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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 1,189 records · Page 66
All sourcesNASA NTRSDOE OSTI
NASA NTRS2017

A New Non-Resonant Laser-Induced Fluorescence Instrument for the Airborne in Situ Measurement of Formaldehyde

A new in situ instrument for gas-phase formaldehyde (HCHO), COmpact Formaldehyde FluorescencE Experiment (COFFEE), is presented. COFFEE utilizes nonresonant laser-induced fluorescence (NR-LIF) to measure HCHO, with 300 mW of 40 kHz 355 nm laser output exciting multiple HCHO absorption features. The resulting HCHO fluorescence is collected at 5 ns resolution, and the fluorescence time profile is fit to yield the ambient HCHO mixing ratio. Typical 1 sigma precision at approximately 0 pptv HCHO is 150 pptv for 1 s data. The compact instrument was designed to operate with minimal in-flight operator interaction and infrequent maintenance (1-2 times per year). COFFEE fits in the wing pod of the Alpha Jet stationed at the NASA Ames Research Center and has successfully collected HCHO data on 27 flights through 2017 March. The frequent flights, combined with a potentially long-term data set, makes the Alpha Jet a promising platform for validation of satellite-based column HCHO.

Nonresonant laser-induced fluorescenc↗
DOE OSTI2024

The Number and Pattern of Viral Genomic Reassortments are not Necessarily Identifiable from Segment Trees

Reassortment is an evolutionary process common in viruses with segmented genomes. These viruses can swap whole genomic segments during cellular co-infection, giving rise to novel progeny formed from the mixture of parental segments. Since large-scale genome rearrangements have the potential to generate new phenotypes, reassortment is important to both evolutionary biology and public health research. However, statistical inference of the pattern of reassortment events from phylogenetic data is exceptionally difficult, potentially involving inference of general graphs in which individual segment trees are embedded. In this paper, we argue that, in general, the number and pattern of reassortment events are not identifiable from segment trees alone, even with theoretically ideal data. We call this fact the fundamental problem of reassortment, which we illustrate using the concept of the “first-infection tree,” a potentially counterfactual genealogy that would have been observed in the segment trees had no reassortment occurred. Further, we illustrate four additional problems that can arise logically in the inference of reassortment events and show, using simulated data, that these problems are not rare and can potentially distort our observation of reassortment even in small data sets. Finally, we discuss how existing methods can be augmented or adapted to account for not only the fundamental problem of reassortment, but also the four additional situations that can complicate the inference of reassortment.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Hydropower potential derived from streamflow extremes for Alaska, USA

Alaska is an expansive region known for its abundant natural resources, including thousands of miles of streams and rivers. These rivers represent potential opportunities for future hydropower development that could provide reliable energy supply for local communities. There is limited long-term high temporal resolution streamflow data available for the region, making data-driven estimates of potential hydropower and its variability across the state challenging. This study provides a novel data-driven approach for hydropower capacity estimation across Alaska. We use supervised machine learning to develop a relationship between the daily and peak flow duration curves in order to augment the size of our dataset from 44 sites to 67 sites. We perform a stochastic hydropower estimation across the 67 sites and identify approximately 1000 MW of total potential hydropower capacity distributed across these sites. Our study provides the first step towards more comprehensive hydropower estimation for this critical region, highlighting the need for future work integrating high-resolution spatial data, community needs, and economic constraints in estimates of potential hydropower development in Alaska.

Hydropower↗
NASA NTRS1984

Estimates of the generation of available potential energy by infrared radiation

Data from the National Meteorological Center and net outgoing infrared radiation (IR) data measured by NOAA satellites for January 1977 are used to compute estimates of the spectral and spatial contributions to the net generation of available potential energy in the Northern Hemisphere due to infrared radiation. Although these estimates are necessarily crude, the results obtained indicate that IR causes destruction of both zonal and eddy available potential energy. The contributions from midlatitudes to the zonal and eddy generation are about -5.0 W/sq m and about -0.6 W/sq m, respectively. The eddy generation is due almost entirely to stationary wavenumbers one and two. Comparison with earlier studies and computation of Newtonian cooling coefficients are discussed.

