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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
NASA NTRS2014

Complete Decoding and Reporting of Aviation Routine Weather Reports (METARs)

Aviation Routine Weather Report (METAR) provides surface weather information at and around observation stations, including airport terminals. These weather observations are used by pilots for flight planning and by air traffic service providers for managing departure and arrival flights. The METARs are also an important source of weather data for Air Traffic Management (ATM) analysts and researchers at NASA and elsewhere. These researchers use METAR to correlate severe weather events with local or national air traffic actions that restrict air traffic, as one example. A METAR is made up of multiple groups of coded text, each with a specific standard coding format. These groups of coded text are located in two sections of a report: Body and Remarks. The coded text groups in a U.S. METAR are intended to follow the coding standards set by National Oceanic and Atmospheric Administration (NOAA). However, manual data entry and edits made by a human report observer may result in coded text elements that do not follow the standards, especially in the Remarks section. And contrary to the standards, some significant weather observations are noted only in the Remarks section and not in the Body section of the reports. While human readers can infer the intended meaning of non-standard coding of weather conditions, doing so with a computer program is far more challenging. However such programmatic pre-processing is necessary to enable efficient and faster database query when researchers need to perform any significant historical weather analysis. Therefore, to support such analysis, a computer algorithm was developed to identify groups of coded text anywhere in a report and to perform subsequent decoding in software. The algorithm considers common deviations from the standards and data entry mistakes made by observers. The implemented software code was tested to decode 12 million reports and the decoding process was able to completely interpret 99.93 of the reports. This document presents the deviations from the standards and the decoding algorithm. Storing all decoded data in a database allows users to quickly query a large amount of data and to perform data mining on the data. Users can specify complex query criteria not only on date or airport but also on weather condition. This document also describes the design of a database schema for storing the decoded data, and a Data Warehouse web application that allows users to perform reporting and analysis on the decoded data. Finally, this document presents a case study correlating dust storms reported in METARs from the Phoenix International airport with Ground Stops issued by Air Route Traffic Control Centers (ATCSCC). Blowing widespread dust is one of the weather conditions when dust storm occurs. By querying the database, 294 METARs were found to report blowing widespread dust at the Phoenix airport and 41 of them reported such condition only in the Remarks section of the reports. When METAR is a data source for an ATM research, it is important to include weather conditions not only from the Body section but also from the Remarks section of METARs.

METAR Decoder/Parser↗
DOE OSTI2025

Rheological Properties of Enzymatically Hydrolyzed Corn Stover Pretreated via Deacetylation and Mechanical Refining

Lignocellulosic biomass is a feedstock for fuels and chemicals that does not compete with food resources and has less contaminants than refuse-derived biomass feedstocks. To convert lignocellulosics to biofuels or value-added products, multiple processing steps are typically necessary. One method of producing biofuels from lignocellulosic biomass utilizes a deacetylation and mechanical refining pretreatment and an enzymatic hydrolysis reaction to produce fermentable sugars from cellulose and hemicellulose. The rheological properties of biomass, such as yield stress and plastic viscosity, change during enzymatic hydrolysis and alter the energy requirements for pumping and mixing, an important consideration for the design of processing equipment. The dynamic changes in rheological properties that occur in a corn stover feedstock undergoing enzymatic hydrolysis are characterized in this work, and the influence on pressure losses in piping systems is estimated. Two rheometer geometries were fabricated with stereolithography 3D printing to reduce wall slip and sample ejection. The slurries have complex rheological behaviors that include shear-thinning behavior. Shear stress ramps were performed on samples at 20 and 50 degrees C using the custom geometries, and the Herschel-Bulkley model was fit to the data. The dynamic nature of the rheological properties is correlated with changes in the average fiber length at various extents of reaction, and the influence of solids concentration on the observed rheology and piping pressure losses is discussed.

09 BIOMASS FUELS↗
DOE OSTI2021

Hospice Landscape Report

In July 2018, CMS requested assistance from Oak Ridge National Laboratory (ORNL) to provide expert data science support aimed at developing algorithms for data mining of medical data for operational and payment purposes. The project is intended to be exploratory: work is aimed at alleviating challenges associated with improper payments, specifically audit methodologies and targeting and changes to risk scores. Project goals include developing new, sophisticated methods for audit targeting and improved profile– payment error correlations, specifically focused on Medicare Part C, the program under which MAOs provide health care services to beneficiaries. ORNL conducted RADV analyses against RAPS and EDS data as well as a hospice landscape analysis per a January 2015 dataset that included Medicare beneficiaries who were in hospice in 2017 and 2018. Ongoing work under this project also involves development of predictive models for RADV investigations and hospice landscape.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Conservation of Species- and Trait-Based Modeling Network Interactions in Extremely Acidic Microbial Community Assembly

