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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 397 records · Page 22
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Chemical Consequence Analysis and Atmospheric Dispersion Coefficients under DOE-STD-3009-2014 Nuclear Safety Analysis

During preparation of non-reactor nuclear facility documented safety analyses (DSAs), chemical consequence analysis is an important contributor to correctly identifying and classifying nuclear safety controls. The Department of Energy (DOE) recently-issued DOE-STD-3009-2014, which increases the focus on chemical hazards within non-reactor nuclear facilities, and imposes additional requirements. Chemical consequence analysis can be significantly more complicated than radiological consequence analysis. Specifically, atmospheric dispersion factors used in chemical consequence analysis must consider several additional factors, such as the energy of the release, buoyancy, and initial chemical concentration. This paper describes the overall requirements of chemical consequence analysis under DOE-STD- 3009-2014, and provides specific guidance for determining an applicable atmospheric dispersion coefficient for use in chemical consequence analysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Assessment of Spatiotemporal Variability of Evapotranspiration and Its Governing Factors in a Mountainous Watershed

Evapotranspiration (ET) is a key component of the water balance, which influences hydrometeorology, water resources, carbon and other biogeochemical cycles, and ecosystem diversity. This study aims to investigate the spatio-temporal variations of ET at the East River watershed in Colorado and analyze the factors that control these variations. ET was acquired using the community land model (CLM) simulations and was compared with the values estimated using Fu’s equation and a watershed-scale water balance equation. The simulation results showed that 55% of annual precipitation in the East River is lost to ET, in which 75% of the ET comes from the summer months (May to September). We also found that the contribution of transpiration to the total ET was ~50%, which is much larger than that of soil evaporation (32%) and canopy evaporation (18%). Spatial analysis indicated that the ET is greater at elevations of 2950–3200 m and lower along the river valley (<2750 m) and at the high elevations (>3900 m). A correlation analysis of factors affecting ET showed that the land elevation, air temperature, and vegetation are closely correlated and together they govern the ET spatial variability. The results also suggested that ET in areas with more finely textured soil is slightly larger than regions with coarse-texture soil. This study presents a promising approach to the assessment of ET with a high spatiotemporal resolution over watershed scales and investigates factors controlling ET spatiotemporal variations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Microvascular invasion and grading in hepatocellular carcinoma: correlation with major and ancillary features according to LIRADS

Purpose: To assess major and ancillary parameters that could be correlated with Microvascular Invasion (MIV) and with histologic grade of HCC. Materials and methods: In this retrospective study, we assessed 62 patients (14 women–48 men; mean age, 63 years; range 38–80 years) that underwent hepatic resection for HCC. All patients were subject to Multidetector computed tomography (MDCT); 40 to Magnetic Resonance (MR) study. The radiologist assessed major and ancillary features according to LIRADS (v. 2018) and reported any radiological accessory findings if detected. Results: No major feature showed statistically significant differences and correlation with grading. Mean ADC value was correlated with grading and with MIV status. No major feature was correlated to MIV; progressive contrast enhancement and satellite nodules showed statistically different percentages with respect to the presence of MIV, so as at the monovariate correlation analysis, satellite nodules were correlated with the presence of MIV. At multivariate regression analysis, no factor proved to be strong predictors of grading while progressive contrast enhancement and satellite nodules were significantly associated with the MIV. Conclusion: Mean ADC value is correlated to HCC grading and MIV status. Progressive contrast enhancement and the presence of satellite nodules are correlated to MIV status.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2021

Comparative Virulence and Genomic Analysis of Streptococcus suis Isolates

Streptococcus suis is a zoonotic bacterial swine pathogen causing substantial economic and health burdens to the pork industry. Mechanisms used by S. suis to colonize and cause disease remain unknown and vaccines and/or intervention strategies currently do not exist. Studies addressing virulence mechanisms used by S. suis have been complicated because different isolates can cause a spectrum of disease outcomes ranging from lethal systemic disease to asymptomatic carriage. The objectives of this study were to evaluate the virulence capacity of nine United States S. suis isolates following intranasal challenge in swine and then perform comparative genomic analyses to identify genomic attributes associated with swine-virulent phenotypes. No correlation was found between the capacity to cause disease in swine and the functional characteristics of genome size, serotype, sequence type (ST), or in vitro virulence-associated phenotypes. A search for orthologs found in highly virulent isolates and not found in non-virulent isolates revealed numerous predicted protein coding sequences specific to each category. While none of these predicted protein coding sequences have been previously characterized as potential virulence factors, this analysis does provide a reliable one-to-one assignment of specific genes of interest that could prove useful in future allelic replacement and/or functional genomic studies. Collectively, this report provides a framework for future allelic replacement and/or functional genomic studies investigating genetic characteristics underlying the spectrum of disease outcomes caused by S. suis isolates.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2007