Hansen, A. R.↗
DOE OSTI2023

Data Validation Experiments with a Computer-Generated Imagery Dataset for International Nuclear Safeguards

Computer vision models have great potential as tools for international nuclear safeguards verification activities, but off-the-shelf models require fine-tuning through transfer learning to detect relevant objects. Because open-source examples of safeguards-relevant objects are rare, and to evaluate the potential of synthetic training data for computer vision, we present the Limbo dataset. Limbo includes both real and computer-generated images of uranium hexafluoride containers for training computer vision models. Here, we generated these images iteratively based on results from data validation experiments that are detailed here. The findings from these experiments are applicable both for the safeguards community and the broader community of computer vision research using synthetic data.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2016

DEVELOPMENT OF INTERATOMIC POTENTIALS IN TUNGSTEN-RHENIUM SYSTEMS

Reference data are generated using the ab initio method to fit interatomic potentials for the W-Re system. The reference data include single phases of W and Re, strained structures, slabs, systems containing several concentrations of vacancies, systems containing various types of interstitial defects, melt structures, structures in the σ and χ phases, and structures containing several concentrations of solid solutions of Re in bcc W and W in hcp Re. Future work will start the fitting iterations.

Density Functional Theory↗
DOE OSTI2018

Slycat™ User Manual

Slycat™ is a web-based system for performing data analysis and visualization of potentially large quantities of remote, high-dimensional data. Slycat™ specializes in working with ensemble data. An ensemble is a group of related data sets, which typically consists of a set of simulation runs exploring the same problem space. An ensemble can be thought of as a set of samples within a multi-variate domain, where each sample is a vector whose value defines a point in high-dimensional space. To understand and describe the underlying problem being modeled in the simulations, ensemble analysis looks for shared behaviors and common features across the group of runs. Additionally, ensemble analysis tries to quantify differences found in any members that deviate from the rest of the group. The Slycat™ system integrates data management, scalable analysis, and visualization. Results are viewed remotely on a user’s desktop via commodity web clients using a multi-tiered hierarchy of computation and data storage, as shown in Figure 1. Our goal is to operate on data as close to the source as possible, thereby reducing time and storage costs associated with data movement. Consequently, we are working to develop parallel analysis capabilities that operate on High Performance Computing (HPC) platforms, to explore approaches for reducing data size, and to implement strategies for staging computation across the Slycat™ hierarchy. Within Slycat™, data and visual analysis are organized around projects, which are shared by a project team. Project members are explicitly added, each with a designated set of permissions. Although users sign-in to access Slycat™, individual accounts are not maintained. Instead, authentication is used to determine project access. Within projects, Slycat™ models capture analysis results and enable data exploration through various visual representations. Although for scientists each simulation run is a model of real-world phenomena given certain conditions, we use the term model to refer to our modeling of the ensemble data, not the physics. Different model types often provide complementary perspectives on data features when analyzing the same data set. Each model visualizes data at several levels of abstraction, allowing the user to range from viewing the ensemble holistically to accessing numeric parameter values for a single run. Bookmarks provide a mechanism for sharing results, enabling interesting model states to be labeled and saved.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1989

Corrosion testing of candidates for the alkaline fuel cell cathode

Current/voltage data was obtained for specially made corrosion electrodes of some oxides and of gold materials for the purpose of developing a screening test of catalysts and supports for use at the cathode of the alkaline fuel cell. The data consists of measurements of current at fixed potentials and cyclic voltammograms. These data will have to be correlated with longtime performance data in order to fully evaluate this approach to corrosion screening. Corrosion test screening of candidates for the oxygen reduction electrode of the alkaline fuel cell was applied to two substances, the pyrochlore Pb2Ru2O6.5 and the spinel NiCo2O4. The substrate gold screen and a sample of the IFC Orbiter Pt-Au performance electrode were included as blanks. The pyrochlore data indicate relative stability, although nothing yet can be said about long term stability. The spinel was plainly unstable. For this type of testing to be validated, comparisons will have to be made with long term performance tests.

Singer, Joseph↗
NASA NTRS1990

Corrosion testing of candidates for the alkaline fuel cell cathode

Current/voltage data have been obtained for specially made corrosion electrodes of some oxides and of gold materials for the purpose of developing a screening test of catalysts and supports for use at the cathode of the alkaline fuel cell. The data consist of measurements of current at fixed potentials and cyclic voltammograms. These data will have to be correlated with longtime performance data in order to evaluate fully this approach to corrosion screening.

