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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Boosted dark matter and its implications for the features in IceCube HESE data

Here we study the implications of the premise that any new, relativistic, highly energetic neutral particle that interacts with quarks and gluons would create cascade-like events in the IceCube (IC) detector. Such events would be observationally indistinguishable from neutral current deep-inelastic (DIS) scattering events due to neutrinos. Consequently, one reason for deviations, breaks or excesses in the expected astrophysical power-law neutrino spectrum could be the flux of such a particle. Motivated by features in the recent 1347-day IceCube high energy starting event (HESE) data, we focus on particular boosted dark matter (χ) related realizations of this premise. Here, χ is assumed to be much lighter than, and the result of, the slow decay of a massive scalar (φ ) which constitutes a major fraction of the Universe's dark matter (DM) . We show that this hypothesis, coupled with a standard power-law astrophysical neutrino flux is capable of providing very good fits to the present data, along with a possible explanation of other features in the HESE sample. These features include a) the paucity of events beyond ~ 2 PeV b) a spectral feature resembling a dip or a spectral change in the 400 TeV–1 PeV region and c) an excess in the 50-100 TeV region. We consider two different boosted DM scenarios, and determine the allowed mass ranges and couplings for four different types of mediators (scalar, pseudoscalar, vector and axial-vector) which could connect the standard and dark sectors. We consider constraints from gamma-ray observations and collider searches. We find that the gamma-ray observations provide the most restrictive constraints, disfavouring the 1σ allowed parameter space from IC fits, while still being consistent with the 3σ allowed region. We also test our proposal and its implications against the (statistically independent) sample of six year through-going muon track data recently released by IceCube.

79 ASTRONOMY AND ASTROPHYSICS↗
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 OSTI2014

Application of the Combined Judgmental and Randomly Placed Sampling Method

In the wake of the 2001 anthrax incidents in the United States, there has been considerable discussion about the role of judgmental and probabilistic sampling strategies, particularly in the context of clearance sampling. The Combined Judgmental and Random (CJR) methodology provides a statistical methodology that allows practitioners to leverage information from both judgmental and randomly selected sample locations and then quantify the confidence in negative results. The objective of the CJR sampling design is to demonstrate, with high probability, that a high percentage of the decision area (or population) is acceptable, given that none of the samples are unacceptable. The purpose of this document is to assist practitioners to appropriately use the CJR methodology and to implement this sampling design in Visual Sample Plan (VSP). We begin by defining some fundamental terms. A decision area is the geographical or spatial area (indoor or outdoor) about which practitioners wish to draw a conclusion on the basis of sampling and other relevant information. Decision areas typically include all or part of a building, but they may be any contaminated (or potentially contaminated) area for which characterization or clearance is required. In this report, a statistical sampling approach refers to any sampling approach based on a mathematical or statistical model that provides confidence or probability statements about the decision area. Statistical sampling approaches typically involve taking samples at random locations, or at the nodes of a randomly located grid or lattice that is superimposed on the decision area. The term probabilistic sampling is often used to describe statistical sampling designs that exclusively use randomly located samples. This terminology implies that probabilistic statements can only be made based upon the results of randomly placed samples. However, the CJR method utilizes a Bayesian model that gives rise to a formal probabilistic statement regarding the acceptability of the decision area based upon the information obtained from both judgmental and random samples. Judgmental samples play a vital role in the characterization and clearance process because they include the informed prior belief and expert knowledge of personnel involved in the sampling process.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2012

