Search NASA⌕ Search

SEARCH · Search NASA

Results for “Random ray”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
NASA NTRS2014

James Webb Space Telescope (JWST) Stationkeeping Monte Carlo Simulations

The James Webb Space Telescope (JWST) will launch in 2018 into a Libration Point Orbit (LPO) around the Sun-EarthMoon (SEM) L2 point, with a planned mission lifetime of 11 years. This paper discusses our approach to Stationkeeping (SK) maneuver planning to determine an adequate SK delta-V budget. The SK maneuver planning for JWST is made challenging by two factors: JWST has a large Sunshield, and JWST will be repointed regularly producing significant changes in Solar Radiation Pressure (SRP). To accurately model SRP we employ the Solar Pressure and Drag (SPAD) tool, which uses ray tracing to accurately compute SRP force as a function of attitude. As an additional challenge, the future JWST observation schedule will not be known at the time of SK maneuver planning. Thus there will be significant variation in SRP between SK maneuvers, and the future variation in SRP is unknown. We have enhanced an earlier SK simulation to create a Monte Carlo simulation that incorporates random draws for uncertainties that affect the budget, including random draws of the observation schedule. Each SK maneuver is planned to optimize delta-V magnitude, subject to constraints on spacecraft pointing. We report the results of the Monte Carlo simulations and discuss possible improvements during flight operations to reduce the SK delta-V budget.

Monte Carlo↗
NASA NTRS2005

Strong-field Gravitational Effects in the Timing and Spectroscopy of X-Ray Binaries

Using the ray-tracing code described, we developed additional features to the hot spot model to explain the broadening of the quasi-periodic oscillation (QPO) peaks as well as the damping of higher frequency harmonics in the power spectrum. We derived a number of analytic results that agree closely with more detailed numerical calculations. Three primary pieces are developed: the superposition of multiple hot spots with finite lifetimes and random phases, a width in the radial distribution of geodesic orbits, and the scattering of photons from the hot spot through a corona around the black hole. The complete model is used to fit the observed power spectra of both type A and type B QPOs seen in XTE 51550-564, giving confidence limits on each of the model parameters. These results were presented in a conference paper and in a refereed publication. We also explored the possibility of using higher-order statistics, particularly the bispectrum and bicoherence, to distinguish between competing QPO models. These methods were applied to the hot spot model and a method was proposed to map out the spacetime metric around Kerr black holes in Ref. 3 below.

Bertschinger, Edmund↗
NASA NTRS2014

System-Level Radiation Hardening

Although system-level radiation hardening can enable the use of high-performance components and enhance the capabilities of a spacecraft, hardening techniques can be costly and can compromise the very performance designers sought from the high-performance components. Moreover, such techniques often result in a complicated design, especially if several complex commercial microcircuits are used, each posing its own hardening challenges. The latter risk is particularly acute for Commercial-Off-The-Shelf components since high-performance parts (e.g. double-data-rate synchronous dynamic random access memories - DDR SDRAMs) may require other high-performance commercial parts (e.g. processors) to support their operation. For these reasons, it is essential that system-level radiation hardening be a coordinated effort, from setting requirements through testing up to and including validation.

Radiation Hardness Assurance (RHA)↗
DOE OSTI2026

3D Deep Learning Joint Inversion of Active Seismic Full Waveform and Passive Seismic Traveltime Data for Reservoir Imaging and Uncertainty Quantification

