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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 1,711 records · Page 95
All sourcesNASA NTRSDOE OSTI
NASA NTRS1982

Long term frequency stability analysis of the GPS NAVSTAR 6 Cesium clock

Time domain measurements, taken between the NAVSTAR 6 Spacecraft Vehicle (SV) and the Vandenberg Global Positioning System (GPS) Monitor Site, by a pseudo random noise receiver, were collected over an extended period of time and analyzed to estimate the long term frequency stability of the NAVSTAR 6 onboard frequency standard, referenced to the Vandenberg MS frequency standard. The technique employed separates the clock offset from the composite signal by first applying corrections for equipment delays, ionospheric delay, tropospheric delay, Earth rotation and the relativistic effect. The data are edited and smoothed using the predicted SV ephemeris to calculate the geometric delay. Then all available passes from each of the four GPS monitor stations, are collected at 1-week intervals and used to calculate the NAVSTAR orbital elements. The procedure is then completed by subtracting the corrections and the geometric delay, using the final orbital elements, from the composite signal, thus leaving the clock offset and random error.

Mccaskill, T. B.↗
DOE OSTI2024

Effects of quasiparticle-vibration coupling on Gamow-Teller strength and 𝛽 decay with the Skyrme proton-neutron finite-amplitude method

We adapt the proton-neutron finite-amplitude method, which in its original form is an efficient implementation of the Skyrme quasiparticle random phase approximation, to include the coupling of quasiparticles to like-particle phonons. The approach allows us to add beyond-quasiparticle random-phase approximation correlations to computations of Gamow-Teller strength and 𝛽-decay rates in deformed nuclei for the first time. We test the approach in several deformed isotopes for which measured strength distributions are available. Furthermore, the additional correlations dramatically improve agreement with the data, and will lead to improved global 𝛽-decay rates.

Beta decay↗
NASA NTRS1972

The effect of multiple encounters on short period comet orbits

The observed orbital elements of short period comets are found to be consistent with the hypothesis of derivation from long period comets as long as two assumptions are made. First, the distribution of short period comets has been randomized by multiple encounters with Jupiter and second, the short period comets have lower velocities of encounter with Jupiter than is generally expected. Some 16% of the observed short period comets have lower encounter velocities than is allowed mathematically using Laplace's method. This may be due to double encounter processes with Jupiter and Saturn, or as a result of prolonged encounters. The distribution of unobservable short period comets can be inferred in part from the observed comets. Many have orbits between Jupiter and Saturn with somewhat higher inclinations than those with perihelions near the earth. Debris from those comets may form the major component of the zodiacal dust.

Lowrey, B. E.↗
NASA NTRS1990

The effect of atomic oxygen on altered and coated Kapton surfaces for spacecraft applications in low earth orbit

A commercially applied silicon oxide coating on Kapton and an alternative material with Si groups on the surface were evaluated for durability with respect to atomic oxygen in both a random plasma and a directed atomic oxygen beam system. It is found that the alternative to Kapton, DuPont 93-1, is not adequately protecting to last 15 years in LEO, the desired operation time of the Space Station Freedom. The coated Kapton is considered to be promising due to the adherence of the coating and lack of extensive tearing at undercut defect sites. Fewer defects in the coating and elimination of long scratches and uncoated areas would substantially improve the durability of this material.

Rutledge, Sharon K.↗
NASA NTRS1996

A Microstructural Analysis of Orientation Variation in Epitaxial AlN on Si, Its Probable Origin, and Effect on Subsequent GaN Growth

A structural examination of aluminum nitride growth on [111] silicon was carried out using transmission electron microscopy. Electron diffraction indicates that the basal planes of the wurtzitic overlayer mimic the orientation of the close-packed planes of the substrate. However, considerable, random rotation in the basal plane and random out-of-plane tilts were evident. This article examines these issues with a structural examination of AlN and GaN/AlN on silicon and compares the findings to those reported in the literature.

