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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 1,207 records · Page 67
All sourcesNASA NTRSDOE OSTI
NASA NTRS1998

Pursuit Latency for Chromatic Targets

The temporal dynamics of eye movement response to a change in direction of stimulus motion has been used to compare the processing speeds of different types of stimuli (Mulligan, ARVO '97). In this study, the pursuit response to colored targets was measured to test the hypothesis that the slow response of the chromatic system (as measured using traditional temporal sensitivity measures such as contrast sensitivity) results in increased eye movement latencies. Subjects viewed a small (0.4 deg) Gaussian spot which moved downward at a speed of 6.6 deg/sec. At a variable time during the trajectory, the dot's direction of motion changed by 30 degrees, either to the right or left. Subjects were instructed to pursue the spot. Eye movements were measured using a video ophthalmoscope with an angular resolution of approximately 1 arc min and a temporal sampling rate of 60 Hz. Stimuli were modulated in chrominance for a variety of hue directions, combined with a range of small luminance increments and decrements, to insure that some of the stimuli fell in the subjects' equiluminance planes. The smooth portions of the resulting eye movement traces were fit by convolving the stimulus velocity with an exponential having variable onset latency, time constant and amplitude. Smooth eye movements with few saccades were observed for all stimuli. Pursuit responses to stimuli having a significant luminance component are well-fit by exponentials having latencies and time constants on the order of 100 msec. Increases in pursuit response latency on the order of 100-200 msec are observed in response to certain stimuli, which occur in pairs of complementary hues, corresponding to the intersection of the stimulus section with the subjects' equiluminant plane. Smooth eye movements can be made in response to purely chromatic stimuli, but are slower than responses to stimuli with a luminance component.

Mulligan, Jeffrey B.↗
NASA NTRS1999

Validity of the Relation Between Spontaneous and Stimulated Emissions in Semiconductors

The Einstein relation between spontaneous emission and absorption was originally derived for a system consists of a two-state subsystem representing matter and harmonic fields representing radiation. The derivation is based on the detailed balance between these two subsystems under thermal equilibrium. The relationship was later investigated in connection with the interactions between radiation field and solids or semiconductors. The simple derivation dose not hold for semiconductors in general. In certain limiting cases, simple relation was obtained. The validity of this relation is important not only because of its fundamental role connecting two of the most fundamental optical processes in semiconductors, but mostly also because of its wide use as a practical method to measure the optical gain of a semiconductor. The validity of this relation for semiconductors has been an issue of controversial for some time. In this paper we numerically examine the validity of this relationship for several different lineshapes including Lorentzian, Gaussian, Sech, and a convoluted double Lorentzians (CDL). We find out that at relatively low density above transparency level, all first three lineshapes violate the Einstein relation. The relation is approximately valid at high density. At very high density, the validity of the Einstein relation holds well for all three lineshapes. The reason behind this observation is explained. The CDL lineshape has been shown analytically to obey the Einstein relationship previously. We show that for a 2D semiconductor with parabolic bands, the CDL lineshape can be integrated analytically. This analytic lineshape is compared with a simple Lorentzian lineshape.

Ning, Cun-Zheng↗
DOE OSTI2022

Apodization Specific Fitting for Improved Resolution, Charge Measurement, and Data Analysis Speed in Charge Detection Mass Spectrometry

Short-time Fourier transforms with short segment lengths are typically used to analyze single ion charge detection mass spectrometry (CDMS) data either to overcome effects of frequency shifts that may occur during the trapping period or to more precisely determine the time at which an ion changes mass or charge, or enters an unstable orbit. The short segment lengths can lead to scalloping loss unless a large number of zero-fills are used, making computational time a significant factor in real-time analysis of data. Apodization specific fitting leads to a 9-fold reduction in computation time compared to zero-filling to a similar extent of accuracy. This makes possible real-time data analysis using a standard desktop computer. Rectangular apodization leads to higher resolution than the more commonly used Gaussian or Hann apodization and makes it possible to separate ions with similar frequencies, a significant advantage for experiments in which the masses of many individual ions are measured simultaneously. Equally important is a >20% increase in S/N obtained with rectangular apodization compared to Gaussian or Hann, which directly translates to a corresponding improvement in accuracy of both charge measurements and ion energy measurements that rely on the amplitudes of the fundamental and harmonic frequencies. Finally, combined with computing the fast Fourier transform in a lower-level language, this fitting procedure eliminates computational barriers and should enable real-time processing of CDMS data on a laptop computer.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1990

