SEARCH · Search NASA

Results for “FIPS”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 73 records · Page 4

All sources NASA NTRS DOE OSTI

NASA NTRS2000

Does UV CETI Suffer from the MAD Syndrome?

Data have been reduced and partially analyzed and models have been fitted. ASCA data indicate a metal-poor corona, with metals down by a factor of 3 or more relative to the photospheric values. EUVE data show a FIP effect, which is expected if the metals are enhanced rather than depleted. An absolute measure of the metal abundance has not yet been performed for the EUVE data. Either the FIP effect is in operation in the presence of a global depletion of metals, or the ASCA analysis is giving the wrong answer. The latter could be the case if the plasma models applied are incomplete. Further investigation into this is warranted prior to publication.

Drake, Jeremy↗

NASA NTRS2002

Chemical Compositions and Abundance Anomalies in Stellar Coronae ADP99

We have been investigating different statistical methods for analysing the metal abundances of sources with low S/N. A Bayesian technique has been developed that determines the most probable line-to-continuum ratio in the source, thereby leading to the metallicity. This method is a promising approach with which to mine the ASCA archive. Some of this work has now been published in conference proceedings. The flavour of the project has changed very slightly in the last year owing to the increasing availability of several good quality Chandra HETG and LETG spectra for stars for which we had reduced and analysed ASCA data. The Chandra grating spectra in principle provide a means of calibrating the results from the low resolution ASCA spectra and we have started some work toward that goal. One paper concerning abundance ratios in active stars is appearing shortly in conference proceedings and is being readied for publication in a main-stream astrophysical journal. This paper demonstrates for the first time that abundance anomalies cannot be categorized simply in terms of First Ionization Potential (FIP) or inverse-FIP based effects. Different Ne enhancements are found in different star types but a link between enhancement factors and stellar properties is not obvious. The publication noted as in preparation in an earlier report, finding strong Ne enhancements in active stars, is now published. These results will again be used to "calibrate" low resolution results for which line ratio techniques cannot be employed.

Drake, Jeremy↗

NASA NTRS2003

Temporal Evolution of a Streamer Complex: Coronal and In-Situ Plasma Parameters

In this paper we report on observations acquired by the Ultra Violet Coronagraph Spectrometer (UVCS) aboard the Solar and Heliospheric Observatory (SOHO), from 10 to 17 June 2000, at the time of a SOHO-Sun-Ulysses quadrature. UVCS took data at 1.6 and 1.9 solar radii, with a slit normal to the solar radius and centered along the radial to Ulysses. A streamer complex was sampled by UVCS, throughout the quadrature campaign, giving us the opportunity to derive plasma parameters in different streamers, and to compare them with plasma properties measured in situ. Large Angle Spectroscopic Coronagraph (LASCO) images above 2 solar radii helped us understand the temporal evolution of the streamer complex. We derive densities, temperatures and elemental abundances in two streamers, which have different temperatures and element abundances. In spite of these differences, both structures have the same FIP bias. The Fe/O ratio, which may be considered a proxy for the FIP effect, was measured (\it in situ} by the Solar Wind Ion Composition Spectrometer (SWICS) aboard the Ulysses spacecraft. Values of Fe/O measured in the corona, at the sites where in situ plasma originated, agree with in situ Fe/O values.

Bemporad, A.↗

NASA NTRS2005

Chemical Compositions and Anomalies in Stellar Coronae

In summary, as the papers cited here and in earlier reports demonstrate, this award has enabled us to obtain a fairly good picture of the abundance anomalies in stellar coronae. The "inverse FIP" effect in very active stars has now been fleshed out as a more complex anomaly depending on FIP, whereas before it appeared only in terms of a general metal paucity, the recent solar abundance assessment of Asplund et a1 will, if correct, challenge some of the older interpretations of coronal abundance anomalies since they imply quite different relative abundances of CNO compared with Fe, Mg and Si. Further investigations have been in into the possibility of modeling some of the recent coronal abundance anomaly results in terms of Alfven wave-driven separation of neutrals and ions in the upper chromosphere. This work still remains in the seed stage, and future funding from a different program will be requested to pursue it further.