STATISTICAL EVALUATION OF SMALL SCALE MIXING DEMONSTRATION SAMPLING AND BATCH TRANSFER PERFORMANCE - 12093

The ability to effectively mix, sample, certify, and deliver consistent batches of High Level Waste (HLW) feed from the Hanford Double Shell Tanks (DST) to the Waste Treatment and Immobilization Plant (WTP) presents a significant mission risk with potential to impact mission length and the quantity of HLW glass produced. DOE's Tank Operations Contractor, Washington River Protection Solutions (WRPS) has previously presented the results of mixing performance in two different sizes of small scale DSTs to support scale up estimates of full scale DST mixing performance. Currently, sufficient sampling of DSTs is one of the largest programmatic risks that could prevent timely delivery of high level waste to the WTP. WRPS has performed small scale mixing and sampling demonstrations to study the ability to sufficiently sample the tanks. The statistical evaluation of the demonstration results which lead to the conclusion that the two scales of small DST are behaving similarly and that full scale performance is predictable will be presented. This work is essential to reduce the risk of requiring a new dedicated feed sampling facility and will guide future optimization work to ensure the waste feed delivery mission will be accomplished successfully. This paper will focus on the analytical data collected from mixing, sampling, and batch transfer testing from the small scale mixing demonstration tanks and how those data are being interpreted to begin to understand the relationship between samples taken prior to transfer and samples from the subsequent batches transferred. An overview of the types of data collected and examples of typical raw data will be provided. The paper will then discuss the processing and manipulation of the data which is necessary to begin evaluating sampling and batch transfer performance. This discussion will also include the evaluation of the analytical measurement capability with regard to the simulant material used in the demonstration tests. The paper will conclude with a discussion of the analysis results illustrating the relationship between the pre-transfer samples and the batch transfers, which support the recommendation regarding the need for a dedicated feed sampling facility.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2012

HIGH-REDSHIFT COOL-CORE GALAXY CLUSTERS DETECTED VIA THE SUNYAEV-ZEL'DOVICH EFFECT IN THE SOUTH POLE TELESCOPE SURVEY

We report the first investigation of cool-core properties of galaxy clusters selected via their Sunyaev-Zel'dovich (SZ) effect. We use 13 galaxy clusters uniformly selected from 178 deg{sup 2} observed with the South Pole Telescope (SPT) and followed up by the Chandra X-ray Observatory. They form an approximately mass-limited sample (>3 Multiplication-Sign 10{sup 14} M{sub Sun} h {sup -1}{sub 70}) spanning redshifts 0.3 < z < 1.1. Using previously published X-ray-selected cluster samples, we compare two proxies of cool-core strength: surface brightness concentration (c{sub SB}) and cuspiness ({alpha}). We find that c{sub SB} is better constrained. We measure c{sub SB} for the SPT sample and find several new z > 0.5 cool-core clusters, including two strong cool cores. This rules out the hypothesis that there are no z > 0.5 clusters that qualify as strong cool cores at the 5.4{sigma} level. The fraction of strong cool-core clusters in the SPT sample in this redshift regime is between 7% and 56% (95% confidence). Although the SPT selection function is significantly different from the X-ray samples, the high-z c{sub SB} distribution for the SPT sample is statistically consistent with that of X-ray-selected samples at both low and high redshifts. The cool-core strength is inversely correlated with the offset between the brightest cluster galaxy and the X-ray centroid, providing evidence that the dynamical state affects the cool-core strength of the cluster. Larger SZ-selected samples will be crucial in understanding the evolution of cluster cool cores over cosmic time.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

Evidence for non-exponential elastic proton-proton differential cross-section at low |t| and $\sqrt{s}$ = 8 TeV by TOTEM

The TOTEM experiment has made a precise measurement of the elastic proton–proton differential cross-section at the centre-of-mass energy √s = 8 TeV based on a high-statistics data sample obtained with the β* = 90 m optics. Both the statistical and systematic uncertainties remain below 1%, except for the t -independent contribution from the overall normalisation. This unprecedented precision allows to exclude a purely exponential differential cross-section in the range of four-momentum transfer squared 0.027 < |t| < 0.2 GeV 2 with a significance greater than 7 σ. Two extended parametrisations, with quadratic and cubic polynomials in the exponent, are shown to be well compatible with the data. As a result, using them for the differential cross-section extrapolation to t=0, and further applying the optical theorem, yields total cross-section estimates of (101.5 ± 2.1) mb and (101.9 ± 2.1) mb, respectively, in agreement with previous TOTEM measurements.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2018

