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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 1,765 records · Page 98
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

Prevalence and Predictors of Neoadjuvant Therapy for Stage IIIA Non-Small Cell Lung Cancer in the National Cancer Database: Importance of Socioeconomic Status and Treating Institution

Purpose: The optimal locoregional therapy for stage IIIA non-small cell lung cancer (NSCLC) is controversial, with definitive chemoradiation therapy (CRT) and neoadjuvant therapy followed by surgery (NT-S) serving as competing strategies. In this study, we used the National Cancer Database to determine the prevalence and predictors of NT in a large, modern cohort of patients. Methods and Materials: Patients with stage IIIA NSCLC treated with CRT or NT-S between 2003 and 2010 at programs accredited by the Commission on Cancer were included. Predictors were categorized as clinical, time/geographic, socioeconomic, and institutional. In accord with the National Cancer Database, institutions were classified as academic/research program and as comprehensive and noncomprehensive community cancer centers. Logistic regression and random effects multilevel logistic regression were performed for univariable and multivariable analyses, respectively. Results: The cohort consisted of 18,581 patients, 3,087 (16.6%) of whom underwent NT-S (10.6% induction CRT, 6% induction chemotherapy). The prevalence of NT-S was constant over time, but there were significant relative 31% and 30% decreases in pneumonectomy and right-sided pneumonectomy, respectively, over time (P trend <.02). In addition to younger age, lower T stage, and favorable comorbidity score, indicators of higher socioeconomic status were strong independent predictors of NT-S, including white race, higher income, and private/managed insurance. The type of institution (academic/research program vs comprehensive or noncomprehensive community cancer centers, odds ratio 1.54 and 2.08, respectively) strongly predicted NT-S, but treatment volume did not. Conclusions: Neoadjuvant therapy followed by surgery was an uncommon treatment approach in Commission on Cancer programs, and the prevalence of postinduction pneumonectomy decreased over time. Higher socioeconomic status and treatment at academic institutions were significant predictors of NT-S. Further research should be performed to enable a better understanding of these disparities.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2016

The electronics and data acquisition system for the DarkSide-50 veto detectors

DarkSide-50 is a detector for dark matter candidates in the form of weakly interacting massive particles. It utilizes a liquid argon time projection chamber for the inner main detector, surrounded by a liquid scintillator veto (LSV) and a water Cherenkov veto detector (WCV). The LSV and WCV act as the neutron and cosmogenic muon veto detectors for DarkSide-50. This paper describes the electronics and data acquisition system used for these two detectors. The system is made of a custom built front end electronics and commercial National Instruments high speed digitizers. The front end electronics, the DAQ, and the trigger system have been used to acquire data in the form of zero-suppressed waveform samples from the 110 PMTs of the LSV and the 80 PMTs of the WCV. The veto DAQ system has proven its performance and reliability. This electronics and DAQ system can be scaled and used as it is for the veto of the next generation DarkSide-20k detector.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2013

The Gene Ontology (GO) Cellular Component Ontology: integration with SAO (Subcellular Anatomy Ontology) and other recent developments

Background: The Gene Ontology (GO) (http://www.geneontology.org/) contains a set of terms for describing the activity and actions of gene products across all kingdoms of life. Each of these activities is executed in a location within a cell or in the vicinity of a cell. In order to capture this context, the GO includes a sub-ontology called the Cellular Component (CC) ontology (GO-CCO). The primary use of this ontology is for GO annotation, but it has also been used for phenotype annotation, and for the annotation of images. Another ontology with similar scope to the GO-CCO is the Subcellular Anatomy Ontology (SAO), part of the Neuroscience Information Framework Standard (NIFSTD) suite of ontologies. The SAO also covers cell components, but in the domain of neuroscience. Description: Recently, the GO-CCO was enriched in content and links to the Biological Process and Molecular Function branches of GO as well as to other ontologies. This was achieved in several ways. We carried out an amalgamation of SAO terms with GO-CCO ones; as a result, nearly 100 new neuroscience-related terms were added to the GO. The GO-CCO also contains relationships to GO Biological Process and Molecular Function terms, as well as connecting to external ontologies such as the Cell Ontology (CL). Terms representing protein complexes in the Protein Ontology (PRO) reference GO-CCO terms for their species-generic counterparts. GO-CCO terms can also be used to search a variety of databases. Conclusions: In this publication we provide an overview of the GO-CCO, its overall design, and some recent extensions that make use of additional spatial information. One of the most recent developments of the GO-CCO was the merging in of the SAO, resulting in a single unified ontology designed to serve the needs of GO annotators as well as the specific needs of the neuroscience community.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2016

