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At least 991 records · Page 55

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NASA NTRS2016

An Evaluation of Flash Cells Used in Critical Applications

Due to the common use of Flash technology in many commercial and industrial Programmable Logic Devices (PLDs) such as FPGAs and mixed-signal microcontrollers, flash technology is being utilized in fuzed munition applications. This presents a long-term reliability issue for both DoD and NASA safety- and mission-critical applications. A thorough understanding of the data retention failure modes and statistics associated with Flash data retention is of vital concern to the fuze safety community. A key retention parameter for a flash cell is the threshold voltage (VTH), which is an indirect indicator of the amount of charge stored on the cells floating gate. Initial test results based on a study of charge loss in flash cells in an FPGA device is presented. Statistical data taken from a small sample set indicates quantifiable charge loss for devices stored at both room temperature and 150 C. Initial evaluation of the distribution of threshold voltage in a large sample set (800 devices) is presented. The magnitude of charge loss from exposure to electrostatic discharge and electromagnetic fields is measured and presented. Simulated data (and measured data as available) resultant from harsh-environment testing (neutron, heavy ion, EMP) is presented.

data retention↗

NASA NTRS2016

An Evaluation of Flash Cells Used in Critical Applications

Data Retention↗

NASA NTRS2017

Determination of the Risk of Radiation-Associated Circulatory and Cancer Disease Mortality in a NASA Early Astronaut Cohort

Of the many possible health challenges posed during extended exploratory missions to space, the effects of space radiation on cardiovascular disease and cancer are of particular concern. There are unique challenges to estimating those radiation risks; care and appropriate and rigorous methodology should be applied when considering small cohorts such as the NASA astronaut population. The objective of this work was to determine if there was sufficient evidence for excess risk of cardiovascular disease and cancer in early NASA astronaut cohorts. NASA astronauts in selection groups 1-7 were chosen; this relatively homogeneous cohort consists of 73 white males, who unlike today's astronauts, maintained similar smoking and drinking habits to the general US population, and have published radiation doses. The participants flew in space on missions Mercury through Shuttle and received space radiation doses between 0-74.1 milligrays. Cause of death information was obtained from the Lifetime Surveillance of Astronaut Health (LSAH) program at NASA Johnson Space Center. Mortality was compared with the US male population. Trends of mortality with dose were assessed using a logistic model, fitted by maximum likelihood. Only 32 (43.84 percent) of the 73 early astronauts have died. Standard mortality ratios (SMRs) for cancer (n=7, SMR=43.4, 95 percent CI 17.8, 84.9), all circulatory disease (n=7, SMR=33.2, 95 percent CI 13.7, 65.0), and ischemic heart disease (IHD) (n=5, SMR=40.1, 95 percent CI 13.2, 89.4) were significantly lower than for the US white male population. For cerebrovascular disease, the upper confidence interval for SMR included 100, indicating it was not significantly different from the US population (n=2, SMR = 77.0, 95 percent CI 9.4, 268.2). The power of the study is low and remains below 10 percent even when risks 10 times those reported in the literature are assumed. Due to small sample size, there is currently insufficient statistical power to evaluate space radiation exposure effects on mortality in NASA astronauts. In addition to a comprehensive longitudinal study of NASA astronauts, a research strategy of low dose epidemiology data integration with cell and animal studies should be utilized for space radiation risk assessment in the astronauts.

Elgart, S. R.↗

NASA NTRS2021

Investigation on the Origins of Comets as Revealed through IR High Resolution Spectroscopy: I. Molecular Abundances

We report and analyze molecular abundances updatedin twenty comets by employingmodern data reduction procedures and molecular models. Using boxplots and scatterplots, we examine how the different molecular species are distributed among the comet population, while by means of pie charts we investigate the relative proportions of these molecular species in each comet. We compare these results with the orbital parametersof the selected targets in order to identify trends related to the dynamical history of each comet. In this way, we identify at least three chemical classes based mainly on relative abundances of CO, CH3OH, CH4, C2H6, HCN and NH3. The combination of relative abundances and orbital parameters is then compared with chemical models of planetary system formation and may offer an alternative approach to investigate the origin and evolution of the material in cometary nuclei.Our study also confirms the need to add more objects to our sample in order to improve the statistics, especially for hyper-volatiles (i.e. CH4and CO) in Jupiter Family comets.