Observations of CO in the Magellanic irregular galaxy NGC 55

The content of molecular gas in galaxies, mainly H2, is one of the key observations necessary for the understanding of star formation processes and history. As the CO molecule is the most widely distributed molecule after H2 and has easily observable mm lines, it is used as a tracer for the molecular gas. CO was detected towards the direction where the H alpha and 6 cm radio continuum emission is strongest (Hummel et al. 1986). Here, researchers present the Gaussian line parameters in tabular form. The distribution of CO corresponds well with the intense HI cloud near the bar of NGC 55. The extent of the CO cloud is about 975 pc perpendicular to the major axis. As the radio continuum and the H alpha emission also peaks in this region, it is most probably associated with the star forming region in NGC 55. Assuming that the molecular gas is in virial equilibrium, researchers derive a mass of about 8 times 10(exp 7) solar magnitude. The molecular mass found indicates that the conversion factor for the molecular mass in Irr galaxies as inferred from CO line emission is indeed higher by up to a factor of 20 compared to the canonical value for the Galaxy.

Heithausen, Andreas↗
DOE OSTI2026

Robust negativity in the quantum-to-classical transition of Kerr dynamics

Here, we quantify the quantum-to-classical transition of the single-mode Kerr nonlinear dynamics in the presence of loss. We establish three timescales that govern the dynamics, each with distinct characteristics. For times short compared with the Ehrenfest time, the evolution is classical, characterized by Gaussian dynamics. For sufficiently long times, as we increase the initial photon number, unitary Kerr evolution would generate macroscopic superpositions of coherent states (so-called kitten states). However, this is severely restricted in the presence of small photon loss, and the expectation values of observables coincide with their classical values. The intermediate timescale, however, shows resilient quantum behavior in the macroscopic limit. We show that in the mean-field non-Gaussian regime, the Kerr Hamiltonian (with small photon loss) generates a significant amount of Wigner-negativity, and classical flow is recovered only if the loss rate grows with system size. Our results broaden the usual understanding of quantum-to-classical transitions and demonstrate the potential for creating robust nonclassical resources for continuous-variable quantum information processing in the presence of loss.

Raza, Mohsin [University of New Mexico, Albuquerqu↗
NASA NTRS1993

Statistics of multi-look AIRSAR imagery: A comparison of theory with measurements

The intensity and amplitude statistics of SAR images, such as L-Band HH for SEASAT and SIR-B, and C-Band VV for ERS-1 have been extensively investigated for various terrain, ground cover and ocean surfaces. Less well-known are the statistics between multiple channels of polarimetric of interferometric SAR's, especially for the multi-look processed data. In this paper, we investigate the probability density functions (PDF's) of phase differences, the magnitude of complex products and the amplitude ratios, between polarization channels (i.e. HH, HV, and VV) using 1-look and 4-look AIRSAR polarimetric data. Measured histograms are compared with theoretical PDF's which were recently derived based on a complex Gaussian model.

Lee, J. S.↗
NASA NTRS2000

The High Mosaicity Illusion: Revealing the True Physical Characteristics of Macromolecular Crystals