Drake, Jeremy↗

NASA NTRS2016

Correlation of Coronal Plasma Properties and Solar Magnetic Field in a Decaying Active Region

We present the analysis of a decaying active region observed by the EUV Imaging Spectrometer on Hinode during 2009 December 7-11. We investigated the temporal evolution of its structure exhibited by plasma at temperatures from 300,000 to 2.8 million degrees, and derived the electron density, differential emission measure, effective electron temperature, and elemental abundance ratios of Si/S and Fe/S (as a measure of the First Ionization Potential (FIP) Effect). We compared these coronal properties to the temporal evolution of the photospheric magnetic field strength obtained from the Solar and Heliospheric Observatory Michelson Doppler Imager magnetograms. We find that, while these coronal properties all decreased with time during this decay phase, the largest change was at plasma above 1.5 million degrees. The photospheric magnetic field strength also decreased with time but mainly for field strengths lower than about 70 Gauss. The effective electron temperature and the FIP bias seem to reach a basal state (at 1.5 x 10(exp 6) K and 1.5, respectively) into the quiet Sun when the mean photospheric magnetic field (excluding all areas <10 G) weakened to below 35 G, while the electron density continued to decrease with the weakening field. These physical properties are all positively correlated with each other and the correlation is the strongest in the high-temperature plasma. Such correlation properties should be considered in the quest for our understanding of how the corona is heated. The variations in the elemental abundance should especially be considered together with the electron temperature and density.

Sun: abundances↗

NASA NTRS2018

Element Abundance Ratios in the Quiet Sun Transition Region

Element abundance ratios of magnesium to neon (Mg/Ne) and neon to oxygen (Ne/O) in the transition region of the quiet Sun have been derived by re-assessing previously published data from the Coronal Diagnostic Spectrometer on board the Solar and Heliospheric Observatory in the light of new atomic data. The quiet Sun Mg/Ne ratio is important for assessing the effect of magnetic activity on the mechanism of the first ionization potential (FIP) effect, while the Ne/O ratio can be used to infer the solar photospheric abundance of neon, which cannot be measured directly. The average Mg/Ne ratio is found to be 0.52+/-0.11, which applies over the temperature region 0.2-0.7MK, and is consistent with the earlier study. The Ne/O ratio is, however, about 40%larger, taking the value 0.24+/-0.05 that applies to the temperature range 0.08-0.40MK. The increase is mostly due to changes in ionization and recombination rates that affect the equilibrium ionization balance. If the Ne/O ratio is interpreted as reflecting the photospheric ratio, then the photospheric neon abundance is 8.08+/-0.09 or 8.15+/-0.10 (on a logarithmic scale for which hydrogen is 12), according to whether the oxygen abundances of M.Asplund et al. or E.Caffau et al. are used. The updated photospheric neon abundance implies a Mg/Ne FIP bias for the quiet Sun of 1.6+/-0.6.

transition region↗

NASA NTRS2021

Simultaneous Multiwavelength Flare Observations of EV Lacertae

We present the first results of our ongoing project conducting simultaneous multiwavelength observations of flares on nearby active M dwarfs. We acquired data of the nearby dM3.5e star EV Lac using five different observatories: NASA's Transiting Exoplanet Survey Satellite (TESS), NASA's Neil Gehrels Swift Observatory (Swift), NASA's Neutron Interior Composition Explorer (NICER), the University of Hawaii 2.2-meter telescope (UH88), and the Las Cumbres Observatory Global Telescope (LCOGT) Network. During the ∼25 days of TESS observations, we acquired three simultaneous UV/X-ray observations using Swift that total ∼18 ks, 21 simultaneous epochs totaling ∼98 ks of X-ray data using NICER, one observation (∼3 hr) with UH88, and one observation (∼3 hr) with LCOGT. We identified 56 flares in the TESS light curve with estimated energies in the range log E(T) (erg) = (30.5–33.2), nine flares in the Swift UVM2 light curve with estimated energies in the range log E(UV) (erg) = (29.3–31.1), 14 flares in the NICER light curve with estimated minimum energies in the range log E(N) (erg) = (30.5–32.3), and 1 flare in the LCOGT light curve with log E(L) (erg) = 31.6. We find that the flare frequency distributions (FFDs) of TESS and NICER flares have comparable slopes, β(T) = −0.67 ± 0.09 and β(N) = − 0.65 ± 0.19, and the FFD of UVOT flares has a shallower slope (β(U) = −0.38 ± 0.13). Furthermore, we do not find conclusive evidence for either the first ionization potential (FIP) or the inverse FIP effect during coronal flares on EV Lac.