Here, we present deep learning (DL) networks for three-dimensional (3D) joint inversion of active seismic full waveform and passive seismic traveltime data to image reservoirs and their properties and quantify imaging uncertainties. Active seismic full-waveform data can provide high-resolution monitoring images but are collected only intermittently because of their high acquisition cost. In contrast, passive seismic data can be gathered at relatively low cost between regular active surveys, although their imaging quality can be compromised by factors such as low signal-to-noise ratios and limited ray coverage of the target. Although these datasets are routinely acquired together at CO 2 storage sites, their combined inversion within a 3D DL framework has not been previously demonstrated. To our knowledge, this is the first study to address this gap, combining the strength of both data types. For efficient data storage and DL training with large 3D seismic datasets, we use a 3D data matrix in which a random number of passive seismic traveltime data are stored as parabolic envelopes using one-hot encoding and a 3D full-waveform data matrix in which multiple shot gathers are summed. Two network architectures are evaluated: a single-encoder U-Net for single-data type inversion and a dual-encoder U-Net for joint inversion of active and passive seismic data. We also evaluate the single-encoder U-Net for joint inversion by concatenating full-waveform data and traveltime data. We propose a systematic approach for selecting an optimal dropout rate that balances regularization during training and Monte Carlo dropout-based uncertainty quantification during prediction by examining the correlation coefficient between standard deviation and prediction error, along with the training misfit, across a range of dropout rates. 3D DL inversion experiments include five different network configurations, with evaluations under ideal, noisy and dropout-enabled conditions. Both model and data uncertainties are assessed, as well as their combined effects. Across all conditions, the networks consistently predict accurate CO 2 saturation models with low prediction errors, such as a structural similarity index of 0.993 and CO 2 difference of 1.1%. Uncertainty estimates show strong spatial correlation with prediction errors, confirming the effectiveness of the proposed dropout selection approach. The results demonstrate that our DL approach, utilizing compact data representations and appropriate uncertainty quantification, yields accurate subsurface images under various inversion conditions and provides valuable insights into the reliability of predictions.

Um, Evan Schankee [Lawrence Berkeley National Labo↗
NASA NTRS1991

Detection of coherent 7.6 Hz oscillations during a burst from Aquila X-1

The results are reported of timing and spectral analysis of the X-ray source Aql X-1 (X1908 + 005) using data obtained with the Einstein SSS and MPC instruments. A classic type I burst was observed from Aql X-1 in both detectors, and a coherent modulation with a period of 131.66 + or - 0.02 (7.6 Hz) and a pulsed fraction of 10 percent was detected in the SSS data (0.64-4.5 keV) during the period of enhanced emission. The signal has a random occurrence probability of less than 5 x 10 to the -5th. The sensitivity of the MPC for high-resolution timing during the burst is greatly reduced because of the low-duty cycle during the burst, and the modulation is not detected. There is no evidence for a loss of coherence during the 80 s or so when it is observable. It is argued that an asymmetrical burst occurring on a neutron star rotating at 7.6 Hz offers a plausible explanation for the oscillation.

Schoelkopf, R. J.↗
NASA NTRS1989

Vela X-1 pulse timing. II - Variations in pulse frequency

The pulsed X-ray emission of Vela X-1 during May 1978 and December-January 1978-1979 is investigated analytically on the basis of published satellite observations. The data are compiled in tables and graphs and discussed in detail, with reference to data for the entire 1975-1982 period. Variations in pulse frequency are identified on time scales from 2 to 2600 days; the lower nine octaves are characterized as white noise (or random walk in pulse frequency), while the longer-period variations are attributed to changes in neutron-star rotation rates.

Deeter, J. E.↗
NASA NTRS1991

A stochastic regulator for integrated communication and control systems. I - Formulation of control law. II - Numerical analysis and simulation

A state feedback control law for integrated communication and control systems (ICCS) is formulated by using the dynamic programming and optimality principle on a finite-time horizon. The control law is derived on the basis of a stochastic model of the plant which is augmented in state space to allow for the effects of randomly varying delays in the feedback loop. A numerical procedure for synthesizing the control parameters is then presented, and the performance of the control law is evaluated by simulating the flight dynamics model of an advanced aircraft. Finally, recommendations for future work are made.

Liou, Luen-Woei↗
NASA NTRS1993

SRAM As An Array Of Energetic-Ion Detectors

Static random-access memory (SRAM) designed for use as array of energetic-ion detectors. Exploits well-known tendency of incident energetic ions to cause bit flips in cells of electronic memories. Design of ion-detector SRAM involves modifications of standard SRAM design to increase sensitivity to ions. Device fabricated by use of conventional complementary metal oxide/semiconductor (CMOS) processes. Potential uses include gas densimetry, position sensing, and measurement of cosmic-ray spectrum.

