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At least 649 records · Page 36
All sourcesNASA NTRSDOE OSTI
NASA NTRS1975

The use of unsupervised clustering as a classifier for LACIE MSS data

The author has identified the following significant results. This classification method appears to give accurate field center results and to give practical, statistically consistent and accurate estimates of crop proportions. The accuracy of this method is attributable to certain qualities of the particular clustering algorithm. These qualities are freedom from assumptions about Gaussian data, and the continual updating of distribution estimates, including updating the number of modes. This method is relatively tolerant of errors in the determination of crop type, as crop identity is used only for identifying clusters, and not for computing signatures.

Pentland, A. P.↗
NASA NTRS1978

Structure and evolution of solar radio bursts at 26.4 MHz

Results are reported for multiple-baseline interferometric measurements of type II, III, IV, and V solar radio bursts at 26.4 MHz. Thirty-two burst events in a two-month period are analyzed by fitting a double-Gaussian two-dimensional source-brightness distribution model to the observed interferometer visibility function. The multibaseline time-sharing interferometer system employed is described in detail, the model-fitting technique is outlined, and values of the model-fit parameters are given for all 32 cases, which include two type II bursts, three type IV bursts, 17 type III bursts, seven type V bursts, and three bursts of type III, V pairs. The temporal evolution of source structure, size, and motion is examined for the different burst types. The core-halo source structure for the type III bursts is interpreted in comparison to two models, one of which assumes scattering and refraction of a point source while the other postulates primarily refraction from an ensemble of sources distributed over a wide sector in solar longitude.

Chen, H. S.-L.↗
NASA NTRS1983

The utility of calibration - Landsat 4 TM simulator data, Patrick Draw, Wyoming

A novel calibration approach was used for Landsat 4 TM simulator data acquired at the Patrick Draw test site, Wyoming, where the 'true' reflectance spectrum for any pixel area cannot be practically determined because of mixing of spectral components. An empirically derived function was first applied to the scanner data to remove the brightness gradient due to directional scattering and surface geometry. Based on the observation that the distribution of scanner brightness values (DN) were Gaussian, the minimum, mean, and maximum DN for each band were extracted and plotted versus the similar percent reflectance values determined from a large representative collection of field reflectance data for the area. These plots provided linear transformations relating DN value to reflectance in each band.

Lang, H. R.↗
NASA NTRS2013

Kepler Observations of Rapid Optical Variability in the BL Lac Object W2r192+42

We present the first Kepler monitoring of a strongly variable BL Lac, W2R1926+42. The light curve covers 181 days with approx. 0.2% errors, 30 minute sampling and >90% duty cycle, showing numerous delta-I/I > 25% flares over timescales as short as a day. The flux distribution is highly skewed and non-Gaussian. The variability shows a strong rms-flux correlation with the clearest evidence to date for non-linearity in this relation. We introduce a method to measure periodograms from the discrete autocorrelation function, an approach that may be well-suited to a wide range of Kepler data. The periodogram is not consistent with a simple power-law, but shows a flattening at frequencies below 7x10(exp -5) Hz. Simple models of the power spectrum, such as a broken power law, do not produce acceptable fits, indicating that the Kepler blazar light curve requires more sophisticated mathematical and physical descriptions than currently in use.

galaxies↗
NASA NTRS2019

Statistical Study on Multispacecraft Widespread Solar Energetic Particle Events During Solar Cycle 24

We conduct a statistical study on the large three-spacecraft widespread solar energetic particle (SEP) events. Longitudinal distributions of the peak intensities, onset delays, and relation between the SEP intensity, coronal mass ejection (CME) shock speed, width, and the kinetic energy of the CME have been investigated. We apply a Gaussian fit to obtain the SEP intensity Io and distribution width and a forward-modeling fit to determine the true shock speed and true CME width. We found a good correction between and connection angel to the flare site and Io and the kinetic energy of the CME. By including the true chock speed and true CME widths, we reduce root-mean-square errors on the predicted SEP intensity by ~41% for protons compared to Richards et al.'s (2014, https://doi.org/10.1007/s11207-014-0524-8) prediction. The improved correction between the CME kinetic energy and SEP intensity provides strong evidence for the CME-shock acceleration theory of SEPs. In addition, we found that electron and proton release time delays (DTs) relative to Type II radio bursts increase with connection angles. The average electron (proton) DT is ~14 (32) min for strongly anisotropic events and ~2.5 (4.4) hr for weakly anisotropic events. Poor magnetic connectivity and large scattering effects are two main reasons to cause large delays.

