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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS1972

Statistical analysis of several terminal area traffic collision hazard factors.

An 11 hr sample of air traffic, comprising 584 tracks recorded at Atlanta during peak periods of August 1967, is analyzed to examine the statistical characteristics of range-guard intrusions and airspace conflicts in a terminal area. The number of intrusions (of an imaginary 3-naut mile, 500-ft range guard surrounding each aircraft) and number of conflicts (of the projected airspace for two aircraft) for a track exhibit Poisson variations with track duration. The hourly rate of intrusions follows the gas model square-law variation with traffic density, but the hourly conflict rate, contrary to the gas model, decreases with greater traffic density.

Ruetenik, J. R.↗
NASA NTRS1989

Void statistics, scaling, and the origins of large-scale structure

The probability that a volume of the universe of given size and shape spaced at random will be void of galaxies is used here to study various models of the origin of cosmological structures. Numerical simulations are conducted on hot-particle and cold-particle-modulated inflationary models with and without biasing, on isothermal or initially Poisson models, and on models where structure is seeded by loops of cosmic string. For the Pisces-Perseus redshift compilation of Giovanelli and Haynes (1985), it is found that hierarchical scaling is obeyed for subsamples constructed with different limiting magnitudes and subsamples taken at random. This result confirms that the hierarchical ansatz holds valid to high order and supports the idea that structure in the observed universe evolves by a regular process from an almost Gaussian primordial state. Neutrino models without biasing show the effect of a strong feature in the initial power spectrum. Cosmic string models do not agree well with the galaxy data.

Fry, J. N.↗
DOE OSTI2022

The impact of detection rate changes and correlations on random-coincidence background measurements

Coincidence detection of multiple particles emitted during an experiment can yield a new depth of understanding of the underlying process under study. However, the probability of detecting particles that are generated from the same physical event within a given coincidence time window is generally much lower than that of detecting particles that appear in the same coincidence time window, but were not created from the same physical event, and are therefore detected randomly in coincidence with each other. Thus, accurate and precise methods of measuring this random-coincidence background are essential for a wide variety of fields of science. A method to determine this background directly using the data themselves without any additional experimental run time or fake signals introduced in the data was recently established (O’Donnell, 2016). This method yields a statistical uncertainty on the random-coincidence background that is orders of magnitude smaller than that of the true coincidence data, though the potential for systematic errors of backgrounds from this method was never explored. In this work, we discuss common varieties of correlated and uncorrelated changes in the detection rates of each particle detected in an experiment. Here we demonstrate here that a correlation between particle detection rates from, for example, an incident particle beam that initiates a physical process of interest, creates systematic errors in the random-coincidence background measurement. We also discuss the impact of a variety of other realistic scenarios for rate changes in experiments. Lastly, a method is introduced to correct for errors in the random-coincidence background from any source, yielding an optimization between statistical precision and eliminating potential lingering systematic errors.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2015

Measurement of neutron and gamma-ray noise in large subcritical condition for criticality safety - 14485

Various experimental methods have been proposed for subcriticality measurement and neutron noise analysis method is one of important experimental techniques for this purpose. The variance to mean value method, called Feynman-alpha method, is one of well-known noise analysis methods. In this method, variation of neutron count rate distribution from the Poisson distribution caused by fission chain reactions, which is called Y-value, is measured, however, it is difficult to measure the Y-value in large subcritical state such as nuclear fuel facility, because number of emitted neutrons by fission chain reaction is small, which causes large statistical error. We developed new experimental technique based on Feynman-alpha method combined with pulsed neutron source, called Delayed Neutron Noise Analysis (DNNA) method, to monitor the change of subcriticality. In this new method, neutron and gamma-ray counts measured only appeared in the delayed neutron region after injection of pulsed neutron are analyzed, and the prompt neutron region is completely ignored. The advantage of DNNA compared with conventional method is that spatial dependency of detector positions on measured results can be greatly decreased, which result in increase of accuracy of measured subcriticality. The validity of the DNNA method was experimentally investigated in the Kyoto University Critical Assembly (KUCA) at Kyoto University Research Reactor Institute. In the experiments, pulsed neutrons by D-T reactions are injected into the core and we used {sup 3}He detectors to measure neutron noise signals and BGO scintillation detectors to measure gamma-ray noise signals, and all data in the delayed neutron region were analyzed based on Feynman-alpha method. From the experimental results, it was found that the Y-values are clearly larger than zero in the case of existence of fuel assemblies and this method can be applied to detection of hidden special nuclear materials for example in a cargo container. (authors)

