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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 1,045 records · Page 58
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Validation of a reduced-order jet model for subsonic and underexpanded hydrogen jets

Much effort has been made to model hydrogen releases from leaks during potential failures of hydrogen storage systems. A reduced-order jet model can be used to quickly characterize these flows, with low computational cost. Notional nozzle models are often used to avoid modeling the complex shock structures produced by the underexpanded jets by determining an “effective” source to produce the observed downstream trends. In our work, the mean hydrogen concentration fields were measured in a series of subsonic and underexpanded jets using a planar laser Rayleigh scattering system. Furthermore, we compared the experimental data to a reduced order jet model for subsonic flows and a notional nozzle model coupled to the jet model for underexpanded jets. The values of some key model parameters were determined by comparisons with the experimental data. Finally, the coupled model was also validated against hydrogen concentrations measurements for 100 and 200 bar hydrogen jets with the predictions agreeing well with data in the literature.

08 HYDROGEN↗
DOE OSTI2019

Simulation Study of the Influence of Experimental Variations on the Structure and Quality of Plasma Liners

Simulation studies of a section of a spherically imploding plasma liner, formed by the merger of six hypersonic plasma jets, have been performed at conditions relevant to the Plasma Liner Experiment (PLX) [S. C. Hsu et al., IEEE Trans. Plasma Sci. 46, 1951 (2018)]. The main aim of simulations was the sensitivity study of the detailed structure of plasma liners and their global properties to experimental mass variations and timing jitter across the six plasma jets. Experimentally observable synthetic quantities have been computed using simulation data and compared with the available experimental data. Simulations predicted that the primary oblique shock wave structure is preserved at small experimental variations. At later phases of the liner implosion, primary shocks and, especially, secondary shocks are more sensitive to experimental variations. These conclusions follow from the simulation data as well as the experimental CCD camera images. Small displacements of the shock wave structures may also cause significant changes in the synthetic interferometer data at early time. Our studies showed that the global properties of the plasma liners (averaged Mach number and averaged ram pressure along leading edges of plasma liners) are not very sensitive to experimental variations. Simulation data of the liner structure were largely confirmed by the PLX experimental data.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2018

Maximizing ozone signals among chemical, meteorological, and climatological variability

The detection of meteorological, chemical, or other signals in modeled or observed air quality data – such as an estimate of a temporal trend in surface ozone data, or an estimate of the mean ozone of a particular region during a particular season – is a critical component of modern atmospheric chemistry. However, the magnitude of a surface air quality signal is generally small compared to the magnitude of the underlying chemical, meteorological, and climatological variabilities (and their interactions) that exist both in space and in time, and which include variability in emissions and surface processes. This can present difficulties for both policymakers and researchers as they attempt to identify the influence or signal of climate trends (e.g., any pauses in warming trends), the impact of enacted emission reductions policies (e.g., United States NO x State Implementation Plans), or an estimate of the mean state of highly variable data (e.g., summertime ozone over the northeastern United States). Here we examine the scale dependence of the variability of simulated and observed surface ozone data within the United States and the likelihood that a particular choice of temporal or spatial averaging scales produce a misleading estimate of a particular ozone signal. Our main objective is to develop strategies that reduce the likelihood of overconfidence in simulated ozone estimates. We find that while increasing the extent of both temporal and spatial averaging can enhance signal detection capabilities by reducing the noise from variability, a strategic combination of particular temporal and spatial averaging scales can maximize signal detection capabilities over much of the continental US. For signals that are large compared to the meteorological variability (e.g., strong emissions reductions), shorter averaging periods and smaller spatial averaging regions may be sufficient, but for many signals that are smaller than or comparable in magnitude to the underlying meteorological variability, we recommend temporal averaging of 10–15 years combined with some level of spatial averaging (up to several hundred kilometers). If this level of averaging is not practical (e.g., the signal being examined is at a local scale), we recommend some exploration of the spatial and temporal variability to provide context and confidence in the robustness of the result. These results are consistent between simulated and observed data, as well as within a single model with different sets of parameters. The strategies selected in this study are not limited to surface ozone data and could potentially maximize signal detection capabilities within a broad array of climate and chemical observations or model output.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

