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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 1,531 records · Page 85
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Characterization Results for the 2014 HTF 3H & 2H Evaporator Overhead Samples

This report tabulates the radiochemical analysis of the 3H and 2H evaporator overhead samples for 137 Cs, 90 Sr, and 129 I to meet the requirements in the Effluent Treatment Project (ETP) Waste Acceptance Criteria (WAC) (rev. 6). This report identifies the sample receipt date, preparation method, and analysis performed in the accumulation of the listed values. All data was found to be within the ETP WAC (rev. 6) specification for the Waste Water Collection Tanks (WWCT).

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2016

Correlates of Sensitive Technologies

By “Quantitative Empirical Analysis” (QEA) is intended the use of statistical methods to infer, from data that often tend to be of a historical nature, the characteristics of states that correlate with some designated dependent variable (e.g. proliferation of nuclear weapons). QEA is a well-established approach in the social sciences, but is not notably well-known among physical scientists, who tend to think of the social sciences as inherently qualitative. This article attempts to provide a snapshot of research, most of which has evolved over the past decade, involving the application of QEA to issues in which the dependent variable of interest is intended as some measure of nuclear proliferation. Standard practices in QEA are described, especially as they relate to data collection. The QEA approach is compared and contrasted to other quantitative approaches to studying proliferation-related issues, including a “figure of merit” approach that has largely been developed within the DOE complex, and two distinct methodologies termed in a recent US National Academy of Sciences study as “case by case” and “predefined framework.” Sample results from QEA applied to proliferation are indicated, as are doubts about such quantitative approaches. A simplistic decision-theoretic model of the optimal time for the international community to intervene in a possible proliferation scenario is used to illustrate the possibility of synergies between different approaches

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2019

Synchrotron Based Microstructural Characterization Method Development for Pu Oxides

Identification of new plutonium oxide signatures is a high priority focus area of the technical nuclear forensics and nonproliferation communities. Comprehensive materials science studies of plutonium oxide are needed to advance the understanding of the microcrystalline properties and their relationship to macro-scale morphologies and signatures. Plutonium oxide particle growth is depenedent on the microcrystalline strucutures, grain size, and orientation. Microcrystalline structures have been found to vary for plutonium oxide based on the oxidation state of plutonium, concentration of reactants, and the physiochemical conditions of precipitation. Empirical observation confirms the relationship between processing conditions and particle morphology. High sensitivity, non destructive analysis of individual microcrystalline grains requires the use of bright sources of X-rays produced by synchrotron radiation, such as those at the Advanced Photon Source. The light source can reveal higher resolution crystallographic mapping, more sensitive chemical analysis, and higher fidelity morphological information than any current methods at SRNL Progress of FY19 was the analysis of the synchrotron data. Areas of focus included XANES oxidation state and EXAFS to measure bond distances with modeling. Most measurements for XANES indicated that the plutonium was in the +4 oxidation state, however, some indicated that there could also be a +5 oxidation state. The EXAFS measurements showed typical Pu – O bonding distance of 2.33 and Pu – Pu bonding distances of 3.81 A; however, some samples also showed that there could be shorter Pu – O distances of approximately 1.81 A, indicative of plutonium in the +5 oxidation state.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Structural Polymorphism of Chitin and Chitosan in Fungal Cell Walls From Solid-State NMR and Principal Component Analysis

Chitin is a major carbohydrate component of the fungal cell wall and a promising target for novel antifungal agents. However, it is technically challenging to characterize the structure of this polymer in native cell walls. Here, we recorded and compared 13 C chemical shifts of chitin using isotopically enriched cells of six Aspergillus, Rhizopus, and Candida strains, with data interpretation assisted by principal component analysis (PCA) and linear discriminant analysis (LDA) methods. The structure of chitin is found to be intrinsically heterogeneous, with peak multiplicity detected in each sample and distinct fingerprints observed across fungal species. Fungal chitin exhibits partial similarity to the model structures of α- and γ-allomorphs; therefore, chitin structure is not significantly affected by interactions with other cell wall components. Addition of antifungal drugs and salts did not significantly perturb the chemical shifts, revealing the structural resistance of chitin to external stress. In addition, the structure of the deacetylated form, chitosan, was found to resemble a relaxed two-fold helix conformation. This study provides high-resolution information on the structure of chitin and chitosan in their cellular contexts. The method is applicable to the analysis of other complex carbohydrates and polymer composites.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Legacy Analysis of Milky Way Dwarf Spheroidal Satellite Galaxies: An Update