Xie, H.↗
DOE OSTI2023

Towards Realistic and High Fidelity Models for Nuclear Reactor Power Synthesis Simulation with Self-Powered Neutron Detectors

As presented in this report, a weighting function–based inferencing method is being applied to synthesize the power distribution in next-generation and university research reactors based on simulated self power neutron detector (SPND) responses. The overall goal is to assess the impacts of sensor uncertainty and true power distribution perturbations on the error in the synthesized power distribution. Regarding sensor uncertainty, the NuScale Small Modular Reactor (SMR) and the Westinghouse AP1000 serve as testbeds for analyzing the impact of varying the sensor uncertainty, as well as varying the number of sensors per sensor string in the reactor core. The reactor models are informed by Monte Carlo N-Particle (MCNP) neutron flux tallies. For the NuScale SMR and Westinghouse AP1000, the SPND response functions (i.e., the response of the SPNDs to individual segments of fuel) were determined homogeneously. Regarding an analysis of power distribution perturbation detection, the Texas A&M Testing, Research, Isotopes, General Atomics Reactor (TAMU TRIGA) reactor was used as a demonstration case with one particular arrangement of SPNDs; the response functions for this reactor model were determined heterogeneously, making this a uniquely high-fidelity demonstration of perturbation detection. Finally, SPND models generated in the Geometry and Tracking 4 (Geant4) code have been generated and tested for comparison with traditionally implemented analytical SPND models, with the intent for Geant4 integration with the full methodological framework. SPND current outputs as a function of distance from some fuel assembly segment in the NuScale SMR are compared with the analytically determined currents. Results from the sensor uncertainty simulations for the NuScale SMR and AP1000 indicate that the average error in the inferred power distribution on the fuel assembly segment level is reasonably low, being slightly less than the random uncertainty applied to all respective SPNDs in both cores. For example, if all SPNDs in the core have a random uncertainty of 5%, then the corresponding fuel assembly segment level error (i.e. difference between the true and inferred local power) is ~2–3%. However, the maximum error in the inferred power distribution on the fuel assembly segment level can be considerably high (>15%) when SPND random uncertainties start to exceed ~3%. In general, the average and maximum errors in the inferred power distribution were slightly higher in the AP1000 as opposed to the NuScale SMR for the sensor string configurations considered herein. Another result determined from analysis of the sensor uncertainty simulations was that increasing the number of SPNDs per string does not clearly reduce inferred power distribution error and can in fact make the error large in some cases; however, this assessment may skewed due to imposed iteration limits. Results from the perturbation detection demonstration using the high-fidelity TAMU TRIGA model indicate that, given the arrangement of 17 SPND strings and 4 SPNDs per string considered herein, there is a clear, provable ability to infer a localized Gaussian-type peak perturbation in the 3D power distribution. Such a perturbation was detected with an average fuel assembly segment level error of 0.19%, and the general visualization of the detected perturbation clearly indicates that the magnitude and shape were appropriately resolved. Finally, the electrical current output generated by the Geant4 modeled SPND indicates significant magnitude differences than the analytically modeled SPND, demonstrating the need for accurate SPND models which account for finite sensor geometry effects to inform the power synthesis work described herein.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

Subordinated Gaussian Processes for Solar Irradiance

Traditionally the power grid has been a one-way street with power flowing from large transmission-connected generators through the distribution network to consumers. This paradigm is changing with the introduction of distributed renewable energy resources (DERs), and with it, the way the grid is managed. There is currently a dearth of high fidelity solar irradiance datasets available to help grid researchers understand how expansion of DERs could affect future power system operations. Realistic simulations of by-the-second solar irradiances are needed to study how DER variability affects the grid. Irradiance data are highly non-stationary and non-Gaussian, and even modern time series models are challenged by their distributional properties. We develop a subordinated non-Gaussian stochastic model whose simulations realistically capture the distribution and dependence structure in measured irradiance. We illustrate our approach on a fine resolution dataset from Hawaii, where our approach outperforms standard nonlinear time series models.