Singer, Joseph↗
NASA NTRS2000

Remotely-Sensed Geology from Lander-Based to Orbital Perspectives: Results for FIDO Rover Field Tests

Tests of the FIDO (Field Integration Design and Operations) rover and Athena-like operational scenarios were conducted May 7-16, 2000. A group located at the Jet Propulsion Lab, Pasadena, CA, formed the Core Operations Team (COT) that designed experiments and command sequences while another team tracked, maintained, and secured the rover in the field. The COT had no knowledge of the specific field location, thus the tests were done "blind." In addition to FIDO rover instrumentation, the COT had access to LANDSAT 7, TIMS, and AVIRIS regional coverage and color descent images. Using data from the FIDO instruments, primarily a color microscopic imager (CMI), infrared point spectrometer (IPS; 1.5-2.4 microns), and a three-color stereo panoramic camera (Pancam), the COT correlated lithologic features (mineralogy, rock types) from the simulated landing site to a regional scale. The May test results provide an example of how to relate site geology from landed rover investigations to the regional geology using remote sensing. The capability to relate mineralogic signatures using the point IR spectrometer to remotely sensed, multispectral or hyperspectral data proved to be key to integration of the in-situ and remote data. This exercise demonstrated the potential synergy between lander-based and orbital data, and highlighted the need to investigate a landing site in detail and at multiple scales.

Jolliff, B.↗
NASA NTRS2001

Cloud Overlapping Detection Algorithm Using Solar and IR Wavelengths With GOSE Data Over ARM/SGP Site

One of the most perplexing problems in satellite cloud remote sensing is the overlapping of cloud layers. Although most techniques assume a 1-layer cloud system in a given retrieval of cloud properties, many observations are affected by radiation from more than one cloud layer. As such, cloud overlap can cause errors in the retrieval of many properties including cloud height, optical depth, phase, and particle size. A variety of methods have been developed to identify overlapped clouds in a given satellite imager pixel. Baum el al. (1995) used CO2 slicing and a spatial coherence method to demonstrate a possible analysis method for nighttime detection of multilayered clouds. Jin and Rossow (1997) also used a multispectral CO2 slicing technique for a global analysis of overlapped cloud amount. Lin et al. (1999) used a combination infrared, visible, and microwave data to detect overlapped clouds over water. Recently, Baum and Spinhirne (2000) proposed 1.6 and 11 microns. bispectral threshold method. While all of these methods have made progress in solving this stubborn problem, none have yet proven satisfactory for continuous and consistent monitoring of multilayer cloud systems. It is clear that detection of overlapping clouds from passive instruments such as satellite radiometers is in an immature stage of development and requires additional research. Overlapped cloud systems also affect the retrievals of cloud properties over the ARM domains (e.g., Minnis et al 1998) and hence should identified as accurately as possible. To reach this goal, it is necessary to determine which information can be exploited for detecting multilayered clouds from operational meteorological satellite data used by ARM. This paper examines the potential information available in spectral data available on the Geostationary Operational Environmental Satellite (GOES) imager and the NOAA Advanced Very High Resolution Radiometer (AVHRR) used over the ARM SGP and NSA sites to study the capability of detecting overlapping clouds

Kawamoto, Kazuaki↗
NASA NTRS2001

Cloud Overlapping Detection Algorithm Using Solar and IR Wavelengths with GOES Data Over ARM/SGP Site

One of the most perplexing problems in satellite cloud remote sensing is the overlapping of cloud layers. Although most techniques assume a one layer cloud system in a given retrieval of cloud properties, many observations are affected by radiation from more than one cloud layer. As such, cloud overlap can cause errors in the retrieval of many properties including cloud height, optical depth, phase, and particle size. A variety of methods have been developed to identify overlapped clouds in a given satellite imager pixel. Baum et al used CO2 slicing and a spatial coherence method to demonstrate a possible analysis method for nighttime detection of multilayered clouds. Jin and Rossow also used a multispectral CO2 slicing technique for a global analysis of overlapped cloud amount. Lin et al. used a combination infrared (IR), visible (VIS), and microwave data to detect overlapped clouds over water. Recently, Baum and Spinhirne proposed a 1.6 and 11 micron bispectral threshold method. While all of these methods have made progress in solving this stubborn problem none have yet proven satisfactory for continuous and consistent monitoring of multilayer cloud systems. It is clear that detection of overlapping clouds from passive instruments such as satellite radiometers is in an immature stage of development and requires additional research. Overlapped cloud systems also affect the retrievals of cloud properties over the Atmospheric Radiation Measurement (ARM) domains and hence should be identified as accurately as possible. To reach this goal, it is necessary to determine which information can be exploited for detecting multilayered clouds from operational meteorological satellite data used by ARM. This paper examines the potential information available in spectral data available on the Geostationary Operational Environmental Satellite (GOES) imager and the National Oceanic Atmospheric Administration (NOAA) Advanced Very High Resolution Radiometer (AVHRR) used over the ARM Program's Southern Great Plains (SGP), and North Slope of Alaska (NSA) sites to study the capability of detecting overlapping clouds.

