autoencoder (CVAE). We present a structured method that can be used in a number of aerospace applications, to optimize the structure and training parameters of the CVAE for belief state inference, using Design of Experiments (DOE) statistical methodologies. The motivation for this specific DOE was to identify the appropriate hyperparameters for measuring the CVAE reconstruction probability and latent space, such that the measurements can be used to infer qualitative state changes for the aircraft. We demonstrate that this process yields information about a trained neural network’s utility for this specific application, along with a quantifiable range of certainty. We execute 84 experiments using loss-of-control flight maneuver data from a NASA T-2 aircraft, demonstrating that this empirical process allows us to construct cheap and simple models with specific attributes amenable to belief state inference in aerospace applications. While theoretically, we could create a single CVAE with an input space the size of all measurable flight variables and environmental dynamics, it becomes intractable to use such a neural network in an in-situ intelligent multi-agent system. Using the recommendations from our case study, we introduce a technical approach for feasibly describing the belief space by (1) identifying significant statistical relationships among flight variables using rule induction, (2) using a set of rules that cover all features to define the input space of multiple CVAEs, and (3) forming a belief space based on the joint probability density of their collective latent spaces. This results in a series of relatively small matrix multiplications that can be performed in real time, as opposed to large matrix computations in a single CVAE. We demonstrate the application of this approach on the T-2 flight loss-of control experiments, using the architecture and hyperparameter recommendations from the case study. We compare the utilities of an individual CVAE trained on all flight variables and multiple CVAEs defined on subsets of flight variables for detecting qualitative changes in flight. We demonstrate that the use of multiple CVAEs with smaller input spaces permits the CVAE to capture more granular relationships in the latent space, permitting better state space characterization and loss-of-control detection.

Design of experiments↗
NASA NTRS1980

Spectral variation of optical depth at Tucson, Arizona between August 1975 and December 1977

A technique proposed by King and Byrne (1976) for inferring the daily value of the total ozone content of the atmosphere is applied to spectral optical depth measurements obtained at Tucson for a 29-month period between August 1975 and December 1977. The selection of wavelength regions appropriate for aerosol optical depth determinations in the visible and near infrared is discussed, and monthly averages of the total and aerosol optical depths are presented for five wavelengths between 0.4400 and 0.8817 microns. Finally, daily values of total ozone content are presented for the entire 133-day data set.

King, M. D.↗
NASA NTRS2001

Wind-Related Modification of Some Small Impact Craters on Mars

Inferred wind-related modifications of impact craters are observed in the vicinity of the Mare Pathfinder (MPF) site and in other regions of Mars. Mars Orbiter Camera (MOC) images show three types of inferred wind-modified morphologies for craters 0.3-1 km in diameter Such modifications could be related to seasonal variations of the strongest winds and a possible paleowind regime. Geomorphic mapping of Big Crater at the MPF shows evidence of former aeolian modification of the crater rim and interiors similar to smaller craters in the area. The morphologic patterns are in good agreement with the results from the Mars Regional Atmospheric Modeling Simulation (MRAMS) of topographically forced wind circulation and atmosphere surface interactions generated by flow over small craters. Simulations show that the maximum surface stress is on the downwind crater rim, consistent with inferred wind modification of the crater rim seen in MOC images. The trend of the Inferred paleowind regime at the MPF site cannot be explained by a change In the global atmospheric circulation resulting ~ from changes in Mars obliquity. We suggest that this wind regime could be associated with a regional meteorological pattern that is not modeled by global scale circulation, An alternative explanation is that Mars spin axis was in a different geographic position than it is at present.