Full Life-Cycle Defect Management Assessment: Initial Inspection Data Collection Results and Research Questions for Further Study

It is often the case in software projects that when schedule and budget resources are limited, the Verification and Validation (V&V) activities suffer. Fewer V&V activities can be afforded and moreover, short-term challenges can result in V&V activities being scaled back or dropped altogether. As a result, too often the default solution is to save activities for improving software quality until too late in the life-cycle, relying on late-term code inspections followed by thorough testing activities to reduce defect counts to acceptable levels. As many project managers realize, however, this is a resource-intensive way of achieving the required quality for software. The Full Life-cycle Defect Management Assessment Initiative, funded by NASA s Office of Safety and Mission Assurance under the Software Assurance Research Program, aims to address these problems by: Improving the effectiveness of early life-cycle V&V activities to make their benefits more attractive to team leads. Specifically, we focus on software inspection, a proven method that can be applied to any software work product, long before executable code has been developed; Better communicating this effectiveness to software development teams, along with suggestions for parameters to improve in the future to increase effectiveness; Analyzing the impact of early life-cycle V&V on the effectiveness and cost required for late life-cycle V&V activities, such as testing, in order to make the tradeoffs more apparent. This white paper reports on an initial milestone in this work, the development of a preliminary model of inspection effectiveness across multiple NASA Centers. This model contributes toward reaching our project goals by: Allowing an examination of inspection parameters, across different types of projects and different work products, for an analysis of factors that impact defect detection effectiveness. Allowing a comparison of this NASA-specific model to existing recommendations in the literature regarding how to plan effective inspections. Forming a baseline model which can be extended to incorporate factors describing: the numbers and types of defects that are missed by inspections; how such defects flow downstream through software development phases; how effectively they can be caught by testing activities in the late stages of development. The model has been implemented in a prototype web-enabled decision-support tool which allows developers to enter their inspection data and receive feedback based on a comparison against the model. The tool also allows users to access reusable materials (such as checklists) from projects included in the baseline. Both the tool itself and the model underlying it will continue to be extended throughout the remainder of this initiative. As results of analyzing inspection effectiveness for defect containment are determined, they can be shared via the tool and also via updates to existing training courses on metrics and software inspections. Moreover, the tool will help satisfy key CMMI requirements for the NASA Centers, as it will enable NASA to take a global view across peer review results for various types of projects to identify systemic problems. This analysis can result in continuous improvements to the approach to verification.

Shull, Forrest↗
DOE OSTI2024

Strategic Siting of Direct Air Capture Facilities in the United States

Direct air capture (DAC) systems that capture carbon dioxide (CO 2 ) directly from the atmosphere are garnering considerable attention for their potential role as negative emission technologies in achieving net-zero CO 2 emission goals. Common DAC technologies are based either on liquid–solvent (L-DAC) or solid–sorbent (S-DAC) to capture CO 2 . A comprehensive multi-factor comparative economic analysis of the deployment of L-DAC and S-DAC facilities across various United States (U.S.) cities is presented in this paper. The analysis considers the influence of various factors on the favorability of DAC deployment, including local climatic conditions such as temperature, humidity, and CO 2 concentrations; the availability of energy sources to power the DAC system; and costs for the transport and storage of the captured CO 2 along with the consideration of the regional market and policy drivers. The deployment analysis in over 70 continental U.S. cities shows that L-DAC and S-DAC complement each other spatially, as their performance and operational costs vary in different climates. L-DAC is more suited to the hot, humid Southeast, while S-DAC is preferrable in the colder, drier Rocky Mountain region. Strategic deployment based on regional conditions and economics is essential for promoting the commercial adoptability of DAC, which is a critical technology to meet the CO 2 reduction targets.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2016

A Deep Generative Deconvolutional Image Model

A deep generative model is developed for representation and analysis of images, based on a hierarchical convolutional dictionary-learning framework. Stochastic unpooling is employed to link consecutive layers in the model, yielding top-down image generation. A Bayesian support vector machine is linked to the top-layer features, yielding max-margin discrimination. Deep deconvolutional inference is employed when testing, to infer the latent features, and the top-layer features are connected with the max-margin classifier for discrimination tasks. The model is efficiently trained using a Monte Carlo expectation-maximization (MCEM) algorithm; the algorithm is implemented on graphical processor units (GPU) to enable large-scale learning, and fast testing. Excellent results are obtained on several benchmark datasets, including ImageNet, demonstrating that the proposed model achieves results that are highly competitive with similarly sized convolutional neural networks.

