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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 397 records · Page 22
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Local and long-range atomic/magnetic structure of non-stoichiometric spinel iron oxide nanocrystallites

Spinel iron oxide nanoparticles of different mean sizes in the range 10–25 nm have been prepared by surfactant-free up-scalable near- and super-critical hydrothermal synthesis pathways and characterized using a wide range of advanced structural characterization methods to provide a highly detailed structural description. The atomic structure is examined by combined Rietveld analysis of synchrotron powder X-ray diffraction (PXRD) data and time-of-flight neutron powder-diffraction (NPD) data. The local atomic ordering is further analysed by pair distribution function (PDF) analysis of both X-ray and neutron total-scattering data. It is observed that a non-stoichiometric structural model based on a tetragonal γ-Fe 2 O 3 phase with vacancy ordering in the structure (space group P 4 3 2 1 2) yields the best fit to the PXRD and total-scattering data. Detailed peak-profile analysis reveals a shorter coherence length for the superstructure, which may be attributed to the vacancy-ordered domains being smaller than the size of the crystallites and/or the presence of anti-phase boundaries, faulting or other disorder effects. The intermediate stoichiometry between that of γ-Fe 2 O 3 and Fe 3 O 4 is confirmed by refinement of the Fe/O stoichiometry in the scattering data and quantitative analysis of Mössbauer spectra. The structural characterization is complemented by nano/micro-structural analysis using transmission electron microscopy (TEM), elemental mapping using scanning TEM, energy-dispersive X-ray spectroscopy and the measurement of macroscopic magnetic properties using vibrating sample magnetometry. Notably, no evidence is found of a Fe 3 O 4 /γ-Fe 2 O 3 core-shell nanostructure being present, which had previously been suggested for non-stoichiometric spinel iron oxide nanoparticles. Finally, the study is concluded using the magnetic PDF (mPDF) method to model the neutron total-scattering data and determine the local magnetic ordering and magnetic domain sizes in the iron oxide nanoparticles. The mPDF data analysis reveals ferrimagnetic collinear ordering of the spins in the structure and the magnetic domain sizes to be ∼60–70% of the total nanoparticle sizes. The present study is the first in which mPDF analysis has been applied to magnetic nanoparticles, establishing a successful precedent for future studies of magnetic nanoparticles using this technique.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2014

2D image of local density and magnetic fluctuations from line-integrated interferometry-polarimetry measurements

Combined polarimetry-interferometry capability permits simultaneous measurement of line-integrated density and Faraday effect with fast time response (∼1 μs) and high sensitivity. Faraday effect fluctuations with phase shift of order 0.05° associated with global tearing modes are resolved with an uncertainty ∼0.01°. For physics investigations, local density fluctuations are obtained by inverting the line-integrated interferometry data. The local magnetic and current density fluctuations are then reconstructed using a parameterized fit of the polarimetry data. Reconstructed 2D images of density and magnetic field fluctuations in a poloidal cross section exhibit significantly different spatial structure. Combined with their relative phase, the magnetic-fluctuation-induced particle transport flux and its spatial distribution are resolved.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Performance Evaluation of Vertical Federated Machine Learning Against Adversarial Threats on Wide-Area Control System: Preprint

Federated machine learning (FL) is gaining significant popularity to develop cybersecurity solutions in power grids because of its advanced capability to support decentralized data handing at local devices, its privacy preservation, and its low-bandwidth requirement. However, the evolving adversarial machine learning (AML) threats raise significant concerns for the cybersecurity of FL architectures. The FL-based split neural network (SplitNN) achieves high performance through the decentralized training of local neural network models while preserving data privacy across multiple entities. In this paper, we propose a methodology for evaluating the performance of a vertical FLbased anomaly detector against different types of AML attacks, including denial-of-service attacks, adversarial data injection attacks, and replay attacks on the trained local models deployed in the grid network. For a case study, we consider the modified IEEE 13-bus system, and we develop SplitNN-based binary and multiclass classification models to detect, locate, and identify different types of data integrity attacks on the volt-watt control with two pooling layers: maximum pooling and AvgPool. Our experimental results, computed through performance metrics, reveal that the severity of these AML attacks varies with the integrated pooling mechanism, the type of classification model, and the nature of the cyberattack. Further, the AML attacks negatively impacted the prediction time per sample for the pretrained SplitNN during the online testing.

adversarial threats↗
NASA NTRS1975

SEASAT economic assessment. Volume 9: Ports and harbors case study and generalization

This case study and generalization quantify benefits made possible through improved weather forecasting resulting from the integration of SEASAT data into local weather forecasts. The major source of avoidable economic losses to shipping from inadequate weather forecasting data is shown to be dependent on local precipitation forecasting. The ports of Philadelphia and Boston were selected for study.

