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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 1,009 records · Page 56
All sourcesNASA NTRSDOE OSTI
NASA NTRS2018

Characterization of On-Orbit GPS Transmit Antenna Patterns for Space Users

The GPS Antenna Characterization Experiment (GPS ACE) has made extensive observations of GPS L1 signals received at geosynchronous (GEO) altitude, with the objective of developing comprehensive models of the signal levels and signal performance in the GPS transmit antenna side lobes. The experiment was originally motivated by the fact that data on the characteristics and performance of the GPS signals available in GEO and other high Earth orbits was limited. The lack of knowledge of the power and accuracy of the side lobe signals on-orbit added risk to missions seeking to employ the side lobes to meet navigation requirements or improve performance. The GPS ACE Project lled that knowledge gap through a collaboration between The Aerospace Corporation and NASA Goddard Space Fight Center to collect and analyze observations from GPS side lobe transmissions to a satellite at GEO using a highly-sensitive GPS receiver installed at the ground station. The GPS ACE architecture has been in place collecting observations of the GPS constellation with extreme sensitivity for several years. This sensitivity combined with around-the-clock, all-in-view processing enabled full azimuthal coverage of the GPS transmit gain patterns over time to angles beyond 90 degrees off-boresight. Results discussed in this paper include the reconstructed transmit gain patterns, with comparisons to available pre-fight gain measurements from the GPS vehicle contractors. For GPS blocks with extensive ground measurements, the GPS ACE results show remarkable agreement with ground based measurements. For blocks without extensive ground measurements, the GPS ACE results provide the only existing assessments of the full transmit gain patterns. The paper also includes results of pseudorange deviation analysis to assess systematic errors associated with GPS side lobe signals.

space↗
NASA NTRS2018

Characterization of On-Orbit GPS Transmit Antenna Patterns for Space Users

The GPS Antenna Characterization Experiment (GPS ACE) has made extensive observations of GPS L1 signals received at geosynchronous (GEO) altitude, with the objective of developing comprehensive models of the signal levels and signal performance in the GPS transmit antenna side lobes. The experiment was originally motivated by the fact that data on the characteristics and performance of the GPS signals available in GEO and other high Earth orbits was limited. The lack of knowledge of the power and accuracy of the side lobe signals on-orbit added risk to missions seeking to employ the side lobes to meet navigation requirements or improve performance. The GPS ACE Project lled that knowledge gap through a collaboration between The Aerospace Corporation and NASA Goddard Space Fight Center to collect and analyze observations from GPS side lobe transmissions to a satellite at GEO using a highly-sensitive GPS receiver installed at the ground station. The GPS ACE architecture has been in place collecting observations of the GPS constellation with extreme sensitivity for several years. This sensitivity combined with around-the-clock, all-in-view processing enabled full azimuthal coverage of the GPS transmit gain patterns over time to angles beyond 90 degrees o -boresight. Results discussed in this paper include the reconstructed transmit gain patterns, with comparisons to available pre-fight gain measurements from the GPS vehicle contractors. For GPS blocks with extensive ground measurements, the GPS ACE results show remarkable agreement with ground based measurements. For blocks without extensive ground measurements, the GPS ACE results provide the only existing assessments of the full transmit gain patterns. The paper also includes results of pseudorange deviation analysis to assess systematic errors associated with GPS side lobe signals.

