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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 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
NASA NTRS2012

The Epoch of Disk Formation: z is Approximately l to Today

We present data on galaxy kinematics, morphologies, and star-formation rates over 0.1 less than z less than 1.2 for approximately 500 blue galaxies. These data show how systems like our own Milky-Way have come into being. At redshifts around 1, about half the age of the Universe ago, Milky-Way mass galaxies were different beasts than today. They had a significant amount of disturbed motions, disturbed morphologies, shallower potential wells, higher specific star-formation rates, and likely higher gas fractions. Since redshift approximately 1, galaxies have decreased in disturbed motions, increased in rotation velocity and potential well depth, become more well-ordered morphologically, and decreased in specific star-formation rate. We find interrelationships between these measurements. Galaxy kinematics are correlated with morphology and specific star-formation rate such that galaxies with the fastest rotation velocities and the least amounts of disturbed motions have the most well-ordered morphologies and the lowest specific star-formation rates. The converse is true. Moreover, we find that the rate at which galaxies become more well-ordered kinematically (i.e., increased rotation velocity, decreased disturbed motions) and morphologically is directly proportional to their stellar mass.

Kassin, Susan↗
NASA NTRS2009

Liquid Engine Design: Effect of Chamber Dimensions on Specific Impulse

Which assumption of combustion chemistry - frozen or equilibrium - should be used in the prediction of liquid rocket engine performance calculations? Can a correlation be developed for this? A literature search using the LaSSe tool, an online repository of old rocket data and reports, was completed. Test results of NTO/Aerozine-50 and Lox/LH2 subscale and full-scale injector and combustion chamber test results were found and studied for this task. NASA code, Chemical Equilibrium with Applications (CEA) was used to predict engine performance using both chemistry assumptions, defined here. Frozen- composition remains frozen during expansion through the nozzle. Equilibrium- instantaneous chemical equilibrium during nozzle expansion. Chamber parameters were varied to understand what dimensions drive chamber C* and Isp. Contraction Ratio is the ratio of the nozzle throat area to the area of the chamber. L is the length of the chamber. Characteristic chamber length, L*, is the length that the chamber would be if it were a straight tube and had no converging nozzle. Goal: Develop a qualitative and quantitative correlation for performance parameters - Specific Impulse (Isp) and Characteristic Velocity (C*) - as a function of one or more chamber dimensions - Contraction Ratio (CR), Chamber Length (L ) and/or Characteristic Chamber Length (L*). Determine if chamber dimensions can be correlated to frozen or equilibrium chemistry.

Hoggard, Lindsay↗
NASA NTRS1984

Interplanetary radio storms. I - Extension of solar active regions through the interplanetary medium

About 100 storms of type-III solar radio bursts have been identified in the ISEE-3 radio-experiment data during the 4-yr period around the maximum of the 21st solar cycle. They demonstrate the very frequent presence of streams of suprathermal electrons. Their durations range from 1 to 10 d or more. They are observed up to 100-170 solar radii. Their rate of occurrence is 2 to 3 per solar rotation near solar maximum. It is shown that the time variations of the daily radio-emission intensities correlate with the sunspot-number variations and with the solar activity in general. More specifically, a very good correlation is found with the meter-wave type-III and type-I storms, which demonstrates that the suprathermal electrons responsible for the radio emission have been accelerated below 2 solar radii heliocentric. The different lags observed between the sunspot-number variations, the S-component, and the type-I and type-III storms are discussed.

Bougeret, J.-L.↗
DOE OSTI2019

Convolutional Neural Networks for Hydrometeor Classification using Dual Polarization Doppler Radars

