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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 NTRS2012

On Advanced Estimation Techniques for Exoplanet Detection and Characterization using Ground-based Coronagraphs

The direct imaging of planets around nearby stars is exceedingly difficult. Only about 14 exoplanets have been imaged to date that have masses less than 13 times that of Jupiter. The next generation of planet-finding coronagraphs, including VLT-SPHERE, the Gemini Planet Imager, Palomar P1640, and Subaru HiCIAO have predicted contrast performance of roughly a thousand times less than would be needed to detect Earth-like planets. In this paper we review the state of the art in exoplanet imaging, most notably the method of Locally Optimized Combination of Images (LOCI), and we investigate the potential of improving the detectability of faint exoplanets through the use of advanced statistical methods based on the concepts of the ideal observer and the Hotelling observer. We propose a formal comparison of techniques using a blind data challenge with an evaluation of performance using the Receiver Operating Characteristic (ROC) and Localization ROC (LROC) curves. We place particular emphasis on the understanding and modeling of realistic sources of measurement noise in ground-based AO-corrected coronagraphs. The work reported in this paper is the result of interactions between the co-authors during a week-long workshop on exoplanet imaging that was held in Squaw Valley, California, in March of 2012

coronagraphs↗
NASA NTRS2012

On Advanced Estimation Techniques for Exoplanet Detection and Characterization using Ground-Based Coronagraphs

The direct imaging of planets around nearby stars is exceedingly difficult. Only about 14 exoplanets have been imaged to date that have masses less than 13 times that of Jupiter. The next generation of planet-finding coronagraphs, including VLT-SPHERE, the Gemini Planet Imager, Palomar P1640, and Subaru HiCIAO have predicted contrast performance of roughly a thousand times less than would be needed to detect Earth-like planets. In this paper we review the state of the art in exoplanet imaging, most notably the method of Locally Optimized Combination of Images (LOCI), and we investigate the potential of improving the detectability of faint exoplanets through the use of advanced statistical methods based on the concepts of the ideal observer and the Hotelling observer. We provide a formal comparison of techniques through a blind data challenge and evaluate performance using the Receiver Operating Characteristic (ROC) and Localization ROC (LROC) curves. We place particular emphasis on the understanding and modeling of realistic sources of measurement noise in ground-based AO-corrected coronagraphs. The work reported in this paper is the result of interactions between the co-authors during a week-long workshop on exoplanet imaging that was held in Squaw Valley, California, in March of 2012.

instrumentation↗
DOE OSTI2013

Focused Belief Measures for Uncertainty Quantification in High Performance Semantic Analysis

In web-scale semantic data analytics there is a great need for methods which aggregate uncertainty claims, on the one hand respecting the information provided as accurately as possible, while on the other still being tractable. Traditional statistical methods are more robust, but only represent distributional, additive uncertainty. Generalized information theory methods, including fuzzy systems and Dempster-Shafer (DS) evidence theory, represent multiple forms of uncertainty, but are computationally and methodologically difficult. We require methods which provide an effective balance between the complete representation of the full complexity of uncertainty claims in their interaction, while satisfying the needs of both computational complexity and human cognition. Here we build on J{\o}sang's subjective logic to posit methods in focused belief measures (FBMs), where a full DS structure is focused to a single event. The resulting ternary logical structure is posited to be able to capture the minimal amount of generalized complexity needed at a maximum of computational efficiency. We demonstrate the efficacy of this approach in a web ingest experiment over the 2012 Billion Triple dataset from the Semantic Web Challenge.

belief↗
DOE OSTI2021

Fast & accurate emulation of two-body scattering observables without wave functions

We combine Newton's variational method with ideas from eigenvector continuation to construct a fast & accurate emulator for two-body scattering observables. The emulator will facilitate the application of rigorous statistical methods for interactions that depend smoothly on a set of free parameters. Our approach begins with a trial K or T matrix constructed from a small number of exact solutions to the Lippmann–Schwinger equation. Subsequent emulation only requires operations on small matrices. We provide several applications to short-range potentials with and without the Coulomb interaction and partial-wave coupling. It is shown that the emulator can accurately extrapolate far from the support of the training data. When used to emulate the neutron-proton cross section with a modern chiral interaction as a function of 26 free parameters, it reproduces the exact calculation with negligible error and provides an over 300x improvement in CPU time.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2013