Kuzmin, Ruslan O.↗
NASA NTRS1996

Fossil preservation and the stratigraphic ranges of taxa

The incompleteness of the fossil record hinders the inference of evolutionary rates and patterns. Here, we derive relationships among true taxonomic durations, preservation probability, and observed taxonomic ranges. We use these relationships to estimate original distributions of taxonomic durations, preservation probability, and completeness (proportion of taxa preserved), given only the observed ranges. No data on occurrences within the ranges of taxa are required. When preservation is random and the original distribution of durations is exponential, the inference of durations, preservability, and completeness is exact. However, reasonable approximations are possible given non-exponential duration distributions and temporal and taxonomic variation in preservability. Thus, the approaches we describe have great potential in studies of taphonomy, evolutionary rates and patterns, and genealogy. Analyses of Upper Cambrian-Lower Ordovician trilobite species, Paleozoic crinoid genera, Jurassic bivalve species, and Cenozoic mammal species yield the following results: (1) The preservation probability inferred from stratigraphic ranges alone agrees with that inferred from the analysis of stratigraphic gaps when data on the latter are available. (2) Whereas median durations based on simple tabulations of observed ranges are biased by stratigraphic resolution, our estimates of median duration, extinction rate, and completeness are not biased.(3) The shorter geologic ranges of mammalian species relative to those of bivalves cannot be attributed to a difference in preservation potential. However, we cannot rule out the contribution of taxonomic practice to this difference. (4) In the groups studied, completeness (proportion of species [trilobites, bivalves, mammals] or genera [crinoids] preserved) ranges from 60% to 90%. The higher estimates of completeness at smaller geographic scales support previous suggestions that the incompleteness of the fossil record reflects loss of fossiliferous rock more than failure of species to enter the fossil record in the first place.

NASA Program Exobiology↗
DOE OSTI2021

Particle image velocimetry analysis with simultaneous uncertainty quantification using Bayesian neural networks

Particle image velocimetry (PIV) is an effective tool in experimental fluid mechanics for extracting flow fields from images. Recently, convolutional neural networks (CNNs) have been used to perform PIV analysis with accuracy on par with classical methods. Here we extend the use of CNNs to analyze PIV data while providing simultaneous uncertainty quantification on the inferred flow field. The method we apply in this paper is a Bayesian convolutional neural network (BCNN) which learns distributions of the CNN weights through variational Bayes. In order to demonstrate the utility of BCNNs for the PIV task, we compare the performance of three distinct BCNN models with simple architectures. The first network estimates flow velocity from image interrogation regions only. Our second model learns to infer velocity from both the image interrogation regions and interrogation region cross-correlation maps. Finally, our best performing network infers velocities from interrogation region cross-correlation maps only. We find that BCNNs using interrogation region cross-correlation maps as inputs perform better than those using interrogation windows only as inputs and discuss reasons why this may be the case. Additionally, we test the best performing BCNN on a full synthetic test image pair and a real image pair from the 1st International PIV Challenge. We show that ~98% of true particle displacements from the full synthetic image pair can be captured within the BCNN's 95% confidence intervals, and that the BCNN's performance on the real image pair is quantitatively similar to that of algorithms tested in the 1st International PIV Challenge. Finally, we show that BCNNs can be generalized to be used with multi-pass PIV algorithms with a moderate loss in accuracy, which may be overcome by future work on finetuning and training schemes. So to our knowledge, this is the first use of Bayesian neural networks to perform PIV.

47 OTHER INSTRUMENTATION↗
NASA NTRS1989

Global, seasonal surface variations from satellite radiance measurements

Global, daily, visible, and infrared radiance measurements from the NOAA-5 Scanning Radiometer (SR) are analyzed for the months of January, April, July, and October 1977 to infer surface radiative properties. A radiative transfer model that simulates the spectral and angular characteristics of the NOAA-5 SR measurements is used to retrieve monthly mean surface visible reflectances and temperature at 25 km resolution. These surface properties were found sufficiently accurate for simulation of clear sky radiances to determine global, seasonal variations in cloudiness. Further comparisons of these results with other data highlight the analysis difficulties and radiative model shortcomings that must be overcome to monitor regional and seasonal variations of earth's surface. These preliminary results also provide an estimate of the magnitude of these variations.

Rossow, William B.↗
NASA NTRS2007

Evaluating the Capacity of Global CO2 Flux and Atmospheric Transport Models to Incorporate New Satellite Observations