M Lippi↗

NASA NTRSDate not supplied

Analysis of Hypervelocity-Impacted Thin Films for Space Applications

Exposure to the harsh space environment and hypervelocity impacts from micrometeoroids and small orbital debris can affect space operations through long-term degradation of spacecraft materials, surfaces, or systems. Multi-layer insulation (MLI) and coated polyimide films are space-craft materials commonly found on the external surfaces of spacecraft for thermal control and protection. Characterizing the damage to these exposed materials with in-situ and laboratory measurements can better inform spacecraft designers and operators in understanding and mitigating surface or system degradation. In this paper, we examine flown Hubble Space Telescope (HST) Electronic Bay 5 MLI and coated polyimide ground test articles to characterize hyper-velocity impact damage. Impact feature cavities are inspected to identify damage, which can validate long-term degradation models, improve thermal management systems, or improve accuracy of damage predictions. An overview of the impact characterization using optical microscopy, narrow-band spectroscopy, and scanning election microscopy/energy dispersive x-ray (SEM/EDX) of the two materials is presented. Observations of robustness in the space environment, as well as a detailed assessment of cratering and penetration statistics for the space-exposed sample, also are discussed.

Melissa A Ward↗

NASA NTRSDate not supplied

Analysis of Hypervelocity-Impacted Thin Films for Space Applications

Exposure to the harsh space environment and hypervelocity impacts from micrometeoroids and small orbital debris can affect space operations through long-term degradation of spacecraft materials, surfaces, or systems. Multi-layer insulation (MLI) and coated, polyimide films are spacecraft materials commonly found on the external surfaces of spacecraft for thermal control and protection. Characterizing the damage to these exposed materials with in situ and laboratory measurements can better inform spacecraft designers and operators in understanding and mitigating surface or system degradation. In this paper, we examine flown Hubble Space Telescope (HST) Equipment Bay 5 MLI and coated, polyimide ground test articles to characterize hypervelocity impact damage. Impact feature cavities are inspected to identify damage, which can validate long-term degradation models, improve thermal management systems, or improve accuracy of damage predictions. An overview of the impact characterization using optical microscopy, narrowband spectroscopy, and Scanning Election Microscopy/Energy Dispersive X- ray (SEM/EDX) of the two materials is presented. Observations of robustness in the space environment, as well as a detailed assessment of cratering and penetration statistics for the space-exposed sample, also are discussed.

Melissa A. Ward↗

DOE OSTI2016

Particle Management Strategies for Ultra-high Vacuum Assemblies

The intent of this project is to compare the particle generation and gall prevention characteristics of stainless steel, silver coated, and TiN coated fasteners. To achieve this goal, the following steps were taken: • A testing stand was designed to be compatible with cleanroom requirements. • Data acquisition programs and equipment were obtained and implemented. • Particle count data was collected during the assembly and disassembly of conflat vacuum flanges. • Observations of galling and particle generation phenomena were made. • A Student T-test was applied to the collected particle data to determine the statistical significance of the collected data. • Samples were placed under a Scanning Electron Microscope to examine particle generation phenomena.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2023

Status of Error Correction Studies in Support of FFA@CEBAF

In this work, we examine the beam correction requirements for the FFA@CEBAF energy upgrade. Both hardware and software diagnostic and corrector components are under investigation; in particular the relationship between hardware and software optimization will be developed. To generate a representative sample of errors---from the machine lattice and other beam properties---we construct a Markov Chain Monte Carlo (MCMC) sampler which considers different probability distributions for different types of errors. This sample is used to investigate the statistical sensitivity of the beam to various diagnostic and corrective schema. Once statistics are acquired, we plan to use a variety of optimization techniques to minimize correction time for the electron beam in the FFA arcs designed for the CEBAF upgrade.