42 ENGINEERING↗
DOE OSTI2012

The Feynman-Y Statistic in Relation to Shift-Register Neutron Coincidence Counting: Precision and Dead Time

The Feynman-Y statistic is a type of autocorrelation analysis. It is defined as the excess variance-to-mean ratio, Y = VMR - 1, of the number count distribution formed by sampling a pulse train using a series of non-overlapping gates. It is a measure of the degree of correlation present on the pulse train with Y = 0 for Poisson data. In the context of neutron coincidence counting we show that the same information can be obtained from the accidentals histogram acquired using the multiplicity shift-register method, which is currently the common autocorrelation technique applied in nuclear safeguards. In the case of multiplicity shift register analysis however, overlapping gates, either triggered by the incoming pulse stream or by a periodic clock, are used. The overlap introduces additional covariance but does not alter the expectation values. In this paper we discuss, for a particular data set, the relative merit of the Feynman and shift-register methods in terms of both precision and dead time correction. Traditionally the Feynman approach is applied with a relatively long gate width compared to the dieaway time. The main reason for this is so that the gate utilization factor can be taken as unity rather than being treated as a system parameter to be determined at characterization/calibration. But because the random trigger interval gate utilization factor is slow to saturate this procedure requires a gate width many times the effective 1/e dieaway time. In the traditional approach this limits the number of gates that can be fitted into a given assay duration. We empirically show that much shorter gates, similar in width to those used in traditional shift register analysis can be used. Because the way in which the correlated information present on the pulse train is extracted is different for the moments based method of Feynman and the various shift register based approaches, the dead time losses are manifested differently for these two approaches. The resulting estimates for the dead time corrected first and second order reduced factorial moments should be independent of the method however and this allows the respective dead time formalism to be checked. We discuss how to make dead time corrections in both the shift register and the Feynman approaches.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2017

Electric fields at finite temperature

Partial differential equations for the electric potential at finite temperature, taking into account the thermal Euler–Heisenberg contribution to the electromagnetic Lagrangian are derived. This complete temperature dependence introduces quantum corrections to several well known equations such as the Thomas–Fermi and the Poisson–Boltzmann equation. Our unified approach allows at the same time to derive other similar equations which take into account the effect of the surrounding heat bath on electric fields. We vary our approach by considering a neutral plasma as well as the screening caused by electrons only. The effects of changing the statistics from Fermi–Dirac to the Tsallis statistics and including the presence of a magnetic field are also investigated. Some useful applications of the above formalism are presented.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2012

Noise spatial nonuniformity and the impact of statistical image reconstruction in CT myocardial perfusion imaging

Purpose: To achieve high temporal resolution in CT myocardial perfusion imaging (MPI), images are often reconstructed using filtered backprojection (FBP) algorithms from data acquired within a short-scan angular range. However, the variation in the central angle from one time frame to the next in gated short scans has been shown to create detrimental partial scan artifacts when performing quantitative MPI measurements. This study has two main purposes. (1) To demonstrate the existence of a distinct detrimental effect in short-scan FBP, i.e., the introduction of a nonuniform spatial image noise distribution; this nonuniformity can lead to unexpectedly high image noise and streaking artifacts, which may affect CT MPI quantification. (2) To demonstrate that statistical image reconstruction (SIR) algorithms can be a potential solution to address the nonuniform spatial noise distribution problem and can also lead to radiation dose reduction in the context of CT MPI. Methods: Projection datasets from a numerically simulated perfusion phantom and an in vivo animal myocardial perfusion CT scan were used in this study. In the numerical phantom, multiple realizations of Poisson noise were added to projection data at each time frame to investigate the spatial distribution of noise. Images from all datasets were reconstructed using both FBP and SIR reconstruction algorithms. To quantify the spatial distribution of noise, the mean and standard deviation were measured in several regions of interest (ROIs) and analyzed across time frames. In the in vivo study, two low-dose scans at tube currents of 25 and 50 mA were reconstructed using FBP and SIR. Quantitative perfusion metrics, namely, the normalized upslope (NUS), myocardial blood volume (MBV), and first moment transit time (FMT), were measured for two ROIs and compared to reference values obtained from a high-dose scan performed at 500 mA. Results: Images reconstructed using FBP showed a highly nonuniform spatial distribution of noise. This spatial nonuniformity led to large fluctuations in the temporal direction. In the numerical phantom study, the level of noise was shown to vary by as much as 87% within a given image, and as much as 110% between different time frames for a ROI far from isocenter. The spatially nonuniform noise pattern was shown to correlate with the source trajectory and the object structure. In contrast, images reconstructed using SIR showed a highly uniform spatial distribution of noise, leading to smaller unexpected noise fluctuations in the temporal direction when a short scan angular range was used. In the numerical phantom study, the noise varied by less than 37% within a given image, and by less than 20% between different time frames. Also, the noise standard deviation in SIR images was on average half of that of FBP images. In the in vivo studies, the deviation observed between quantitative perfusion metrics measured from low-dose scans and high-dose scans was mitigated when SIR was used instead of FBP to reconstruct images. Conclusions: (1) Images reconstructed using FBP suffered from nonuniform spatial noise levels. This nonuniformity is another manifestation of the detrimental effects caused by short-scan reconstruction in CT MPI. (2) Images reconstructed using SIR had a much lower and more uniform noise level and thus can be used as a potential solution to address the FBP nonuniformity. (3) Given the improvement in the accuracy of the perfusion metrics when using SIR, it may be desirable to use a statistical reconstruction framework to perform low-dose dynamic CT MPI.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2020