GaN AlN Si epitaxial aluminum gallium nitride↗
DOE OSTI2023

Nanoscale fluctuation of stacking fault energy strengthens multi-principal element alloys

Chemical randomness and the associated energy fluctuation are essential features of multi-principal element alloys (MPEAs). Due to these features, nanoscale stacking fault energy (SFE) fluctuation is a natural and independent contribution to strengthening MPEAs. However, existing models for conventional alloys (i.e., alloys with one principal element) cannot be applied to MPEAs. The extreme values of SFEs required by such models are unknown for MPEAs, which need to calculate the nanoscale volume relevant to the SFE fluctuation. In the present work, we developed an analytic model to evaluate the strengthening effect through the SFE fluctuation, profuse in MPEAs. The model has no adjustable parameters, and all parameters can be determined from experiments and ab initio calculations. Further, this model explains available experimental observations and provides insightful guidance for designing new MPEAs based on the SFE fluctuation. It generally applies to MPEAs in random states and with chemical short-range order.

36 MATERIALS SCIENCE↗
DOE OSTI2020

An Optimized Fibril Network Morphology Enables High‐Efficiency and Ambient‐Stable Polymer Solar Cells

Abstract Morphological stability is crucially important for the long‐term stability of polymer solar cells (PSCs). Many high‐efficiency PSCs suffer from metastable morphology, resulting in severe device degradation. Here, a series of copolymers is developed by manipulating the content of chlorinated benzodithiophene‐4,8‐dione (T1‐Cl) via a random copolymerization approach. It is found that all the copolymers can self‐assemble into a fibril nanostructure in films. By altering the T1‐Cl content, the polymer crystallinity and fibril width can be effectively controlled. When blended with several nonfullerene acceptors, such as TTPTT‐4F, O‐INIC3, EH‐INIC3, and Y6, the optimized fibril interpenetrating morphology can not only favor charge transport, but also inhibit the unfavorable molecular diffusion and aggregation in active layers, leading to excellent morphological stability. The work demonstrates the importance of optimization of fibril network morphology in realizing high‐efficiency and ambient‐stable PSCs, and also provides new insights into the effect of chemical structure on the fibril network morphology and photovoltaic performance of PSCs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Generalizability analysis of tool condition monitoring ensemble machine learning models

Tool condition monitoring (TCM) is an essential research area for the optimization and automation of metal machining processes, and could help manufacturers reduce costs, production time, machine downtime, energy use, and part scrappage. However, TCM systems developed in prior studies have struggled to reach the high level of generalizability which is necessary for industrial applications. This study addresses TCM system generalizability to new machining conditions, how variations in machining and environmental conditions may be used to improve model generalizability, and ensemble machine learning techniques for TCM. Further, milling tool life experiments were conducted using various machining conditions, and the processes' sound, spindle power, and axial load signals were collected. Different machine learning models were evaluated for the prediction of tool wear levels, including four individual models and five ensemble models. Changes in cutting speed were found to display a large effect on model performance, while the chip load showed some effect, and the feed rate had little effect. A simulated noise data augmentation technique for model improvement is applied within TCM for the first time, and resulted in increased model generalizability and reduced overfitting. Across several performance metrics the extremely randomized trees ensemble machine learning model generally performed the best for this application, achieving a leave-one-group-out cross validation accuracy score of 92.4 %, a 10-fold cross validation score of 98.9 %, and an averaged accuracy across 11 generalizability tests of 87.3 %.