MATHEMATICS AND COMPUTING,SOLAR ENERGY↗
NASA NTRS1992

A Gaussian measure of quantum phase noise

We study the width of the semiclassical phase distribution of a quantum state in its dependence on the average number of photons (m) in this state. As a measure of phase noise, we choose the width, delta phi, of the best Gaussian approximation to the dominant peak of this probability curve. For a coherent state, this width decreases with the square root of (m), whereas for a truncated phase state it decreases linearly with increasing (m). For an optimal phase state, delta phi decreases exponentially but so does the area caught underneath the peak: all the probability is stored in the broad wings of the distribution.

Schleich, Wolfgang P.↗
DOE OSTI2021

Data-Driven Multi-agent Deep Reinforcement Learning for Distribution System Decentralized Voltage Control with High Penetration of PVs

This paper proposes a novel model-free/data-driven centralized training and decentralized execution multi-agent deep reinforcement learning (MADRL) framework for distribution system voltage control with high penetration of PVs. The proposed MADRL can coordinate both the real and reactive power control of PVs with existing static var compensators and battery storage systems. Unlike the existing DRL-based voltage control methods, our proposed method does not rely on a system model during both the training and execution stages. This is achieved by developing a new interaction scheme between the surrogate modeling of the original system and the multi-agent soft actor critic (MASAC) MADRL algorithm. In particular, the sparse pseudo-Gaussian process with a few-shots of measurements is utilized to construct the surrogate model of the original environment, i.e., power flow model. This is a data-driven process and no model parameters are needed. Furthermore, the MASAC enabled MADRL allows to achieve better scalability by dividing the original system into different voltage control regions with the aid of real and reactive power sensitivities to voltage, where each region is treated as an agent. This also serves as the foundation for the centralized training and decentralized execution, thus significantly reducing the communication requirements as only local measurements are required for control. Comparative results with other alternatives on the IEEE 123-nodes and 342-nodes systems demonstrate the superiority of the proposed method.

14 SOLAR ENERGY↗
DOE OSTI2023

A tail of eternal inflation

Non-trivial inflaton self-interactions can yield calculable signatures of primordial non-Gaussianity that are measurable in cosmic surveys. We calculate the non-Gaussian corrections to Stochastic Inflation within the framework of Soft de Sitter Effective Theory, from which we derive the associated probability distribution for the scalar fluctuations. As a consequence of this new result, we show that the phase transition to slow-roll eternal inflation is often incalculable in these models. Instead, this transition is sensitive to the non-Gaussian tail of the distribution of scalar fluctuations, which probes physics inside the horizon, potentially beyond the cutoff scale of the Effective Field Theory of Inflation. We delineate the parameter space consistent with current observations and weak coupling at horizon crossing in which the large fluctuations relevant for eternal inflation can only be determined by appealing to a UV completion. We also argue that this breakdown of the perturbative description is required for the de Sitter entropy to reflect the number of de Sitter microstates.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1978

On estimating the phase of a periodic waveform in additive Gaussian noise, part 1

Motivated by recent advances in technology, a new look is taken at the problem of estimating the phase of a periodic waveform in additive Gaussian noise. The maximum a posteriori probability criterion with signal space interpretation is used to obtain the structures of optimum and some suboptimum phase estimators for the following cases: (1) known constant frequency and unknown constant phase with an a priori distribution; (2) unknown constant frequency and phase with a joint a priori distribution; (3) frequency a parameterized function of time with a joint a priori distribution on parameters and phase and (4) frequency a Gaussian random process.