Traditional fuzzy logic hydrometeor classification algorithm is a common way to classify precipitation type from dual polarization doppler radar. We propose a deep learning-based method to estimate hydrometeors efficiently using observed radar variables such as horizontal reflectivity (Z H ), differential reflectivity (Z DR ), correlation coefficient (ρ HV ) and specific differential phase (K DP ) from National Weather Service NEXRAD collected at Vance AFB facility at the first elevation angle from January 1st, 2015 to July 31th, 2019. We stack matrices of values from these four polarimetric variables as one 3D array. Samples are preprocessed and divided into training, validation and test set with four target hydrometeor categories (Ice Crystals (IC), Dry Snow (DS), Light and/or Moderate Rain (RA) and Big Drops (rain) (BD)). We developed and optimized five Convolutional Neural Networks (CNNs) architectures and achieved an accuracy of 87.23% and 93.736% respectively using modified ResNet with two different input data selection strategies for hydrometeor classification. Training data selection strategies were important to ensure use of available samples in training for robust performance evaluated by applying the models to novel time period beyond what was use to train the model. Seasonal variation in atmospheric conditions lead to seasonal patterns of liquid vs solid forms of precipitation, that poses challenge for classifier and offer insights into domain specific approaches required for problem of hydrometeor identification. Computationally efficient and scalable approach for classification of hydrometeors offer opportunties to effectively use the large volumes of rich time series of radar observations that are becoming increasingly available.

Lu, Yuping↗
DOE OSTI2017

A cross-sectional study of the temporal evolution of electricity consumption of six commercial buildings

Current approaches to building efficiency diagnoses include conventional energy audit techniques that can be expensive and time consuming. In contrast, virtual energy audits of readily available 15-minute-interval building electricity consumption are being explored to provide quick, inexpensive, and useful insights into building operation characteristics. A cross sectional analysis of six buildings in two different climate zones provides methods for data cleaning, population-based building comparisons, and relationships (correlations) of weather and electricity consumption. Data cleaning methods have been developed to categorize and appropriately filter or correct anomalous data including outliers, missing data, and erroneous values (resulting in < 0.5% anomalies). The utility of a cross-sectional analysis of a sample set of building's electricity consumption is found through comparisons of baseload, daily consumption variance, and energy use intensity. Correlations of weather and electricity consumption 15-minute interval datasets show important relationships for the heating and cooling seasons using computed correlations of a Time-Specific-Averaged- Ordered Variable (exterior temperature) and corresponding averaged variables (electricity consumption)(TSAOV method). The TSAOV method is unique as it introduces time of day as a third variable while also minimizing randomness in both correlated variables through averaging. This study found that many of the pair-wise linear correlation analyses lacked strong relationships, prompting the development of the new TSAOV method to uncover the causal relationship between electricity and weather. We conclude that a combination of varied HVAC system operations, building thermal mass, plug load use, and building set point temperatures are likely responsible for the poor correlations in the prior studies, while the correlation of time-specific-averaged-ordered temperature and corresponding averaged variables method developed herein adequately accounts for these issues and enables discovery of strong linear pair-wise correlation R values. TSAOV correlations lay the foundation for a new approach to building studies, that mitigates plug load interferences and identifies more accurate insights into weather-energy relationship for all building types. Over all six buildings analyzed the TSAOV method reported very significant average correlations per building of 0.94 to 0.82 in magnitude. Our rigorous statistics-based methods applied to 15- minute-interval electricity data further enables virtual energy audits of buildings to quickly and inexpensively inform energy savings measures.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRSDate not supplied

Utilizing 3D-DIC on Mars 2020 Rover Wheel Assembly: Test-Analysis Correlation

Following the successful implementation of full-field photogrammetry, more specifically three-dimensional Digital Image Correlation (3D-DIC), on the Mars 2020 Heat Shield Structural Failure Review assessment, 3D-DIC was selected as one of the primary measurement techniques for the Mars 2020 Rover wheel assembly qualification test at the NASA Jet Propulsion Laboratory (JPL). To validate the Rover wheel landing loads simulations, it was extremely important to have high confidence in the wheel models. Due to the large deformations and strains that the wheel would be subject to during landing, traditional instrumentation such as linear variable displacement transducers (LVDTs), electrical-resistance strain gages and string potentiometers, would not be sufficient on their own to provide all the necessary validation data. Therefore, the NASA Engineering and Safety Center (NESC) provided the 3D-DIC expertise and support to measure the high deformation and strain in the wheel flexures and qualify the overall structural response of the Mars 2020 rover wheel assembly. There were two key objectives for the photogrammetry technique: (1) monitor the wheel response in real-time, guarding against anomalous behavior and failure, and (2) provide test data for test-analysis correlation to validate and/or improve the high-fidelity computational model. The contents of this paper will focus on the challenges of applying 3D-DIC to the Mars 2020 Rover wheel assembly and how these challenges were overcome. Examples of test-analysis correlation during the stiffness characterization and structural qualification will be presented and discussed in detail. Experimental results were compared with the analysis and showed excellent agreement between the predicted behavior and helped validate the high-fidelity models.