convolutional neural network↗
DOE OSTI2019

Corpus luteum with ovarian stromal edema is associated with pelvic pain and confusion for ovarian torsion

Purpose: To distinguish the corpus luteum with adjacent ovarian stromal edema as an entity associated with pelvic pain, with confounding ultrasound features that may lead to false-positive diagnosis of ovarian torsion. Methods: This is a blinded, retrospective study of 243 corpora lutea on transvaginal ultrasound. Imaging parameters included ovarian and corpus luteum volumes, central cystic space within the corpus luteum, vascularity around the corpus luteum, peripherally displaced follicles, and complex free fluid. Residual volume (ovarian volume minus corpus luteum volume) was used as a surrogate for ovarian stromal edema. Clinical parameters included age, pregnancy, and location/acuity of pain if present. Concern for ovarian torsion in radiology reports was documented. Results: 51.0% (124/243) of patients presented with pain. Multivariate regression analysis of factors significantly associated with pain (including age, p = 0.001; larger corpus luteum volume, p = 0.002; larger residual volume, p < 0.001; complex free fluid, p = 0.002; and peripherally displaced follicles, p < 0.001) left only increased residual volume as significantly associated with pain [OR 1.02–1.16; p = 0.01]. False-positive concern for ovarian torsion on ultrasound was present in 12.9% (16/124) of patients with pain, associated with enlarged ovaries (p < 0.001) and peripherally displaced follicles (p < 0.001). High correlation between location of pain and side of the corpus luteum was demonstrated in patients with pain < 14 days duration (p < 0.001). Conclusion: Corpus luteum with ovarian stromal edema is associated with pelvic pain and can mimic ovarian torsion on ultrasound. Further research should explore diagnostically useful differences between cases of ovarian torsion and cases of ovarian edema related to corpora lutea.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2016

Influences of emission sources and meteorology on aerosol chemistry in a polluted urban environment: results from DISCOVER-AQ California

Abstract. The San Joaquin Valley (SJV) in California experiences persistent air-quality problems associated with elevated particulate matter (PM) concentrations due to anthropogenic emissions, topography, and meteorological conditions. Thus it is important to unravel the various sources and processes that affect the physicochemical properties of PM in order to better inform pollution abatement strategies and improve parameterizations in air-quality models. During January and February 2013, a ground supersite was installed at the Fresno–Garland California Air Resources Board (CARB) monitoring station, where comprehensive, real-time measurements of PM and trace gases were performed using instruments including an Aerodyne high-resolution time-of-flight aerosol mass spectrometer (HR-ToF-AMS) and an Ionicon proton transfer reaction time-of-flight mass spectrometer (PTR-TOF-MS) as part of the NASA Deriving Information on Surface Conditions from Column and Vertically Resolved Observations Relevant to Air Quality (DISCOVER-AQ) campaign. The average submicron aerosol (PM1) concentration was 31.0 µg m−3 and the total mass was dominated by organic aerosols (OA, 55 %), followed by ammonium nitrate (35 %). High PM pollution events were commonly associated with elevated OA concentrations, mostly from primary sources. Organic aerosols had average atomic oxygen-to-carbon (O / C), hydrogen-to-carbon (H / C), and nitrogen-to-carbon (N / C) ratios of 0.42, 1.70, and 0.017, respectively. Six distinct sources of organic aerosol were identified from positive matrix factorization (PMF) analysis of the AMS data: hydrocarbon-like OA (HOA; 9 % of total OA, O / C = 0.09) associated with local traffic, cooking OA (COA; 18 % of total OA, O / C = 0.19) associated with food cooking activities, two biomass burning OA (BBOA1: 13 % of total OA, O / C = 0.33; BBOA2: 20 % of total OA, O / C = 0.60) most likely associated with residential space heating from wood combustion, and semivolatile oxygenated OA (SV-OOA; 16 % of total OA, O / C = 0.63) and low-volatility oxygenated OA (LV-OOA; 24 % of total OA, O / C = 0.90) formed via chemical reactions in the atmosphere. Large differences in aerosol chemistry at Fresno were observed between the current campaign (winter 2013) and a previous campaign in winter 2010, most notably that PM1 concentrations were nearly 3 times higher in 2013 than in 2010. These variations were attributed to differences in the meteorological conditions, which influenced primary emissions and secondary aerosol formation. In particular, COA and BBOA concentrations were greater in 2013 than 2010, where colder temperatures in 2013 likely resulted in increased biomass burning activities. The influence from a nighttime formed residual layer that mixed down in the morning was found to be much more intense in 2013 than 2010, leading to sharp increases in ground-level concentrations of secondary aerosol species including nitrate, sulfate, and OOA, in the morning between 08:00 and 12:00 PST. This is an indication that nighttime chemical reactions may have played a more important role in 2013. As solar radiation was stronger in 2013 the higher nitrate and OOA concentrations in 2013 could also be partly due to greater photochemical production of secondary aerosol species. The greater solar radiation and larger range in temperature in 2013 also likely led to both SV-OOA and LV-OOA being observed in 2013 whereas only a single OOA factor was identified in 2010.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Relationship between isotope ratios in precipitation and stream water across watersheds of the National Ecological Observation Network