Source record↗
DOE OSTI2025

LCLS Big Data Handling – How I Learned to Stop Worrying and Love the Data Deluge

Advanced data and computing systems are vital to Linac Coherent Light Source (LCLS) operations, data interpretation and overall scientific productivity. The transition to MHz-era operation marks a fundamental change in scale that requires new infrastructure and architectures to link LCLS to the required scale of computing needed for scientific interpretation. The LCLS-II Data System meets big data challenges by implementing configurable data reduction that can adapt to multiple science areas, real-time analysis frameworks to provide visualization and fast feedback, and the ability to transfer data to local and remote computational facilities for near real time analysis at the appropriate scale. Feature extracted information generated in the data analysis pipeline - at the edge, local compute, or remote High-Performance Computing (HPC) resources - can be used to steer experiments and inform user decisions during beam time. Artificial Intelligence and Machine Learning (AI/ML) techniques present new opportunities to rapidly analyse large datasets and direct experiments, but create new challenges in scaling, adaptability, complexity, and trustworthiness. We describe how the LCLS-II Data System architecture addresses its data-driven challenges in the areas of data acquisition, data processing, data management, and workflow orchestration to decrease the overall time-to-science and provide a vision for future developments.

artificial intelligence↗
DOE OSTI2017

Combinatorial appraisal of transition states for in situ pair distribution function analysis

In situ total scattering measurements are increasingly utilized to follow atomic and nanoscale structural details of phase transitions and other transient processes in materials. This contribution presents an automated method and associated tool set to analyze series of diffraction and pair distribution function data with a linear combination of end-member states. It is demonstrated that the combinatorial appraisal of transition states (CATS) software tracks phase changes, relative phase fractions and length scales of interest in experimental data series. Here it is further demonstrated, using a series of local structure data simulations, that the misfit of such a model can reveal details of phase aggregation and growth related to the pair distribution function's sensitivity to interphase correlations. CATS may be applied to quantitative evaluation of many transient processes, including amorphous-to-crystalline phase transitions, the evolution of solid-solution behaviors, the precipitation and growth of aggregates, and other atomic to nanoscale details of crystallization and phase transformation phenomena.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Riverbank temperatures on the Selawik River, Alaska 2010-2012, and Koyukuk River, Alaska June to July 2018.

The data package includes temperature measurements from riverbanks along the Selawik and Koyukuk Rivers in northwest Alaska. The Selawik River data also includes meteorological data collected locally and the Koyukuk River includes bulk density and ice content data from the riverbanks. The Selawik River data was collected between 2010 and 2013 with meteorological data collected for the entire time period and riverbank temperatures collected in shorter time intervals between 2010 to 2012. All of the Selawik River data were collected a single river bend. The Koyukuk River temperature data was collected from late June to early July 2018 at a total of five locations on three riverbanks. Ice content measurements on the Koyukuk were made at five riverbank locations. The data collection on both rivers was done in support of studies on the influence of permafrost on riverbank erosion. The temperature data was collected to monitor the thermal conditions of the river banks both seasonally and during periods of erosion. The ice content of the banks was measured to better understand how bank erosion rates are influenced by ice in the frozen riverbanks.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1976

A high speed imaging system for nuclear diagnostics

A high speed imaging system based on state-of-the-art photosensor arrays was designed for use in nuclear diagnostics. The system is comprised of a front end rapid scan solid state camera, a high speed digitizer, and a PCM line driver in a downhole package and a memory buffer system in an uphole trailer. The downhole camera takes a snapshot of a nuclear device created flux stream, digitizes the image and transmits it to the uphole memory system before being destroyed. The memory system performs two functions: it retains the data for local display and processing by a microprocessor, and it buffers the data for retransmission at slower rates to a computational facility. In the talk, the impetus for such a system as well as its operation was discussed, along with systems under development which incorporate higher data rates and more resolution.