Understanding microbial interactions is essential to decipher the mechanisms of community assembly and their effects on ecosystem functioning, however, the conservation of species- and trait-based network interactions along environmental gradient remains largely unknown. Here, by using the network-based analyses with three paralleled data sets derived from 16S rRNA gene pyrosequencing, functional microarray, and predicted metagenome, we test our hypothesis that the network interactions of traits are more conserved than those of taxonomic measures, with significantly lower variation of network characteristics along the environmental gradient in acid mine drainage. The results showed that although the overall network characteristics remained similar, the structural variation was significantly lower at trait levels. The higher conserved individual node topological properties at trait level rather than at species level indicated that the responses of diverse traits remained relatively consistent even though different species played key roles under different environmental conditions. Additionally, the randomization tests revealed that it could not reject the null hypothesis that species-based correlations were random, while the tests suggested that correlation patterns of traits were non-random. Furthermore, relationships between trait-based network characteristics and environmental properties implied that trait-based networks might be more useful in reflecting the variation of ecosystem function. Taken together, our results suggest that deterministic trait-based community assembly results in greater conservation of network interaction, which may ensure ecosystem function across environmental regimes, emphasizing the potential importance of measuring the complexity and conservation of network interaction in evaluating the ecosystem stability and functioning.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

An updated gene atlas for maize reveals organ-specific and stress-induced genes

Maize (Zea mays L.), a model species for genetic studies, is one of the two most important crop species worldwide. The genome sequence of the reference genotype, B73, representative of the stiff stalk heterotic group was recently updated (AGPv4) using long-read sequencing and optical mapping technology. To facilitate the use of AGPv4 and to enable functional genomic studies and association of genotype with phenotype, we determined expression abundances for replicated mRNA-sequencing datasets from 79 tissues and five abiotic/biotic stress treatments revealing 36 207 expressed genes. Characterization of the B73 transcriptome across six organs revealed 4154 organ-specific and 7704 differentially expressed (DE) genes following stress treatment. Gene co-expression network analyses revealed 12 modules associated with distinct biological processes containing 13 590 genes providing a resource for further association of gene function based on co-expression patterns. Presence–absence variants (PAVs) previously identified using whole genome resequencing data from 61 additional inbred lines were enriched in organ-specific and stress-induced DE genes suggesting that PAVs may function in phenological variation and adaptation to environment. Relative to core genes conserved across the 62 profiled inbreds, PAVs have lower expression abundances which are correlated with their frequency of dispersion across inbreds and on average have significantly fewer co-expression network connections suggesting that a subset of PAVs may be on an evolutionary path to pseudogenization. Here, to facilitate use by the community, we developed the Maize Genomics Resource website (maize.plantbiology.msu.edu) for viewing and data-mining these resources and deployed two new views on the maize electronic Fluorescent Pictograph Browser (bar.utoronto.ca/efp_maize).

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Localization of deformation in fluid-saturated sandstone

Herein we discuss a laboratory study of inelastic deformation and localization was conducted to evaluate microseismicity and fracture in fluid-saturated rock. Plane strain compression experiments were performed on oil- and water-saturated Berea sandstone under dry, drained, undrained, and quasi-unjacketed conditions. Parameters associated with the elastic and inelastic material response were accurately measured and used in a constitutive model to predict localization of deformation under the drained and undrained conditions. Acoustic emission (AE) activity was recorded and the onset of inelastic response in fluid-saturated rock, similar to dry rock, coincided with an increase in AE rate. Fracture initiation and propagation were successfully monitored by AE locations. Clustering of AE events and the start of inhomogeneous deformation inferred from displacement measurements are shown to be well correlated with the model prediction of the onset of localized deformation under various rock-fluid interaction conditions.