Benesch, J.↗

DOE OSTI2023

Adaptive, Active Learning, and Multifidelity Monte Carlo Methods in the MOOSE Stochastic Tools Module

MOOSE is an open-source computational platform for constructing multi-physics models and executing them in a massively parallel fashion. It has a stochastic tools module (STM) for forward/inverse uncertainty quantification (UQ) and surrogate modeling. This presentation details some recent developments to the STM with respect to the implementation of adaptive, active learning, and multifidelity Monte Carlo methods for forward UQ of computational models. Specifically, the adaptive Monte Carlo methods include Markov Chain Monte Carlo (MCMC)-driven algorithms like adaptive importance sampling and parallelized subset simulation for statistical QoI estimation, rare events analysis, and stochastic gradient-free optimization. The active learning methods include Gaussian Process (GP) surrogates and their training via Adam optimization, design of acquisition functions, and integration with samplers like Monte Carlo, adaptive importance, and parallelized subset simulation. These active learning methods are also designed to work in a batch mode, wherein, the required calls to the full computational model are executed in parallel whenever a user-specified batch size is met. The multifidelity methods in STM are broadly divided into two categories: hierarchical, where a defined hierarchy exists among the low-fidelity models, and peer, where all the low-fidelity models are treated equally. A GP surrogate is used to learn the differences between the low- and high-fidelity models in both multifidelity categories, and acquisition functions from the active learning classes are used to decide whether to rely on a low-fidelity model or call the expensive high-fidelity model. Alongside the software description and usage, applications are also presented to nuclear engineering computational models including a TRISO nuclear fuel particle, a reactor pressure vessel, and a heat-pipe microreactor.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2018

Proteomics Goes to Court: A Statistical Foundation for Forensic Toxin/Organism Identification Using Bottom-Up Proteomics

Bottom-up proteomics is increasingly being used to characterize unknown environmental, clinical, and forensic samples. Proteomics-based bacterial identification typically proceeds by tabulating peptide “hits” (i.e. confidently identified peptides) associated with the organisms in a database; those organisms with enough hits are declared present in the sample. This approach has proven successful in laboratory studies, however, important research gaps remain. First, the common-practice reliance on unique peptides for identification is susceptible to a phenomenon known as signal erosion. Second, no general guidelines are available for determining how many hits are needed to make a confident identification. These gaps inhibit the transition of this approach to real-world samples where conditions vary and large databases may be needed. We propose statistical criteria for organism identification that applies regardless of sample quality or data analysis pipeline. These criteria are straightforward, producing a p-value on the result. We test the criteria on LC-MS/MS datasets representing 919 different bacterial and toxin datasets acquired with multiple data collection platforms. Results reveal a >95% correct species-level identification rate, demonstrating the effectiveness and robustness of proteomics-based organism/toxin identification.