An experimental system and software have been developed for simultaneously measuring the diffraction resolution and mosaic spread of macromolecular crystals. Hundreds of reflection profiles over a wide resolution range were rapidly measured by using a charge coupled device (CCD) area detector in combination with superfine phi slicing data collection. The contributions of the X-ray beam to the reflection widths were minimized by using a highly-parallel, highly-monochromatic synchrotron source. These contributions and Lorentz effects were evaluated and deconvoluted from the recorded data. Data collection and processing is described. From one degree of superfine phi slice data collected on a crystal of manganese superoxide dismutase the mosaicity of 261 reflections were measured. The average mosaicity was 0.0101 degrees (0.0035) at the full-width-at-half-maximum (FWHM) and ranged from 0.0011 degrees to 0.0188 degrees. Each reflection profile was individually fit with two gaussian profiles with the first gaussian contributing 55% and the second contributing 35% of the reflection. On average, the mosaicity of the first gaussian was 0.0054 degrees (0.0015) and the second was 0.0061 degrees (0.0023). The mosaicity of the crystal was anisotropic with fh, f k, and fl values of 0.0068 degrees, 0.0140 degrees and 0.0046 degrees, respectively at the FWHM. The anisotropic mosaicity analysis indicates that the crystal is the most perfect in the I direction which corresponds to the favored growth direction of the crystal.

Bellamy, Henry↗
NASA NTRS2022

Modeling the East-West Asymmetry of Energetic Particle Fluence in Large Solar Energetic Particle Events Using the iPATH Model

It has been noted that in large solar energetic particle (SEP) events, the peak intensities show an East-West asymmetry with respect to the source flare locations. Using the 2D improved Particle Acceleration and Transport in the Heliosphere (iPATH) model, we investigate the origin of this longitudinal trend. We consider multiple cases with different solar wind speeds and eruption speeds of the coronal mass ejections (CMEs) and fit the longitudinal distributions of time-averaged fluence by symmetric/asymmetric Gaussian functions with three time intervals of 8, 24 and 48 hr after the flare onset time respectively. The simulation results are compared with a statistical study of three-spacecraft events. We suggest that the East-West asymmetry of SEP fluence and peak intensity can be primarily caused the combined effect of an extended shock acceleration process and the evolution of magnetic field connection to the shock front. Our simulations show that the solar wind speed and the CME speed are important factors determining the East-West fluence asymmetry.

Zheyi Ding↗
NASA NTRS1976

Digital processing of satellite imagery application to jungle areas of Peru

The author has identified the following significant results. The use of clustering methods permits the development of relatively fast classification algorithms that could be implemented in an inexpensive computer system with limited amount of memory. Analysis of CCTs using these techniques can provide a great deal of detail permitting the use of the maximum resolution of LANDSAT imagery. Potential cases were detected in which the use of other techniques for classification using a Gaussian approximation for the distribution functions can be used with advantage. For jungle areas, channels 5 and 7 can provide enough information to delineate drainage patterns, swamp and wet areas, and make a reasonable broad classification of forest types.

Pomalaza, J. C.↗
DOE OSTI2021

Estimating basis functions in massive fields under the spatial mixed effects model

Abstract Spatial prediction is commonly achieved under the assumption of a Gaussian random field by obtaining maximum likelihood estimates of parameters, and then using the kriging equations to arrive at predicted values. For massive datasets, fixed rank kriging using the expectation–maximization algorithm for estimation has been proposed as an alternative to the usual but computationally prohibitive kriging method. The method reduces computation cost of estimation by redefining the spatial process as a linear combination of basis functions and spatial random effects. A disadvantage of this method is that it imposes constraints on the relationship between the observed locations and the knots. We develop an alternative method that utilizes the spatial mixed effects model, but allows for additional flexibility by estimating the range of the spatial dependence between the observations and the knots via an alternating expectation conditional maximization algorithm. Experiments show that our methodology improves estimation without sacrificing prediction accuracy while also minimizing the additional computational burden of extra parameter estimation. The methodology is applied to a temperature dataset archived by the United States National Climate Data Center, with improved results over previous methodology.