The timescales associated with precipitation moving through watersheds reveal processes that are critical to understanding many hydrologic systems. Measurements of environmental stable water isotope ratios (δ 2 H and δ 18 O) have been used as tracers to study hydrologic timescales by examining how long it takes for incoming precipitation tracers become stream discharge, yet limited measurements both spatially and temporally have bounded macroscale evaluations so far. Here in this observation driven study across North American biomes within the National Ecological Observation Network (NEON), we examined δ 18 O and δ 2 H stable water isotope in precipitation (δP) and stream water (δQ) at 26 co-located sites. With an average 54 precipitation samples and 139 stream water samples per site collected over 2014–2022, assessment of local meteoric water lines and local stream water lines showed geographic variation across North America. Taking the ratio of estimated seasonal amplitudes of δP and δQ to calculate young water fractions (F yw ), showed a Fyw range from 1% to 93% with most sites having F yw below 20%. Calculate d mean transit times (MTT) based on a gamma convolution model showed a MTT range from 0.10 to 13.2 years, with half of the sites having MTT estimates lower than 2 years. Significant correlations were found between the F yw and watershed area, longest flow length, and the longest flow length/slope. Significant correlations were found between MTT and site latitude, longitude, slope, clay fraction, temperature, precipitation magnitude, and precipitation frequency. The significant correlations between water timescale metrics and the environmental characteristics we report share some similarities with those reported in prior studies, demonstrating that these quantities are primarily driven by site or area specific factors. The analysis of isotope data presented here provides important constraints on isotope variation in North American biomes and the timescales of water movement through NEON study sites.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Getting to the Core of PARAFAC2, A Nonnegative Approach

In this paper, the authors present a novel method of performing PARAFAC2 factorization of three-way data using a compact representation of that data. In the standard PARAFAC2 algorithm, two modes of the data are recovered directly during the decomposition while the third mode is returned as a transformation matrix, which is then used to rotate sets of orthogonal third-mode basis factors into interpretable factors. In our new method, the data are first decomposed into a core matrix and orthogonal factor loading matrices in the first two modes as well as sets of orthogonal factors in the third mode (as in standard PARAFAC2). The core matrix is then decomposed using a the standard PARAFAC2 strategy to produce transformation matrices in all three modes. The algorithm is particularly useful for very large data sets and essentially permits imposition of nonnegativity in all three modes.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Pressure-induced polyamorphism by quantitative structure factor and pair distribution function analysis in two Ce-based metallic glasses

We utilized the pair distribution function method to characterize the pressure-induced polyamorphic transition in Ce60Al20Cu20 and Ce55Al45 metallic glass at room temperature. Using synchrotron high-energy x-ray diffraction we collected scattering information from a large Q-space coverage, which in turn gave a high resolution g(r) that provided accurate local structure information. We observed a sudden change in compressibility and the nearest neighbor distance at 3.50–6.32 GPa for Ce60Al20Cu20 and 2.20–6.89 GPa for Ce55Al45. The origin of the volume collapse seemed to be pressure-induced qualitative changes in bond shortening that corresponded to different coordination spheres. The polyamorphic transitions in these two systems from low-density glass (LDG) to high-density glass (HDG) are associated with local atomic rearrangements.