The Completed SDSS-IV extended Baryon Oscillation Spectroscopic Survey: exploring the halo occupation distribution model for emission line galaxies

We study the modelling of the halo occupation distribution (HOD) for the eBOSS DR16 emission line galaxies (ELGs). Motivated by previous theoretical and observational studies, we consider different physical effects that can change how ELGs populate haloes. We explore the shape of the average HOD, the fraction of satellite galaxies, their probability distribution function (PDF), and their density and velocity profiles. Our baseline HOD shape was fitted to a semi-analytical model of galaxy formation and evolution, with a decaying occupation of central ELGs at high halo masses. We consider Poisson and sub/super-Poissonian PDFs for satellite assignment. We model both Navarro–Frenk–White and particle profiles for satellite positions, also allowing for decreased concentrations. We model velocities with the virial theorem and particle velocity distributions. Additionally, we introduce a velocity bias and a net infall velocity. We study how these choices impact the clustering statistics while keeping the number density and bias fixed to that from eBOSS ELGs. The projected correlation function, w p , captures most of the effects from the PDF and satellites profile. The quadrupole, ξ 2 , captures most of the effects coming from the velocity profile. We find that the impact of the mean HOD shape is subdominant relative to the rest of choices. Here, we fit the clustering of the eBOSS DR16 ELG data under different combinations of the above assumptions. The catalogues presented here have been analysed in companion papers, showing that eBOSS RSD+BAO measurements are insensitive to the details of galaxy physics considered here. These catalogues are made publicly available.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2013

Principal component analysis of modified gravity using weak lensing and peculiar velocity measurements

We perform a principal component analysis to assess ability of future observations to measure departures from General Relativity in predictions of the Poisson and anisotropy equations on linear scales. In particular, we focus on how the measurements of redshift-space distortions (RSD) observed from spectroscopic galaxy redshift surveys will improve the constraints when combined with lensing tomographic surveys. Assuming a Euclid-like galaxy imaging and redshift survey, we find that adding the 3D information decreases the statistical uncertainty by a factor between 3 and 7 compared to the case when only observables from lensing tomographic surveys are used. We also find that the number of well-constrained modes increases by a factor between 3 and 6. Our study indicates the importance of joint galaxy imaging and redshift surveys such as SuMIRe and Euclid to give more stringent tests of the ΛCDM model and to distinguish between various modified gravity and dark energy models.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Constraints from isoscaling on the source size in energetic heavy ion collisions

In the framework of the statistical multifragmentation model, the nuclear isoscaling analysis is extended to constrain the ratio between the sizes of the decaying sources formed in a collision between two heavy ions. It is found that the ratio between the probabilities of observing n fragments in each event, for each of the sources, follows a scaling law, similar to the traditional nuclear isoscaling. However, the corresponding slope is sensitive to the source sizes. This property is explained analytically using the grand-canonical ensemble. Furthermore, the extent to which our findings are affected by finite size effects and by the deexcitation of the hot primary fragments is investigated. The scaling turns out to be robust and weakly affected by effects implied by these two aspects. We also find that the Poisson distribution is a fairly good approximation to the above mentioned probabilities, associated with both the primordial fragments, produced at the breakup stage, and the final ones, found at the end of the fragment deexcitation process.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS1994

Quantum statistics of Raman scattering model with Stokes mode generation

The model describing three coupled quantum oscillators with decay of Rayleigh mode into the Stokes and vibration (phonon) modes is examined. Due to the Manley-Rowe relations the problem of exact eigenvalues and eigenstates is reduced to the calculation of new orthogonal polynomials defined both by the difference and differential equations. The quantum statistical properties are examined in the case when initially: the Stokes mode is in the vacuum state; the Rayleigh mode is in the number state; and the vibration mode is in the number of or squeezed states. The collapses and revivals are obtained for different initial conditions as well as the change in time the sub-Poisson distribution by the super-Poisson distribution and vice versa.