Jarman, Kristin H.↗

DOE OSTI2016

SDSS-IV MaNGA IFS GALAXY SURVEY—SURVEY DESIGN, EXECUTION, AND INITIAL DATA QUALITY

The MaNGA Survey (Mapping Nearby Galaxies at Apache Point Observatory) is one of three core programs in the Sloan Digital Sky Survey IV. It is obtaining integral field spectroscopy for 10,000 nearby galaxies at a spectral resolution of R ∼ 2000 from 3622 to 10354 Å. The design of the survey is driven by a set of science requirements on the precision of estimates of the following properties: star formation rate surface density, gas metallicity, stellar population age, metallicity, and abundance ratio, and their gradients; stellar and gas kinematics; and enclosed gravitational mass as a function of radius. We describe how these science requirements set the depth of the observations and dictate sample selection. The majority of targeted galaxies are selected to ensure uniform spatial coverage in units of effective radius (R{sub e}) while maximizing spatial resolution. About two-thirds of the sample is covered out to 1.5 R{sub e} (Primary sample), and one-third of the sample is covered to 2.5 R{sub e} (Secondary sample). We describe the survey execution with details that would be useful in the design of similar future surveys. We also present statistics on the achieved data quality, specifically the point-spread function, sampling uniformity, spectral resolution, sky subtraction, and flux calibration. For our Primary sample, the median r -band signal-to-noise ratio is ∼70 per 1.4 Å pixel for spectra stacked between 1 R{sub e} and 1.5 R{sub e}. Measurements of various galaxy properties from the first-year data show that we are meeting or exceeding the defined requirements for the majority of our science goals.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2018

Part 2: Forensic attribution profiling of Russian VX in food using liquid chromatography-mass spectrometry

This work is part two of a three-part series in this issue of a Sweden-United States collaborative effort towards the understanding of the chemical attribution signatures of Russian VX (VR) in synthesized samples and complex food matrices. We describe the sourcing of VR present in food based on chemical analysis of attribution signatures by liquid chromatography-tandem mass spectrometry (LC-MS/MS) combined with multivariate data analysis. Analytical data was acquired from seven different foods spiked with VR batches that were synthesized via six different routes in two separate laboratories. The synthesis products were spiked at a lethal dose into seven food matrices: water, orange juice, apple purée, baby food, pea purée, liquid eggs and hot dog. After acetonitrile sample extraction, the samples were analyzed by LC-MS/MS operated in MRM mode. A multivariate statistical calibration model was built on the chemical attribution profiles from 118 VR spiked food samples. Using the model, an external test-set of the six synthesis routes employed for VR production was correctly identified with no observable major impact of the food matrices to the classification. The overall performance of the statistical models was found to be exceptional (94%) for the test set samples retrospectively classified to their synthesis routes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRS1964

Monte Carlo techniques for solving transport problems

The Monte Carlo procedure is a model sampling technique. A model is established, and the behavior of sample units in this model is followed. A sufficient number of sample units are followed to obtain a statistical average or macroscopic quantities, which are the quantities of interest. This technique was used in crude form by Fermi in connection with the building of the first atomic pile. Later, Von Neumann and Ulam developed and used the Monte Carlo procedure extensively in developing the atomic bomb. Since then this technique has gained considerable use in nuclear reactor problems (refs. 1 and 2), and we at the Lewis Research Center have been extending it to thermal radiation (refs. 3 and 4), rarefied gas flows, and plasma flow problems (ref. 5). This technique, which requires a large number of sample histories to obtain solutions with small variances, is receiving greater use because of the development of the high-speed electronic computers.

SAMPLED DATA SYSTEM↗

NASA NTRS1974

Statistical analysis of catalogs of extragalactic objects. III - The Shane-Wirtanen and Zwicky catalogs

Statistical investigation of clustering in the galaxy catalogs compiled by Zwicki et al. (1961-1968) and Shane and Wirtanen (1967). The covariance and power spectrum of the angular distributions are estimated. The space region surveyed in the Zwicki catalog is found to represent a 'fair sample of the universe' in that the statistical nature of the clustering in this catalog is found to be mirrored at smaller angular scales in the deeper survey of Shane and Wirtanen.