Effect of Accounting for Crash Severity on the Relationship between Mass Reduction and Crash Frequency and Risk per Crash

Previous analyses have indicated that mass reduction is associated with an increase in crash frequency (crashes per VMT), but a decrease in fatality or casualty risk once a crash has occurred, across all types of light-duty vehicles. These results are counter-intuitive: one would expect that lighter, and perhaps smaller, vehicles have better handling and shorter braking distances, and thus should be able to avoid crashes that heavier vehicles cannot. And one would expect that heavier vehicles would have lower risk once a crash has occurred than lighter vehicles. However, these trends occur under several alternative regression model specifications. This report tests whether these results continue to hold after accounting for crash severity, by excluding crashes that result in relatively minor damage to the vehicle(s) involved in the crash. Excluding non-severe crashes from the initial LBNL Phase 2 and simultaneous two-stage regression models for the most part has little effect on the unexpected relationships observed in the baseline regression models. This finding suggests that other subtle differences in vehicles and/or their drivers, or perhaps biases in the data reported in state crash databases, are causing the unexpected results from the regression models.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2020

Biodefense Knowledge Management System

After the Amerithrax attacks, the Department of Homeland Security (DHS) recognized the need to link technical scientific information with law enforcement and national security information in the fight against bioterrorism. The Biodefense Knowledge Center (BKC) was formed to provide timely analysis of technical biodefense-related topics to support DHS and its customers in the interagency. The Biodefense Knowledge Management System (BKMS) was created as the backbone for information management within the BKC. It is a scalable, web-based knowledge management system for organizing disparate data sources. By combining information from 35+ data sources, the BKMS provides a searchable repository for technical information including scientific reports, journal articles, news articles, research funding databases, patent databases, and genomic datasets. The current system contains over 58 million documents and 450 million genomic records, and operates at several classification levels.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2013

Outside Mainstream Electronic Databases: Review of Studies Conducted in the USSR and Post-Soviet Countries on Electric Current-Assisted Consolidation of Powder Materials

This paper reviews research articles published in the former USSR and post-soviet countries on the consolidation of powder materials using electric current that passes through the powder sample and/or a conductive die-punch set-up. Having been published in Russian, many of the reviewed papers are not included in the mainstream electronic databases of the scientific articles and thus are not known to the scientific community. The present review is aimed at filling this information gap. In the paper, the electric current-assisted sintering techniques based on high- and low-voltage approaches are presented. The main results of the theoretical modeling of the processes of electromagnetic field-assisted consolidation of powder materials are discussed. Sintering experiments and related equipment are described and the major experimental results are analyzed. Sintering conditions required to achieve the desired properties of the sintered materials are provided for selected material systems. Tooling materials used in the electric current-assisted consolidation set-ups are also described.

powder materials↗
NASA NTRS1994

IRAS images of nearby dark clouds

We have investigated approximately 100 nearby molecular clouds using the extensive, all-sky database of IRAS. The clouds in this study cover a wide range of physical properties including visual extinction, size, mass, degree of isolation, homogeneity and morphology. IRAS 100 and 60 micron co-added images were used to calculate the 100 micron optical depth of dust in the clouds. These images of dust optical depth compare very well with (12)CO and (13)CO observations, and can be related to H2 column density. From the optical depth images we locate the edges of dark clouds and the dense cores inside them. We have identified a total of 43 `IRAS clouds' (regions with A(sub v) greater than 2) which contain a total of 255 `IRAS cores' (regions with A(sub v) greater than 4) and we catalog their physical properties. We find that the clouds are remarkably filamentary, and that the cores within the clouds are often distributed along the filaments. The largest cores are usually connected to other large cores by filaments. We have developed selection criteria to search the IRAS Point Source Catalog for stars that are likely to be associated with the clouds and we catalog the IRAS sources in each cloud or core. Optically visible stars associated with the clouds have been identified from the Herbig and Bell catalog. From these data we characterize the physical properties of the clouds including their star-formation efficiency.