Tanatar, Bilal↗
DOE OSTI2016

THE DATA REDUCTION PIPELINE FOR THE SDSS-IV MaNGA IFU GALAXY SURVEY

Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) is an optical fiber-bundle integral-field unit (IFU) spectroscopic survey that is one of three core programs in the fourth-generation Sloan Digital Sky Survey (SDSS-IV). With a spectral coverage of 3622–10354 Å and an average footprint of ∼500 arcsec{sup 2} per IFU the scientific data products derived from MaNGA will permit exploration of the internal structure of a statistically large sample of 10,000 low-redshift galaxies in unprecedented detail. Comprising 174 individually pluggable science and calibration IFUs with a near-constant data stream, MaNGA is expected to obtain ∼100 million raw-frame spectra and ∼10 million reduced galaxy spectra over the six-year lifetime of the survey. In this contribution, we describe the MaNGA Data Reduction Pipeline algorithms and centralized metadata framework that produce sky-subtracted spectrophotometrically calibrated spectra and rectified three-dimensional data cubes that combine individual dithered observations. For the 1390 galaxy data cubes released in Summer 2016 as part of SDSS-IV Data Release 13, we demonstrate that the MaNGA data have nearly Poisson-limited sky subtraction shortward of ∼8500 Å and reach a typical 10 σ limiting continuum surface brightness μ = 23.5 AB arcsec{sup −2} in a five-arcsecond-diameter aperture in the g -band. The wavelength calibration of the MaNGA data is accurate to 5 km s{sup −1} rms, with a median spatial resolution of 2.54 arcsec FWHM (1.8 kpc at the median redshift of 0.037) and a median spectral resolution of σ = 72 km s{sup −1}.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

SU-F-BRB-10: A Statistical Voxel Based Normal Organ Dose Prediction Model for Coplanar and Non-Coplanar Prostate Radiotherapy

Purpose: Knowledge learned from previous plans can be used to guide future treatment planning. Existing knowledge-based treatment planning methods study the correlation between organ geometry and dose volume histogram (DVH), which is a lossy representation of the complete dose distribution. A statistical voxel dose learning (SVDL) model was developed that includes the complete dose volume information. Its accuracy of predicting volumetric-modulated arc therapy (VMAT) and non-coplanar 4π radiotherapy was quantified. SVDL provided more isotropic dose gradients and may improve knowledge-based planning. Methods: 12 prostate SBRT patients originally treated using two full-arc VMAT techniques were re-planned with 4π using 20 intensity-modulated non-coplanar fields to a prescription dose of 40 Gy. The bladder and rectum voxels were binned based on their distances to the PTV. The dose distribution in each bin was resampled by convolving to a Gaussian kernel, resulting in 1000 data points in each bin that predicted the statistical dose information of a voxel with unknown dose in a new patient without triaging information that may be collectively important to a particular patient. We used this method to predict the DVHs, mean and max doses in a leave-one-out cross validation (LOOCV) test and compared its performance against lossy estimators including mean, median, mode, Poisson and Rayleigh of the voxelized dose distributions. Results: SVDL predicted the bladder and rectum doses more accurately than other estimators, giving mean percentile errors ranging from 13.35–19.46%, 4.81–19.47%, 22.49–28.69%, 23.35–30.5%, 21.05–53.93% for predicting mean, max dose, V20, V35, and V40 respectively, to OARs in both planning techniques. The prediction errors were generally lower for 4π than VMAT. Conclusion: By employing all dose volume information in the SVDL model, the OAR doses were more accurately predicted. 4π plans are better suited for knowledge-based planning than the VMAT plans that are strongly biased in its dose gradient orientation. This project is supported by Varian Medical Systems.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Finding wombling boundaries in LHC data with Voronoi and Delaunay tessellations

We address the problem of finding a wombling boundary in point data generated by a general Poisson point process, a specific example of which is an LHC event sample distributed in the phase space of a final state signature, with the wombling boundary created by some new physics. We discuss the use of Voronoi and Delaunay tessellations of the point data for estimating the local gradients and investigate methods for sharpening the boundaries by reducing the statistical noise. The outcome from traditional wombling algorithms is a set of boundary cell candidates with relatively large gradients, whose spatial properties must then be scrutinized in order to construct the boundary and evaluate its significance. Here we propose an alternative approach where we simultaneously form and evaluate the significance of all possible boundaries in terms of the total gradient flux. We illustrate our method with several toy examples of both straight and curved boundaries with varying amounts of signal present in the data.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS1981