Studies of Fermi Large Area Telescope (LAT) data coincident with dwarf spheroidal satellite galaxies (dSphs) of the Milky Way have put the most stringent constraints on models of annihilating dark matter (DM) with candidate masses in the GeV–TeV range. Recent results found the presence of small, local significance excesses from these targets, at the 2σ–3σ level. However, these excesses disagree on the predicted properties of the DM candidate, and their significance vanishes when considering correction factors for the number of trials. In this work, we apply key improvements to the analysis of dSphs. We use stricter cuts on the data, implement a method to adaptively model the background, and assume an updated framework for DM annihilation. We find that our improved background modeling leads to a better agreement between the model and the data. This produces an increase in the local and global significance of the dSph excess compared to previous studies. Finally, we find that the DM properties obtained in this work are less dependent on the sample of dSphs being considered compared to previous studies, while remaining in agreement with the predictions from the Galactic center excess observed by Fermi/LAT and the antiproton excess observed by the Alpha Magnetic Spectrometer (AMS-02). Considering our improvements, a future significant increase in the number of dwarfs may lead to a definitive confirmation or exclusion of the DM interpretation of the Galactic center excess.

cold dark matter↗
DOE OSTI2015

Parallel log structured file system collective buffering to achieve a compact representation of scientific and/or dimensional data

Collective buffering and data pattern solutions are provided for storage, retrieval, and/or analysis of data in a collective parallel processing environment. For example, a method can be provided for data storage in a collective parallel processing environment. The method comprises receiving data to be written for a plurality of collective processes within a collective parallel processing environment, extracting a data pattern for the data to be written for the plurality of collective processes, generating a representation describing the data pattern, and saving the data and the representation.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2015

Why Use Geo-statistics For Nuclear Decommissioning Projects? - 15567

Before nuclear facilities are dismantled, and contaminated sites remediated, their initial radiological state must be characterized. Combining historical information, non-destructive measurements and lab analysis results, the statistical method of geo-statistics allows all available data for 2D or 3D contamination mapping to be integrated and enhanced, and helps quantify estimation uncertainties. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

Unitarity methods in AdS/CFT

We develop a systematic unitarity method for loop-level AdS scattering amplitudes, dual to non-planar CFT correlators, from both bulk and boundary perspectives. We identify cut operators acting on bulk amplitudes that put virtual lines on shell, and show how the conformal partial wave decomposition of the amplitudes may be efficiently computed by gluing lower-loop amplitudes. A central role is played by the double discontinuity of the amplitude, which has a direct relation to these cuts. We then exhibit a precise, intuitive map between the diagrammatic approach in the bulk using cutting and gluing, and the algebraic, holographic unitarity method of [1] that constructs the non-planar correlator from planar CFT data. Our analysis focuses mostly on four-point, one-loop diagrams — we compute cuts of the scalar bubble, triangle and box, as well as some one-particle reducible diagrams — in addition to the five-point tree and four-point double-ladder. Analogies with S-matrix unitarity methods are drawn throughout.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2013

