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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 721 records · Page 40
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Noise Is Not Error: Detecting Parametric Heterogeneity Between Epidemiologic Time Series

Mathematical models play a central role in epidemiology. For example, models unify heterogeneous data into a single framework, suggest experimental designs, and generate hypotheses. Traditional methods based on deterministic assumptions, such as ordinary differential equations (ODE), have been successful in those scenarios. However, noise caused by random variations rather than true differences is an intrinsic feature of the cellular/molecular/social world. Time series data from patients (in the case of clinical science) or number of infections (in the case of epidemics) can vary due to both intrinsic differences or incidental fluctuations. The use of traditional fitting methods for ODEs applied to noisy problems implies that deviation from some trend can only be due to error or parametric heterogeneity, that is noise can be wrongly classified as parametric heterogeneity. This leads to unstable predictions and potentially misguided policies or research programs. In this paper, we quantify the ability of ODEs under different hypotheses (fixed or random effects) to capture individual differences in the underlying data. We explore a simple (exactly solvable) example displaying an initial exponential growth by comparing state-of-the-art stochastic fitting and traditional least squares approximations. We also provide a potential approach for determining the limitations and risks of traditional fitting methodologies. Finally, we discuss the implications of our results for the interpretation of data from the 2014-2015 Ebola epidemic in Africa.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2016

Preventing Data Ambiguity in Infectious Diseases with Four-Dimensional and Personalized Evaluations

Background Diagnostic errors can occur, in infectious diseases, when anti-microbial immune responses involve several temporal scales. When responses span from nanosecond to week and larger temporal scales, any pre-selected temporal scale is likely to miss some (faster or slower) responses. Hoping to prevent diagnostic errors, a pilot study was conducted to evaluate a four-dimensional (4D) method that captures the complexity and dynamics of infectious diseases. Methods Leukocyte-microbial-temporal data were explored in canine and human (bacterial and/or viral) infections, with: (i) a non-structured approach, which measures leukocytes or microbes in isolation; and (ii) a structured method that assesses numerous combinations of interacting variables. Four alternatives of the structured method were tested: (i) a noise reduction oriented version, which generates a single (one data point-wide) line of observations; (ii) a version that measures complex, three-dimensional (3D) data interactions; (iii) a non-numerical version that displays temporal data directionality (arrows that connect pairs of consecutive observations); and (iv) a full 4D (single line-, complexity-, directionality based) version. Results In all studies, the non-structured approach revealed non-interpretable (ambiguous) data: observations numerically similar expressed different biological conditions, such as recovery and lack of recovery from infections. Ambiguity was also found when the data were structured as single lines. In contrast, two or more data subsets were distinguished and ambiguity was avoided when the data were structured as complex, 3D, single lines and, in addition, temporal data directionality was determined. The 4D method detected, even within one day, changes in immune profiles that occurred after antibiotics were prescribed. Conclusions Infectious disease data may be ambiguous. Four-dimensional methods may prevent ambiguity, providing earlier, in vivo, dynamic, complex, and personalized information that facilitates both diagnostics and selection or evaluation of anti-microbial therapies.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

SAS4A/SASSYS-1 Validation with EBR-II Tests Performed During the SHRT Testing Program

The EBR-II sodium-cooled fast reactor supported a wide range of fast reactor research activities. The final fifteen years of operations at EBR-II were used for experiments and tests to demonstrate the importance of passive safety in liquid metal reactors and the capability of such systems to provide strong passive responses during off-normal conditions. The Shutdown Heat Removal Test program at EBR-II provided test data supporting the validation of computer codes for design, licensing, and operation of LMRs, among other objectives. The program included nearly sixty tests, most of which were protected and unprotected loss of flow and loss of heat sink tests run at various initial powers and flow rates. This report documents the results of modeling and simulation of tests from the Shutdown Heat Removal Test program to support validation of Argonne’s SAS4A/SASSYS-1 fast reactor safety analysis code. SHRT-17 was a protected loss of flow test where a loss of electrical power to all sodium coolant pumps was simulated to demonstrate the effectiveness of natural circulation cooling characteristics. SHRT-45R was an unprotected loss of flow test where the control rod scram function of the plant protection system was disabled to demonstrate the effectiveness of EBR-II’s passive reactivity feedbacks. BOP-301 and BOP-302R were unprotected loss of heat sink tests that demonstrated how reactivity feedback effects driven by changes to the core inlet temperature can shut down the fission process. This validation activity leverages modeling and simulation efforts that originated under an International Atomic Energy Agency Coordinated Research Project for benchmark analysis of the EBR-II Shutdown Heat Removal Tests. The SAS4A/SASSYS-1 models originally developed for the CRP have been modernized to utilize new code features and modeling practices. Differences between the predicted and measured test data were explored and the causes of these differences were identified as being due to modeling approximations, uncertainty in transient component behavior, and instrumentation uncertainties. Overall, it was concluded that for SHRT-17, SHRT-45R, BOP-301, and BOP-302R there was good agreement between the flow, power, and temperature predictions and the measured data.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2020