Mars 2020 Rover Wheel↗
DOE OSTI2020

A Polarimetric Radar Analysis of Ice Microphysical Processes in Melting Layers of Winter Storms Using S-Band Quasi-Vertical Profiles

Quasi-vertical profiles (QVPs) obtained from a database of U.S. WSR-88D data are used to document polarimetric characteristics of the melting layer (ML) in cold-season storms with high vertical resolution and accuracy. A polarimetric technique to define the top and bottom of the ML is first introduced. Using the QVPs, statistical relationships are developed to gain insight into the evolution of microphysical processes above, within, and below the ML, leading to a statistical polarimetric model of the ML that reveals characteristics that reflectivity data alone are not able to provide, particularly in regions of weak reflectivity factor at horizontal polarization Z H . QVP ML statistics are examined for two regimes in the ML data: Z H ≥ 20 dB Z and Z H < 20 dB Z . Regions of Z H ≥ 20 dB Z indicate locations of MLs collocated with enhanced differential reflectivity Z DR and reduced copolar correlation coefficient ρ hv , while for Z H < 20 dB Z a well-defined ML is difficult to discern using Z H alone. Evidence of large Z DR up to 4 dB, backscatter differential phase δ up to 8°, and low ρ hv down to 0.80 associated with lower Z H (from -10 to 20 dB Z ) in the ML is observed when pristine, nonaggregated ice falls through it. Positive correlation is documented between maximum specific differential phase K DP and maximum Z H in the ML; these are the first QVP observations of K DP in MLs documented at S band. Negative correlation occurs between minimum ρ hv in the ML and ML depth and between minimum ρ hv in the ML and the corresponding enhancement of Z H (Δ Z H = Z H max - Z H rain ).

Meteorology & Atmospheric Sciences↗
NASA NTRS1987

Self similarity of two point correlations in wall bounded turbulent flows

The structure of turbulence at a height y from a wall is affected by the local mean shear at y, by the direct effect of the wall on the eddies, and by the action of other eddies close to or far from the wall. Some researchers believe that a single one of these mechanisms is dominant, while others believe that these effects have to be considered together. It is important to understand the relative importance of these effects in order to develop closure models, for example for the dissipation or for the Reynolds stress equation, and to understand the eddy structure of cross correlation functions and other measures. The specific objective was to examine the two point correlation, R sub vv, of the normal velocity component v near the wall in a turbulent channel flow and in a turbulent boundary layer. The preliminary results show that even in the inhomogeneous turbulent boundary layer, the two-point correlation function may have self similar forms. The results also show that the effects of shear and of blocking are equally important in the form of correlation functions for spacing normal to the wall. But for spanwise spacing, it was found that the eddy structure is quire different in these near flows. So any theory for turbulent structure must take both these effects into account.

Hunt, J. C. R.↗
DOE OSTI2017

Spatial Distribution of Resonance in the Velocity Field for Transonic Flow over a Rectangular Cavity

Pulse-burst particle image velocimetry (PIV) has been used to acquire time-resolved data at 37.5 kHz of the flow over a finite-width rectangular cavity at Mach 0.8. Power spectra of the PIV data reveal four resonance modes that match the frequencies detected simultaneously using high-frequency wall pressure sensors but whose magnitudes exhibit spatial dependence throughout the cavity. Spatio-temporal cross-correlations of velocity to pressure were calculated after bandpass filtering for specific resonance frequencies. Cross-correlation magnitudes express the distribution of resonance energy, revealing local maxima and minima at the edges of the shear layer attributable to wave interference between downstream- and upstream-propagating disturbances. Turbulence intensities were calculated using a triple decomposition and are greatest in the core of the shear layer for higher modes, where resonant energies ordinarily are lower. Most of the energy for the lowest mode lies in the recirculation region and results principally from turbulence rather than resonance. Together, the velocity-pressure cross-correlations and the triple-decomposition turbulence intensities explain the sources of energy identified in the spatial distributions of power spectra amplitudes.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS1991