42 ENGINEERING↗
DOE OSTI2023

Using machine learning to predict the correlation of spectra using SDSS magnitudes as an improvement to the Locus Algorithm

The Locus Algorithm is a new technique to improve the quality of differential photometry by optimising the choices of reference stars. At the heart of this algorithm is a routine to assess how good each potential reference star is by comparing its SDSS magnitude values to those of the target star. In this way, the difference in wavelength-dependent effects of the Earth’s atmospheric scattering between target and reference can be minimised. This paper sets out a new way to estimate the quality of each reference star using machine learning. A random subset of stars from SDSS with spectra was chosen. For each one, a suitable reference star, also with a spectrum, was chosen. The correlation between the two spectra in the SDSS r band (between 550 nm and 700 nm) was taken to be the gold-standard measure of how well they match up for differential photometry. The five SDSS magnitude values for each of these stars were used as predictors. A number of supervised machine learning models were constructed on a training set of the stars and were each evaluated on a testing set. The model using Support Vector Regression had the best performance of these models. It was then tested on a final, hold-out, validation set of stars to get an unbiased measure of its performance. With an R 2 of 0.62, the SVR model presents enhanced performance for the Locus Algorithm technique.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Effects of Ionic Group Distribution on the Structure and Dynamics of Amorphous Polymer Melts

Ionizable groups tethered to a polymer backbone often associate to form ionic clusters, whose features are determined by the balance of the polymer backbone and electrostatics. These assemblies impact the dynamics of the macromolecules and their ability to transport ions. Here, using fully atomistic molecular dynamics (MD) simulations, we investigate the effects of the distribution of ionizable groups along the polymer backbone on cluster characteristics and the resulting impacts on the structure and dynamics of amorphous polymers. Particularly, we probe polystyrene sulfonates (PSS) with random, precise, and block configurations of the SO 3 – sulfonate groups along the backbone with Na + as the counterion. We find that the distribution of the ionic groups affects the shape and distribution of the clusters as well as the internal packing of the ionizable groups in the cluster and the number of unique chains that participate in each cluster, affecting the structure and the dynamics of the polymers. Furthermore, the signature of ionic clusters, observed in the static structure factor S(q) for all three distributions, is significantly more pronounced for the precise and blocky polymers compared to the random one. Remarkably, we find that the local mobility of the polymer segments is not only affected by the number and size of the clusters but also by the number of polymer chains associated with clusters.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Magnetic flux noise in superconducting qubits and the gap states continuum

In the present study we investigate the selected local aspects of the metal-induced gap states (MIGSs) at the disordered metal–insulator interface, that were previously proposed to produce magnetic moments responsible for the magnetic flux noise in some of the superconducting qubit modalities. Our analysis attempts to supplement the available studies and provide new theoretical contribution toward their validation. In particular, we explicitly discuss the behavior of the MIGSs in the momentum space as a function of the onsite energy deviation, that mimics random potential disorder at the interface in the local approximation. It is found, that when the difference between the characteristic electronic potentials in the insulator increases, the corresponding MIGSs become more localized. This effect is associated with the increasing degree of the potential disorder that was earlier observed to produce highly localized MIGSs in the superconducting qubits. At the same time, the presented findings show that the disorder-induced localization of the MIGSs can be related directly to the decay characteristics of these states as well as to the bulk electronic properties of the insulator. As a result, our study reinforces plausibility of the previous corresponding investigations on the origin of the flux noise, but also allows to draw future directions toward their better verification.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Development and Validation of Algorithms That Analyze Communicating Thermostat Data to Identify Enclosure Retrofit Opportunities