Pazdernik, Karl↗
DOE OSTI2024

Impact of hydrogenation on the stability and mechanical properties of amorphous boron nitride

Abstract Interconnect materials with ultralow dielectric constant, and good thermal and mechanical properties are crucial for the further miniaturization of electronic devices. Recently, it has been demonstrated that ultrathin amorphous boron nitride (aBN) films have a very low dielectric constant, high density (above 2.1 g cm −3 ), high thermal stability, and mechanical properties. The excellent properties of aBN derive from the nature and degree of disorder, which can be controlled at fabrication, allowing tuning of the physical properties for desired applications. Here, we report an improvement in the stability and mechanical properties of aBN upon hydrogen doping. With the introduction of a Gaussian approximation potential for atomistic simulations, we investigate the changing morphology of aBN with varying H doping concentrations. We found that for 8 at% of H doping, the concentration ofsp 3 -hybridized atoms reaches to a maximum which leads to an improvement of thermal stability and mechanical properties by 20%. These results will be a guideline for experimentalists and process engineers to tune the growth conditions of aBN films for numerous applications.

Materials Science↗
NASA NTRS1989

Neural network implementations of data association algorithms for sensor fusion

The paper is concerned with locating a time varying set of entities in a fixed field when the entities are sensed at discrete time instances. At a given time instant a collection of bivariate Gaussian sensor reports is produced, and these reports estimate the location of a subset of the entities present in the field. A database of reports is maintained, which ideally should contain one report for each entity sensed. Whenever a collection of sensor reports is received, the database must be updated to reflect the new information. This updating requires association processing between the database reports and the new sensor reports to determine which pairs of sensor and database reports correspond to the same entity. Algorithms for performing this association processing are presented. Neural network implementation of the algorithms, along with simulation results comparing the approaches are provided.

Brown, Donald E.↗
NASA NTRS1990

The Navstar GPS master control station's Kalman filter experience

The Navstar Global Positioning System (GPS) is a highly accurate space based navigation system providing all weather, 24 hour a day service to both military and civilian users. The system provides a Gaussian position solution with four satellites, each providing its ephemeris and clock offset with respect to GPS time. The GPS Master Clock Station (MCS) is charged with tracking each Navstar spacecraft and precisely defining the ephemeris and clock parameters for upload into the vehicle's navigation message. Briefly described here are the Navstar system and the Kalman filter estimation process used by MCS to determine, predict, and ensure quality control for each of the satellite's ephemeris and clock states. Routine performance is shown. Kalman filter reaction and response is discussed for anomalous clock behavior and trajectory perturbations. Particular attention is given to MCS efforts to improve orbital adjust modeling. The satellite out of service time due to orbital maneuvering has been reduced in the past year from four days to under twelve hours. The planning, reference trajectory model, and Kalman filter management improvements are explained.

Scardera, Michael P.↗
NASA NTRS2011

Background Studies for Acoustic Neutrino Detection at the South Pole

The detection of acoustic signals from ultra-high energy neutrino interactions is a promising method to measure the flux of cosmogenic neutrinos expected on Earth. The energy threshold for this process depends strongly on the absolute noise level in the target material. The South Pole Acoustic Test Setup (SPATS), deployed in the upper part of four boreholes of the IceCube Neutrino Observatory, has monitored the noise in Antarctic ice at the geographic South Pole for more than two years down to 500m depth. The noise is very stable and Gaussian distributed. Lacking an in-situ calibration up to now, laboratory measurements have been used to estimate the absolute noise level in the 10 to 50 kHz frequency range to be smaller than 20mPa. Using a threshold trigger, sensors of the South Pole Acoustic Test Setup registered acoustic events in the IceCube detector volume and its vicinity. Acoustic signals from refreezing IceCube holes and from anthropogenic sources have been used to test the localization of acoustic events. An upper limit on the neutrino flux at energies E > 10(exp 11) GeV is derived from acoustic data taken over eight months.

Abbasi, R.↗
DOE OSTI2020

Real-time Intrusion Detection for High-bandwidth Research Networks using Unsupervised Deep Learning