Donaldson, Jennifer E.↗
NASA NTRS2020

Characterization of On-Orbit GPS Transmit Antenna Patterns for Space Users

The GPS Antenna Characterization Experiment (GPS ACE) has made extensive observations of GPS L1 signals received at geosynchronous (GEO) altitude, with the objective of developing comprehensive models of the signal levels and signal performance in the GPS transmit antenna side lobes. The experiment was originally motivated by the fact that data on the characteristics and performance of the GPS signals available in GEO and other high Earth orbits was limited. The lack of knowledge of the power and accuracy of the side lobe signals on-orbit added risk to missions seeking to employ the side lobes to meet navigation requirements or improve performance. The GPS ACE Project lled that knowledge gap through a collaboration between The Aerospace Corporation and NASA Goddard Space Fight Center to collect and analyze observations from GPS side lobe transmissions to a satellite at GEO using a highly-sensitive GPS receiver installed at the ground station. The GPS ACE architecture has been in place collecting observations of the GPS constellation with extreme sensitivity for several years. This sensitivity combined with around-the-clock, all-in-view processing enabled full azimuthal coverage of the GPS transmit gain patterns over time to angles beyond 90 degrees o -boresight. Results discussed in this paper include the reconstructed transmit gain patterns, with comparisons to available pre-fight gain measurements from the GPS vehicle contractors. For GPS blocks with extensive ground measurements, the GPS ACE results show remarkable agreement with ground based measurements. For blocks without extensive ground measurements, the GPS ACE results provide the only existing assessments of the full transmit gain patterns. The paper also includes results of pseudorange deviation analysis to assess systematic errors associated with GPS side lobe signals.

Jennifer E Donaldson↗
NASA NTRS2020

Hexcomb Pattern Roughness Effects on Blunt Body Transition and Heating

An experimental investigation of hexcomb pattern surface roughness effects on boundary-layer transition and convective heating has been performed. Two representative entry vehicle geometries, a spherical-cap aeroshell and a sphere-cone aeroshell, were considered. Multiple cast ceramic models of each geometry were fabricated with various roughness pattern densities and depths that simulated an ablated hexcomb-structure thermal protection system. Wind tunnel testing was performed at Mach 6 over a range of Reynolds numbers sufficient to produce laminar, transitional, and turbulent flow. Aeroheating and boundary-layer transition onset data were obtained using global phosphor thermography. The experimental heating data are presented herein, as are comparisons to laminar and turbulent smooth-wall heat transfer distributions from computational flow field simulations. The experimental data were used to develop a unified boundary-layer transition correlation for both sandgrain distributed roughness and hexcomb pattern roughness.

Brian R Hollis↗
NASA NTRS2017

Using Small Unmanned Aerial Systems (sUAS) and Helium Aerostats to Perform Far-Field Radiation Pattern Measurements of High-Frequency Antennas

A new methodology is described for performing near-free space far-field radiation pattern measurements of high frequency (HF) antennas utilizing small Unmanned Aerial Systems (sUAS) and helium-filled aerostat balloons for the radar antennas onboard NASA’s planned Europa Clipper mission to Jupiter’s moon Europa. Adapted from land-based measurements, this test methodology involves hoisting the antenna to be tested above the earth to minimize ground interactions while flying a sUAS with onboard measurement package to map the far field radiation pattern. Initial results producing radiation pattern maps are promising with work remaining to fully adapt fixed VHF measurements to the dynamic HF antenna test setup.

Decrossas, Emmanuel↗
NASA NTRS2021

Revisiting the Global Patterns of Seasonal Cycle in Sea Surface Salinity

Argo profiling floats and L-band passive microwave remote sensing have significantly improved the global sampling of sea surface salinity (SSS) in the past 15 years, allowing the study of the range of SSS seasonal variability using concurrent satellite and in situ platforms. Here, harmonic analysis was applied to four 0.25° satellite products and two 1° in situ products between 2016 and 2018 to determine seasonal harmonic patterns. The 0.25° World Ocean Atlas (WOA) version 2018 was referenced to help assess the harmonic patterns from a long-term perspective based on the 3-year period. The results show that annual harmonic is the most characteristic signal of the seasonal cycle, and semiannual harmonic is important in regions influenced by monsoon and major rivers. The percentage of the observed variance that can be explained by harmonic modes varies with products, with values ranging between 50% and 72% for annual harmonic and between 15% and 19% for semiannual harmonic. The large spread in the explained variance by the annual harmonic reflects the large disparity in nonseasonal variance (or noise) in the different products. Satellite products are capable of capturing sharp SSS features on meso- and frontal scales and the patterns agree well with the WOA 2018. These products are, however, subject to the impacts of radiometric noises and are algorithm dependent. The coarser-resolution in situ products may underrepresent the full range of high-frequency small scale SSS variability when data record is short, which may have enlarged the explained SSS variance by the annual harmonic.