Rauch, L. L.↗
NASA NTRS1996

A Velocity Distribution Model for Steady State Heat Transfer

Consider a box that is filled with an ideal gas and that is aligned along Cartesian coordinates (x, y, z) having until length in the 'y' direction and unspecified length in the 'x' and 'z' directions. Heat is applied uniformly over the 'hot' end of the box (y = 1) and is removed uniformly over the 'cold' end (y = O) at a constant rate such that the ends of the box are maintained at temperatures T(sub 0) at y = O and T(sub 1) at y = 1. Let U, V, and W denote the respective velocity components of a molecule inside the box selected at some random time and at some location (x, y, z). If T(sub 0) = T(sub 1), then U, Y, and W are mutually independent and Gaussian, each with mean zero and variance RT(sub 0), where R is the gas constant. When T(sub 0) does not equal T(sub 1) the velocity components are not independent and are not Gaussian. Our objective is to characterize the joint distribution of the velocity components U, Y, and W as a function of y, and, in particular, to characterize the distribution of V given y. It is hoped that this research will lead to an increased physical understanding of the nature of turbulence.

Hall, Eric B.↗
NASA NTRS1992

Probability distributions for the magnification of quasars due to microlensing

Gravitational microlensing can magnify the flux of a lensed quasar considerably and therefore possibly influence quasar source counts or the observed quasar luminosity function. A large number of distributions of magnification probabilities due to gravitational microlensing for finite sources are presented, with a reasonable coverage of microlensing parameter space (i.e., surface mass density, external shear, mass spectrum of lensing objects). These probability distributions were obtained from smoothing two-dimensional magnification patterns with Gaussian source profiles. Different source sizes ranging from 10 exp 14 cm to 5 x 10 exp 16 cm were explored. The probability distributions show a large variety of shapes. Coefficients of fitted slopes for large magnifications are presented.

Wambsganss, Joachim↗
DOE OSTI2024

Centrality dependence of Lévy-stable two-pion Bose-Einstein correlations in $\sqrt{𝑠{𝑁⁢𝑁}}$ = 200 GeV Au + Au collisions

The PHENIX experiment measured the centrality dependence of two-pion Bose-Einstein correlation functions in $\sqrt{𝑠{𝑁⁢𝑁}}$ = 200 GeV Au + Au collisions at the Relativistic Heavy Ion Collider at Brookhaven National Laboratory. The data are well represented by Lévy-stable source distributions. The extracted source parameters are the correlation-strength parameter 𝜆, the Lévy index of stability 𝛼, and the Lévy-scale parameter 𝑅 as a function of transverse mass 𝑚 𝑇 and centrality. The 𝜆⁡(𝑚 𝑇 ) parameter is constant at larger values of 𝑚 𝑇 , but decreases as 𝑚 𝑇 decreases. The Lévy-scale parameter 𝑅⁡(𝑚 𝑇 ) decreases with 𝑚 𝑇 and exhibits proportionality to the length scale of the nuclear overlap region. The Lévy exponent 𝛼⁡(𝑚 𝑇 ) is independent of 𝑚 𝑇 within uncertainties in each investigated centrality bin, but shows a clear centrality dependence. At all centralities, the Lévy exponent 𝛼 is significantly different from that of Gaussian (𝛼 = 2) or Cauchy (𝛼 = 1) source distributions. Comparisons to the predictions of Monte-Carlo simulations of resonance-decay chains show that, in all but the most peripheral centrality class (50%–60%), the obtained results are inconsistent with the measurements, unless a significant reduction of the in-medium mass of the 𝜂′ meson is included. Finally, in each centrality class, the best value of the in-medium 𝜂′ mass is compared to the mass of the 𝜂 meson, as well as to several theoretical predictions that consider restoration of U 𝐴⁢ (1) symmetry in hot hadronic matter.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS1987

A quantitative approach to the topology of large-scale structure

A quantitative measure of the topology of large-scale structure: the genus of density contours in a smoothed density distribution, is described and applied. For random phase (Gaussian) density fields, the mean genus per unit volume exhibits a universal dependence on threshold density, with a normalizing factor that can be calculated from the power spectrum. If large-scale structure formed from the gravitational instability of small-amplitude density fluctuations, the topology observed today on suitable scales should follow the topology in the initial conditions. The technique is illustrated by applying it to simulations of galaxy clustering in a flat universe dominated by cold dark matter. The technique is also applied to a volume-limited sample of the CfA redshift survey and to a model in which galaxies reside on the surfaces of polyhedral 'bubbles'. The topology of the evolved mass distribution and 'biased' galaxy distribution in the cold dark matter models closely matches the topology of the density fluctuations in the initial conditions. The topology of the observational sample is consistent with the random phase, cold dark matter model.