Correction of magnetooptic device phase errors in optical correlators through filter design modifications

We address the problem of optical phase errors in an optical correlator introduced by the input and filter plane spatial light modulators. Specifically, we study a laboratory correlator with magnetooptic spatial light modulator (MOSLM) devices. We measure and characterize the phase errors, analyze their effects on the correlation process, and discuss a means of correction through a design modification of the binary phase-only optical filter function. The phase correction technique is found to produce correlation results close to those of an error-free correlator.

Downie, John D.↗
NASA NTRS1975

Correlation of low speed wind tunnel and flight test data for V/STOL aircraft

The XV-5B fan-in-wing aircraft and the Y0V-10 RCF rotating cylinder flap aircraft were subjected to wind tunnel tests. These tests were conducted specifically to provide for correlation between wind tunnel and inflight aerodynamics and noise test data. Correlation between aerodynamic and noise data are presented and testing techniques that are related to the accuracy of the data, or that might affect the correlations, are discussed.

Cook, W. L.↗
DOE OSTI2018

Cholesterol inhibits entotic cell-in-cell formation and actomyosin contraction

Highlights: • Lipofectamine 2000 inhibits entotic cell-in-cell formation. • Lipofectamine 2000 inhibits actomyosin contraction. • Cholesterol and phospholipids inhibits entotic cell-in-cell formation. • Cholesterol inhibits the phosphorylation of myosin light chain. Cell-in-cell structure is prevalent in human cancer, and associated with several specific pathophysiological phenomena. Although cell membrane adhesion molecules were found critical for cell-in-cell formation, the roles of other membrane components, such as lipids, remain to be explored. In this study, we attempted to investigate the effects of cholesterol and phospholipids on the formation of cell-in-cell structures by utilizing liposome as a vector. We found that Lipofectamine-2000, the reagent commonly used for routine transfection, could significantly reduce entotic cell-in-cell formation in a cell-specific manner, which is correlated with suppressed actomyosin contraction as indicated by reduced β-actin expression and myosin light chain phosphorylation. The influence on cell-in-cell formation was likely dictated by specific liposome components as some liposomes affected cell-in-cell formation while some others didn't. Screening on a limited number of lipids, the major components of liposome, identified phosphatidylethanolamine (PE), stearamide (SA), lysophosphatidic acid (LPA) and cholesterol (CHOL) as the inhibitors of cell-in-cell formation. Importantly, cholesterol treatment significantly inhibited myosin light chain phosphorylation, which resembles the effect of Lipofectamine-2000, suggesting cholesterol might be partially responsible for liposomes' effects on cell-in-cell formation. Together, our findings supporting a role of membrane lipids and cholesterol in cell-in-cell formation probably via regulating actomyosin contraction.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2019

A composite neural network that learns from multi-fidelity data: Application to function approximation and inverse PDE problems