Kawamoto, K.↗
NASA NTRS1997

The Voyager Interstellar Mission

The Voyager Interstellar Mission began on January 1, 1990, with the primary objective being to characterize the interplanetary medium beyond Neptune and to search for the transition region between the interplanetary medium and the interstellar medium. At the start of this mission, the two Voyager spacecraft had already been in flight for over twelve years, having successfully returned a wealth of scientific information about the planetary systems of Jupiter, Saturn, Uranus, and Neptune, and the interplanetary medium between Earth and Neptune. The two spacecraft have the potential to continue returning science data until around the year 2020. With this extended operating lifetime, there is a high likelihood of one of the two spacecraft penetrating the termination shock and possibly the heliopause boundary, and entering interstellar space before that time. This paper describes the Voyager Interstellar Mission--the mission objectives, the spacecraft and science payload, the mission operations system used to support operations, and the mission operations strategy being used to maximize science data return even in the event of certain potential spacecraft subsystem failures. The implementation of automated analysis tools to offset and enable reduced flight team staffing levels is also discussed.

Flight Experiment↗
NASA NTRS2015

Simultaneous Radar and Satellite Data Storm-Scale Assimilation Using an Ensemble Kalman Filter Approach for 24 May 2011

Assimilating high-resolution radar reflectivity and radial velocity into convection-permitting numerical weather prediction models has proven to be an important tool for improving forecast skill of convection. The use of satellite data for the application is much less well understood, only recently receiving significant attention. Since both radar and satellite data provide independent information, combing these two sources of data in a robust manner potentially represents the future of high-resolution data assimilation. This research combines Geostationary Operational Environmental Satellite 13 (GOES-13) cloud water path (CWP) retrievals with Weather Surveillance Radar-1988 Doppler (WSR-88D) reflectivity and radial velocity to examine the impacts of assimilating each for a severe weather event occurring in Oklahoma on 24 May 2011. Data are assimilated into a 3-km model using an ensemble adjustment Kalman filter approach with 36 members over a 2-h assimilation window between 1800 and 2000 UTC. Forecasts are then generated for 90 min at 5-min intervals starting at 1930 and 2000 UTC. Results show that both satellite and radar data are able to initiate convection, but that assimilating both spins up a storm much faster. Assimilating CWP also performs well at suppressing spurious precipitation and cloud cover in the model as well as capturing the anvil characteristics of developed storms. Radar data are most effective at resolving the 3D characteristics of the core convection. Assimilating both satellite and radar data generally resulted in the best model analysis and most skillful forecast for this event.

Jones, Thomas A.↗
DOE OSTI2015

Stellar LOCI. III. Photometric metallicities for half million FGK stars of Stripe 82

We develop a method to estimate photometric metallicities by simultaneously fitting the dereddened colors u−g, g−r, r−i, and i−z from the SDSS with those predicted by the metallicity-dependent stellar loci. The method is tested with a spectroscopic sample of main-sequence stars in Stripe 82 selected from the SDSS DR9 and three open clusters. With 1% photometry, the method is capable of delivering photometric metallicities precise to about 0.05, 0.12, and 0.18 dex at metallicities of 0.0, −1.0, and −2.0, respectively, comparable to the precision achievable with low-resolution spectroscopy at a signal-to-noise ratio of 10. We apply this method to the re-calibrated Stripe 82 catalog and derive metallicities for about 0.5 million stars of colors 0.3<g−i<1.6 mag and distances between 0.3 and 18 kpc. Potential systematics in the metallicities thus derived, due to the contamination of giants and binaries, are investigated. Photometric distances are also calculated. About 91%, 72%, and 53% of the sample stars are brighter than r = 20.5, 19.5, and 18.5 mag, respectively. The median metallicity errors are around 0.19, 0.16, 0.11, and 0.085 dex for the whole sample, and for stars brighter than r = 20.5, 19.5, and 18.5 mag, respectively. The median distance errors are 8.8%, 8.4%, 7.7%, and 7.3% for the aforementioned four groups of stars, respectively. The data are publicly available. Potential applications of the data in studies of the distribution, (sub) structure, and chemistry of the Galactic stellar populations, are briefly discussed. The results will be presented in future papers.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2011