Active galactic nucleus black hole mass estimates in the era of time domain astronomy

We investigate the dependence of the normalization of the high-frequency part of the X-ray and optical power spectral densities (PSDs) on black hole mass for a sample of 39 active galactic nuclei (AGNs) with black hole masses estimated from reverberation mapping or dynamical modeling. We obtained new Swift observations of PG 1426+015, which has the largest estimated black hole mass of the AGNs in our sample. We develop a novel statistical method to estimate the PSD from a light curve of photon counts with arbitrary sampling, eliminating the need to bin a light curve to achieve Gaussian statistics, and we use this technique to estimate the X-ray variability parameters for the faint AGNs in our sample. We find that the normalization of the high-frequency X-ray PSD is inversely proportional to black hole mass. We discuss how to use this scaling relationship to obtain black hole mass estimates from the short timescale X-ray variability amplitude with precision ∼0.38 dex. The amplitude of optical variability on timescales of days is also anticorrelated with black hole mass, but with larger scatter. Instead, the optical variability amplitude exhibits the strongest anticorrelation with luminosity. We conclude with a discussion of the implications of our results for estimating black hole mass from the amplitude of AGN variability.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1975

Estimating maximum instantaneous distortion from inlet total pressure rms and PSD measurements

An inexpensive method is developed to determine the extreme values of instantaneous inlet distortion. This method also provides insight into the basic mechanics of unsteady inlet flow and the associated engine reaction. The analysis is based on fundamental fluid dynamics and statistical methods to provide an understanding of the turbulent inlet flow and quantitatively relate the rms level and power spectral density (PSD) function of the measured time variant total pressure fluctuations to the strength and size of the low pressure regions. The most probable extreme value of the instantaneous distortion is then synthesized from this information in conjunction with the steady state distortion. Results of the analysis show the extreme values to be dependent upon the steady state distortion, the measured turbulence rms level and PSD function, the time on point, and the engine response characteristics. Analytical projections of instantaneous distortion are presented and compared with data obtained by a conventional, highly time correlated, 40 probe instantaneous pressure measurement system.

Melick, H. C., Jr.↗
NASA NTRS2003

A Gravity-Responsive Time-Keeping Protein of the Plant and Animal Cell Surface

The hypothesis under investigation was that a ubiquinol (NADH) oxidase protein of the cell surface with protein disulfide-thiol interchange activity (= NOX protein) is a plant and animal time-keeping ultradian (period of less than 24 h) driver of both cell enlargement and the biological clock that responds to gravity. Despite considerable work in a large number of laboratories spanning several decades, this is, to my knowledge, our work is the first demonstration of a time-keeping biochemical reaction that is both gravity-responsive and growth-related and that has been shown to determine circadian periodicity. As such, the NOX protein may represent both the long-sought biological gravity receptor and the core oscillator of the cellular biological clock. Completed studies have resulted in 12 publications and two issued NASA-owned patents of the clock activity. The gravity response and autoentrainment were characterized in cultured mammalian cells and in two plant systems together with entrainment by light and small molecules (melatonin). The molecular basis of the oscillatory behavior was investigated using spectroscopic methods (Fourier transform infrared and circular dichroism) and high resolution electron microscopy. We have also applied these findings to an understanding of the response to hypergravity. Statistical methods for analysis of time series phenomena were developed (Foster et al., 2003).