Rishi R. Paudel↗

NASA NTRS2024

Exploring the Role of Type-II Residual Stresses in A Laser Powder Bed Fusion Nickel-Based Superalloy Using Measurement and Modeling

Far-field high-energy X-ray diffraction microscopy (ff-HEDM) and the crystal plasticity finite element method (CPFEM) are used to investigate the role of grain-scale (Type-II) residual stresses on the fatigue life of additively manufactured (AM) Inconel alloy 625 (IN-625). Grain-averaged orientations, centroids, and residual elastic strain tensors from ff-HEDM data are used to instantiate a crystal plasticity model to simulate the effect of residual stresses at the grain scale. Simulation results indicate that the presence of tensile residual strains increase stress localization and heterogeneity within grains, triggering an earlier onset of plasticity. A microscale fatigue indicator parameter (FIP) is computed to model the impact of these residual strains on the cycles to fatigue crack nucleation. The crack nucleation model, based on the computed FIPs, predicts a significant reduction in the number of cycles for fatigue crack nucleation for mid- and high-cycle fatigue due to the residual strain induced localization, while the residual strains have minimal impact on low-cycle fatigue life.

Inconel↗

DOE OSTI2025

TRIM: AI Guided Random Number Generation for Resource-Constrained IoT Systems

Random numbers often serve as the backbone for many security solutions in diverse domains such as cryptography, side channel leakage prevention, and moving target defense. However, generating true random numbers requires a physical source of entropy (e.g. hardware, quantum, environmental phenomenon) making it difficult to realize at a large scale and at a low cost. On the flip side, pseudorandom number generators (easy to implement) following a specific distribution (e.g. Gaussian) can be easily compromised given a sufficient amount of traces. In this work, we have developed a machine learning-guided generative approach that can be used to create portable, resource-efficient, and cost-effective random number generators with high throughput and true randomness characteristics. We implement the proposed approach as a highly parameterized framework and perform extensive evaluation for different settings. The framework was able to learn from true random sources such as irrational numbers and environmental audio noise and imitate those sources towards generating new good quality random numbers on demand. We have generated more than 1 billion bits and observed robust performance in terms of true randomness metrics obtained from NIST SP 800-22 and FIPS 140-1 randomness test suites achieving a throughput of up to 142.85 Mbps. Compared to the state-of-the-art (SOTA) technique, the iso-cost setup of our framework can achieve more than 500 Mbps in a distributed setting. We have evaluated the efficacy of running the true randomness imitation AI models on target edge devices such as Raspberry Pi 4 (Model B), Nvidia Jetson Nano, Nvidia Jetson Orin Nano and Nvidia Jetson Xavier. We have also looked at the security of the TRIM framework itself against different adversarial threat models.

Cybersecurity↗

DOE OSTI2020

Magnetotactic Bacteria Accumulate a Large Pool of Iron Distinct from Their Magnetite Crystals