Buehler, Martin G.↗
NASA NTRS1979

Influence of alignment and surface defects on the performance of X-ray telescopes

The effects of misalignment and surface deformations on the image quality of a grazing incidence telescope with six nested subsystems are investigated. The axial rms-spot size serves as a measure for the image quality. The surface deformations are simulated by ellipsoidal and sinusoidal deviations from the ideal surface. Misalignments are tilts, decenters, and despaces of the individual elements. The effects of each type of defect are analyzed in a single two-element system. The full nested system is then analyzed in the presence of all possible defects on all 12 elements, whereby the magnitude of the defects is randomized within a given upper limit.

Korsch, D.↗
NASA NTRS1992

Ultrasoft x ray bursts: A clue to the origin of gamma ray bursts?

A search was conducted for short timescale (less than or approx. 10 s) faint X ray bursts in the complete 201,000,000 photon Einstein Observatory imaging proportional counter (IPC) data base. Some 73,000,000 events were extracted which were distributed among 11,230 observing intervals with an average observing time of approx. 1400 seconds. To exclude all sources, only those spatial pixels were searched with a count rate less than 6 x 10(exp -4) counts/sec sq arcmin. The mean count rate was much less. All files with less than 400 secs of observing time were excluded. The data was then binned into overlapping cells 4'.3 by 4'.3 by 10 secs in volume, and all the space-time cells were searched to locate cells with more than 5 counts in a 10 sec interval; i.e., a minimum flux enhancement of 50 over the mean rate for that point in space. Some 52 such events were found. An annulus was inspected around the event to see if it coincided with a general rise in the counter's event rate. Ten events did coincide with counter phenomena; these were associated with sunrise, sunset, or the approach of the South Atlantic Anomaly and were excluded. The remaining 42 events were then examined in an attempt to associate them with instrumental or environmental artifacts. The event occurrence times are uniformly distributed over the course of the mission and show no correlation with local solar time; their positions are randomly distributed in geographic, Galactic, and celestial coordinates. Their summed radial distribution is consistent with the point response function of the IPC for a soft source, indicating that the events are focused by the Observatory's mirror system. The integrated spectrum is, indeed, quite soft and is very similar to that of the cataclysmic variable star U Gem in outburst. Most of the events have risetimes of less than or approx. 1 sec and decay times ranging from 1 to 20 sec. Their positions are not associated with any class of catalogued objects. Several possible origins are discussed for the events; if they are associated with gamma ray bursters, they provide interesting constraints on the space density and repetition rate of the underlying source population.

Helfand, D. J.↗
NASA NTRS2007

Radiation Test Challenges for Scaled Commerical Memories

As sub-100nm CMOS technologies gather interest, the radiation effects performance of these technologies provide a significant challenge. In this talk, we shall discuss the radiation testing challenges as related to commercial memory devices. The focus will be on complex test and failure modes emerging in state-of-the-art Flash non-volatile memories (NVMs) and synchronous dynamic random access memories (SDRAMs), which are volatile. Due to their very high bit density, these device types are highly desirable for use in the natural space environment. In this presentation, we shall discuss these devices with emphasis on considerations for test and qualification methods required.