L-band↗
NASA NTRS2022

A Closer Look at Non-Random Patterns Within Chemistry Space for a Smaller, Earlier Amino Acid Alphabet

Recent findings, in vitro and in silico, are strengthening the idea of a simpler, earlier stage of genetically encoded proteins which used amino acids produced by prebiotic chemistry. These findings motivate a re-examination of prior work which has identified unusual properties of the set of twenty amino acids found within the full genetic code, while leaving it unclear whether similar patterns also characterize the subset of prebiotically plausible amino acids. We have suggested previously that this ambiguity may result from the low number of amino acids recognized by the definition of prebiotic plausibility used for the analysis. Here, we test this hypothesis using significantly updated data for organic material detected within meteorites, which contain several coded and non-coded amino acids absent from prior studies. In addition to confirming the well-established idea that “late” arriving amino acids expanded the chemistry space encoded by genetic material, we find that a prebiotically plausible subset of coded amino acids generally emulates the patterns found in the full set of 20, namely an exceptionally broad and even distribution of volumes and an exceptionally even distribution of hydrophobicities (quantified as logP) over a narrow range. However, the strength of this pattern varies depending on both the size and composition the library used to create a background (null model) for a random alphabet, and the precise definition of exactly which amino acids were present in a simpler, earlier code. Findings support the idea that a small sample size of amino acids caused previous ambiguous results, and further improvements in meteorite analysis, and/or prebiotic simulations will further clarify the nature and extent of unusual properties. We discuss the case of sulfur-containing amino acids as a specific and clear example and conclude by reviewing the potential impact of better understanding the chemical “logic” of a smaller forerunner to the standard amino acid alphabet.

Amino acids↗
NASA NTRSDate not supplied

Preliminary Design of a Deployable Optical Space Array Based on a Thickened Origami Flasher Pattern

Performance of space-based optics could be greatly enhanced by using deployable origami-based arrays, which can offer a large aperture size relative to their stowed volume when compared to traditional technology, thus improving imaging quality. In this work, we select, develop, and adapt the origami flasher pattern to serve as the foundation for a deployable array that shows promise for meeting stringent optical requirements. We apply a novel thickness accommodation technique, outline an approach for implementing the technique, improve stability by adjusting geometric characteristics of the pattern, and create an array of frames for housing optical elements in a co-planar configuration. Problems of non-rigid foldability in the flasher pattern are addressed. A prototype is created and tested. We find that the deployable flasher shows promise as an optical array. By following the guidelines in this work, more efficient and powerful optical arrays can be developed.

Jared Hunter↗
DOE OSTI2014

Nanopatterns by phase separation of patterned mixed polymer monolayers

Micron-size and sub-micron-size patterns on a substrate can direct the self-assembly of surface-bonded mixed polymer brushes to create nanoscale patterns in the phase-separated mixed polymer brush. The larger scale features, or patterns, can be defined by a variety of lithographic techniques, as well as other physical and chemical processes including but not limited to etching, grinding, and polishing. The polymer brushes preferably comprise vinyl polymers, such as polystyrene and poly(methyl methacrylate).

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2015

Replication of patterned thin-film structures for use in plasmonics and metamaterials

The present invention provides templating methods for replicating patterned metal films from a template substrate such as for use in plasmonic devices and metamaterials. Advantageously, the template substrate is reusable and can provide plural copies of the structure of the template substrate. Because high-quality substrates that are inherently smooth and flat are available, patterned metal films in accordance with the present invention can advantageously provide surfaces that replicate the surface characteristics of the template substrate both in the patterned regions and in the unpatterned regions.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2015

Sequential Pattern Mining of Electronic Healthcare Reimbursement Claims: Experiences and Challenges in Uncovering How Patients are Treated by Physicians