As we enter the new era of satellite remote sensing for CO2 and other carbon cyclerelated quantities, advanced modeling and analysis capabilities are required to fully capitalize on the new observations. Model estimates of CO2 surface flux and atmospheric transport are required for initial constraints on inverse analyses, to connect atmospheric observations to the location of surface sources and sinks, and ultimately for future projections of carbon-climate interactions. For application to current, planned, and future remotely sensed CO2 data, it is desirable that these models are accurate and unbiased at time scales from less than daily to multi-annual and at spatial scales from several kilometers or finer to global. Here we focus on simulated CO2 fluxes from terrestrial vegetation and atmospheric transport mutually constrained by analyzed meteorological fields from the Goddard Modeling and Assimilation Office for the period 1998 through 2006. Use of assimilated meteorological data enables direct model comparison to observations across a wide range of scales of variability. The biospheric fluxes are produced by the CASA model at lxi degrees on a monthly mean basis, modulated hourly with analyzed temperature and sunlight. Both physiological and biomass burning fluxes are derived using satellite observations of vegetation, burned area (as in GFED-2), and analyzed meteorology. For the purposes of comparison to CO2 data, fossil fuel and ocean fluxes are also included in the transport simulations. In this presentation we evaluate the model's ability to simulate CO2 flux and mixing ratio variability in comparison to in situ observations at sites in Northern mid latitudes and the continental tropics. The influence of key process representations is inferred. We find that the model can resolve much of the hourly to synoptic variability in the observations, although there are limits imposed by vertical resolution of boundary layer processes. The seasonal cycle and its interannual variations generally respond adequately, but discrepancies in the tropics suggest the need for a refinement of the soil moisture dependence of the respiration flux in CASA. Examples and inferences for interpretation of satellite data will be discussed. In general, the fidelity of these simulations leads us to anticipate incorporation of real-time, highly resolved remote sensing and other observations into quantitative analyses that will reduce uncertainty in the terrestrial CO2 sink and revolutionize our understanding of the key processes controlling atmospheric CO2 and its evolution with time.

Kawa, S. R.↗
NASA NTRS2013

Strong Temporal Variation Over One Saturnian Year: From Voyager to Cassini

Here we report the combined spacecraft observations of Saturn acquired over one Saturnian year (approximately 29.5 Earth years), from the Voyager encounters (1980-81) to the new Cassini reconnaissance (2009-10). The combined observations reveal a strong temporal increase of tropic temperature (approximately 10 Kelvins) around the tropopause of Saturn (i.e., 50 mbar), which is stronger than the seasonal variability (approximately a few Kelvins). We also provide the first estimate of the zonal winds at 750 mbar, which is close to the zonal winds at 2000 mbar. The quasi-consistency of zonal winds between these two levels provides observational support to a numerical suggestion inferring that the zonal winds at pressures greater than 500 mbar do not vary significantly with depth. Furthermore, the temporal variation of zonal winds decreases its magnitude with depth, implying that the relatively deep zonal winds are stable with time.

Cassini↗
DOE OSTI2021

Spectroscopic and Photometric Monitoring of a Poorly Known Highly Luminous OH/IR Star: IRAS 18278+0931

We present the time-dependent properties of a poorly known OH/IR star, IRAS 18278+0931 (hereafter IRAS 18+09), toward the Ophiuchus constellation. We have carried out long-term optical/near-infrared photometric and spectroscopic observations to study the object. From optical R- and I-band light curves, the period of IRAS 18+09 is estimated to be 575 ± 30 days and the variability amplitudes range from ΔR ∼ 4.0 mag to ΔI ∼ 3.5 mag. From the standard period–luminosity relations, the distance (D) to the object, 4.0 ± 1.3 kpc, is estimated. Applying this distance in the radiative transfer model, the spectral energy distribution is constructed from multiwavelength photometric and IRAS-LRS spectral data, which provide the luminosity, optical depth, and gas mass-loss rate of the object to be 9600 ± 500 L {sub ⊙}, 9.1 ± 0.6 at 0.55 μm, and 1.0 × 10{sup −6} M {sub ⊙} yr{sup −1}, respectively. The current mass of the object is inferred to be in the range 1.0−1.5 M {sub ⊙} assuming solar metallicity. Notably, the temporal variation of atomic and molecular features (e.g., TiO, Na i, Ca i, CO, H{sub 2}O) over the pulsation cycle of the OH/IR star illustrates the sensitivity of the spectral features to the dynamical atmosphere as observed in pulsating AGB stars.

36 MATERIALS SCIENCE↗
NASA NTRS1972

An analysis of the Venus measurements

Plots of the Mariner 5 and Venera 4, 5, and 6 pressure vs temperature show that the Venera profiles are essentially congruent with the Mariner 5 day and night profiles, but are displaced 28 percent higher in pressure. Data suggest a variability in the atmospheric water vapor content in the region from 30 to 50 km. The Venera 7 measurements are interpreted as evidence for updrafts, down-drafts, horizontal wind layers, and nonaqueous precipitation. The previously observed band of retrograde winds which circle the equator with an average speed of 110 m/s is found to extend downward to the one atmosphere level at the equatorial morning terminator. The possibility of a low altitude equator-to-pole circulation with warm gas rising at the poles is inferred. Venera 7 temperature data used with radar topography and microwaves interferometer measurements suggest that the variation of surface temperature with altitude in a band about the equator is less than 5 K/km. The available data are used to calculate a model of the structure of the Venus atmosphere for the first 75 km above the equatorial region.