LaBel, Kenneth A.↗
NASA NTRS2016

Machine-z: Rapid Machine-Learned Redshift Indicator for Swift Gamma-Ray Bursts

Studies of high-redshift gamma-ray bursts (GRBs) provide important information about the early Universe such as the rates of stellar collapsars and mergers, the metallicity content, constraints on the re-ionization period, and probes of the Hubble expansion. Rapid selection of high-z candidates from GRB samples reported in real time by dedicated space missions such as Swift is the key to identifying the most distant bursts before the optical afterglow becomes too dim to warrant a good spectrum. Here, we introduce 'machine-z', a redshift prediction algorithm and a 'high-z' classifier for Swift GRBs based on machine learning. Our method relies exclusively on canonical data commonly available within the first few hours after the GRB trigger. Using a sample of 284 bursts with measured redshifts, we trained a randomized ensemble of decision trees (random forest) to perform both regression and classification. Cross-validated performance studies show that the correlation coefficient between machine-z predictions and the true redshift is nearly 0.6. At the same time, our high-z classifier can achieve 80 per cent recall of true high-redshift bursts, while incurring a false positive rate of 20 per cent. With 40 per cent false positive rate the classifier can achieve approximately 100 per cent recall. The most reliable selection of high-redshift GRBs is obtained by combining predictions from both the high-z classifier and the machine-z regressor.

gamma-ray burst: general↗
DOE OSTI2025

Lyotropic Liquid Crystal Mediated Assembly of Donor Polymers Enhances Efficiency and Stability of Blade-Coated Organic Solar Cells

Conjugated polymers can undergo complex, concentration-dependent self-assembly during solution processing, yet little is known about its impact on film morphology and device performance of organic solar cells. Herein, lyotropic liquid crystal (LLC) mediated assembly across multiple conjugated polymers is reported, which generally gives rise to improved device performance of blade-coated non-fullerene bulk heterojunction solar cells. Using D18 as a model system, the formation mechanism of LLC is unveiled employing solution X-ray scattering and microscopic imaging tools: D18 first aggregates into semicrystalline nanofibers, then assemble into achiral nematic LLC which goes through symmetry breaking to yield a chiral twist-bent LLC. The assembly pathway is driven by increasing solution concentration – a common driving force during evaporative assembly relevant to scalable manufacturing. This assembly pathway can be largely modulated by coating regimes to give 1) lyotropic liquid crystalline assembly in the evaporation regime and 2) random fiber aggregation pathway in the Landau–Levich regime. The chiral liquid crystalline assembly pathway resulted in films with crystallinity 2.63 times that of films from the random fiber aggregation pathway, significantly enhancing the T80 lifetime by 50-fold. The generality of LLC-mediated assembly and enhanced device performance is further validated using polythiophene and quinoxaline-based donor polymers.

14 SOLAR ENERGY↗
NASA NTRS2000

Induction of a bystander mutagenic effect of alpha particles in mammalian cells

Ever since the discovery of X-rays was made by Rontgen more than a hundred years ago, it has always been accepted that the deleterious effects of ionizing radiation such as mutation and carcinogenesis are attributable mainly to direct damage to DNA. Although evidence based on microdosimetric estimation in support of a bystander effect appears to be consistent, direct proof of such extranuclear/extracellular effects are limited. Using a precision charged particle microbeam, we show here that irradiation of 20% of randomly selected A(L) cells with 20 alpha particles each results in a mutant fraction that is 3-fold higher than expected, assuming no bystander modulation effect. Furthermore, analysis by multiplex PCR shows that the types of mutants induced are significantly different from those of spontaneous origin. Pretreatment of cells with the radical scavenger DMSO had no effect on the mutagenic incidence. In contrast, cells pretreated with a 40 microM dose of lindane, which inhibits cell-cell communication, significantly decreased the mutant yield. The doses of DMSO and lindane used in these experiments are nontoxic and nonmutagenic. We further examined the mutagenic yield when 5-10% of randomly selected cells were irradiated with 20 alpha particles each. Results showed, likewise, a higher mutant yield than expected assuming no bystander effects. Our studies provide clear evidence that irradiated cells can induce a bystander mutagenic response in neighboring cells not directly traversed by alpha particles and that cell-cell communication process play a critical role in mediating the bystander phenomenon.