42 ENGINEERING↗
NASA NTRS2011

NASA Occupant Protection Standards Development

Current National Aeronautics and Space Administration (NASA) occupant protection standards and requirements are based on extrapolations of biodynamic models, which were based on human tests performed under pre-Space Shuttle human flight programs where the occupants were in different suit and seat configurations than is expected for the Multi Purpose Crew Vehicle (MPCV) and Commercial Crew programs. As a result, there is limited statistical validity to the occupant protection standards. Furthermore, the current standards and requirements have not been validated in relevant spaceflight suit, seat configurations or loading conditions. The objectives of this study were to develop new standards and requirements for occupant protection and rigorously validate these new standards with sub-injurious human testing. To accomplish these objectives we began by determining which critical injuries NASA would like to protect for. We then defined the anthropomorphic test device (ATD) and the associated injury metrics of interest. Finally, we conducted a literature review of available data for the Test Device for Human Occupant Restraint New Technology (THOR-NT) ATD to determine injury assessment reference values (IARV) to serve as a baseline for further development. To better understand NASA s environment, we propose conducting sub-injurious human testing in spaceflight seat and suit configurations with spaceflight dynamic loads, with a sufficiently high number of subjects to validate no injury during nominal landing loads. In addition to validate nominal loads, the THOR-NT ATD will be tested in the same conditions as the human volunteers, allowing correlation between human and ATD responses covering the Orion nominal landing environment and commercial vehicle expected nominal environments. All testing will be conducted without the suit and with the suit to ascertain the contribution of the suit to human and ATD responses. In addition to the testing campaign proposed, additional data analysis is proposed to mine existing human injury and response data from other sources, including military volunteer testing, automotive Crash Injury Research Engineering Network (CIREN), and IndyCar impact and injury data. These data sources can allow a better extrapolation of the ATD responses to off-nominal conditions above the nominal range that can safely be tested. These elements will be used to develop injury risk functions for each of the injury metrics measured from the ATD. These risk functions would serve as the basis for the NASA standards. Finally, we propose defining standard test methodology for evaluating future spacecraft designs against the IARVs, including developing a star-rating system to allow crew safety comparisons between vehicles.

Somers, Jeffrey T.↗
DOE OSTI2025

Influence of stacking fault energy and hydrogen on deformation mechanisms in high Mn austenitic steels during in-situ tensile testing

High Mn austenitic steels are considered an economical alloy system for hydrogen storage and transport applications. This study used stacking fault energy (SFE) as a design parameter to achieve hydrogen embrittlement (HE)-resistant high Mn austenitic alloys. The role of hydrogen on the deformation mechanisms of low (29 mJ/m 2 ) and high SFE (49 mJ/m 2 ) alloys was evaluated through in-situ neutron diffraction during tensile loading. Hydrogen-precharging increased yield strength, partly due to hydrogen-induced lattice distortion (i.e., solute strengthening). Hydrogen accelerated the increase in defect density, including dislocations and stacking faults. The formation of planar deformation structures (twins and stacking faults), relative to dislocations, plays a critical role in promoting hydrogen-assisted fracture. The stacking fault frequency parameter obtained from neutron diffraction quantifies planar deformation tendencies, correlated with HE sensitivity. The higher SFE alloy exhibited greater resistance to HE, associated with the reduced propensity to form stacking faults and twins upon deformation in the hydrogen-precharged condition.

High Mn austenitic steel↗
DOE OSTI2018

Predicting the 3D fatigue crack growth rate of small cracks using multimodal data via Bayesian networks: In-situ experiments and crystal plasticity simulations

Small crack propagation accounts for most of the fatigue life of engineering structures subject to high cycle fatigue loading conditions. Determining the fatigue crack growth rate of small cracks propagating into polycrystalline engineering alloys is critical to improving fatigue life predictions, thus lowering cost and increasing safety. In this work, cycle-by-cycle data of a small crack propagating in a beta metastable titanium alloy is available via phase and diffraction contrast tomography. Crystal plasticity simulations are used to supplement experimental data regarding the micromechanical fields ahead of the crack tip. Experimental and numerical results are combined into a multimodal dataset and sampled utilizing a non-local data mining procedure. Furthermore, to capture the propensity of body-centered cubic metals to deform according to the pencil-glide model, a non-local driving force is postulated. The proposed driving force serves as the basis to construct a data-driven probabilistic crack propagation framework using Bayesian networks as building blocks. The spatial correlation between the postulated driving force and experimental observations is obtained by analyzing the results of the proposed framework. Results show that the above correlation increases proportionally to the distance from the crack front until the edge of the plastic zone. Moreover, the predictions of the propagation framework show good agreement with experimental observations. Finally, we studied the interaction of a small crack with grain boundaries (GBs) utilizing various slip transmission criteria, revealing the tendency of a crack to cross a GB by propagating along the slip directions minimizing the residual Burgers vector within the GB.