We examine the use of electronic healthcare reimbursement claims (EHRC) for analyzing healthcare delivery and practice patterns across the United States (US). We show that EHRCs are correlated with disease incidence estimates published by the Centers for Disease Control. Further, by analyzing over 1 billion EHRCs, we track patterns of clinical procedures administered to patients with autism spectrum disorder (ASD), heart disease (HD) and breast cancer (BC) using sequential pattern mining algorithms. Our analyses reveal that in contrast to treating HD and BC, clinical procedures for ASD diagnoses are highly varied leading up to and after the ASD diagnoses. The discovered clinical procedure sequences also reveal significant differences in the overall costs incurred across different parts of the US, indicating a lack of consensus amongst practitioners in treating ASD patients. We show that a data-driven approach to understand clinical trajectories using EHRC can provide quantitative insights into how to better manage and treat patients. Based on our experience, we also discuss emerging challenges in using EHRC datasets for gaining insights into the state of contemporary healthcare delivery and practice in the US.

Pullum, Laura L↗
DOE OSTI2015

Constructing Patient Specific Clinical Trajectories from Electronic Healthcare Reimbursement Claims using Sequential Pattern Mining

We examine the use of electronic healthcare reimbursement claims (EHRC) for analyzing healthcare delivery and practice patterns across the United States (US). By analyzing over 1 billion EHRCs, we track patterns of clinical procedures administered to patients with heart disease (HD) using sequential pattern mining algorithms. Our analyses reveal that the clinical procedures performed on HD patients are highly varied leading up to and after the primary diagnosis. The discovered clinical procedure sequences reveal significant differences in the overall costs incurred across different parts of the US, indicating significant heterogeneity in treating HD patients. We show that a data-driven approach to understand patient specific clinical trajectories constructed from EHRC can provide quantitative insights into how to better manage and treat patients.

Pullum, Laura L↗
DOE OSTI2016

Photovoltaic cell with nano-patterned substrate

A photovoltaic solar cell comprises a nano-patterned substrate layer. A plurality of nano-windows are etched into an intermediate substrate layer to form the nano-patterned substrate layer. The nano-patterned substrate layer is positioned between an n-type semiconductor layer composed of an n-type semiconductor material and a p-type semiconductor layer composed of a p-type semiconductor material. Semiconductor material accumulates in the plurality of nano-windows, causing a plurality of heterojunctions to form between the n-type semiconductor layer and the p-type semiconductor layer.

14 SOLAR ENERGY↗
DOE OSTI2017

VIPRAM_L1CMS: a 2-Tier 3D Architecture for Pattern Recognition for Track Finding

In HEP tracking trigger applications, flagging an individual detector hit is not important. Rather, the path of a charged particle through many detector layers is what must be found. Moreover, given the increased luminosity projected for future LHC experiments, this type of track finding will be required within the Level 1 Trigger system. This means that future LHC experiments require not just a chip capable of high-speed track finding but also one with a high-speed readout architecture. VIPRAM_L1CMS is 2-Tier Vertically Integrated chip designed to fulfill these requirements. It is a complete pipelined Pattern Recognition Associative Memory (PRAM) architecture including pattern recognition, result sparsification, and readout for Level 1 trigger applications in CMS with 15-bit wide detector addresses and eight detector layers included in the track finding. Pattern recognition is based on classic Content Addressable Memories with a Current Race Scheme to reduce timing complexity and a 4-bit Selective Precharge to minimize power consumption. VIPRAM_L1CMS uses a pipelined set of priority-encoded binary readout structures to sparsify and readout active road flags at frequencies of at least 100MHz. VIPRAM_L1CMS is designed to work directly with the Pulsar2b Architecture.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

Activity Time-Use Patterns and Experienced Satisfaction: Travel Behavioral Dynamics from the 2010–2013 American Time-Use Survey Data