Peebles, P. J. E.↗

DOE OSTI2023

Optimizing metaproteomics database construction: lessons from a study of the vaginal microbiome

Metaproteomics, a method for untargeted, high-throughput identification of proteins in complex samples, provides functional information about microbial communities and can tie functions to specific taxa. Metaproteomics often generates less data than other omics techniques, but analytical workflows can be improved to increase usable data in metaproteomic outputs. Identification of peptides in the metaproteomic analysis is performed by comparing mass spectra of sample peptides to a reference database of protein sequences. Although these protein databases are an integral part of the metaproteomic analysis, few studies have explored how database composition impacts peptide identification. Here, we used cervicovaginal lavage (CVL) samples from a study of bacterial vaginosis (BV) to compare the performance of databases built using six different strategies. We evaluated broad versus sample-matched databases, as well as databases populated with proteins translated from metagenomic sequencing of the same samples versus sequences from public repositories. Smaller sample-matched databases performed significantly better, driven by the statistical constraints on large databases. Additionally, large databases attributed up to 34% of significant bacterial hits to taxa absent from the sample, as determined orthogonally by 16S rRNA gene sequencing. We also tested a set of hybrid databases which included bacterial proteins from NCBI RefSeq and translated bacterial genes from the samples. These hybrid databases had the best overall performance, identifying 1,068 unique human and 1,418 unique bacterial proteins, ~30% more than a database populated with proteins from typical vaginal bacteria and fungi. Our findings can help guide the optimal identification of proteins while maintaining statistical power for reaching biological conclusions.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRS1972

Paleomagnetism of the Mesozoic in Alaska

Over 400 oriented cores of Permian, Triassic, Jurassic, and Cretaceous sedimentary and igneous rocks were collected from 34 sites at 10 areas throughout southern Alaska. After magnetic cleaning in successively higher alternating fields 179 samples were considered to be stable and to give statistically consistent results within each site and age group. Due to the lack of a sufficient number of stable samples, the results from Permian, Triassic, and Cretaceous rocks were inconclusive. The nine remaining Jurassic sites represent 100 samples from three general areas in southern Alaska. The southern Alaskan Jurassic paleomagnetic pole is significantly different from the North American Jurassic pole. This suggests that since the Jurassic, southern Alaska must have moved approximately 18 degrees north and rotated 52 degrees clockwise to reach its present position. Tectonic interpretation of these results give a possible explanation for many of the geologic features observed in southern Alaska.

Packer, D. R.↗

NASA NTRS1981

Information density and efficiency of two-dimensional /2-D/ sampled imagery

Information density and efficiency (i.e., the ratio of information density to data density) are used as criteria for assessing the quality of 2-D sampled and quantized imagery as a function of the statistical properties of random radiance fields, the spatial response (PSF or MTF) and sensitivity of imaging systems, and the sampling and quantization intervals. Computational results are intuitively satisfying: they are consistent with experimental and theoretical results obtained by earlier investigators concerned with the performance of TV cameras, and they provide useful guidelines for optimizing the design of line-scan and sensor-array imaging systems, especially if these systems use a digital communication link for transmitting data.

Huck, F. O.↗

DOE OSTI2019

A multivariate approach to ensure statistical reproducibility of climate model simulations

Effective utilization of novel hybrid architectures of pre-exascale and exascale machines requires transformations to global climate modeling systems that may not reproduce the original model solution bit-for-bit. Round-off level differences grow rapidly in these non-linear and chaotic systems. This makes it difficult to isolate bugs/errors from innocuous growth expected from round-off level differences. Here, we apply two modern multivariate two sample equality of distribution tests to evaluate statistical reproducibility of global climate model simulations using standard monthly output of short (~ 1-year) simulation ensembles of a control model and a modified model of US Department of Energy's Energy Exascale Earth System Model (E3SM). Both the tests are able to identify changes induced by modifications to some model tuning parameters. We also conduct formal power analyses of the tests by applying them on designed suites of short simulation ensembles each with an increasingly different climate from the control ensemble. The results are compared against those from another such test. These power analyses provide a framework to quantify the degree of differences that can be detected confidently by the tests for a given ensemble size (sample size). This will allow model developers using the tests to make an informed decision when accepting/rejecting an unintentional non-bit-for-bit change to the model solution.

Mahajan, Salil↗