ABSTRACT Magnetotactic bacteria (MTB) are ubiquitous aquatic microorganisms that form intracellular nanoparticles of magnetite (Fe 3 O 4 ) or greigite (Fe 3 S 4 ) in a genetically controlled manner. Magnetite and greigite synthesis requires MTB to transport a large amount of iron from the environment. Most intracellular iron was proposed to be contained within the crystals. However, recent mass spectrometry studies suggest that MTB may contain a large amount of iron that is not precipitated in crystals. Here, we attempted to resolve these discrepancies by performing chemical and magnetic assays to quantify the different iron pools in the magnetite-forming strain Magnetospirillum magneticum AMB-1, as well as in mutant strains showing defects in crystal precipitation, cultivated at various iron concentrations. All results show that magnetite represents at most 30% of the total intracellular iron under our experimental conditions and even less in the mutant strains. We further examined the iron speciation and subcellular localization in AMB-1 using the fluorescent indicator FIP-1, which was designed for the detection of labile Fe(II). Staining with this probe suggests that unmineralized reduced iron is found in the cytoplasm and associated with magnetosomes. Our results demonstrate that, under our experimental conditions, AMB-1 is able to accumulate a large pool of iron distinct from magnetite. Finally, we discuss the biochemical and geochemical implications of these results. IMPORTANCE Magnetotactic bacteria (MTB) produce iron-based intracellular magnetic crystals. They represent a model system for studying iron homeostasis and biomineralization in microorganisms. MTB sequester a large amount of iron in their crystals and have thus been proposed to significantly impact the iron biogeochemical cycle. Several studies proposed that MTB could also accumulate iron in a reservoir distinct from their crystals. Here, we present a chemical and magnetic methodology for quantifying the iron pools in the magnetotactic strain AMB-1. Results showed that most iron is not contained in crystals. We then adapted protocols for the fluorescent Fe(II) detection in bacteria and showed that iron could be detected outside crystals using fluorescence assays. This work suggests a more complex picture for iron homeostasis in MTB than previously thought. Because iron speciation controls its fate in the environment, our results also provide important insights into the geochemical impact of MTB.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

EAGLE-I Power Outage Data 2023

The provided EAGLE-I historic dataset includes 1 year of power outage information at the county level for 2023 at 15-minute intervals collected by the EAGLE-I program at ORNL. The data has been collected from utility's public outage maps using an ETL process. The dataset details FIPS code, county name, state name, total number of customers without power, and a date/timestamp. Also included is the EAGLE-I coverage of each state for each year. For detailed metadata, refer to the metadata DOI.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2025

EAGLE-I Power Outage Data 2024

The provided EAGLE-I historic dataset includes power outage information at the county level for 2024 at 15-minute intervals collected by the EAGLE-I program at ORNL. The data has been collected from utility's public outage maps using an ETL process. The dataset details FIPS code, county name, state name, total number of customers without power, total customers per county, and a date/timestamp. For detailed metadata, refer to the linked metadata DOI.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2023

EAGLE-I Power Outage Data 2014 - 2022

The provided EAGLE-I historic dataset includes eight years of power outage information at the county level from 2014 to 2022 at 15-minute intervals collected by the EAGLE-I program at ORNL. The data has been collected from utility's public outage maps using an ETL process. The dataset details FIPS code, county name, state name, total number of customers without power, and a date/timestamp. Also included is the EAGLE-I coverage of each state for each year. For detailed metadata, refer to the metadata DOI.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2026

EAGLE-I County Customer Dataset Fall 2025

This dataset provides a combination of modeled and collected county-level electric customer counts derived from 2023 EIA-861 utility customer data, 2021 HIFLD electric retail service territory boundaries, 2021 LandScan population estimates, and 2025 EAGLE-I customer outages. The dataset details county FIPS code, number of customers, and customer type (modeled, collected, mixed). Outage data in included for all 50 U.S. states, Puerto Rico, and the District of Columbia (excluding other U.S. territories).