Ainsworth, J. E.↗
NASA NTRS1990

3-D components of a biological neural network visualized in computer generated imagery. II - Macular neural network organization

Computer-assisted reconstructions of small parts of the macular neural network show how the nerve terminals and receptive fields are organized in 3-dimensional space. This biological neural network is anatomically organized for parallel distributed processing of information. Processing appears to be more complex than in computer-based neural network, because spatiotemporal factors figure into synaptic weighting. Serial reconstruction data show anatomical arrangements which suggest that (1) assemblies of cells analyze and distribute information with inbuilt redundancy, to improve reliability; (2) feedforward/feedback loops provide the capacity for presynaptic modulation of output during processing; (3) constrained randomness in connectivities contributes to adaptability; and (4) local variations in network complexity permit differing analyses of incoming signals to take place simultaneously. The last inference suggests that there may be segregation of information flow to central stations subserving particular functions.

Ross, Muriel D.↗
NASA NTRS1991

NASA Li/CF(x) cell problem analysis: Scanning electron microscopy with energy dispersive x ray spectrometry

An analysis was made of Lithium/carbon fluoride cell parts for possible chloride contamination induced by exposure to thionyl chloride (SOCl2); various samples were submitted for analysis. Only a portion of the analysis which has been conducted is covered, herein, namely analysis by scanning electron microscopy with energy dispersive x ray spectrometry (SEM/EDS). A strip of nickel was exposed to SOCl2 vapors to observe variations in surface concentrations of sulfur and chlorine with time. By detecting chlorine one can not infer contamination by SOCl2 only that contamination is present. Six samples of stainless steel foil were analyzed for chlorine using EDS. Chlorine was not detected on background samples but was detected on the samples which had been handled including those which had been cleaned. Cell covers suspected of being contaminated while in storage and covers which were not exposed to the same storage conditions were analyzed for chlorine. Although no chlorine was found on the covers from cells, it was found on all stored covers. Results are presented with techniques shown for analysis and identification. Relevant photomicrographs are presented.

Baker, John↗
NASA NTRS2003

Global and Local Helioseismic Studies of Solar Convection Zone Dynamics Using SOI-MDI on SOHO

Our joint collaborative analyses of global mode data to characterize the solar differential rotation (e.g. Thompson et al. 1996, Schou et al. 1998), and most recently to detect and analyze temporal variations in angular velocity Omega profiles both within the convection zone and in the deeper radiative interior (e.g. Howe et al 2000a,b; Toomre et al. 2000), have led to a series of fascinating discoveries. These should be pursued further as the solar cycle continues. The physical deductions being made from these studies have been greatly strengthened by utilizing both SOI-MDI and GONG data in order to have two independent observational realizations of Doppler images spanning a five-year interval, using two separate procedures to determine global mode splittings, and then analyzing those splitting data sets using both RLS and SOLA inversion procedures. There are considerable subtleties in the effects of instrumental response functions and calibrations, sensitivity of peak finding algorithms and their mode leakage estimates, and stochastic variations in mode amplitudes that can all contribute to apparent changes in the Omega profiles being inferred from sequences of helioseismic data. We have come to understand the implications of many of these calibration and analysis steps, greatly aided by frequent multi-week collaborative working sessions in our Helioseismic Analysis Facility (HAF) at JILA involving many members of the SO1 dynamics and inversion team, including most of our Co-Is during the summer months when we hold intensive working sessions. Considerable further focused attention is required in a collaborative setting on such global mode issues as we continue studying the changing sun.