Eyer, H. H.↗
DOE OSTI2016

Argonne News Brief: First Sensors for Chicago’s “City Fitness Tracker”

This week in Chicago, the Array of Things team installed its first 50 nodes on city streets to kick off the groundbreaking urban sensing project. Array of Things is designed as a “fitness tracker” for the city, collecting new streams of data on Chicago’s environment, infrastructure, and activity. This hyper-local, open data can help researchers, city officials, and software developers study and address critical city challenges, such as preventing urban flooding, improving traffic safety and air quality, and assessing the nature and impact of climate change.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2020

Architecture of a catalytically active homotrimeric plant cellulose synthase complex

Cellulose is an essential plant cell wall component and represents the most abundant biopolymer on Earth. Supramolecular plant cellulose synthase complexes organize multiple linear glucose polymers into microfibrils as load-bearing wall components. We determined the structure of a poplar cellulose synthase CesA homotrimer that suggests a molecular basis for cellulose microfibril formation. This complex, stabilized by cytosolic plant-conserved regions and helical exchange within the transmembrane segments, forms three channels occupied by nascent cellulose polymers. Secretion steers the polymers toward a common exit point, which could facilitate protofibril formation. CesA’s N-terminal domains assemble into a cytosolic stalk that interacts with a microtubule-tethering protein and may thus be involved in CesA localization. Here, our data suggest how cellulose synthase complexes assemble and provide the molecular basis for plant cell wall engineering.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRSDate not supplied

Treating gridded geospatial data as point data to simplify analytics

Gridded geospatial remote sensing (satellite) data has traditionally been stored in file-based multidimensional arrays to preserve the locality of data. Measurements from locations that are physically next to each other on earth remain next to each other in the arrays. Maintaining this locality is useful when running calculations like reprojection, but unnecessary for many other calculations. This talk will go through a real world example of a tool redesign at the Goddard Earth Sciences Data and Information Services Center (GES DISC), showing the advantages of using the data frame model for calculating summary statistics, where measurement proximity is unimportant.

Analysis-ready data↗
DOE OSTI2022

Accelerating shared file checkpoint with local burst buffers

A data management system and method for accelerating shared file checkpointing. Written application data is aggregated in an application data file created in a local burst buffer memory at a compute node, and an associated data mapping built index to maintain information related to the offsets into a shared file at which segments of the application data is to be stored in a parallel file system, and where in the buffer those segments are located. The node asynchronously transfers a data file containing the application data and the associated data mapping index to a file server for shared file storage. The data management system and method further accelerates shared file checkpointing in which a shared file, together with a map file that specifies how the shared file is to be distributed, is asynchronously transferred to local burst buffer memories at the nodes to accelerate reading of the shared file.

Gooding, Thomas↗
NASA NTRS1986

University participation via UNIDATA, part 2

The University Corporation for Atmospheric Research (UCAR) is presently completing UNIDATA, Phase II, considered to be the design phase of the UNIDATA Project. The four major components of the UNIDATA System are: (1) global services which access is provided, (2) long haul communication for providing that access, (3) local services for providing access and local management of acquired data, and (4) local interactive processing and graphical display. Each component is described in detail with linkages among the components elucidated. Within this framework, access to the PCDS is discussed. It is pointed out that access to the PCDS could occur via general purpose computer-to-computer communications providing remote log on to the system. The UNIDATA System could also be used to transfer information from the PCDS, provided the appropriate software is available to receive the data. Both of these scenarios require agreements on the access protocols and appropriate physical connections. Universities' needs for weather information on a near real-time basis, and UNIDATA has already established a satellite broadcast data service for this purpose.

Fulker, D. W.↗
NASA NTRS1988

Interpolation methods for shaped reflector analysis

The diffraction analysis of reflector surfaces which are described only at a discrete set of locations usually leads to the requirement of an interpolation to determine the surface characteristics over a continuum of locations. Two methods of interpolation, the global and the local methods, are presented. The global interpolation representation is a closed-form or series expression valid over the entire surface. The coefficients of a series expression are found by an integration of all of the raw data. Since the number of coefficients used to describe the surface is much smaller than the number of raw data points, the integration effectively provides a smoothing of the raw data. The local interpolation provides a closed-form expression for only a small area of the reflector surface. The subreflector is divided into sectors each of which has constant discretized data. Each area segment is then locally described by a two-dimensional quadratic surface. The second derivative data give the desired smoothed values.