The Global Ocean Data Analysis Project version 2 (GLODAPv2) – an internally consistent data product for the world ocean

Version 2 of the Global Ocean Data Analysis Project (GLODAPv2) data product is composed of data from 724 scientific cruises covering the global ocean. It includes data assembled during the previous efforts GLODAPv1.1 (Global Ocean Data Analysis Project version 1.1) in 2004, CARINA (CARbon IN the Atlantic) in 2009/2010, and PACIFICA (PACIFic ocean Interior CArbon) in 2013, as well as data from an additional 168 cruises. Data for 12 core variables (salinity, oxygen, nitrate, silicate, phosphate, dissolved inorganic carbon, total alkalinity, pH, CFC-11, CFC-12, CFC-113, and CCl 4 ) have been subjected to extensive quality control, including systematic evaluation of bias. The data are available in two formats: (i) as submitted but updated to WOCE exchange format and (ii) as a merged and internally consistent data product. In the latter, adjustments have been applied to remove significant biases, respecting occurrences of any known or likely time trends or variations. Adjustments applied by previous efforts were re-evaluated. Hence, GLODAPv2 is not a simple merging of previous products with some new data added but a unique, internally consistent data product. In conclusion, this compiled and adjusted data product is believed to be consistent to better than 0.005 in salinity, 1 % in oxygen, 2 % in nitrate, 2 % in silicate, 2 % in phosphate, 4 µmol kg -1 in dissolved inorganic carbon, 6 µmol kg -1 in total alkalinity, 0.005 in pH, and 5 % for the halogenated transient tracers.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2019

Everybody Needs Somebody Sometimes: Validation of Adaptive Recovery in Robotic Space Operations

This work assesses an adaptive approach to fault recovery in autonomous robotic space operations, which uses indicators of opportunity, such as physiological state measurements and observations of past human assistant performance, to inform future selections. We validated our reinforcement learning approach using data we collected from humans executing simulated mission scenarios. We present a method of structuring human-factors experiments that permits collection of relevant indicator of opportunity and assigned assistance task performance data, as well as evaluation of our adaptive approach, without requiring large numbers of test subjects. Application of our reinforcement learning algorithm to our experimental data shows that our adaptive assistant selection approach can achieve lower cumulative regret compared to existing non-adaptive baseline approaches when using real human data. Our work has applications beyond space robotics to any application where autonomy failures may occur that require external intervention.

Human-centered robotics↗
DOE OSTI2013

Comparison of Burnup Credit Uncertainty Quantification Methods

The recent revision of Interim Staff Guidance (ISG-8 revision 3), issued by the US Nuclear Regulatory Commission, on burnup credit for criticality safety analysis of pressurized water reactor spent fuel in transportation and storage casks expands the nuclides that can be credited in the fuel composition to include minor actinides and fission products. The technical basis for development of the uncertainties associated with calculated nuclide concentrations in spent nuclear fuel that are recommended in ISG-8 was established through the use of measured isotopic data acquired from destructive radiochemical assay data for spent fuel samples. These data provide a direct experimental basis for determining uncertainties in the calculated nuclide concentrations. To provide additional insight into code uncertainties resulting from nuclear data and also the level of conservatism associated with using experimental assay benchmark data for uncertainty evaluation, a new uncertainty analysis tool in the SCALE code system that performs stochastic sampling of nuclear data has been applied to representative burnup credit calculations for spent fuel pool and dry cask storage applications methodology. The nuclear data uncertainty analysis capabilities in Sampler can account for uncertainty contributions from cross sections, fission yields, and decay data by using correlated sampling of covariance files developed for all nuclear data used by SCALE. These uncertainties associated with nuclear data evaluations are compared to corresponding values developed in ISG-8 that are based on destructive assay data, as well as to values obtained using an alternate methodology that was developed by the Electric Power Research Institute based on reactor core simulation data.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2019