Presently the training of neural networks relies on data of comparable accuracy but in real applications only a very small set of high-fidelity data is available while inexpensive lower fidelity data may be plentiful. We propose a new composite neural network (NN) that can be trained based on multi-fidelity data. It is comprised of three NNs, with the first NN trained using the low-fidelity data and coupled to two high-fidelity NNs, one with activation functions and another one without, in order to discover and exploit nonlinear and linear correlations, respectively, between the low-fidelity and the high-fidelity data. We first demonstrate the accuracy of the new multi-fidelity NN for approximating some standard benchmark functions but also a 20-dimensional function that is not easy to approximate with other methods, e.g. Gaussian process regression. Subsequently, we extend the recently developed physics-informed neural networks (PINNs) to be trained with multi-fidelity data sets (MPINNs). MPINNs contain four fully-connected neural networks, where the first one approximates the low-fidelity data, while the second and third construct the correlation between the low- and high-fidelity data and produce the multi-fidelity approximation, which is then used in the last NN that encodes the partial differential equations (PDEs). Specifically, by decomposing the correlation into a linear and nonlinear part, the present model is capable of learning both the linear and complex nonlinear correlations between the low- and high-fidelity data adaptively. By training the MPINNs, we can: (1) obtain the correlation between the low- and high-fidelity data, (2) infer the quantities of interest based on a few scattered data, and (3) identify the unknown parameters in the PDEs. In particular, we employ the MPINNs to learn the hydraulic conductivity field for unsaturated flows as well as the reactive models for reactive transport. The results demonstrate that MPINNs can achieve relatively high accuracy based on a very small set of high-fidelity data. Despite the relatively low dimension and limited number of fidelities (two-fidelity levels) for the benchmark problems in the present study, the proposed model can be readily extended to very high-dimensional regression and classification problems involving multi-fidelity data.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS2008

Multilayer Piezoelectric Stack Actuator Characterization

Future NASA missions are increasingly seeking to use actuators for precision positioning to accuracies of the order of fractions of a nanometer. For this purpose, multilayer piezoelectric stacks are being considered as actuators for driving these precision mechanisms. In this study, sets of commercial PZT stacks were tested in various AC and DC conditions at both nominal and extreme temperatures and voltages. AC signal testing included impedance, capacitance and dielectric loss factor of each actuator as a function of the small-signal driving sinusoidal frequency, and the ambient temperature. DC signal testing includes leakage current and displacement as a function of the applied DC voltage. The applied DC voltage was increased to over eight times the manufacturers' specifications to investigate the correlation between leakage current and breakdown voltage. Resonance characterization as a function of temperature was done over a temperature range of -180C to +200C which generally exceeded the manufacturers' specifications. In order to study the lifetime performance of these stacks, five actuators from one manufacturer were driven by a 60volt, 2 kHz sine-wave for ten billion cycles. The tests were performed using a Lab-View controlled automated data acquisition system that monitored the waveform of the stack electrical current and voltage. The measurements included the displacement, impedance, capacitance and leakage current and the analysis of the experimental results will be presented.

active mirrors↗
NASA NTRS2013

Correlation of Gear Surface Fatigue Lives to Lambda Ratio (Specific Film Thickness)

The effect of the lubrication regime on gear performance has been recognized, qualitatively, for decades. Often the lubrication regime is characterized by the specific film thickness being the ratio of lubricant film thickness to the composite surface roughness. Three studies done at NASA to investigate gearing pitting life are revisited in this work. All tests were done at a common load. In one study, ground gears were tested using a variety of lubricants that included a range of viscosities, and therefore the gears operated with differing film thicknesses. In a second and third study, the performance of gears with ground teeth and superfinished teeth were assessed. Thicker oil films provided longer lives as did improved surface finish. These datasets were combined into a common dataset using the concept of specific film thickness. This unique dataset of more 258 tests provides gear designers with some qualitative information to make gear design decisions.

gear↗
NASA NTRS2011

The Radio/Gamma-Ray Connection in Active Galactic Nuclei in the Era of the Fermi Large Area Telescope

We present a detailed statistical analysis of the correlation between radio and gamma-ray emission of the active galactic nuclei (AGNs) detected by Fermi during its first year of operation, with the largest data sets ever used for this purpose.We use both archival interferometric 8.4 GHz data (from the Very Large Array and ATCA, for the full sample of 599 sources) and concurrent single-dish 15 GHz measurements from the OwensValley RadioObservatory (OVRO, for a sub sample of 199 objects). Our unprecedentedly large sample permits us to assess with high accuracy the statistical significance of the correlation, using a surrogate data method designed to simultaneously account for common-distance bias and the effect of a limited dynamical range in the observed quantities. We find that the statistical significance of a positive correlation between the centimeter radio and the broadband (E > 100 MeV) gamma-ray energy flux is very high for the whole AGN sample, with a probability of <10(exp -7) for the correlation appearing by chance. Using the OVRO data, we find that concurrent data improve the significance of the correlation from 1.6 10(exp -6) to 9.0 10(exp -8). Our large sample size allows us to study the dependence of correlation strength and significance on specific source types and gamma-ray energy band. We find that the correlation is very significant (chance probability < 10(exp -7)) for both flat spectrum radio quasars and BL Lac objects separately; a dependence of the correlation strength on the considered gamma-ray energy band is also present, but additional data will be necessary to constrain its significance.