Machine Learning for Neutron Resonance Evaluations [Slides]

The performance of nuclear reactors and other nuclear systems depends on a precise understanding of the neutron interaction cross sections for materials used in these systems. These cross sections exhibit a resonance structure whose shape is determined in part by the angular momentum quantum numbers of the resonances. The correct assignment of the quantum numbers of neutron resonances is therefore of paramount importance. In this presentation, we describe the application of machine learning to automate the quantum number assignments. Scikit-learn classifiers were trained on simulated resonance data whose statistical properties were chosen to mimic real data. We explored the use of several physics (and random matrix theory)-motivated features for training the classifiers, including the nearest neighbor spacing distribution, cumulative level distribution, and channel width distributions. Initial results demonstrated that we can determine resonance spin groups somewhat reliably. We are now investigating the application of our approach to 52 Cr resonance data.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Quality Assurance and Quality Control (QA/QC) of Meteorological Time Series Data for Billy Barr, East River, Colorado USA

A comprehensive Quality Assurance (QA) and Quality Control (QC) statistical framework consists of three major phases: Phase 1—Preliminary raw data sets exploration, including time formatting and combining datasets of different lengths and different time intervals; Phase 2—QA of the datasets, including detecting and flagging of duplicates, outliers, and extreme values; and Phase 3—the development of time series of a desired frequency, imputation of missing values, visualization and a final statistical summary. The time series data collected at the Billy Barr meteorological station (East River Watershed, Colorado) were analyzed. The developed statistical framework is suitable for both real-time and post-data-collection QA/QC analysis of meteorological datasets.The files that are in this data package include one excel file, converted to CSV format (Billy_Barr_raw_qaqc.csv) that contains the raw meteorological data, i.e., input data used for the QA/QC analysis. The second CSV file (Billy_Barr_1hr.csv) is the QA/QC and flagged meteorological data, i.e., output data from the QA/QC analysis. The last file (QAQC_Billy_Barr_2021-03-22.R) is a script written in R that implements the QA/QC and flagging process. The purpose of the CSV data files included in this package is to provide input and output files implemented in the R script.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2004

Increasing Access and Usability of Remote Sensing Data: The NASA Protected Area Archive

Although remote sensing data are now widely available, much of it at low or no-cost, many managers of protected conservation areas do not have the expertise or tools to view or analyze it. Thus access to it by the protected area management community is effectively blocked. The Protected Area Archive will increase access to remote sensing data by creating collections of satellite images of protected areas and packaging them with simple-to-use visualization and analytical tools. The user can easily locate the area and image of interest on a map, then display, roam, and zoom the image. A set of simple tools will be provided so the user can explore the data and employ it to assist in management and monitoring of their area. The 'Phase 1 ' version requires only a Windows-based computer and basic computer skills, and may be of particular help to protected area managers in developing countries.

remote sensing↗
DOE OSTI2016

A poly-epoxy surface explored by Hartree-Fock ΔSCF simulations of C1s XPS spectra