Wood, Douglas O. S.↗
NASA NTRS2004

Final Summary of Research Report to the National Aeronautics and Space Administration Cosmochemistry Program

The discovery of presolar grains in meteorites is one of the most exciting recent developments in meteoritics. Six types of presolar grain have been discovered: diamond, Sic, graphite, Si3N4, Al2O3 and MgAl2O4. These grains have been identified as presolar because their isotopic compositions are very different from those of Solar System materials. Comparison of their isotopic compositions with astronomical observations and theoretical models indicates most of the grains formed in the envelopes of highly evolved stars. They are, therefore, a new source of information with which to test astrophysical models of the evolution of these stars. In fact, because several elements can often be measured in the same grain, including elements that are not measurable spectroscopically in stars, the grain data provide some very stringent constraints for these models. Our primary goal is to create large, unbiased, multi-isotope databases of single presolar Sic, Si,N,, oxide and graphite grains in meteorites, as well as any new presolar grain types that are identified in the future. These will be used to: (i) test stellar and nucleosynthetic models, (ii) constrain the galactic chemical evolution (GCE) paths of the isotopes of Si, Ti, 0 and Mg, (iii) establish how many stellar sources contributed to the Solar System, (iv) constrain relative dust production rates of various stellar types and (v) assess how representative of galactic dust production the record in meteorites is. The primary tool for this project is a highly automated grain analysis system we have developed for the Carnegie 6f ion probe.

O'D.Alexander, Conel↗
NASA NTRS2003

Final Summary of Research Report to the National Aeronautics and Space Administration Cosmochemistry Program

The discovery of presolar grains in meteorites is one of the most exciting recent developments in meteoritics. Six types of presolar grain have been discovered: diamond, Sic, graphite, Si3N4, Al2O3 and MgAl2O4. These grains have been identified as presolar because their isotopic compositions are very different from those of Solar System materials. Comparison of their isotopic compositions with astronomical observations and theoretical models indicates most of the grains formed in the envelopes of highly evolved stars. They are, therefore, a new source of information with which to test astrophysical models of the evolution of these stars. In fact, because several elements can often be measured in the same grain, including elements that are not measurable spectroscopically in stars, the grain data provide some very stringent constraints for these models. Our primary goal is to create large, unbiased, multi-isotope databases of single presolar Sic, Si,N,, oxide and graphite grains in meteorites, as well as any new presolar grain types that are identified in the future. These will be used to: (i) test stellar and nucleosynthetic models, (ii) constrain the galactic chemical evolution (GCE) paths of the isotopes of Si, Ti, O and Mg, (iii) establish how many stellar sources contributed to the Solar System, (iv) constrain relative dust production rates of various stellar types and (v) assess how representative of galactic dust production the record in meteorites is. The primary tool for this project is a highly automated grain analysis system on the Carnegie 6f ion probe.

O'D. Alexander, Conel↗
NASA NTRS2007

Software Sharing Enables Smarter Content Management

In 2004, NASA established a technology partnership with Xerox Corporation to develop high-tech knowledge management systems while providing new tools and applications that support the Vision for Space Exploration. In return, NASA provides research and development assistance to Xerox to progress its product line. The first result of the technology partnership was a new system called the NX Knowledge Network (based on Xerox DocuShare CPX). Created specifically for NASA's purposes, this system combines Netmark-practical database content management software created by the Intelligent Systems Division of NASA's Ames Research Center-with complementary software from Xerox's global research centers and DocuShare. NX Knowledge Network was tested at the NASA Astrobiology Institute, and is widely used for document management at Ames, Langley Research Center, within the Mission Operations Directorate at Johnson Space Center, and at the Jet Propulsion Laboratory, for mission-related tasks.

Source record↗
NASA NTRS2016

Global Comparison of CFD and Wind-Tunnel-Derived Force and Moment Databases for the Space Launch System

Recently a very large (739 runs) collection of high-fidelity RANS CFD solutions was obtained for Space Launch System ascent aerodynamics for the vehicle to be used for the first exploratory (unmanned) mission (EM-1). The extensive computations, at full-scale conditions, were originally developed to obtain detailed line and protuberance loads and surface pressures for venting analyses. The line loads were eventually integrated for comparison of the resulting forces and moments to the database that was derived from wind tunnel tests conducted at sub-scale conditions. The comparisons presented herein cover the ranges 0.5 < or = M(infinity) < or = 5, −6deg < or = alpha < or = 6deg, and −6deg < or = beta < or = 6deg. For detailed comparisons, slender-body-theory-based component build-up aero models from missile aerodynamics are used. The differences in the model fit coefficients are shown to be relatively small except for the low supersonic Mach number range, 1.1 < or = M(infinity) < or = 2.0. The analysis is intended to support process improvement and development of uncertainty models.