Ackermann, M.↗
DOE OSTI2017

Experimental study on team coordination of NPP plant operators based on the simultaneous NIRS measurements - 266

One of the key features when dealing with severe situations far beyond the previous experiences and expectations is the coordination capability among operators with different roles. In this study, the feasibility of estimating coordination capability of nuclear plant operators has been examined based on the correlation analysis of brain activities among operators. The cognitive experiments have been performed in the full scope NPP simulator at BWR Operator Training Center Cooperation. Four experienced instructors participated in the experiments. They played different roles such as shift supervisor, turbine operator, reactor operator and auxiliary operator and were instructed to go through four training scenarios shown below with NIRS devices attached. The brain activity of each operator has been measured along with the progress of anomaly events and the correlation of brain activities for every pair of operators have been calculated. The correlations of brain activities have also analyzed focusing on the specific events along with the progress in the anomaly scenarios. It has been shown in the results that the higher correlation among all operators were observed when the global events occurred and the higher correlation among specific pair of operators related to the specific event were partially observed. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2026

Transformative Impacts of Laser-Induced Breakdown Spectroscopy on Environmental and Biological Research at Oak Ridge National Laboratory

This manuscript will present an advancement of transformative research that has been conducted at Oak Ridge National Laboratory (ORNL) over a 25-year period (2000–2025) on a variety of environmental and biological matrices. These investigations derived a fundamental understanding of how elemental detection and analysis of these matrices led to the knowledge and discovery of natural processes in plants and the environment. Each project led to the initiation of a new research area which unearthed awesome and novel breakthroughs. Highlights are listed below: 1. The preliminary research at ORNL centered on the detection of aerosols utilizing Laser-induced Breakdown Spectroscopy (LIBS) technology. The Clean Air Act Amendment (CAAA) of 1990 highlighted the importance of identifying hazardous air pollutants (HAPs) due to their impact on environmental and human health, thereby underscoring the need to detect various toxic elements. Research in aerosol chemistry aimed to identify these harmful elements released by factories during periods of increased emissions in their manufacturing processes. LIBS emerged as the most effective method for real-time, in situ measurements of metal species in both gaseous and aerosol phases. 2. An understanding of the presence of total carbon in soils gives perspective on how to develop carbon sequestration strategies. The recognition that carbon sinks can evolve back to carbon sources to emit back to the atmosphere was an important consideration. Also, the concentration of carbon in soil indicates the health of land areas for growing crops successfully. 3. The direct detection of most of the elements in a wood sample in a single emission spectrum, without sample preparation, encouraged the research to use the LIBS technique for preservative treated wood coupled with use of multivariate statistical methodology. Additionally, it encouraged the researchers to try to differentiate natural woods from different parts of the country, and it was successfully demonstrated that LIBS coupled with MVA analysis could differentiate wood of different species from each other and of similar species grown in different environments based on their elemental spectra. This was a breakthrough since it revealed a systematic approach to connect elemental scarcity and abundance to either drought or typical rainfall conditions for the hardwood trees grown in specific areas. 4. Furthermore, the research progressed to reveal physiological and developmental processes contributing to biomass production such that the variation in leaf elemental composition increases our understanding of terrestrial nutrient cycles, as well as tracking the transfer of toxic elements from soils to living organisms. 5. Recently another breakthrough viz., ionomics initiated the correlation of elements to specific genes, uncovering the function that the element performed in the plant. More recently, this has been extended from plants to fungi as well as fungi growing in symbiotic relations with plants.

09 BIOMASS FUELS↗