Studying Neutral Current Elastic Scattering and the Strange Axial Form Factor in MicroBooNE

One of the least constrained contributions to the neutral current (NC) elastic neutrino-proton cross section is the strange axial form factor, which represents the strange quark spin contribution to the spin structure of the proton. This becomes the net strange spin contribution, $\Delta s$, in the limit when the negative four-momentum transfer squared ($Q^2$) is zero. The strange axial form factor can be determined by studying NC elastic scattering events in the MicroBooNE detector. MicroBooNE's unique ability to detect low-energy protons is expected to allow the reconstruction of these events with a $Q^2$ as low as 0.10 GeV$^2$ and to determine the strange axial form factor in a model-independent approach. We present a selection of neutral current elastic events in a subset of MicroBooNE neutrino data, as well as our plan to extract the strange part of the axial form factor and $\Delta s$ from this selection in the full data set.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2013

Production and Injection data for NV Binary facilities

Excel files are provided with well production and injection data for binary facilities in Nevada. The files contain the data that reported montly to the Nevada Bureau of Mines and Geology (NBMG) by the facility operators. this data has been complied into Excel spreadsheets for each of the facilities given on the NBMG web site.

15 GEOTHERMAL ENERGY↗
DOE OSTI2024

DASEventNet: AI‐Based Microseismic Detection on Distributed Acoustic Sensing Data From the Utah FORGE Well 16A (78)‐32 Hydraulic Stimulation

Abstract Distributed acoustic sensing (DAS) has emerged as a promising seismic technology for monitoring microearthquakes (MEQs) with high spatial resolution. Efficient algorithms are needed for processing large DAS data volumes. This study introduces a deep learning (DL) model based on a Residual Convolutional Neural Network (ResNet) for detecting MEQs using DAS data, named as DASEventNet. The test data were collected from the Utah FORGE 16A (78)‐32 hydraulic stimulation experiments conducted in April 2022. The DASEventNet model achieves a remarkable accuracy of 100% when discriminating MEQs from noise in the raw test set of 260 examples. Surprisingly, the model identified weak MEQ signatures that have been manually categorized as noise. The decision‐making process with the model is decoded by the classic activation map, which illuminates learning features of the DASEventNet model. These features provide clear illustrations of weak MEQs and varied noise types. Finally, we apply the trained model to the entire period (∼7 days) of continuous DAS recordings and find that it discovers >5,700 new MEQs, previously unregistered in the public Silixa DAS catalog. The DASEventNet model significantly outperforms the traditional seismic method Short‐Term Average/Long‐Term Average (STA/LTA), which detected only 1,307 MEQs. The DASEventNet detection threshold is M w −1.80 compared to the minimum magnitude of M w −1.14 detected by STA/LTA. The spatiotemporal distribution of the newly identified MEQs defines an extensive stimulation zone and more accurately characterizes fracture geometry. Our results highlight the potential of DL for long‐term, real‐time microseismic monitoring that can improve enhanced geothermal systems and other activities that include subsurface hydraulic fracturing.

15 GEOTHERMAL ENERGY↗
DOE OSTI2025

Mondo: integrating disease terminology across communities

Precision medicine aims to enhance diagnosis, treatment, and prognosis by integrating multimodal data at the point of care. However, challenges arise due to the vast number of diseases, differing methods of classification, and conflicting terminological coding systems and practices used to represent molecular definitions of disease. This lack of interoperability artificially constrains the potential for diagnosis, clinical decision support, care outcome analysis, as well as data linkage across research domains to support the development or repurposing of therapeutics. There is a clear and pressing need for a unified system for managing disease entities⁠—including identifiers, synonyms, and definitions. To address these issues, we created the Mondo disease ontology—a community-driven, open-source, unified disease classification system that harmonizes diverse terminologies into a consistent, computable framework. Mondo integrates key medical and biomedical terminologies, including Online Mendelian Inheritance in Man (OMIM), Orphanet, Medical Subject Headings (MeSH), National Cancer Institute Thesaurus (NCIt), and more, to provide a comprehensive and accurate representation of disease concepts with fully provenanced and attributed links back to the sources. Mondo can be used as the handle for curation of gene–disease associations utilized in diagnostic applications, research applications such as computational phenotyping, and in clinical coding systems in clinical decision support by pointing the clinician to the numerous knowledge resources linked to the Mondo identifier. Mondo's community-centric approach, stewarded by the Monarch Initiative's expertise in ontologies, ensures that the ontology remains adaptable to the evolving needs of biomedical research and clinical communities, as well as the knowledge providers.