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2021

Online Optimization of NSLS-II Dynamic Aperture and Injection Transient (Facility Improvement Project)

The Facility Improvement Project (FIP) “Methods of online optimization of NSLS-II storage ring concurrent with user operations” proposed and approved in 2018 is now complete. The first goal is the online optimization of nonlinear beam dynamics to increase the beam lifetime and injection efficiency. We have developed a model-independent optimization technique using advanced algorithms. Using this technique, we increased the NSLS-II dynamic aperture by 20% and reduced the amplitude-dependent tune shift by a factor of two. We applied sextupole optimization to the new high-chromaticity lattice, which has been developed to improve the beam stability and to increase the single-bunch beam intensity. We were able to double the injection efficiency and exceed 90%. The second goal of this project is to provide the top-off injection with minimized perturbations of the beamline user operations. To achieve the transparent injection, we optimize the matching of four storage ring injection kickers reducing the perturbation of the stored beam orbit. The first application of the online optimization resulted in a reduction of the amplitude of residual beam oscillation by a factor of six, from 1300 μm down to 200 μm. Further improvement was limited by the timing jitter of the trigger boards. Then, we replaced all trigger boards with a new design and reduced the timing jitter by a factor of five, from 5 ns down to 1 ns. This upgrade resulted in the injection transient reduction from 200 μm to 120 μm. To optimize the full set of kicker parameters, including the trigger timing, amplitude, and pulse width, we upgraded all kicker power supplies with the capability of tunable waveform width. As a result, we have reduced the injection transient to the limit of 60 μm.

43 PARTICLE ACCELERATORS↗

DOE OSTI2025

Enterprise Artificial Intelligence Strategy for Los Alamos National Laboratory

In the 1984 martial arts drama film, The Karate Kid, a young Daniel LaRusso is unexpectedly placed in an adversarial environment unable to eYectively adapt to a series of new threats and limitations. Fortunately for the main character, once placed under the tutelage of a Mr. Miyagi, he finds resiliency not through the adoption of new tools, but a re-focused set of fundamentals. Much in the same way that Daniel learns waxing on and buYing oY car wax by hand has rewards for Karate, LANL is choosing the harder path of self-hosting Large Language Models (LLMs) for enterprise use instead of only relying on buying access to a hosted AI service like Azure’s OpenAI Application Programming Interface (API). We also are not willing to wait for software-as-a-service (SAAS) AI services to meet us where we need to be from a FedRAMP accreditation standpoint. Our operations regularly depend on access at CUI, UCNI, ITAR and other FIPS-199 moderate-impact data levels and hosting our own services gives us the right security and compliance posture to be useful across the broad range of our work at LANL. With the rise in threats to critical infrastructure, cloud service providers (CSPs), and supply chain attacks from both state and non-state actors, we are not placing the bet that SAAS hosted AI services will be available when we need them. Should a major event occur, we do not want our staY and operations left without a pathway for us to fix the problem and resume the use of AI tools.

42 ENGINEERING↗

DOE OSTI2025

Front-of-Meter Model Results

These files contains aggregations of key variables from the NREL Distributed Wind Futures Study using full parcel level data. These variables describe total technical and economic potential for distributed wind turbine deployment. Aggregations are available at the (1) county, (2) zipcode (zip code tabulation area or zcta), and (3) US Census block group level. Each scenario is coded with the scenario name (e.g., baseline) and year (e.g., 2022). Those files postfixed with 'econpot' contain results for only those parcels that are economically viable while the files postfixed with 'techpot' include results for all parcels that are technically feasible. Hence these correspond to technoeconomic and technical potential respectively. The data are available as CSV or Geopackage. Columns in the files are as follows: * geoid: geographic identifier (FIPS code or similar) * min_techpot_sum_kw: technical potential for all parcels in kW using turbines downsized to demand when appropriate * max_techpot_sum_kw: technical potential for all parcels in kW without downsizing turbines * aep_sum_kwh: annual energy production estimate in kWh * cf_mean_ratio: mean capacity factor * lcoe_mean_cents_per_kwh: mean levelized cost of energy for parcels in geography in cents per kWh * lcoe_std_cents_per_kwh: standard deviation of the above * parcel_area_sum_acres: total area of viable parcels in acres * n_turbines: number of cited turbines (one per viable parcel currently) Note: These are preliminary results from the full-parcel 2024 update of the Distributed Wind Energy Futures study. Please take care when making use of the data, and feel free to contact the team with any questions. Full documentation in support of these data is in progress and will follow.

17 WIND ENERGY↗

DOE OSTI2025

Behind-the-Meter Model Results

17 WIND ENERGY↗