Enhancing Model Predictability for a Scramjet Using Probabilistic Learning on Manifolds

In this study, the computational burden of a large-eddy simulation for reactive flows is exacerbated in the presence of uncertainty in flow conditions or kinetic variables. A comprehensive statistical analysis, with a sufficiently large number of samples, remains elusive. Statistical learning is an approach that allows for extracting more information using fewer samples. Such procedures, if successful, will greatly enhance the predictability of models in the sense of improving exploration and characterization of uncertainty due to model error and input dependencies, all while being constrained by the size of the associated statistical samples. In this paper, it is shown how a recently developed procedure for probabilistic learning on manifolds can serve to improve the predictability in a probabilistic framework of a scramjet simulation. The estimates of the probability density functions of the quantities of interest are improved together with estimates of the statistics of their maxima. Lastly, it is also demonstrated how the improved statistical model adds critical insight to the performance of the model.

42 ENGINEERING↗
DOE OSTI2014

Statistical Evaluation of Tank 12 Sampling Options

Savannah River Remediation (SRR) is preparing Tank 12 for removal from service and has issued a scope of work to the Savannah River National Laboratory (SRNL) under a Task Technical Request (TTR) G-TTR-H-00007 (Savannah River Remediation, 2014) to provide statistical support for the Sample Location Determination Report (SLDR) and the Tank-Specific Sampling and Analysis Plan (TSAP). In response SRNL has issued a Task Technical and Quality Assurance Plan (TTQAP) (Shine, 2014) outlining the strategy for assessing sampling options.

Shine, G.↗
DOE OSTI2023

Earth mover’s distance as a measure of CP violation

We introduce a new unbinned two sample test statistic sensitive to CP violation utilizing the optimal transport plan associated with the Wasserstein (earth mover’s) distance. The efficacy of the test statistic is shown via two examples of CP asymmetric distributions with varying sample sizes: the Dalitz distributions of B 0 → K + π – π 0 and of D 0 → π + π – π 0 decays. The windowed version of the Wasserstein distance test statistic is shown to have comparable sensitivity to CP violation as the commonly used energy test statistic, but also retains information about the localized distributions of CP asymmetry over the Dalitz plot. For large statistic datasets we introduce two modified Wasserstein distance based test statistics — the binned and the sliced Wasserstein distance statistics, which show comparable sensitivity to CP violation, but improved computing time and memory scalings. Finally, general extensions and applications of the introduced statistics are discussed.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2016

Minimum local distance density estimation

We present a local density estimator based on first-order statistics. To estimate the density at a point, $x$, the original sample is divided into subsets and the average minimum sample distance to $x$ over all such subsets is used to define the density estimate at $x$. The tuning parameter is thus the number of subsets instead of the typical bandwidth of kernel or histogram-based density estimators. The proposed method is similar to nearest-neighbor density estimators but it provides smoother estimates. We derive the asymptotic distribution of this minimum sample distance statistic to study globally optimal values for the number and size of the subsets. Simulations are used to illustrate and compare the convergence properties of the estimator. The results show that the method provides good estimates of a wide variety of densities without changes of the tuning parameter, and that it offers competitive convergence performance.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Microstructure Development of 308L Stainless Steel During Additive Manufacturing

$In$ $situ$ high-energy X-ray diffraction measurements were completed during deposition of 308L stainless steel wire onto a 304L stainless steel substrate. Attempts were made to extract microstructural features such as phase fraction and internal stress, as well as temperature evolution immediately following the deposition. The limited data that could be collected during deposition and rapid solidification are critically examined. High-energy X-rays coupled with relatively slow detectors were utilized to enable determination of orientation-dependent lattice parameters accurately enough to comment on phase strain evolution between austenite and ferrite. Here, information about the hydrostatic and deviatoric stress states of the constituent phases was determined on time scales that are relevant to their development. However, the time resolution of the technique was insufficient to monitor phase evolution during the solid–solid phase transformation and, more so, during solidification. Moreover, the accurate and absolute determination of inherently statistical parameters, such as phase fraction, depends critically on the ability to sample a statistically significant numbers of grains in the microstructure.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Quantification of Organic Porosity and Water Accessibility in Marcellus Shale Using Neutron Scattering