biomedical informatics↗
DOE OSTI2015

CORONAL PROPERTIES OF THE SEYFERT 1.9 GALAXY MCG-05-23-016 DETERMINED FROM HARD X-RAY SPECTROSCOPY WITH NuSTAR

Measurements of the high-energy cut-off in the coronal continuum of active galactic nuclei have long been elusive for all but a small number of the brightest examples. We present a direct measurement of the cut-off energy in the nuclear continuum of the nearby Seyfert 1.9 galaxy MCG-05-23-016 with unprecedented precision. The high sensitivity of NuSTAR up to 79 keV allows us to clearly disentangle the spectral curvature of the primary continuum from that of its reflection component. Using a simple phenomenological model for the hard X-ray spectrum, we constrain the cut-off energy to 116{sub −5}{sup +6} keV with 90% confidence. Testing for more complex models and nuisance parameters that could potentially influence the measurement, we find that the cut-off is detected robustly. We further use simple Comptonized plasma models to provide independent constraints for both the kinetic temperature of the electrons in the corona and its optical depth. At the 90% confidence level, we find kT{sub e} = 29 ± 2 keV and τ {sub e} = 1.23 ± 0.08 assuming a slab (disk-like) geometry, and kT{sub e} = 25 ± 2 keV and τ {sub e} = 3.5 ± 0.2 assuming a spherical geometry. Both geometries are found to fit the data equally well and their two principal physical parameters are correlated in both cases. With the optical depth in the τ {sub e} ≳ 1 regime, the data are pushing the currently available theoretical models of the Comptonized plasma to the limits of their validity. Since the spectral features and variability arising from the inner accretion disk have been observed previously in MCG-05-23-016, the inferred high optical depth implies that a spherical or disk-like corona cannot be homogeneous.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Fallon, NV FORGE well 21-31 Lithology, Mineral, Image Log, and Injection Test data

Attached is 5 datasets collected from Fallon FORGE well 21-31 located in Churchill County, Nevada collected and interpreted between Feburary 2018-January 2020. This submission includes 1) new lithology interpretation derived from petrographic thin sections of sidewall cores taken from well 21-31, 2) X-Ray Diffraction (XRD) interpretation of sidewall cores and cuttings from well 21-31, 3) Hyperspectral (Short-Wave Infrared and Long-Wave Infrared) interpretation of cuttings and sidewall cores from well 21-31, 4) Interpretation of Formation MicroImager (FMI) and Borehole Televiewer (BHTV) image logs for natural fractures and induced structures for well 21-31, 5) Injection test data and associated analytical model parameters from well testing of well 21-31.