Whereas poly-epoxy polymers represent a class of materials with a wide range of applications, the structural disorder makes them difficult to model. In the present work, we use good experimental model samples in the sense that they are pure, fully polymerized, flat and smooth, defect-free, and suitable for ultrahigh vacuum x-ray photoelectron spectroscopy, XPS, experiments. In parallel, we perform Hartree-Fock, HF, calculations of the binding energies, BEs, of the C1s electrons in a model molecule composed of the two constituents of the poly-epoxy sample. These C1s BEs were determined using the HF ΔSCF method, which is known to yield accurate values, especially for the shifts of the BEs, ΔBEs. We demonstrate the benefits of combining rigorous theory with careful XPS measurements in order to obtain correct assignments of the C1s XPS spectra of the polymer sample. Both the relative binding energies—by the ΔSCF method—and relative intensities—in the sudden approximation, SA, are calculated. It results in an excellent match with the experimental spectra. We are able to identify 9 different chemical environments under the C1s peak, where an exclusively experimental work would have found only 3 contributions. In addition, we observe that some contributions are localized at discrete binding energies, whereas others allow a much wider range because of the variation of their second neighbor bound polarization. Therefore, HF-ΔSCF simulations significantly increase the spectral resolution of XPS and thus offer a new avenue for the exploration of the surface of polymers.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1973

Application of ERTS data to the detection of thin cirrus and clear air turbulence

The feasibility of detecting a thin cirrus and clear air turbulence from ERTS MSS data is explored. The result of analyses indicates that a thin cirrus not shown in conventional meteorological satellite picture can be revealed in ERTS MSS picture. It is also found that the core of jet stream can be located with high accuracy from ERTS pictures and the possible area of clear air turbulence can be predicted if the data of the quality of ERTS data are available in real time.

Tsuchiya, K.↗
NASA NTRS1973

Application of ERTS data to the detection of thin cirrus and clean air turbulence

The author has identified the following significant results. The feasibility of detecting a thin cirrus and clear air turbulence from ERTS-1 MSS data is explored. The result of analyses indicates that a thin cirrus not shown in a conventional meteorological satellite picture can be revealed in ERTS-1 MSS pictures. Is also found that the core of jet stream can be located with high accuracy from ERTS-1 pictures and the possible area of clear air turbulence can be predicted if the data of the quality of ERTS-1 data are available in real time.

Tsuchiya, K.↗
NASA NTRS1994

Basic Space Science; United Nations/European Space Agency Workshops for Developing Countries, 2nd, Bogota, Colombia, November 9-13, 1992

The conference primarily covered astrophysical and astronomical topics on stellar and solar modeling and processes, high magnetic field influence on stellar spectra, cosmological topics utilizing Cosmic Background Explorer (COBE) data and radioastronomic mapping as well as cosmic gravitational instability calculations, astrometry of open clusters amd solar gravitational focusing, extremely energetic gamma rays, interacting binaries, and balloon-borne instrumentation. Other papers proposed an active Search for Extraterrestrial Intelligence (SETI) communication scheme to neighboring solar-like systems and more direct involvement of and with the public in astronomy and space exploration projects.

Haubold, Hans J.↗
NASA NTRS1998

Remote Observing with the Keck Telescope Using the ACTS Satellite

As a technical demonstration project for the NASA Advanced Communications Technology Satellite (ACTS), we have implemented remote observing on the 10-meter Keck II telescope on Mauna Kea in Hawaii from the California Institute of Technology campus in Pasadena. The data connection consists of optical fiber networks in Hawaii and California, connecting the end-points to high data rate (HDR) ACTS satellite antennae at JPL in Pasadena and at the Tripler Army Medical Center in Honolulu. The terrestrial fiber networks run the asynchronous transfer mode (ATM) protocol at DS-3 (45 Mbit/sec) speeds, providing ample bandwidth to enable remote observing with a software environment identical to that used for on-site observing in Hawaii. This experiment has explored the data requirements of remote observing with a modern research telescope and large-format detector arrays. While the maximum burst data rates are lower than those required for many other applications (e.g., HDTV), the network reliability and data integrity requirements are critical. As we show in this report, the former issue particularly may be the greatest challenge for satellite networks for this class of application. We have also experimented with the portability of standard TCP/IP applications to satellite networks, demonstrating the need for alternative TCP congestion algorithms and minimization of bit error rates (BER). Reliability issues aside, we have demonstrated that true remote observing over high-speed networks provides several important advantages over standard observing paradigms. Technical advantages of the high-speed network access include more rapid download of data to a user's home institution and the opportunity for alternative communication facilities between members of an observing team, such as audio- and videoconferencing.