Non-NASA Center↗
NASA NTRS2018

Using Machine-Learning Methods and Expert Prediction Probabilities to Forecast Solar Flares

It has long been known that studying connection between solar flares and properties of magnetic field in active regions is very important for understanding the flare physics and developing space weather forecasts. The Helioseismic and Magnetic Imager onboard the Solar Dynamics Observatory (SDO/HMI) obtains tremendous amounts of magnetic field data products. However the operational NOAA Space Weather Prediction Center (SWPC) forecasts of solar flares still represent prediction probabilities issued by the experts. In this research we investigate the possibilities to enhance the daily operational flare forecasts performed at the SWPC by developing a synergy of the expert predictions and physics-based criteria, and by employing machine-learning methods. Among the physics-based criteria we consider the descriptors of the Polarity Inversion Line (PIL) and Space weather HMI Active Region Patches (SHARP), and derive from them daily characteristics of the entire Sun. We also consider the daily descriptors of the GOES Soft X-Ray (SXR) 1-8 Angstroms flux such as the flare history of the previous days and averaged X-Ray flux. We estimate the effectiveness in separation of flaring and non-flaring cases for each characteristic, as well as for the expert prediction probabilities, and find that some PIL, SHARP and SXR descriptors are as effective as the expert prediction probabilities and should be considered to issue the flare forecast. Finally, we train and test several Machine-Learning classification algorithms (Support Vector Classifiers with various kernel functions, k-Nearest Neighbor Classifier, Random Forest Classifier, and Neural Networks) using the most effective descriptors and expert prediction probabilities, and compare the obtained predictions with the current SWPC forecasts.

Machine-Learning↗
NASA NTRS1973

X-ray observations of characteristic structures and time variations from the solar corona - Preliminary results from Skylab.

Examples taken from the S-054 X-ray telescope observations made during the first Skylab mission show the hot coronal plasma tracing the configuration of the magnetic fields. The high spectral resolution and sensitivity of the instrument has enabled the following two facts to be more firmly established: (1) that the 'quiet homogeneous corona' is in fact highly structured and that the structures observed appear to be the results of dispersed active region magnetic fields; and (2) that numerous bright points are distributed randomly on the disk. Their presence at high latitudes may play a role in solar cycle models. In addition, the capability of Skylab for studying time evolution has enabled the restructuring of coronal features to be seen at times of high activity, indicating a restructuring of the coronal magnetic fields.

Vaiana, G. S.↗
NASA NTRS1989

Fast spectroscopic variations on rapidly-rotating, cool dwarfs. 3: Masses of circumstellar absorbing clouds on AB Doradus

New time-resolved H alpha, Ca II H and K and Mg II h and k spectra of the rapidly-rotating K0 dwarf star AB Doradus (= HD 36705). The transient absorption features seen in the H alpha line are also present in the Ca II and Mg II resonance lines. New techniques are developed for measuring the average strength of the line absorption along lines of sight intersecting the cloud. These techniques also give a measure of the projected cloud area. The strength of the resonance line absorption provides useful new constraints on the column densities, projected surface areas, temperatures and internal turbulent velocity dispersions of the circumstellar clouds producing the absorption features. At any given time the star appears to be surrounded by at least 6 to 10 clouds with masses in the range 2 to 6 x 10(exp 17) g. The clouds appear to have turbulent internal velocity dispersions of order 3 to 20 km/s, comparable with the random velocities of discrete filamentary structures in solar quiescent prominences. Night-to-night changes in the amount of Ca II resonance line absorption can be explained by changes in the amplitude of turbulent motions in the clouds. The corresponding changes in the total energy of the internal motions are of order 10(exp 29) erg per cloud. Changes of this magnitude could easily be activated by the frequent energetic (approximately 10(exp 34) erg) x ray flares seen on this star.

Cameron, A. Collier↗
NASA NTRS2003

A broadband superconducting detector suitable for use in large arrays

Cryogenic detectors are extremely sensitive and have a wide variety of applications (particularly in astronomy), but are difficult to integrate into large arrays like a modern CCD (charge-coupled device) camera. As current detectors of the cosmic microwave background (CMB) already have sensitivities comparable to the noise arising from the random arrival of CMB photons, the further gains in sensitivity needed to probe the very early Universe will have to arise from large arrays. A similar situation is encountered at other wavelengths.

Crogenic↗