Annual energy savings of up to $\$ 4$ to $\$ 5$ billion could be achieved nationwide through basic insulation and heating system retrofits of existing homes. However, current utility energy efficiency programs are costly and challenging to scale. Customer acquisition occurs primarily through energy bill mailers, mass media, and online advertising that lack specificity about home-specific retrofit opportunities, expected energy savings, and cost-effectiveness. Specific retrofit opportunities are identified via on-site home energy assessments (HEAs) that are inconvenient to homeowners, expensive, and of variable accuracy. We developed computational algorithms that automatically analyze communicating thermostat (CT) heating data that could be used to increase the customer uptake of insulation and air sealing energy conservation measures (ECMs) by identifying homes with the most significant retrofit opportunities, estimating post-retrofit energy savings, and formulating home-specific outreach. The algorithms are based on an extended second-order grey-box model that characterizes a building’s thermal response using lumped elements, coupled with an empirical model of infiltration that accounts for both wind and stack effects. The basic parameters of the model correspond to actual physical parameters of the home, i.e., the home’s overall R-value of and the building envelope ACH50. Unlike the conventional approach, which estimates model parameters based on the best fit to the observed time-dependent room temperature, our approach derives correlations between the daily heating system runtime and temperature difference (indoor-outdoor) that are more robust to data quality issues in real-world applications. We also used HEA data for algorithm development and validation. With the help of our utility partners, Eversource and National Grid, we obtained data sets for hundreds of Massachusetts homes. For each home, these data sets included three sets of information anonymized by the utility: (1) CT data (HVAC runtime, room temperature, and, for some vendors, outdoor temperature and wind speed) collected by the CT vendor (one of three) over a heating season, (2) HEA report performed by the HEA vendor (same vendor for all homes), (3) Monthly utility gas bills coincident with the CT data (3 to 24 per home, depending on availability). For some homes, we also obtained blower-door test results. Initially, we applied the algorithms developed to homes with a single CT and then extended them to homes with two CTs by using an equivalent home approach. Finally, we developed algorithms for prediction of energy savings and a methodology of comparing our predictions with those generated by HEAs. The main technical results indicate that we can reliably identify homes with insulation and/or air sealing retrofit opportunities and provide accurate savings predictions. Our hypothesis is that the algorithms could be applied to utility energy efficiency programs to identify homes that could realize significant energy savings from insulation and/or air sealing retrofits. This information could then be used to reach out to those homes with highly customized outreach, thereby delivering increased program energy savings and cost-effectiveness. This would: Significantly increase the uptake rate of on-site HEAs, and Significantly increase the fraction of HEAs resulting in ECM implementation. To test these hypotheses, we designed and conducted a randomized controlled trial (RCT). The RCT results suggest that personal messaging leads to a two- to five-fold increase in the HEA uptake rate.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS1979

Radar error statistics for the space shuttle

Radar error statistics of C-band and S-band that are recommended for use with the groundtracking programs to process space shuttle tracking data are presented. The statistics are divided into two parts: bias error statistics, using the subscript B, and high frequency error statistics, using the subscript q. Bias errors may be slowly varying to constant. High frequency random errors (noise) are rapidly varying and may or may not be correlated from sample to sample. Bias errors were mainly due to hardware defects and to errors in correction for atmospheric refraction effects. High frequency noise was mainly due to hardware and due to atmospheric scintillation. Three types of atmospheric scintillation were identified: horizontal, vertical, and line of sight. This was the first time that horizontal and line of sight scintillations were identified.

Lear, W. M.↗
NASA NTRS1984

Intermediate-wavelength magnetic anomalies over the central Pacific

A technique to extract the intermediate wavelength anomaly field from random ship tracks has been developed and is applied to extract the field from marine survey data of the central Pacific in the band pass of 4000-400 km. The technique minimizes the effects of external field sources, secular variation, and strike aliasing. The derived data field is compared to the equivalent MAGSAT data set, and it is shown that anomalies observed in both fields are correlatable to geologic features within the oceanic lithosphere but differ in amplitude by a factor of two. Likely sources for this discrepancy are identified. It is also shown that remanent magnetization of the central Pacific seamounts produces negative magnetic anomalies which are observed at satellite altitude.

Labrecque, J. L.↗
NASA NTRS1986

Sensitivity of an atmospheric photochemistry model to chlorine perturbations including consideration of uncertainty propagation