SATELLITE COMMUNICATIONS↗
DOE OSTI2013

Reassessment of True Core Collapse Differential Pressure Values for Filter Elements in Safety Critical Environments - 13076

As the areas of application for diverse filter types increases, the mechanics and material sciences associated with the hardware and its relationship with more and more arduous process environments becomes critical to the successful and reliable operation of the filtration equipment. Where the filter is the last safe barrier between the process and the life environment, structural integrity and reliability is paramount in both the validation and the ethical acceptability of the designed equipment. Core collapse is a key factor influencing filter element selection, and is an extremely complex issue with a number of variables and failure mechanisms. It is becoming clear that the theory behind core collapse calculations is not always supported with real tested data. In exploring this issue we have found that the calculation method is not always reflective of the true as tested collapse value, with the calculated values being typically in excess or even an order of magnitude higher than the tested values. The above claim is supported by a case study performed by the author, which disproves most of what was previously understood to be true. This paper also aims to explore the various failure mechanisms of different configurations of filter core, comparing calculated collapse values against real tested values, with a view to understanding a method of calculating their true collapse value. As the technology is advancing, and filter elements are being used in higher temperature, higher pressure, more radioactive and more chemically aggressive environments, confidence in core collapse values and data is crucial. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
NASA NTRS2008

Validation of a Remote Sensing Based Index of Forest Disturbance Using Streamwater Nitrogen Data

Vegetation disturbances are known to alter the functioning of forested ecosystems by contributing to export ('leakage') of dissolved nitrogen (N), typically nitrate-N, from watersheds that can contribute to acidification of acid-sensitive streams, leaching of base cations, and eutrophication of downstream receiving waters. Yet, at a landscape scale, direct evaluation of how disturbance is linked to spatial variability in N leakage is complicated by the fact that disturbances operate at different spatial scales, over different timescales, and at different intensities. In this paper we explore whether data from synoptic streamwater surveys conducted in an Appalachian oak-dominated forested river basin in western MD (USA) can be used to test and validate a scalable, synthetic, and integrative forest disturbance index (FDI) derived from Landsat imagery. In particular, we found support for the hypothesis that the interannual variation in spring baseflow total dissolved nitrogen (TDN) and nitrate-N concentrations measured at 35 randomly selected stream stations varied as a linear function of the change in FDI computed for the corresponding set of subwatersheds. Our results demonstrate that the combined effects of forest disturbances can be detected using synoptic water quality data. It appears that careful timing of the synoptic baseflow sampling under comparable phenological and hydrometeorological conditions increased our ability to identify a forest disturbance signal.

Eshleman, Keith N.↗
DOE OSTI2017

A Workflow for Visual Diagnostics of Binary Classifiers using Instance-Level Explanations

In this paper, we propose a visual analytics workflow to help data scientists explore, diagnose, and understand the decisions made by a binary classifier. The approach leverages “instance-level explanations”, measures of local feature relevance that explain single instances and uses them to build a set of visual representations that guide the users in their investigation. The workflow is based on three main visual representations and steps: one based on aggregate statistics to see how data distributes across correct or incorrect decisions; one based on explanations to understand which features are used to make these decisions; and one based on raw data, to derive insights on potential root causes for the observed patterns. The work is validated through a long-term collaboration with a group of healthcare professionals who used our method to make sense of machine learning models they developed. The case studies from this collaboration demonstrate that the proposed method helps experts derive useful knowledge about the model and the phenomena it describes and also generates useful hypotheses on how a model can be improved.

Krause, Josua↗
DOE OSTI2013

A NEW X-RAY VIEW OF THE SUPERNOVA REMNANT G272.2-3.2 AND ITS ENVIRONMENT

We present an analysis of Chandra X-Ray Observatory data detailing a Galactic supernova remnant, G272.2-3.2. A clear shell of emission is resolved as a series of filaments and knots around the entire rim of the remnant. Spectral analysis of these features show that they are consistent with shock heating of interstellar material in a clumpy medium. We contrast these X-ray images with 22 {mu}m Wide-field Infrared Survey Explorer (WISE) data to verify this interaction. Spatially separated from the shell we see a central diffuse region dominated by harder, hotter emission. Spatial spectroscopy shows a clear enhancement of metals consistent with a Type Ia explosion, namely S, Si, and Fe. We find no clear evidence for a compact object or pulsar wind nebula and argue for a Type Ia origin. Consideration of the ionization timescales suggest an age of 11,000 yr for G272.2-3.2.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