Uncertainty of Personnel Dosimetry Systems Using Performance Data Testing

While accreditation programs require a study of uncertainty for each dosimeter model for which accreditation is sought (Torres 2005, DOE 1986), no one method is specifically recommended by accrediting bodies. Typically, the methods used to determine uncertainty have included the partial differentiation method described in the U.S. Guide to Uncertainty in Measurements (ANSI 1997) or the use of Monte Carlo techniques and probability distribution functions to generate simulated dose results. Each of these techniques has particular strengths and should be employed when the areas of uncertainty are required to be understood in detail. However, the uncertainty of dosimeter results can also be determined using a Model II One-Way Analysis of Variance technique and accreditation testing data (Cummings and Flood 2010). The strengths of this method are (1) the method is based in robust and well-accepted statistical techniques; (2) the method is straightforward and easily applied to dose algorithms, which are so complex as to render the use of other methods unwieldy; and (3) the method uses dosimeter performance data obtained during accreditation. The general method and criteria of inclusion of radiation types and fields are discussed.

Cummings, Frederick (Rick) M.↗
DOE OSTI2021

Topological network analysis of patient similarity for precision management of acute blood pressure in spinal cord injury

Background: Predicting neurological recovery after spinal cord injury (SCI) is challenging. Using topological data analysis, we have previously shown that mean arterial pressure (MAP) during SCI surgery predicts long-term functional recovery in rodent models, motivating the present multicenter study in patients. Methods: Intra-operative monitoring records and neurological outcome data were extracted (n = 118 patients). We built a similarity network of patients from a low-dimensional space embedded using a non-linear algorithm, Isomap, and ensured topological extraction using persistent homology metrics. Confirmatory analysis was conducted through regression methods. Results: Network analysis suggested that time outside of an optimum MAP range (hypotension or hypertension) during surgery was associated with lower likelihood of neurological recovery at hospital discharge. Logistic and LASSO (least absolute shrinkage and selection operator) regression confirmed these findings, revealing an optimal MAP range of 76–[104-117] mmHg associated with neurological recovery. Conclusions: We show that deviation from this optimal MAP range during SCI surgery predicts lower probability of neurological recovery and suggest new targets for therapeutic intervention. Funding: NIH/NINDS: R01NS088475 (ARF); R01NS122888 (ARF); UH3NS106899 (ARF); Department of Veterans Affairs: 1I01RX002245 (ARF), I01RX002787 (ARF); Wings for Life Foundation (ATE, ARF); Craig H. Neilsen Foundation (ARF); and DOD: SC150198 (MSB); SC190233 (MSB); DOE: DE-AC02-05CH11231 (DM).

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2014

Nonlinear force-free extrapolation of the coronal magnetic field based on the magnetohydrodynamic relaxation method

We develop a nonlinear force-free field (NLFFF) extrapolation code based on the magnetohydrodynamic (MHD) relaxation method. We extend the classical MHD relaxation method in two important ways. First, we introduce an algorithm initially proposed by Dedner et al. to effectively clean the numerical errors associated with ∇ · B . Second, the multigrid type method is implemented in our NLFFF to perform direct analysis of the high-resolution magnetogram data. As a result of these two implementations, we successfully extrapolated the high resolution force-free field introduced by Low and Lou with better accuracy in a drastically shorter time. We also applied our extrapolation method to the MHD solution obtained from the flux-emergence simulation by Magara. We found that NLFFF extrapolation may be less effective for reproducing areas higher than a half-domain, where some magnetic loops are found in a state of continuous upward expansion. However, an inverse S-shaped structure consisting of the sheared and twisted loops formed in the lower region can be captured well through our NLFFF extrapolation method. We further discuss how well these sheared and twisted fields are reconstructed by estimating the magnetic topology and twist quantitatively.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

Nonparametric estimators for incomplete surveys

Nonparametric estimators, such as the 1/V{sub max} estimator and the C{sup −} estimator, have been applied extensively to estimate luminosity functions (LFs) of astronomical sources from complete, truncated survey data sets. Application of such estimators to incomplete data sets typically requires further truncation of data, separation into subsets of constant completeness, and/or correction for incompleteness-induced bias. In this paper, we derive generalizations of the above estimators designed for use with incomplete, truncated data sets. We compare these generalized nonparametric estimators, investigate some of their simple statistical properties, and validate them using Monte Carlo simulation methods. We apply a nonparametric estimator to data obtained from the extended Baryon Oscillation Spectroscopic Survey to estimate the QSO LF for redshifts 0.68<z<4.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Grain Boundary Plane Measurement Using Transmission Electron Microscopy Automated Crystallographic Orientation Mapping for Atom Probe Tomography Specimens