Pores within organic matter (OM) are a significant contributor to the total pore system in gas shales. These pores contribute most of the storage capacity in gas shales. Here we present a novel approach to characterize the OM pore structure (including the porosity, specific surface area, pore size distribution, and water accessibility) in Marcellus shale. By using ultrasmall and small-angle neutron scattering, and by exploiting the contrast matching of the shale matrix with suitable mixtures of deuterated and protonated water, both total and water-accessible porosity were measured on centimeter-sized samples from two boreholes from the nanometer to micrometer scale with good statistical coverage. Samples were also measured after combustion at 450 °C. Analysis of scattering data from these procedures allowed quantification of OM porosity and water accessibility. OM hosts 24–47% of the total porosity for both organic-rich and -poor samples. This porosity occupies as much as 29% of the OM volume. In contrast to the current paradigm in the literature that OM porosity is organophilic and therefore not likely to contain water, our results demonstrate that OM pores with widths >20 nm exhibit the characteristics of water accessibility. In conclusion, our approach reveals the complex structure and wetting behavior of the OM porosity at scales that are hard to interrogate using other techniques.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2012

User's manual for the BROOM decision support system

The Building Restoration Operations Optimization Model (BROOM) software system, developed by Sandia National Laboratories, is a comprehensive system designed to improve the efficiency and quality of sample collection, data management, and interpretation. Currently, BROOM is capable of supporting sampling efforts at facilities contaminated with chemical and/or biological agents. BROOM provides advanced visualization, analysis, and sampling optimization functions, which speed up the sampling process and lower the associated sampling costs. BROOM enables the user to develop a defensible sampling plan based on statistical analysis of sample results. BROOM consists of two applications: one that runs on a hand-held PDA and one that runs on a Windows desktop/laptop. This document covers the installation and basic operation of both components and provides examples of the application of these tools during and following an actual field exercise.

Knowlton, Robert G.↗
DOE OSTI2016

Application of MARSSIM and MARSAME Guidance to Footprint Reduction Projects at a DOE Site (LA-UR-15-28730) - 16216

Department of Energy regulations require that potentially contaminated items and materials being released to the public are monitored and that any residual radioactive contamination does not contribute more than 10 μSv/y (1 mrem/y). In footprint reduction and demolition projects, buildings with potential residual contamination must be carefully and systematically surveyed prior to recycling materials or releasing debris for burial in commercial landfills. Multi-agency guidance is available to assure statistically representative sampling of the items and materials, appropriate measurement quality objectives, and valid statistical approaches for release decisions. Additionally, implementing a cost-effective evaluation program for releases requires working closely with regulators and waste generators and developing a technically sound process to account for naturally occurring radioactive material (NORM) in building materials. Los Alamos National Laboratory has successfully implemented the available guidance for footprint reduction projects to help divert clean, recyclable materials from landfills and limit the possibility of mistakenly disposing of NORM as low level waste. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2019

Development and Comparison of Purgeable Mercury Values in SRR Samples Measured by SRNL and Eurofins FGS