Toomre, Juri↗
NASA NTRS2007

SAGE III Aerosol Extinction Validation in the Arctic Winter: Comparisons with SAGE II and POAM III

The use of SAGE III multiwavelength aerosol extinction coefficient measurements to infer PSC type is contingent on the robustness of both the extinction magnitude and its spectral variation. Past validation with SAGE II and other similar measurements has shown that the SAGE III extinction coefficient measurements are reliable though the comparisons have been greatly weighted toward measurements made at mid-latitudes. Some aerosol comparisons made in the Arctic winter as a part of SOLVE II suggested that SAGE III values, particularly at longer wavelengths, are too small with the implication that both the magnitude and the wavelength dependence are not reliable. Comparisons with POAM III have also suggested a similar discrepancy. Herein, we use SAGE II data as a common standard for comparison of SAGE III and POAM III measurements in the Arctic winters of 2002/2003 through 2004/2005. During the winter, SAGE II measurements are made infrequently at the same latitudes as these instruments. We have mitigated this problem through the use potential vorticity as a spatial coordinate and thus greatly increased the number of coincident events. We find that SAGE II and III extinction coefficient measurements show a high degree of compatibility at both 1020 nm and 450 nm except a 10-20% bias at both wavelengths. In addition, the 452 to 1020-nm extinction ratio shows a consistent bias of approx. 30% throughout the lower stratosphere. We also find that SAGE II and POAM III are on average consistent though the comparisons show a much higher variability and larger bias than SAGE II/III comparisons. In addition, we find that the two data sets are not well correlated below 18 km. Overall, we find both the extinction values and the spectral dependence from SAGE III are robust and we find no evidence of a significant defect within the Arctic vortex.

Thomason, L. W.↗
NASA NTRS2016

Holocene Accumulation and Ice Flow near the West Antarctic Ice Sheet Divide Ice Core Site

The West Antarctic Ice Sheet Divide Core (WDC) provided a high-resolution climate record from near the Ross-Amundsen Divide in Central West Antarctica. In addition, radar-detected internal layers in the vicinity of the WDC site have been dated directly from the ice core to provide spatial variations in the age structure of the region. Using these two data sets together, we first infer a high-resolution Holocene accumulation-rate history from 9.2 thousand years of the ice-core timescale and then confirm that this climate history is consistent with internal layers upstream of the core site. Even though the WDC was drilled only 24 kilometers from the modern ice divide, advection of ice from upstream must be taken into account. We evaluate histories of accumulation rate by using a flowband model to generate internal layers that we compare to observed layers. Results show that the centennially averaged accumulation rate was over 20 percent lower than modern at 9.2 thousand years before present (B.P.), increased by 40 percent from 9.2 to 2.3 thousand years B.P., and decreased by at least 10 percent over the past 2 thousand years B.P. to the modern values; these Holocene accumulation-rate changes in Central West Antarctica are larger than changes inferred from East Antarctic ice-core records. Despite significant changes in accumulation rate, throughout the Holocene the regional accumulation pattern has likely remained similar to today, and the ice-divide position has likely remained on average within 5 kilometers of its modern position. Continent-scale ice-sheet models used for reconstructions of West Antarctic ice volume should incorporate this accumulation history.

ice↗
NASA NTRS2004

Meridional Variations of C2H2 and C2H6 in Jupiter's Atmosphere from Cassini CIRS Infrared Spectra

The abundances of hydrocarbons such as acetylene (C2H2) and ethane (C2H6) in Jupiter's atmosphere are important physical quantities, constraining our models of the chemical and dynamical processes. However, our knowledge of these quantities and their vertical and latitudinal variations has remained sparse. The flyby of the Cassini spacecraft with Jupiter at the end of 2000 provided an excellent opportunity to observe the infrared spectrum with the Composite Infrared Spectrometer (CIRS) instrument, mapping the spatial variation of emissions from 10-1400 cm-1. CIRS spectra taken at the highest resolution (0.5 cm-1) in early December 2000 have been analysed to infer atmospheric temperatures in the stratosphere at 0.5-20 mbar via the v4 of CH4, and in the troposphere at 100-400 mbar, via the hydrogen collision-induced continuum absorption at 600-800 cm. Simultaneously, we have searched for meridional abundance variations in C2H2 and C2H6 via the v5 and vg bands respectively. Tropospheric absorption and stratospheric emission are highly anti-correlated at the CIM resolution, introducing a non-uniqueness into the retrievals, which means that vertical gradient and column abundance cannot be simultaneously found without additional constraints. If we assume the profile shapes from photochemical model calculations, we show that the column abundance of C2H2 must decrease sharply towards the poles, while C2H6 is constant or slightly increasing. The relevance of these results to current photochemical and dynamical knowledge of Jupiter's atmosphere is discussed.

Nixon, C. A.↗