Abstract Grain boundaries are critical in determining the properties of materials, including mechanical stability, conductivity, and corrosion resistance. The specific properties of materials depend not only on the misorientation of the crystals, the three most commonly characterized parameters, but also on the angle of the grain boundary plane between the two crystals, the final two parameters in the five-parameter macroscopic description of the grain boundary. The method presented here allows for the direct measurement of all five parameters of the grain boundary in a transmission electron microscopy specimen of various morphologies. This is especially applicable to atom probe specimens, where only a single-tilt axis is generally available, allowing the crystallographic description to be matched to the detailed chemical data available in the atom probe tomography. This method provides a platform for efficient grain boundary analysis in unique samples, saving operator time and allowing for ease of acquisition and interpretation in comparison with traditional electron diffraction methods.

Materials Science↗
DOE OSTI2024

Simulator Data Analysis to Inform Digitalized Environment Impacts on Human Reliability

The U.S. Nuclear Regulatory Commission (NRC) has developed a human reliability analysis (HRA) method, termed the Integrated Human Event Analysis System for Event and Condition Assessment (IDHEAS-ECA), in order to estimate human error probabilities (HEPs) in risk-informed regulatory applications. To update the quantification part of IDHEAS-ECA, the NRC required human performance and error data from fully digitalized main control rooms (MCRs); therefore, it requested that Idaho National Laboratory (INL) revisit previous data collection studies and investigate how the following three factors impact human reliability: self-checking, peer-checking, and automation. The HRA data collection studies revisited were the Human Reliability Data Extraction (HuREX) project, developed by the Korea Atomic Energy Research Institute (KAERI), and the Simplified Human Error Experimental Program (SHEEP), developed by INL. HuREX is a representative HRA data collection study that collects human reliability data from full-scope simulators staffed by licensed operators. SHEEP, on the other hand, has been proposed to complement such full-scope studies by collecting data via simplified simulators staffed by non-licensed student operators. In the HuREX study, KAERI collected HRA data from fully digitalized MCRs for the Advanced Power Reactor (APR)–1400. The SHEEP data were obtained from simplified simulators that partially mimicked the features of digitalized MCRs. The present report mainly discusses how the impacts of the aforementioned three factors on human errors were derived from these two data collection studies.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2019

Development of an Efficient Enzyme Production and Structure-Based Discovery Platform for BACE1 Inhibitors

BACE1 (Beta-site Amyloid Precursor Protein (APP) Cleaving Enzyme 1) is a promising therapeutic target for Alzheimer’s Disease (AD). However, efficient expression, purification, and crystallization systems are not well described or detailed in the literature nor are approaches for treatment of enzyme kinetic data for potent inhibitors well described. As such, we developed a platform for expression and purification of BACE1, including protein refolding from E.coli inclusion bodies, in addition to optimizing a reproducible crystallization procedure of BACE1 bound with inhibitors. We also report a detailed approach to the proper analysis of enzyme kinetic data for compounds that exhibit either rapid-equilibrium or tight-binding mechanisms. Our methods allow for the purification of ~15 mg of BACE1 enzyme from 1 L of culture which is higher than reported yields in the current literature. To evaluate the data analysis approach developed here, a well-known potent inhibitor and two of its derivatives were tested, analyzed, and compared. The inhibitory constants (K i ) obtained from the kinetic studies are in agreement with dissociation constants (K d ) that were also determined using isothermal titration calorimetry (ITC) experiments. The X-ray structures of these three compounds in complex with BACE1 were readily obtained and provide important insight into the structure and thermodynamics of the BACE1-inhibitor interactions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