NASA Human Research Wiki - An Online Collaboration Tool

In preparation for exploration-class missions, the Exploration Medical Capability (ExMC) element of NASA's Human Research Program (HRP) has compiled a large evidence base, which previously was available only to persons within the NASA community. The evidence base is comprised of several types of data, for example: information on more than 80 medical conditions which could occur during space flight, derived from several sources (including data on incidence and potential outcomes of these medical conditions, as captured in the Integrated Medical Model's Clinical Finding Forms). In addition, approximately 35 gap reports are included in the evidence base, identifying current understanding of the medical challenges for exploration, as well as any gaps in knowledge and/or technology that would need to be addressed in order to provide adequate medical support for these novel missions. In an effort to make the ExMC information available to the general public and increase collaboration with subject matter experts within and outside of NASA, ExMC has developed an online collaboration tool, very similar to a wiki, titled the NASA Human Research Wiki. The platform chosen for this data sharing, and the potential collaboration it could generate, is a MediaWiki-based application that would house the evidence, allow "read only" access to all visitors to the website, and editorial access to credentialed subject matter experts who have been approved by the Wiki's editorial board. Although traditional wikis allow users to edit information in real time, the NASA Human Research Wiki includes a peer review process to ensure quality and validity of information. The wiki is also intended to be a pathfinder project for other HRP elements that may want to use this type of web-based tool. The wiki website will be released with a subset of the data described and will continue to be populated throughout the year.

Barr, Y. R.↗
DOE OSTI2020

Substation Secondary Asset Health Monitoring and Management System (SSHM)

Electric Power Group, LLC (EPG) was awarded DOE OE0000850 to design, develop, and demonstrate a real-time software application for substation secondary equipment health monitoring and management at host utility American Electric Power (AEP), a cost share partner. This project addresses the need for monitoring substation equipment health and providing operators with tools to identify and take pre-emptive action to avoid catastrophic equipment failure. By monitoring synchrophasor data in real time, data anomalies that indicate potential asset failure can be detected and alerts can be sent to operators in time to take corrective actions. EPG developed two data driven algorithms to identify abnormal equipment signature patterns as well as a method using substation linear state estimation (SLSE). The software has been deployed on hardened PC’s and tested and validated for cost share partner AEP’s substations - 138kV and 765 kV. The SSHM software has been accepted by AEP and final demonstration of DOE - OE0000850 for AEP and DOE was successfully completed on March 17th, 2020. EPG developed the Substation Secondary Asset Health Monitoring (SSHM) Platform to analyze equipment failure signatures in PMU data and alert substation personnel when pre-emptive inspection, repairs and other actions are warranted to prevent potential catastrophic failures. This is the first system that automatically monitors the health of substation secondary assets and alerts users to emerging failures using synchrophasor measurements. SSHM uses high resolution PMU data from PTs, CTs, and CCVTs to analyze equipment signatures and identify anomalies that are precursor indicators of potential equipment failure. When an anomaly is detected, there is a likelihood of potential failure of monitored equipment, the system alerts the user with visual alarms including alarm trend charts and indicator lights on a oneline diagram of the substation.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRSDate not supplied

Molecular dynamics simulation of effects of solutes on dislocation propagation in Ni-based superalloys

Ni-based superalloys are used in the hot sections of jet turbine engines because of their high strength, stability and resistance to oxidation. The properties of these alloys can be further optimized by adding alloying elements. Therefore, a fundamental knowledge on the effect of different elements on properties of Ni-based superalloys is required. Molecular dynamics simulation could shed light here but its application is hindered by the absence of reliable and computationally cheap semi-empirical potential of the interatomic interaction for 4 and more element alloys. We will present a new Ni-Al-Cr-Nb Finnis-Sinclair (FS) potential specially designed to simulate the dislocation propagation from to  phase. In order to construct this potential, we designed a special algorithm to incorporate the data on element partitioning in the potential development procedure. For example, it is known from experiment, that Cr is mostly present in the gamma phase. Figure 1 shows a snapshot obtained after equilibration of the model of the Ni68Al17Cr15 alloy at T=1000 K using the hybrid Monte-Carlo (MC)/molecular dynamics (MD) simulation with the developed semi-empirical potential. One can clearly see that the Cr partitioning is in agreement with the experimental data. We will discuss the developed algorithm to incorporate the solute partition data in details. Using the developed semi-empirical potential, we first investigated the effect of anti-site defects in the  phase on the single dislocation propagation. It was found that the dislocation velocity increases with the increasing of the anti-site defect concentration. This effect was attributed to smaller number of Al-Al pairs forming during the dislocation migration in the presence of the anti-site defects. Next, we investigated the effect of Nb on the dislocation pair propagation in the Kolbe mechanism. It was found that the addition of Nb leads to considerable decrease in the dislocation propagation rate. This is in agreement with the experimental data on the effect of Nb on the creep resistance of the Ni-based superalloys. We will discuss the origin of this effect.

Mikhail I. Mendelev↗