Morre, D. James↗
NASA NTRS1966

Problems of stellar dynamics

Many-body problem, continuum, and statistical methods applied to dynamics of star clusters, with bibliography

STAR CLUSTER↗
DOE OSTI2015

A model and variance reduction method for computing statistical outputs of stochastic elliptic partial differential equations

We present a model and variance reduction method for the fast and reliable computation of statistical outputs of stochastic elliptic partial differential equations. Our method consists of three main ingredients: (1) the hybridizable discontinuous Galerkin (HDG) discretization of elliptic partial differential equations (PDEs), which allows us to obtain high-order accurate solutions of the governing PDE; (2) the reduced basis method for a new HDG discretization of the underlying PDE to enable real-time solution of the parameterized PDE in the presence of stochastic parameters; and (3) a multilevel variance reduction method that exploits the statistical correlation among the different reduced basis approximations and the high-fidelity HDG discretization to accelerate the convergence of the Monte Carlo simulations. The multilevel variance reduction method provides efficient computation of the statistical outputs by shifting most of the computational burden from the high-fidelity HDG approximation to the reduced basis approximations. Furthermore, we develop a posteriori error estimates for our approximations of the statistical outputs. Based on these error estimates, we propose an algorithm for optimally choosing both the dimensions of the reduced basis approximations and the sizes of Monte Carlo samples to achieve a given error tolerance. We provide numerical examples to demonstrate the performance of the proposed method.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2017

Identification of Uranium Minerals in Natural U-Bearing Rocks Using Infrared Reflectance Spectroscopy

The identification of minerals, including uranium-bearing minerals, is traditionally a labor-intensive-process using x-ray diffraction (XRD), fluorescence, or other solid-phase and wet chemical techniques. While handheld XRD and fluorescence instruments can aid in field identification, handheld infrared reflectance spectrometers can also be used in industrial or field environments, with rapid, non-destructive identification possible via spectral analysis of the solid’s reflectance spectrum. We have recently developed standard laboratory measurement methods for the infrared (IR) reflectance of solids and have investigated using these techniques for the identification of uranium-bearing minerals, using XRD methods for ground-truth. Due to the rich colors of such species, including distinctive spectroscopic signatures in the infrared, identification is facile and specific, both for samples that are pure or are partially composed of uranium (e.g. boltwoodite, schoepite, tyuyamunite, carnotite, etc.) or non-uranium minerals. The method can be used to detect not only pure and partial minerals, but is quite sensitive to chemical change such as hydration (e.g. schoepite). We have further applied statistical methods, in particular classical least squares (CLS) and multivariate curve resolution (MCR) for discrimination of such uranium minerals and two uranium pure chemicals (U3O8 and UO2) against common background materials (e.g. silica sand, asphalt, calcite, K-feldspar) with good success. Each mineral contains unique infrared spectral features; some of the IR features are similar or common to entire classes of minerals, typically arising from similar chemical moieties or functional groups in the minerals: phosphates, sulfates, carbonates, etc. These characteristic 2 infrared bands generate the unique (or class-specific) bands that distinguish the mineral from the interferents or backgrounds. We have observed several cases where the chemical moieties that provide the spectral discrimination in the longwave IR do so by generating upward-going reststrahlen bands in the reflectance data, but the same minerals have other weaker (overtone) bands, sometimes from the same chemical groups, that are manifest as downward-going transmission-type features in the midwave and shortwave infrared.

Beiswenger, Toya N.↗
DOE OSTI2012

IDENTIFYING STAR STREAMS IN THE MILKY WAY HALO

We develop statistical methods for identifying star streams in the halo of the Milky Way that exploit observed spatial and radial velocity distributions. Within a great circle, departures of the observed spatial distribution from random provide a measure of the likelihood of a potential star stream. Comparisons between the radial velocity distribution within a great circle and the radial velocity distribution of the entire sample also measure the statistical significance of potential streams. The radial velocities enable construction of a more powerful joint statistical test for identifying star streams in the Milky Way halo. Applying our method to halo stars in the Hypervelocity Star (HVS) survey, we detect the Sagittarius stream at high significance. Great circle counts and comparisons with theoretical models suggest that the Sagittarius stream comprises 10%-17% of the halo stars in the HVS sample. The population of blue stragglers and blue horizontal branch stars varies along the stream and is a potential probe of the distribution of stellar populations in the Sagittarius dwarf galaxy prior to disruption.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1991

C-statistic fitting routines: User's manual and reference guide

The computer program is discussed which can read several input files and provide a best set of values for the functions provided by the user, using either C-statistic or the chi(exp 2) statistic method. The program consists of one main routine and several functions and subroutines. Detail descriptions of each function and subroutine is presented. A brief description of the C-statistic and the reason for its application is also presented.