Hemsch, Michael J.↗
NASA NTRS2020

Methods of Measuring Secondary Electron Emission and Analysis of Spacecraft Charging Simulation

The scope of the internship project was to help the Electrostatics and Surface Physics Laboratory (ESPL) at KSC gain an understanding as to what parameters related to secondary electron emission (SEE), and electrostatic discharge (ESD) could be measured within its own facilities. As well as assistance in developing a plan for the ESPL to acquire the capabilities to measure other necessary parameters, to reduce the reliance on measurement data from facilities outside of the agency. The intern also worked closely with agency customers of the Launch Services Program (LSP) in expanding the MAPTIS database to incorporate various electrostatic and physical properties of materials used in the Gateway Program. This involved cross-center collaboration with industry and NASA contracted academia members in order to fill in the gaps of data that is missing from the database. Overall, the internship provided assistance in coordinating the approval for more materials to be added to the MAPTIS database, and continuing to assist the team at the ESPL in their consulting work for the agency through the use of various spacecraft charging and ESD simulation programs (i.e., NASCAP, NUMIT2.1). As well as assisting in the CAD design and implementation of an electrodynamic dust shield (EDS) for use in upcoming spaceflight missions. This was all done with the aim of helping the ESPL demonstrate its capabilities for the agency, and to continue expanding and localizing measurement techniques at KSC to help streamline obtaining the information NASA needs to ensure safety in current and future missions.

dust↗
NASA NTRS2022

Maine Ecological Forecasting II: Identifying Forest Cover and Assessing Federally Endangered Atlantic Salmon Habitat in Maine Using Earth Observations

Major declines in Atlantic salmon (Salmo salar) populations have occurred alongside dam construction, shifting temperatures, and changing land use and land cover (LULC), restricting the last remaining wild population in the United States to Maine. In collaboration with the Maine Department of Marine Resources and the Downeast Salmon Federation, the NASA DEVELOP team utilized Earth observations to assess changes within critical salmon habitat. The team used the Landsat 5 Thematic Mapper (TM), Landsat 8 Operation Land Imager (OLI), Sentinel-2 MultiSpectral Instrument (MSI), and National Land Cover Database (NLCD) to refine historical LULC maps from 1985 to 2021. The team also used elevation data from the Shuttle Radar Topography Mission (SRTM) and IDRISI TerrSet Land Change Modeler to forecast LULC change to 2040. From Terra Moderate Resolution Imaging Spectroradiometer (MODIS) land surface temperature (LST) data, the team derived a time series, summer averages, and anomaly maps between 2000 and 2021. The team analyzed LST in relation to LULC classes, specifically forest cover type, and in-situ stream temperature from the Spatial Hydro-Ecological Decision System (EcoSHEDS). LULC trends from 1985 to 2021 revealed a net transition of coniferous forest to other classes, such as deciduous forest and developed land. The team found an association between warmer temperatures and a greater presence of developed and mixed forest classes per 10,000 acres across Maine. These visualizations and analyses will aid partners in identifying riparian locations with ideal or unfavorable habitat conditions to inform Atlantic salmon population recovery efforts.

Tony Bowman↗
DOE OSTI2025

Understanding Pore Filling Processes and Adsorption/Desorption Hysteresis in Nanoporous Metal–Organic Frameworks: Insights from Grand Canonical Monte Carlo Simulations and Free Energy Calculations

Grand canonical Monte Carlo (GCMC) simulations were used to investigate pore filling and hysteresis in nanoporous metal-organic frameworks (MOFs). Adsorption and desorption isotherms were calculated for argon at 87 K in 1866 MOFs from the CoRE MOF database and for short n-alkanes in selected MOFs, keeping the adsorbent structure rigid. Analysis of the molecular configurations showed two different mechanisms and origins of hysteresis: one involving a transition of the adsorbate arrangement in the pores similar to a gas-to-liquid transition associated with a large change in the loading and one more similar to a liquid-to-solid transition associated with a relatively small change in the loading. Our GCMC simulations in MOFs with diverse pore topologies indicate exceptions to an empirical relationship for the minimum diameter of a cylindical pore required for hysteresis as a function of the adsorbate diameter and reduced temperature. The simulations reveal some structures where isotherms exhibit two steps in the adsorption branch and only one step in the desorption branch. Hysteresis loops with a different number of adsorption and desorption steps are not common. Here, to better understand why hysteresis is observed in the GCMC simulations, the concept of the transition probability for observing a step in the adsorption isotherm at a given pressure in a GCMC simulation is introduced. We used two different methods to calculate the transition probabilities and find that these yield comparable results. Furthermore, the transition probability provides a measure for the length of GCMC simulations to yield reliable results.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