36 MATERIALS SCIENCE↗
NASA NTRS2008

Verification of Atmospheric Signals Associated with Major Seismicity by Space and Terrestrial Observations

Observations from the last twenty years suggest the existence of electromagnetic (EM) phenomena during or preceding some earthquakes [Haykawa et a!, 2004; Pulinets at al, 1999,2004, 2006, Ouzounov et all 2007 and Liu et all 20041. Both our previous studies [Pulinets at al, 2005, 2006, Ouzounov et al, 2006, 20071 and the latest review by the Earthquake Remote Precursor Sensing panel [ERPS; 2003- 20051; have shown that there were precursory atmospheric TIR signals observed on the ground and in space associated with several recent earthquakes. [Tramutoli at al, 2005, 2006, Cervone et al, 2006, Ouzounov et all 2004,2006JT.o study these signals, we applied both multi parameter statistical analysis and data mining methods that require systematic measurements from an Integrated Sensor Web of observations of several physical and environmental parameters. These include long wave earth infra-red radiation, ionospheric electrical and magnetic parameters, temperature and humidity of the boundary layer, seismicity and may be associated with major earthquakes. Our goal is to verify the earthquake atmospheric correlation in two cases: (i) backward analysis - 2000-2008 hindcast monitoring of multi atmospheric parameters over the Kamchatka region, Russia ; and (ii) forward real-time alert analysis over different seismo-tectonic regions for California, Turkey, Taiwan and Japan. Our latest results, from several post-earthquake independent analyses of more then 100 major earthquakes, show that joint satellite and some ground measurements, using an integrated web, could provide a capability for observing pre-earthquake atmospheric signals by combining the information from multiple sensors into a common framework. Using our methodology, we evaluated and compared the observed signals preceding the latest M7.9 Sichuan earthquake (0511212008), M8.0 earthquake in Peru (0811512007), M7.6 Kashmir earthquake (1010812005) and M9.0 Sumatra earthquake (1212812004). We found evidence of the systematic appearance of both atmospheric and ionospheric anomalies preceding most of the major events during the period of our analysis 2001 -2008.

Taylor, Patrick↗
NASA NTRS2012

Revamping Spacecraft Operational Intelligence

The EPOXI flight mission has been testing a new commercial system, Splunk, which employs data mining techniques to organize and present spacecraft telemetry data in a high-level manner. By abstracting away data-source specific details, Splunk unifies arbitrary data formats into one uniform system. This not only reduces the time and effort for retrieving relevant data, but it also increases operational visibility by allowing a spacecraft team to correlate data across many different sources. Splunk's scalable architecture coupled with its graphing modules also provide a solid toolset for generating data visualizations and building real-time applications such as browser-based telemetry displays.

Hwang, Victor↗
DOE OSTI2026

Boron-Based Neutron Scintillator Screen Characterization with X-Rays and Neutrons

Recent work on boron-based neutron scintillator screens suggests these screens can offer superior performance when compared to commonly used screens. Borated neutron scintillator screens perform well in terms of light output (5-6 times greater than a standard Gadox screen) and detection effi-ciency (larger than standard LiF+ZnS screens). However, previously manu-factured boron-based screens have exhibited non-uniform surface coating and a poor mixture between phosphor and converter particles. The objective of this work was to evaluate newly fabricated scintillator screens to deter-mine if enhanced fabrication methods produced a more homogeneous distribution between neutron converter and scintillation phosphor particles. Uniformity of scintillator material deposition was also inspected. This new iteration of screens appeared more uniform than previous generations with the new coating method improving surface chemistry and scintillator material homogeneity. Additionally, a new methodology for screen characterization, involving the correlation of a neutron image taken with a borated scintillator screen to X-ray computed tomography of that same screen, was demonstrated to elucidate a relationship between scintillator screen thickness and relative light output of the screen under neutron exposure. This method suggested that the ideal thickness of scintillator material was ~150 µm to maximize light output of the screen.

36 - MATERIALS SCIENCE↗
DOE OSTI2017

Consumption Behavior Analytics-Aided Energy Forecasting and Dispatch

For decades, electricity customers have been treated as mere recipients of electricity in vertically integrated power systems. However, as customers have widely adopted distributed energy resources and other forms of customer participation in active dispatch (such as demand response) have taken shape, the value of mining knowledge from customer behavior patterns and using it for power system operation is increasing. Further, the variability of renewable energy resources has been considered a liability to the grid. However, electricity consumption has shown the same level of variability and uncertainty, and this is sometimes overlooked. This article investigates data analytics and forecasting methods to identify correlations between electricity consumption behavior and distributed photovoltaic (PV) output. The forecasting results feed into a predictive energy management system that optimizes energy consumption in the near future to balance customer demand and power system needs.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Mining experimental magnetized liner inertial fusion data: Trends in stagnation morphology