A stochastic-dynamic model for global atmospheric mass-field statistics

Global atmospheric mass field error correlations based on satellite observations and on numerical forecasts show strong and systematic latitude dependence. A model for the latitude dependent spatial correlation structure of mass field forecast errors is derived from dynamical considerations. Three methods of solution were tested. In the first method, the equation was solved by expansion in spherical harmonics, and the correlation function was computed analytically using the expansion coefficients. In the second method, the finite difference equivalent of the equation was solved using a fast poisson solver. The correlation function was computed using stratified sampling of the individual realizations. In the third method, a higher order equation was derived, and solved directly in finite differences by two successive applications of the fast poisson solver. The three methods were compared for accuracy and efficiency, and the third method was chosen as clearly superior.

Ghil, M.↗
DOE OSTI2016

Global sensitivity analysis in stochastic simulators of uncertain reaction networks

Stochastic models of chemical systems are often subjected to uncertainties in kinetic parameters in addition to the inherent random nature of their dynamics. Uncertainty quantification in such systems is generally achieved by means of sensitivity analyses in which one characterizes the variability with the uncertain kinetic parameters of the first statistical moments of model predictions. In this work, we propose an original global sensitivity analysis method where the parametric and inherent variability sources are both treated through Sobol’s decomposition of the variance into contributions from arbitrary subset of uncertain parameters and stochastic reaction channels. The conceptual development only assumes that the inherent and parametric sources are independent, and considers the Poisson processes in the random-time-change representation of the state dynamics as the fundamental objects governing the inherent stochasticity. Here, a sampling algorithm is proposed to perform the global sensitivity analysis, and to estimate the partial variances and sensitivity indices characterizing the importance of the various sources of variability and their interactions. The birth-death and Schlögl models are used to illustrate both the implementation of the algorithm and the richness of the proposed analysis method. The output of the proposed sensitivity analysis is also contrasted with a local derivative-based sensitivity analysis method classically used for this type of systems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Exact and efficient hybrid Monte Carlo algorithm for accelerated Bayesian inference of gene expression models from snapshots of single-cell transcripts

Single cells exhibit a significant amount of variability in transcript levels, which arises from slow, stochastic transitions between gene expression states. Elucidating the nature of these states and understanding how transition rates are affected by different regulatory mechanisms require state-of-the-art methods to infer underlying models of gene expression from single cell data. A Bayesian approach to statistical inference is the most suitable method for model selection and uncertainty quantification of kinetic parameters using small data sets. However, this approach is impractical because current algorithms are too slow to handle typical models of gene expression. To solve this problem, we first show that time-dependent mRNA distributions of discrete-state models of gene expression are dynamic Poisson mixtures, whose mixing kernels are characterized by a piecewise deterministic Markov process. Here, we combined this analytical result with a kinetic Monte Carlo algorithm to create a hybrid numerical method that accelerates the calculation of time-dependent mRNA distributions by 1000-fold compared to current methods. We then integrated the hybrid algorithm into an existing Monte Carlo sampler to estimate the Bayesian posterior distribution of many different, competing models in a reasonable amount of time. We demonstrate that kinetic parameters can be reasonably constrained for modestly sampled data sets if the model is known a priori. If there are many competing models, Bayesian evidence can rigorously quantify the likelihood of a model relative to other models from the data. We demonstrate that Bayesian evidence selects the true model and outperforms approximate metrics typically used for model selection.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1975

Combined magnetic and gravity analysis

Efforts are made to identify methods of decreasing magnetic interpretation ambiguity by combined gravity and magnetic analysis, to evaluate these techniques in a preliminary manner, to consider the geologic and geophysical implications of correlation, and to recommend a course of action to evaluate methods of correlating gravity and magnetic anomalies. The major thrust of the study was a search and review of the literature. The literature of geophysics, geology, geography, and statistics was searched for articles dealing with spatial correlation of independent variables. An annotated bibliography referencing the Germane articles and books is presented. The methods of combined gravity and magnetic analysis techniques are identified and reviewed. A more comprehensive evaluation of two types of techniques is presented. Internal correspondence of anomaly amplitudes is examined and a combined analysis is done utilizing Poisson's theorem. The geologic and geophysical implications of gravity and magnetic correlation based on both theoretical and empirical relationships are discussed.

Hinze, W. J.↗