Gott, J. Richard, III↗
NASA NTRS1967

Detection and estimation theory

Dynamic systems, and electronic theory on nonlinear intervals, and performance bounds of optimum detection for Gaussian signals

ELECTRONICS↗
NASA NTRS1998

[Cosmic Microwave Background (CMB) Anisotropies]

One of the main areas of research is the theory of cosmic microwave background (CMB) anisotropies and analysis of CMB data. Using the four year COBE data we were able to improve existing constraints on global shear and vorticity. We found that, in the flat case (which allows for greatest anisotropy), (omega/H)0 less than 10(exp -7), where omega is the vorticity and H is the Hubble constant. This is two orders of magnitude lower than the tightest, previous constraint. We have defined a new set of statistics which quantify the amount of non-Gaussianity in small field cosmic microwave background maps. By looking at the distribution of power around rings in Fourier space, and at the correlations between adjacent rings, one can identify non-Gaussian features which are masked by large scale Gaussian fluctuations. This may be particularly useful for identifying unresolved localized sources and line-like discontinuities. Levin and collaborators devised a method to determine the global geometry of the universe through observations of patterns in the hot and cold spots of the CMB. We have derived properties of the peaks (maxima) of the CMB anisotropies expected in flat and open CDM models. We represent results for angular resolutions ranging from 5 arcmin to 20 arcmin (antenna FWHM), scales that are relevant for the MAP and COBRA/SAMBA space missions and the ground-based interferometer. Results related to galaxy formation and evolution are also discussed.

Silk, Joseph↗
NASA NTRS1994

The motions of clusters and group of galaxies

The distributions of peculiar velocities of rich clusters and of groups of galaxies are investigated for different cosmological models and are compared with observations. Four cosmological models are studied: standard cold dark matter (CDM) (omega = 1); low-density CDM (omega = 0.3); hot dark matter (HDM) (omega = 1); and primeval baryonic isocurvature (PBI) (omega = 0.3). All models are normalized to the microwave background fluctuations observed by Cosmic Background Explorer (COBE). We find that rich clusters of galaxies exhibit a Maxwellian distribution of peculiar velocities in all models, as expected from a Gaussian initial density field. The clusters appear to be fundamental and efficient tracers of the large-scale velocity field. The cluster three-dimensional velocity distribution typically peaks at v approximately 600 km/s and extends to high cluster velocities of v approximately 2000 km/s. The low-density CDM model exhibits somewhat lower velocities: it peaks at approximately 400 km/s and extends to approximately 1200 km/s. Approximately 10% (approximately 1% for low-density CDM) of all model rich clusters move with high peculiar velocities of V greater than or = 10(exp 3) km/s. The highest velocity clusters frequently originate in dense superclusters. The model velocity distributions of rich clusters are compared with the model velocity distributions of small groups of galaxies, and of the total matter. The group velocity distribution is, in general, similar to the velocity distribution of the rich clusters. The matter velocity distribution is similar to that of the rich clusters for the omega = 0.3 models; these models exhibit Maxwellian velocity distributions for clusters, for groups, and for matter that are all similar to one another. The mass distribution in the omega = 1 models, however, exhibits a longer tail of high velocities than do the clusters. This high-velocity tail originates mostly from the high velocities that exist within rich clusters. The model velocity distributions of groups and clusters of galaxies are compared with observations. The data exhibit a larger high-velocity tail, to v(sub r) greater than or = 2000 km/s, than is seen in the model simulations (except for HDM). Because of the large observational uncertainties, however, the data are consistent at a approximately 1-3 sigma level with the model predictions and with a Gaussian initial density field. Accurate observations of cluster peculiar velocities, especially at the high-velocity tail, shoud provide powerful constraints on the cosmological models.

Bahcall, Neta A.↗