Models of stratospheric photochemistry are generally tested by comparing their predictions for the composition of the present atmosphere with measurements of species concentrations. These models are then used to make predictions of the atmospheric sensitivity to perturbations. Here the problem of the sensitivity of such a model to chlorine perturbations ranging from the present influx of chlorine-containing compounds to several times that influx is addressed. The effects of uncertainties in input parameters, including reaction rate coefficients, cross sections, solar fluxes, and boundary conditions, are evaluated using a Monte Carlo method in which the values of the input parameters are randomly selected. The results are probability distributions for present atmosheric concentrations and for calculated perturbations due to chlorine from fluorocarbons. For more than 300 Monte Carlo runs the calculated ozone perturbation for continued emission of fluorocarbons at today's rates had a mean value of -6.2 percent, with a 1-sigma width of 5.5 percent. Using the same runs but only allowing the cases in which the calculated present atmosphere values of NO, NO2, and ClO at 25 km altitude fell within the range of measurements yielded a mean ozone depletion of -3 percent, with a 1-sigma deviation of 2.2 percent. The model showed a nonlinear behavior as a function of added fluorocarbons. The mean of the Monte Carlo runs was less nonlinear than the model run using mean value of the input parameters.

Stolarski, R. S.↗
NASA NTRS1988

Channel formation in Pb-Sn, Pb-Sb, and Pb-Sn-Sb alloy ingots and comparison with the system NH4Cl-H2O

The formation of segregation channels during the unidirectional solidification of base chilled ingots has been studied as a function of composition in binary Pb-Sn and Pb-Sb and ternary Pb-Sn-Sb alloys. The patterns of channel distribution were characterized in the binary and ternary systems and are described as functions of temperature gradients, growth rates, dendrite spacings, and interdendritic permeabilities. Channels appear to nucleate at random across a dendritic front and subsequently to interact as they propagate, decreasing in density across the front. Assuming that the interdendritic spacing is the characteristic distance for a liquid perturbation, yields critical effective Rayleigh numbers which lie within a factor of x 40 for both metallic and aqueous systems. This correlation is close, considering the sensitivity to any assumed dimension and the range of material properties involved, and is taken to support a model for channel nucleation occurring close to the dendritic growth front.

Hellawell, A.↗
NASA NTRS1991

Effect of 29 days of simulated microgravity on maximal oxygen consumption and fat-free mass of rats

Effects of a 29-days exposure to simulated microgravity on the values of maximal oxygen consumption and fat-free mass (FFM) and on the mechanical efficiency of running were investigated in rats randomly assigned to one of three regimens: head-down suspension (HDS) at 45 deg, horizontal suspension (HS), or cage control (CC). Before suspension and on days 7, 14, 21, and 28, five exercise performance tests were carried out, with measurements related to maximal oxygen consumption, treadmill run time, and mechanical efficiency. It was found that maximal oxygen consumption of both HDS and HS groups decreased significantly at day 7, after which the HDS rats remained decreased while the HS rats returned to presuspension values. Apparent mechanical efficiency in the HDS and HS groups decreased by 22-35 percent during the experimental period, and FFM decreased significantly.

Woodman, Christopher R.↗
NASA NTRS1995

Dynamic response of a pulsed Burke-Schumann diffusion flame

Turbulent flames are often envisioned as an ensemble of random vortices interacting with the combustion process. A better understanding of the vortex-flame interactions therefore would be useful in improving the modeling of turbulent diffusion flames. Substantial simplification may be made by investigating controlled interactions in a laminar flame, as opposed to random interactions in a turbulent flame. The general goals of the research project are to improve our understanding of (1) the influence of buoyancy on co-flow diffusion flames and (2) the effects of buoyancy on vortex-flame interactions in co-flow diffusion flames. As a first step toward objective (2), we conducted a joint experimental and numerical investigation of the vortex-flame interaction. Vortices were produced by mechanically pulsing the fuel flow at a low frequency, e.g., 10 Hz. Experiments were conducted using a nonflickering Burke-Schumann flame in both microgravity (mu-g) and normal gravity (1g) as a means of varying the buoyant force without modification of the pressure (i.e., density). The effects of buoyant convection may then be determined by a comparison of the mu-g and 1g results. The mu-g results may also reveal the important mechanisms which are masked or overwhelmed by buoyant convection in 1g. A numerical investigation was conducted using a validated, time-accurate numerical code to study the underlying physics during the flame interaction and to assist the interpretation of the experimental results.

Sheu, Jyh-Cherng↗