Savannah River Remediation (SRR) requested the development of mercury speciation capabilities at the Savannah River National Laboratory (SRNL) to support the Liquid Waste Operations at SRS. As part of that method development, SRR requested that SRNL Analytical Development (AD) compare their results with those obtained from their outside contract laboratory, Eurofins Frontier Global Sciences (FGS). This document reports on this method development work performed at SRNL as well as the comparative analyses conducted between the two laboratories. Development, optimization, and validation were undertaken at SRNL to produce a method for the species-specific analysis of dissolved gaseous mercury (DGM) in samples from SRR. It was determined that DGM present in SRR samples represented a combination of various soluble and volatile mercury species- and is thus referred to in this document as purgeable mercury. A method has been developed and analytically validated for the analysis of purgeable mercury in caustic nuclear waste. Using multivariate optimization, an efficient and sensitive method was produced. Total recovery of spiked purgeable mercury from deionized water was 99.4 ±10.6% and 91.6 ±14.9% from spiked high-activity tank waste samples. Calibration, by external calibration and standard addition calibration, maintained a mean accuracy of 101 ±5% and 99.9 ±1.7%, respectively. An interlaboratory comparison was performed between SRNL and Eurofins FGS in the co-analysis of three quarterly SRR Tank 50 samples. The statistical evaluations presented in this document support the following conclusions: for internal validation data, the two laboratories demonstrate biases of -4.3% for SRNL and 4.4% for Eurofins FGS, though neither are statistically significant at the 5% level. While the percent relative standard deviation for each of the laboratories is rather large (21.5% for SRNL and 18.4% for Eurofins FGS), there is no indication of a statistically significant difference between the two laboratories in the precision of these results. For the three sets of SRR quarterly Tank 50 samples, there is no indication of a statistically significant bias between the two laboratories at the 5% significance level. These results indicate that SRNL may provide data to the customer of statistically similar quality to Eurofins FGS.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2019

Gamma Ray Spectrometry Assay Results of 242 Pu Samples at the Chemistry and Metallurgy Research Facility

Thirty individual items at the Chemistry and Metallurgy Research (CMR) facility with accountable amounts of 242 Pu required assay by gamma ray spectrometry in order to establish their masses with reasonable precision. There were two phases to this measurement campaign: 1) a preliminary screening phase in which each item was measured for a short 600 second count time to establish the relative masses between similar or like items, and 2) a second phase in which groups of items were counted for a considerably longer time in order to establish the group mass of 242 Pu in a reasonable time frame. The data from the two phases were assessed in a manner that allowed the project team to assign a 242 Pu mass to each individual item in the inventory, with the exception of three column tubes that could not be measured individually because of radiological contamination issues. The project team performed technical analyses with the SNAP™ analysis routine, PC-FRAM plutonium isotopic routine, and the NEN-2 PeakEasy routine. When total measurement uncertainties are factored in, the individual mass quantities calculated for all samples are statistically equivalent to the expected mass of 0.88 grams of total plutonium per sample.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2018

D-Guaranteed Discrimination of Statistical Hypotheses: a Review of Results and Unsolved Problems

We compare two sequential d-guaranteed tests and an optimal d-guaranteed test based on a fixed number of observations with respect to the average number of observations within the most accepted practical applications of Bayesian probabilistic models. We consider the sequential “first skipping” test, the sequential locally efficient test based on the score statistic, and the test based on a fixed number of observations that minimizes the necessary sample size. We study various characteristics of these tests connected with the number of observations within three probabilistic models, namely, the normal (ϑ, σ{sup 2}) distribution of the observed random variable and the normal a priori distribution of ϑ with fixed σ{sup 2}; the exponential distribution with the intensity parameter ϑ and the a priori gamma distribution of ϑ; and the Bernoulli sampling with the success probability ϑ and the a priori beta distribution of ϑ. We discuss the connection of the d-posterior approach with the compound decision problem as applied to the analysis of data provided by microchips (when the false discovery rate, or FDR, for short, is treated as the d-risk of the first kind). We present the vast data on characteristics of the mentioned tests obtained by the method of mathematical modeling in several tables. We discuss unsolved problems of the d-guaranteed discrimination of hypotheses with the minimal number of observations and approaches to their solution.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Statistical Methods for Improved Evaluation of Environmental Sample Data quarterly FY18Q2

We will develop an enhanced statistical framework to evaluate environmental swipe samples collected at nuclear facilities with the goal of identifying anomalies associated with potential undeclared activities. Our approach will be based on Bayesian methodology and time series analysis. This overall framework should result in a more cost effective and operationally effective approach to environmental swipe sample analysis and interpretation.

97 MATHEMATICS AND COMPUTING↗