Nowadays, data generated by large-scale scientific experiments are on the scale of petabytes per month. These data are transferred through dedicated high-bandwidth networks across distributed collaboration sites for processing, storage, and analysis. Like general purpose networks, research networks experience attacks. However, monitoring traffic in such high-bandwidth network environments is challenging with conventional deep packet inspection (DPI)- based network intrusion detection systems (NIDS). Recently, machine learning (ML) algorithms have shown potential in detecting anomalous patterns with better generalizability and faster speed. Compared to the general purpose networks, traffic movement in research network is less volatile and more likely to benefit from the ML-based anomaly analysis. We present ThunderSecure, an efficient AI-powered system for detecting anomalies in 100G research networks. ThunderSecure implements a high-throughput packet processing infrastructure using multi-cores and GPUs. It takes time-series statistics from a variety of network measurements and uses 2D Convolutional Neural Network (CNN) to explore both spatial and temporal dependencies in network data stream. Patterns of science data traffic are learned with a one-class neural network, which blends an Adversarial Autoencoder (AAE) with Gaussian mixture density estimation. Testing traffic flows exhibiting significant deviations from the learned baseline of normality are marked as anomalies. We trained ThunderSecure on hundreds of billions of science data packets recorded from a 100G research network at Fermi National Accelerator Laboratory. The detection performance was evaluated on traffic captured from the same research network days and weeks after the training with different types of attack flows injected. To the best of our knowledge, this is the first ML work in the area of network anomaly detection that has been validated on such extreme scale datasets. Results show that ThunderSecure can recognize science data traffic that are captured long after the training and make nearly certain detection on those with anomalous flows injected, even in the case when the anomaly-to-normal mixing ratio is 0.1%.

Gong, Qian↗
NASA NTRS2012

Background Studies for Acoustic Neutrino Detection at the South Pole

The detection of acoustic signals from ultra-high energy neutrino interactions is a promising method. to measure the flux of cosmogenic neutrinos expected on Earth. The energy threshold for this process depends strongly on the absolute noise level in the target material. The South Pole Acoustic Test Setup (SPATS). deployed in the upper part of four boreholes of the IceCube Neutrino Observatory, has monitored the noise in Antarctic ice at the geographic South Pole for more than two years down to 500 m depth. The noise is very stable and Gaussian distributed, Lacking an in situ calibration up to now, laboratory measurements have been used to estimate the absolute noise level in the 10-50 kHz frequency range to be smaller than 20 mPa. Using a threshold trigger. sensors of the South Pole Acoustic Test Setup registered acoustic events in the IceCube detector volume and its vicinity. Acoustic signals from refreezing IceCube holes and from anthropogenic sources have been used to test the localization of acoustic events. An upper limit on the neutrino flux at energies E(sub v) > 10(exp 11) GeV is derived from acoustic data taken over eight months.

Abbasi, R.↗
DOE OSTI2020

Targets and processes for fabricating same

In one embodiment, the present disclosure provides a target or mold having one or more support arms coupled to a substrate. The support arm can be used in handling or positioning a target. In another embodiment, the present disclosure provides target molds, targets produced using such molds, and a method for producing the targets and molds. In various implementations, the targets are formed in a number of disclosed shapes, including a funnel cone, a funnel cone having an extended neck, those having Gaussian-profile, a cup, a target having embedded metal slugs, metal dotted foils, wedges, metal stacks, a Winston collector having a hemispherical apex, and a Winston collector having an apex aperture. In yet another embodiment, the present disclosure provides a target mounting and alignment system.

Malekos, Steven↗
NASA NTRS2000

Condition Monitoring for Helicopter Data

In this paper the classical "Westland" set of empirical accelerometer helicopter data is analyzed with the aim of condition monitoring for diagnostic purposes. The goal is to determine features for failure events from these data, via a proprietary signal processing toolbox, and to weigh these according to a variety of classification algorithms. As regards signal processing, it appears that the autoregressive (AR) coefficients from a simple linear model encapsulate a great deal of information in a relatively few measurements; it has also been found that augmentation of these by harmonic and other parameters can improve classification significantly. As regards classification, several techniques have been explored, among these restricted Coulomb energy (RCE) networks, learning vector quantization (LVQ), Gaussian mixture classifiers and decision trees. A problem with these approaches, and in common with many classification paradigms, is that augmentation of the feature dimension can degrade classification ability. Thus, we also introduce the Bayesian data reduction algorithm (BDRA), which imposes a Dirichlet prior on training data and is thus able to quantify probability of error in an exact manner, such that features may be discarded or coarsened appropriately.

Wen, Fang↗