HIERARCHICAL FORMATION IN ACTION: CHARACTERIZING ACCELERATED GALAXY EVOLUTION IN COMPACT GROUPS USING WHOLE-SKY WISE DATA

Compact groups provide an environment to study the growth of galaxies amid multiple prolonged interactions. With their dense galaxy concentrations and relatively low velocity dispersions, compact groups mimic the conditions of hierarchical galaxy assembly. Compact group galaxies are known to show a bimodality in Spitzer IRAC infrared color space: galaxies are preferentially either quiescent with low specific star formation rates (SSFRs) or prolifically forming stars—galaxies with moderate levels of specific star formation are rare. Previous Spitzer IRAC studies identifying this “canyon” have been limited by small number statistics. We utilize whole-sky Wide-field Infrared Survey Explorer (WISE) data to study 163 compact groups, thereby tripling our previous sample and including more galaxies with intermediate mid-IR colors indicative of moderate SSFRs. We define a distinct WISE mid-IR color space (log[((f{sub 12})/(f{sub 4.6}))]) versus (log[((f{sub 22})/(f{sub 3.4}))]) that we use to identify canyon galaxies from the larger sample. We confirm that compact group galaxies show a bimodal distribution in the mid-infrared and identify 37 canyon galaxies with reliable photometry and intermediate mid-IR colors. Morphologically, we find that the canyon harbors a large population of both Sa–Sbc and E/S0 type galaxies, and that they fall on the optical red sequence rather than the green valley. Finally, we provide a catalog of WISE photometry for 567 of 652 galaxies selected from the sample of 163 compact groups.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1980

Energetic particle penetrations into the inner magnetosphere

The nose structures observed on 90-deg pitch angle ion spectrograms characteristic of energetic particle injection into the ring current region of the inner magnetosphere in the afternoon to midnight sector are examined in detail on the basis of Explorer 45 data. A statistical analysis of the time dependence of nose structures yields a highest probability of occurrence at around 2000 MLT, and most events are found to occur on successive passes. The appearance of nose events is also related to an enhancement or change in configuration of the geoelectric field which alters magnetospheric convection patterns to drive an ion front close to the earth, where it can be observed by Explorer 45. The observed characteristics of nose structures are interpreted in terms of adiabatic charged particle motions in the magnetosphere in a Volland-Stern convection electric field model, which is also applied to explain the energy spectra and dispersion in penetration distances of electrons and ions observed in the postmidnight to morning sectors.

Ejiri, M.↗
NASA NTRSDate not supplied

Web-based Visualization and Analytics of Petascale Data: Equity as a Tide that Lifts All Boats

Scientists generate petabytes of data daily to help uncover environmental trends or behaviors that are hard to predict. For example, understanding climate simulations based on the long-term average of temperature, precipitation, and other environmental variables is essential to predicting and establishing root causes of future undesirable scenarios and assessing possible mitigation strategies. While supercomputer centers provide a powerful infrastructure for generating petabytes of simulation output, accessing and analyzing these datasets interactively remains challenging on multiple fronts. This paper presents an approach to managing, visualizing, and analyzing petabytes of data within a browser on equipment ranging from the top NASA supercomputer to commodity hardware like a laptop. Our novel data fabric abstraction layer allows user-friendly querying of scientific information while hid-ing the complexities of dealing with file systems or cloud services.We also optimize network utilization while streaming from petas-cale repositories through state-of-the-art progressive compression algorithms. Based on this abstraction, we provide customizable dashboards that can be accessed from any device with any inter-net connection, enabling interactive visual analysis of vast amounts of data to a wide range of users - from top scientists with access to leadership-class computing environments to undergraduate students of disadvantaged backgrounds from minority-serving institutions. We focus on NASA’s use of petascale climate datasets as an example of particular societal impact and, therefore, a case where achieving equity in science participation is critical. We validate our approach by improving the ability of climate scientists to visually explore their data via two fully interactive dashboards. We further validate our approach by deploying the dashboards and simplified training materials in the classroom at a minority-serving institution.These dashboards, released in simplified form to the general public, contribute significantly to a broader push to democratize the access and use of climate data.

Data visualization↗