15 GEOTHERMAL ENERGY↗
DOE OSTI2014

SESAME 96170, a solid-liquid equation of state for CeO2

I describe an equation of state (EOS) for the low-pressure solid phase and liquid phase of cerium (IV) oxide, CeO 2 . The models and parameters used to calculate the EOS are presented in detail, and I compare with data for the full-density crystal. Hugoniot data are available only for high-porosity powders, and I discuss difficulties in comparing with such data. I have constructed SESAME 96170, an EOS for cerium (IV) oxide that includes the ambient solid and liquid phases. The EOS extends over the full standard SESAME range, but should not be used at low temperatures and high densities because of the lack of a high-pressure solid phase. I have described the models used to compute the three terms of the EOS (cold curve, nuclear, and thermal electronic), and I have given the parameters used in the models. They were determined by comparison with experimental data at P = 1 atm, including the constant-pressure specific heat, coefficient of thermal expansion, and melting and boiling points. The EOS compares well with data in its intended range of validity, but the presence of high-frequency optical modes in its phonon spectrum limits the agreement of our models with thermal data. The next step is to construct a multiphase EOS that includes the low- and high-pressure solid phases and the liquid. The DAC data from Duclos will most strongly constrain the parameters of the high-pressure solid. A remaining issue is the comparison of the crystal-density EOS with experimental Hugoniot data, which are taken at much lower initial data because the samples are porous powders. A satisfactory means of modeling porosity, allowing comparison of theory and experiment, has not yet been produced.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Predicting Execution Times for Disk-based and In-Situ Parallel Data Analytics (Final Technical Report)

In recent years, there has been a significant amount of interests in in-situ analytics on simulation programs. For a variety of reasons, it is desirable to be able to predict the execution time of an analytics program. At the same time, frameworks such as MapReduce have become popular for scientific data analytics. This paper focuses on developing performance models for predicting execution time of parallel data analytics, with a special emphasis on in-situ analytics. We take two distinct approach towards performance prediction. We first expand SKOPE (a SKeleton framewOrk for Performance Exploration) with performance models for disk data read, cache performance, and page fault penalty. Second, an analytical performance model is also developed. We have evaluated our performance prediction framework as well as the analytical model on three hardware setups with well-known data mining algorithms implemented in three programming paradigms, MapReduce, MATE (a MapReduce-like parallel system with an alternate API for multi-core environments) and Smart (a MapReduce-like framework for in-situ analytics). Results show that our performance prediction framework along with the incorporated performance models are capable of accurately predicting execution times for parallel scientific analytics on different hardware setups.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Enabling X-ray free electron laser crystallography for challenging biological systems from a limited number of crystals

There is considerable potential for X-ray free electron lasers (XFELs) to enable determination of macromolecular crystal structures that are difficult to solve using current synchrotron sources. Prior XFEL studies often involved the collection of thousands to millions of diffraction images, in part due to limitations of data processing methods. We implemented a data processing system based on classical post-refinement techniques, adapted to specific properties of XFEL diffraction data. When applied to XFEL data from three different proteins collected using various sample delivery systems and XFEL beam parameters, our method improved the quality of the diffraction data as well as the resulting refined atomic models and electron density maps. Moreover, the number of observations for a reflection necessary to assemble an accurate data set could be reduced to a few observations. These developments will help expand the applicability of XFEL crystallography to challenging biological systems, including cases where sample is limited.

43 PARTICLE ACCELERATORS↗
NASA NTRS1984

Evaluation of a velocity-split solution of the Navier-Stokes equations for fighter forebodies

A velocity-splitting method of solving the three-dimensional Navier-Stokes equations, originally designed for afterbody flows, is examined for its applicability for predicting fighter forebody flows. Results from the AFTEND Code are compared with wind tunnel data for two fighter configurations at a Mach number of 0.9 and angles-of-attack from 0 deg to 20 deg. Results compare well with data, and in areas where data do not exist, the viscous AFTEND results show realistic effects of viscosity compared to inviscid predictions. The inviscid results themselves are in general superior to results obtained from a small-disturbance transonic potential code.

Yaros, S. F.↗
NASA NTRS1985

Study of spectral/radiometric characteristics of the Thematic Mapper for land use applications

The radiometric characteristics of LANDSAT 5 TM data were analyzed. Effects which were found earlier and quantified in LANDSAT 4 TM data were quantified for LANDSAT-5 data as well, including: scan-direction-related signal droop and scan correlated level shifts. Coincident LANDSAT 4 and 5 fully corrected (CCT-PT) TM data were analyzed, and band-by-band relationships between the two sensors were derived in terms of both signal counts and radiance.

Malila, W. A.↗