Nousek, John A.↗
NASA NTRS1993

Objective determination of image end-members in spectral mixture analysis

Spectral mixture analysis was shown to be a powerful, multifaceted tool for analysis of multi- and hyper-spectral data. The essence of the first phase of the approach is to determine a set of image end-members that best account for the spectral variance in an image cube within a constrained, linear least squares mixing model. The selection of the image end-member is usually achieved using a priori knowledge and successive trial and error solutions to refine the total number and physical location of the end-members. However, in many situations a more objective method of determining these essential components is desired. The problem of image end-member determination was approached objectively by using the inherent variance of the data. Unlike purely statistical methods such as factor analysis, this approach derives solutions that conform to a physically realistic model.

Tompkins, Stefanie↗
NASA NTRS1993

Objective determination of image end-members in spectral mixture analysis of AVIRIS data

Spectral mixture analysis has been shown to be a powerful, multifaceted tool for analysis of multi- and hyper-spectral data. Applications of AVIRIS data have ranged from mapping soils and bedrock to ecosystem studies. During the first phase of the approach, a set of end-members are selected from an image cube (image end-members) that best account for its spectral variance within a constrained, linear least squares mixing model. These image end-members are usually selected using a priori knowledge and successive trial and error solutions to refine the total number and physical location of the end-members. However, in many situations a more objective method of determining these essential components is desired. We approach the problem of image end-member determination objectively by using the inherent variance of the data. Unlike purely statistical methods such as factor analysis, this approach derives solutions that conform to a physically realistic model.

Tompkins, Stefanie↗
NASA NTRS2016

Uncertainty Analysis of the NASA Glenn 8x6 Supersonic Wind Tunnel

This paper presents methods and results of a detailed measurement uncertainty analysis that was performed for the 8- by 6-foot Supersonic Wind Tunnel located at the NASA Glenn Research Center. The statistical methods and engineering judgments used to estimate elemental uncertainties are described. The Monte Carlo method of propagating uncertainty was selected to determine the uncertainty of calculated variables of interest. A detailed description of the Monte Carlo method as applied for this analysis is provided. Detailed uncertainty results for the uncertainty in average free stream Mach number as well as other variables of interest are provided. All results are presented as random (variation in observed values about a true value), systematic (potential offset between observed and true value), and total (random and systematic combined) uncertainty. The largest sources contributing to uncertainty are determined and potential improvement opportunities for the facility are investigated.

Error↗
DOE OSTI2016

iGeoT v1.0

iGeoT v1.0 automates into a stand-alone computer program the multicomponent chemical geothermometry code GeoT v2.1 and the numerical optimization engine of iTOUGH2. iGeoT allows for optimizations of GeoT runs using multiple water chemical analyses. The underlying geothermometry method is that previously developed by Reed and Spycher (1984) using the computed saturation indices of multiple minerals. GeoT automatically reconstitutes deep fluid compositions and estimates reservoir temperature from statistical evaluation of computed mineral saturation indices. The output include estimated temperatures following various statistical methods and their range of uncertainty. The computer program also outputs temperatures predicted using classical geothermometers. Input parameters include water composition and, optionally, gas composition, fraction of gas discharge, dilution/evaporation factor (in case of boiling or mixing with dilute waters), and end-member water composition (in case of mixing with other non-dilute waters). The dilution/evaporation factor, fraction of gas discharge, and concentration of various aqueous and gas species can be automatically estimated by numerical optimization. This program was designed for geothermal applications.

Spycher, Nicolas↗