Galindo-Israel, Victor↗
DOE OSTI2020

Detailed space–time variations of the seismic response of the shallow crust to small earthquakes from analysis of dense array data

SUMMARY We compute high-resolution space–time variations of subsurface seismic properties from autocorrelation functions (ACF’s) of noise and local earthquakes, recorded by the Sage Brush Flat dense array deployed around the Clark branch of the San Jacinto fault. The resolved temporal changes are referred to as apparent velocity changes because they reflect both nonlinear response and variations of material properties such as cracking and damage. Apparent velocity changes are estimated at four frequency bands (10–15, 10–20, 15–30 and 20–40 Hz) for two local earthquake data sets. In one analysis, ACF’s from P- and S-wave windows of 31 small events with magnitudes below 3.1 are used to compute the apparent velocity variations with respect to the mean ACF of each phase, and we also use the mean ACF of noise data as reference to estimate the changes. In a further analysis, the temporal evolution of properties is computed using moving time windows in continuous waveform over one-hour long data with noise and earthquake signals. The apparent velocity changes and recovery times are frequency dependent and present a strong spatial variability across the array. The resolved changes are larger and recovery time shorter with data associated with higher frequencies. At frequencies larger than 15 Hz, and using the mean ACF of noise data as a reference, the apparent average velocity changes across the array during the passage of the P and S waves from the small local events are 2.5 per cent and 6 per cent, respectively. The apparent velocity changes decrease by one order of magnitude when the earthquake data are used as a reference. The relatively large changes in response to very low ground motion have important implications on nonlinear processes involving degradation and healing of the subsurface material during common earthquake shaking.

Geochemistry & Geophysics↗
DOE OSTI2016

Contaminant point source localization error estimates as functions of data quantity and model quality

We develop empirically-grounded error envelopes for localization of a point contamination release event in the saturated zone of a previously uncharacterized heterogeneous aquifer into which a number of plume-intercepting wells have been drilled. We assume that flow direction in the aquifer is known exactly and velocity is known to within a factor of two of our best guess from well observations prior to source identification. Other aquifer and source parameters must be estimated by interpretation of well breakthrough data via the advection-dispersion equation. We employ high performance computing to generate numerous random realizations of aquifer parameters and well locations, simulate well breakthrough data, and then employ unsupervised machine optimization techniques to estimate the most likely spatial (or space-time) location of the source. Tabulating the accuracy of these estimates from the multiple realizations, we relate the size of 90% and 95% confidence envelopes to the data quantity (number of wells) and model quality (fidelity of ADE interpretation model to actual concentrations in a heterogeneous aquifer with channelized flow). We find that for purely spatial localization of the contaminant source, increased data quantities can make up for reduced model quality. For space-time localization, we find similar qualitative behavior, but significantly degraded spatial localization reliability and less improvement from extra data collection. Since the space-time source localization problem is much more challenging, we also tried a multiple-initial-guess optimization strategy. Furthermore, this greatly enhanced performance, but gains from additional data collection remained limited.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Soil Water Percolation Flux, April 2017 to March 2019, BR-Ma2, Manaus

Soil water percolation flux measurements derived from six passive wick flux meters across three topographic positions (valley, slope and plateau). Data has been processed to compute the mean for each topographic position where two flux meters were installed at each topographic position. Missing data represented a few percent of the total data set and were filled using two approaches. In the event one of the flux meters malfunctioned, we used data from the other sensor from the same topographic position without averaging. When both sensors were not working, such as during the period from September to October 2017 for the slope and valley and July 2018 for the plateau, data was filled using a nonlinear regression model that was based on local precipitation data and coefficients that were empirically derived for each topographic position. The metadata tab included in the .csv has additional information on locations where the sensors were installed, and other installation/maintenance details. Contact ksolander@lanl.gov if you need to use this dataset for additional information.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1980

Equations for determining aircraft motions for accident data

Procedures for determining a comprehensive accident scenario from a limited data set are reported. The analysis techniques accept and process data from either an Air Traffic Control radar tracking system or a foil flight data recorder. Local meteorological information at the time of the accident and aircraft performance data are also utilized. Equations for the desired aircraft motions and forces are given in terms of elements of the measurement set and certain of their time derivatives. The principal assumption made is that aircraft side force and side-slip angle are negligible. An estimation procedure is outlined for use with each data source. For the foil case, a discussion of exploiting measurement redundancy is given. Since either formulation requires estimates of measurement time derivatives, an algorithm for least squares smoothing is provided.

Bach, R. E., Jr.↗