From microbial diversity to functional potential using dimensionality reduction

The high dimensionality of microbial diversity data from ‘omics observations can be reduced using Machine Learning, with many recent studies showcasing ML utility for exploratory ecological feature finding and process prediction. Here, we compare the Self Organizing Map (SOM) dimensionality reduction method to the well-documented sample-based Principal Coordinate Analysis (PCoA) and taxa-based Weighted Gene Correlation Network Analysis (WGCNA) using near daily 16S rRNA gene amplicon sequencing data from the 2019 to 2020 MOSAiC International Arctic Drift Expedition. We then map k-means clustering outputs from each method to available metagenomes, extracting functionally distinct seasonal microbial ecotypes in the surface Arctic Ocean. Our results indicate the SOM method better represented expected seasonal transitions and identified a greater number of metabolically distinct functional groups than the more traditional PCoA ordination. Ultimately, we identified four community ecotypes with distinct taxonomic and functional cut-offs driven by seasonality, water mass, and substrate turnover, highlighting the importance of succession in functional diversity for the central Arctic Ocean. These results reinforce ML dimensionality reduction as a meaningful translator in the mining of historical amplicon datasets to address modern mechanistic questions and potentially provide ’omics informed ecotype diversity to leverage in mechanistic biogeochemical models.

Arctic Ocean↗
DOE OSTI2026

Characterizing skyrmion flow phases with principal component analysis

Principal component analysis (PCA) is a powerful method that can identify patterns in large, complex data sets by constructing low-dimensional order parameters from higher-dimensional feature vectors. There are increasing efforts to use space-and-time-dependent PCA to detect transitions in nonequilibrium systems that are difficult to characterize with equilibrium methods. Here, we demonstrate that feature vectors incorporating the position and velocity information of driven skyrmions moving through random disorder permit PCA to resolve different types of disordered skyrmion motion as a function of driving force and the ratio of the Magnus force to the dissipation. Since the Magnus force creates gyroscopic motion and a finite Hall angle, skyrmions can exhibit a greater range of flow phases than what is observed in overdamped driven systems with quenched disorder. We show that in addition to identifying previously known skyrmion flow phases, PCA detects several additional phases, including different types of channel flow, moving fluids, and partially ordered states. Guided by the PCA analysis, we further characterize the disordered flow phases to elucidate the different microscopic dynamics and show that the changes in the PCA-derived order parameters can be connected to features in bulk transport measures, including the transverse and longitudinal velocity-force curves, differential conductivity, topological defect density, and changes in the skyrmion Hall angle as a function of drive. We discuss how asymmetric feature vectors can be used to improve the resolution of the PCA analysis, and how this technique can be extended to find disordered phases in other nonequilibrium systems with time-dependent dynamics.

36 MATERIALS SCIENCE↗
DOE OSTI2020

SpotSDC: Revealing the Silent Data Corruption Propagation in High-Performance Computing Systems

We report the trend of rapid technology scaling is expected to make the hardware of high-performance computing (HPC) systems more susceptible to computational errors due to random bit flips. Some bit flips may cause a program to crash or have a minimal effect on the output, but others may lead to silent data corruption (SDC), i.e., undetected yet significant output errors. Classical fault injection analysis methods employ uniform sampling of random bit flips during program execution to derive a statistical resiliency profile. However, summarizing such fault injection result with sufficient detail is difficult, and understanding the behavior of the fault-corrupted program is still a challenge. In this article, we introduce SpotSDC, a visualization system to facilitate the analysis of a program's resilience to SDC. SpotSDC provides multiple perspectives at various levels of detail of the impact on the output relative to where in the source code the flipped bit occurs, which bit is flipped, and when during the execution it happens. SpotSDC also enables users to study the code protection and provide new insights to understand the behavior of a fault-injected program. Based on lessons learned, we demonstrate how what we found can improve the fault injection campaign method.

97 MATHEMATICS AND COMPUTING↗