36 MATERIALS SCIENCE↗
DOE OSTI2025

The water use of data center workloads: A review and assessment of key determinants

The global importance of data center water use is increasing with the rapid growth of digitalization and artificial intelligence. This study analyzes the factors influencing workload-level water use, measured in liters consumed per workload, to guide water-saving strategies in data centers. Our findings reveal workload-level water use variations exceeding 10,000-fold, driven by over 1000-fold differences in water consumption per kilowatt hour of server electricity consumed and approximately 10-fold differences in server workload efficiency. Key determinants are ranked as server efficiency, electrical grid water consumption factors, server utilization, cooling system type, infrastructure efficiency, climate zone, inactive server percentage, and server refresh cycle. Notably, there is no single recipe for minimizing water use; instead, optimal outcomes depend on tailored combinations of these factors. This analysis addresses critical knowledge gaps by identifying the determinants of data center water use and exploring their achievable minima under diverse site-specific constraints.

Data centers↗
DOE OSTI2020

LIGHT DUTY VEHICLE CHOICE MODELS EXAMINING ALTERNATIVE FUEL TECHNOLOGY PREFERENCES AMONG COMMERCIAL FLEET OWNERS

Agent-based transportation models are critical tool for evaluating energy use, emissions and mobility impacts of transportation. In this context, vehicle ownership models are critical for linking agent activities to their impacts on the transportation system. However, no agent-based freight transportation models to date has been developed that predicts the fuel technology that is preferred by establishments when purchasing a Light Duty Vehicle (LDV) for business purposes. This research addresses this gap by using recently collected survey data to estimate a discrete choice model that can be applied in the agent-based context.

commercial↗
DOE OSTI2017

Global patterns of drought recovery

Drought has major impacts on natural and human systems, and is especially important for land carbon sink variability due to its influence on terrestrial biosphere climate regulation. While 20th Century trends in drought regimes have been varied, “more extreme extremes”, including more frequent and severe droughts, are expected in the 21st Century. Recovery time, the length of time an ecosystem requires to revert to its pre-drought functional state, is a critical metric of drought impact. Yet the factors influencing drought recovery and its spatiotemporal patterns are largely unknown. Here we use three independent global data products of gross primary productivity to show that, across diverse terrestrial ecosystems, drought recovery times are strongly associated with climate and carbon cycle dynamics, with biodiversity and CO 2 fertilization as secondary factors. Our analysis also provides two key insights into the spatiotemporal patterns of drought recovery time: (1) Across the globe, recovery is longest in the tropics and high northern latitudes—critical tipping elements in Earth’s climate system. (2) Drought impacts, the area of ecosystems under active recovery and recovery times, have increased over the 20th century. If future droughts become more frequent, time between droughts may become shorter than drought recovery time, leading to chronically impacted ecosystems.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

On the mechanism of soot nucleation

The mechanism of carbon particulate (soot) inception has been a subject of numerous studies and debates. The article begins with a critical review of prior proposals, proceeds to the analysis of factors enabling the development of a meaningful nucleation flux, and then introduces new ideas that lead to the fulfillment of these requirements. In the new proposal, a rotationally-activated dimer is formed in the collision of an aromatic molecule and an aromatic radical; the two react during the lifetime of the dimer to form a stable, doubly-bonded bridge between them, with the reaction rooted in a five-member ring present on the molecule edge. Several such reactions were examined theoretically and the most promising one generated a measurable nucleation flux. The consistency of the proposed model with known aspects of soot particle nanostructure is discussed. Here, the foundation of the new model is fundamentally the H-Abstraction-Carbon-Addition (HACA) mechanism with the reaction affinity enhanced by rotational excitation.

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

An analytic asymmetric-piston model for the impact of mode-1 shell asymmetry on ICF implosions

For many years, low mode asymmetry in inertially confined fusion (ICF) implosions has been recognized as a potential performance limiting factor, but analysis has been limited to using simulations and searching for data correlations. In this paper, an analytically solvable model based upon the simple picture of an asymmetric piston is presented. Asymmetry of the shell driving the implosion, as opposed to asymmetry in the hot-spot, is key to the model. The model provides a unifying framework for the action of mode-1 shell asymmetry and the resulting connections between various diagnostic signatures. A key variable in the model is the shell asymmetry fraction, f, which is related to the areal density variation of the shell surrounding the hot-spot. It is shown that f is simply related to the observed hot-spot mode-1 velocity and to the concept of residual energy in an implosion. The model presented in this paper yields explicit expressions for the hot-spot diameter, stagnation pressure, hot-spot energy, inertial confinement-time, Lawson parameter, hot-spot temperature, and fusion yield under the action of mode-1 asymmetry. Agreement is found between the theory scalings when compared to ICF implosion data from the National Ignition Facility and to large ensembles of detailed simulations, making the theory a useful tool for interpreting data. The theory provides a basis for setting tolerable limits on asymmetry.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