In magnetized liner inertial fusion (MagLIF), a cylindrical liner filled with fusion fuel is imploded with the goal of producing a one-dimensional plasma column at thermonuclear conditions. However, structures attributed to three-dimensional effects are observed in self-emission x-ray images. Despite this, the impact of many experimental inputs on the column morphology has not been characterized. We demonstrate the use of a linear regression analysis to explore correlations between morphology and a wide variety of experimental inputs across 57 MagLIF experiments. Results indicate the possibility of several unexplored effects. For example, we demonstrate that increasing the initial magnetic field correlates with improved stability. Although intuitively expected, this has never been quantitatively assessed in integrated MagLIF experiments. We also demonstrate that azimuthal drive asymmetries resulting from the geometry of the “current return can” appear to measurably impact the morphology. In conjunction with several counterintuitive null results, we expect the observed correlations will encourage further experimental, theoretical, and simulation-based studies. Finally, we note that the method used in this work is general and may be applied to explore not only correlations between input conditions and morphology but also with other experimentally measured quantities.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2019

Integrated Bioinformatic Analyses and Immune Characterization of New Neisseria gonorrhoeae Vaccine Antigens Expressed during Natural Mucosal Infection

There is an increasingly severe trend of antibiotic-resistant Neisseria gonorrhoeae strains worldwide and new therapeutic strategies are needed against this sexually-transmitted pathogen. Despite the urgency, progress towards a gonococcal vaccine has been slowed by a scarcity of suitable antigens, lack of correlates of protection in humans and limited animal models of infection. N. gonorrhoeae gene expression levels in the natural human host does not reflect expression in vitro, further complicating in vitro-basedvaccine analysis platforms. We designed a novel candidate antigen selection strategy (CASS), based on a reverse vaccinology-like approach coupled with bioinformatics. We utilized the CASS to mine gonococcal proteins expressed during human mucosal infection, reported in our previous studies, and focused on a large pool of hypothetical proteins as an untapped source of potential new antigens. Via two discovery and analysis phases (DAP), we identified 36 targets predicted to be immunogenic, membrane-associated proteins conserved in N. gonorrhoeae and suitable for recombinant expression. Six initial candidates were produced and used to immunize mice. Characterization of the immune responses indicated cross-reactive antibodies and serum bactericidal activity against different N. gonorrhoeae strains. These results support the CASS as a tool for the discovery of new vaccine candidates.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1976

Development of a multi-disciplinary ERTS user program in the state of Ohio

The author has identified the following significant results. A preliminary comparison of the land use maps derived from high altitude photography and imagery generated from land use CCT's shows considerable correlation of data. Most land use features are best identified on LANDSAT data taken over a full year, showing the effects of the four seasons. It appears that the most cost effective and timely way of providing land use data is to use LANDSAT data for identifying 75 to 90 percent of land use categories, using temporal data. For surface mining, close examination of LANDSAT, Skylab, and aircraft data covering the same area where linears were found seems to indicate that the type of resolution characteristic of LANDSAT data results in a better definition of linears of one or more miles. Long line linears were found in the vicinity of known gas production areas in Ohio.

Baldridge, P. E.↗
NASA NTRS1997

Advanced Algorithms and High-Performance Testbed for Large-Scale Site Characterization and Subsurface Target Detecting Using Airborne Ground Penetrating SAR

A team of US Army Corps of Engineers, Omaha District and Engineering and Support Center, Huntsville, let Propulsion Laboratory (JPL), Stanford Research Institute (SRI), and Montgomery Watson is currently in the process of planning and conducting the largest ever survey at the Former Buckley Field (60,000 acres), in Colorado, by using SRI airborne, ground penetrating, Synthetic Aperture Radar (SAR). The purpose of this survey is the detection of surface and subsurface Unexploded Ordnance (UXO) and in a broader sense the site characterization for identification of contaminated as well as clear areas. In preparation for such a large-scale survey, JPL has been developing advanced algorithms and a high-performance restbed for processing of massive amount of expected SAR data from this site. Two key requirements of this project are the accuracy (in terms of UXO detection) and speed of SAR data processing. The first key feature of this testbed is a large degree of automation and a minimum degree of the need for human perception in the processing to achieve an acceptable processing rate of several hundred acres per day. For accurate UXO detection, novel algorithms have been developed and implemented. These algorithms analyze dual polarized (HH and VV) SAR data. They are based on the correlation of HH and VV SAR data and involve a rather large set of parameters for accurate detection of UXO. For each specific site, this set of parameters can be optimized by using ground truth data (i.e., known surface and subsurface UXOs). In this paper, we discuss these algorithms and their successful application for detection of surface and subsurface anti-tank mines by using a data set from Yuma proving Ground, A7, acquired by SRI SAR.

Fijany, Amir↗