A catastrophic tropical drought kills hydraulically vulnerable tree species

Drought-related tree mortality is now a widespread phenomenon predicted to increase in magnitude with climate change. However, the patterns of which species and trees are most vulnerable to drought, and the underlying mechanisms have remained elusive, in part due to the lack of relevant data and difficulty of predicting the location of catastrophic drought years in advance. In this work, we used long-term demographic records and extensive databases of functional traits and distribution patterns to understand the responses of 20–53 species to an extreme drought in a seasonally dry tropical forest in Costa Rica, which occurred during the 2015 El Niño Southern Oscillation event. Overall, species-specific mortality rates during the drought ranged from 0% to 34%, and varied little as a function of tree size. By contrast, hydraulic safety margins correlated well with probability of mortality among species, while morphological or leaf economics spectrum traits did not. This firmly suggests hydraulic traits as targets for future research.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Tree-Based Ensemble Learning Models for Wall Temperature Predictions in Post-Critical Heat Flux Flow Regimes at Subcooled and Low-Quality Conditions

Accurately predicting post-critical heat flux (CHF) heat transfer is an important but challenging task in water-cooled reactor design and safety analysis. Although numerous heat transfer correlations have been developed to predict post-CHF heat transfer, these correlations are only applicable to relatively narrow ranges of flow conditions due to the complex physical nature of the post-CHF heat transfer regimes. In this paper, a large quantity of experimental data is collected and summarized from the literature for steady-state subcooled and low-quality film boiling regimes with water as the working fluid in vertical tubular test sections. In addition, a low-quality water film boiling (LWFB) database is consolidated with a total of 22,813 experimental data points, which cover a wide flow range of the system pressure from 0.1 to 9.0 MPa, mass flux from 25 to 2750 kg/m 2 s, and inlet subcooling from 1 to 70 °C. Two machine learning (ML) models, based on random forest (RF) and gradient boosted decision tree (GBDT), are trained and validated to predict wall temperatures in post-CHF flow regimes. The trained ML models demonstrate significantly improved accuracies compared to conventional empirical correlations. To further evaluate the performance of these two ML models from a statistical perspective, three criteria are investigated and three metrics are calculated to quantitatively assess the accuracy of these two ML models. For the full LWFB database, the root-mean-square errors between the measured and predicted wall temperatures by the GBDT and RF models are 5.7% and 6.2%, respectively, confirming the accuracy of the two ML models.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2015

SU-E-T-126: Application of PIPSpro and EPID for Quality Assurance of Medical Accelerators

Purpose: The purpose is to study applying PIPSpro and EPID for routine quality assurance of medical accelerators. Methods: (1) The coincidence of Light field and radiation field: Placed the FC-2 phantom on the treatment couch at the 100cm SSD. Using jaw set 10×10 cm{sup 2} or 15×15 cm{sup 2} field. Verified that the light field aligns with the engraved squares on the phantom. Placed the Crosshair Marker phantom on the top of the FC-2 phantom with the cross-hair and spherical marker aligned to the center of the light field. Acquired images with EPID and the images should be exported preferably in DICOM format. Analyzed Follow the recommended procedures in the radiation light field module of PIPSpro software.(2)MLC QA:Set up the MLC phantom on the treatment couch at isocenter. Positioned the EPID imager at the highest possible position without colliding with either the couch or the phantom. Created and delivered four different patterns for testing the MLC leaf position, leaf width, multi-port and leaf transmission. (3)Radiation isocenter test: Included the isocenter of collimator rotation, gantry rotation and couch rotation. Set the jaws of the collimator to create a thin field as 0.4cm x 20cm.Irradiated film or EPID using an equidistant 15° spacing angles with rotating collimator, gantry and couch respectively. Results: We analyzed imagers from EPID and film with PIPSPro software. As a Result, we acquired the specifications of medical accelerators quickly. In the meantime, the results were saved to database for trending and future analysis. Conclusion: Quality assurance of medical accelerator is very important. We used PIPSpro and EPID for routine detection, not only improved our efficiency, but also saved the cost. It is an good method.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2019

easyaccess: Enhanced SQL command line interpreter for astronomical surveys

easyaccess is an enhanced command line interpreter and Python package created to facilitate access to astronomical catalogs stored in SQL Databases. It provides a custom interface with custom commands and was specifically designed to access data from the Dark Energy Survey Oracle database, including autocompletion of tables, columns, users and commands, simple ways to upload and download tables using csv, fits and HDF5 formats, iterators, search and description of tables among others. It can easily be extended to another surveys or SQL databases. The package was completely written in Python and support customized addition of commands and functionalities. Visit https://github.com/mgckind/easyaccess to view installation instructions, tutorials, and the Python source code for easyaccess.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