Central to the theory of activity-based approaches is the role of time-use and its impacts on various decision processes related to individual activity-travel patterns, thereby determining ones’ daily well-being. This research aims at quantifying and investigating the underlying correlation of time-use and happiness using the repeated cross-section data from the 2010-2013 American Time Use Survey Well-Being module. The survey specifically records reported levels of activity satisfaction as measured through – happiness, meaningfulness, tiredness, sadness and stress experienced from activity participation. Using these scores, we first construct a composite degree of activity satisfaction that a person experiences using latent class cluster analysis. A series of regression models are then estimated to jointly analyze episodic duration and satisfaction separately for each of years from 2010-2013, by controlling for socioeconomics, household lifecycle stages (29-groups based on age, gender, marital status and presence of children), activity characteristics and global life and health assessment measures. Overall, model estimation results reveal a strong negative correlation between episodic duration and happiness from individual activity engagement patterns. This correlation pattern is temporally stable for the years 2010-2013, with minor variations. Results also suggest that household lifecycle stage has a major impact on activity time-use and satisfaction behavior. Further, single parent and younger couples (25 years to 45 years) with children are more likely to engage in longer and less happy episodes due to family commitments. The model findings also show a strong correlation between health conditions and activity happiness.

Ravulaparthy, Srinath↗
DOE OSTI2020

Optically enhanced patternable photosensitivity via oxygen excitation

A method is disclosed for performing a three dimensional (3D) printing process. The method involves generating a primary light beam having a wavelength sufficient to initiate polymerization of a photoresin, and patterning the primary light beam into a patterned primary beam. The patterned primary beam may be directed toward an ultraviolet (UV) or visible light sensitive photoresin to initiate polymerization of select areas of the photoresin. The photoresin may be illuminated with a secondary light beam having a wavelength of about 765 nm to stimulate triplet oxygen into singlet oxygen, to thus control oxygen inhibition in additional areas bordering the select areas, to control polymerization inhibition in the additional areas bordering the select areas.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Examining Perceptual Luminance Uniformity of Simulated Luminaire Patterns

Luminaire luminance uniformity is an important aspect that can affect perceived lighting quality, discomfort glare, and efficacy. While several metrics have been proposed to characterize luminance uniformity, previous studies have shown that current metrics such as Max:Min or Avg:Min luminance ratios can be insensitive to important differences in luminance gradient that may affect perceived uniformity. In an attempt to resolve this issue, previous studies incorporated a contrast sensitivity function for the human eye based on spatial frequency, such as in the UHVS metric; however, this metric has not been comprehensively studied in relation to perceived uniformity ratings. The study presented in this paper aimed to examine the relationship between the UHVS metric and perceived uniformity ratings. Specifically, the study used a web-based questionnaire that presented simulated luminance patterns and asked participants to assess uniformity using a two-alternative forced-choice procedure. Responses were collected and analyzed from 94 participants. The results showed a significant correlation and relationship between the UHVS metric and perceived uniformity. However, comparisons between patterns that had similar UHVS and between patterns that had larger differences in UHVS did not yield consistent results. These results suggest that the UHVS metric might be used for general guidance but may warrant further studies to better understand its sensitivity and improve its alignment with perceived uniformity ratings.

Abboushi, Belal K.↗
DOE OSTI2020

Deep Learning Prediction of Interspecies Interactions from Self-organized Spatiotemporal Patterns of Co-evolving Organisms

Microorganisms colonizing natural habits such as soils co-evolve to form specific spatial patterns through interspecies interactions. These self-organized patterns are a key ecological phenotype, which provides critical information on their interaction mechanisms. However, conventional network inference techniques that analyze species population data in bulk have yet to be extended to account for such spatial heterogeneity. Here we proposed supervised deep learning as a new network inference tool for predicting interspecies interactions from spatiotemporal patterns of microbial evolution. Due to lack of biological imaging data that can be used for training deep learning networks, we used in silico data generated from high-fidelity agent-based models to determine model structure and parameters. Even though networks were trained under simple configurations where interaction coefficients are assumed to be spatially invariant, we demonstrated that the resulting model can be utilized to successfully predict spatial variation of interactions in more complex domains (i.e., configured with a context-dependent mixture of interaction coefficients) as well as in simple domains without further training. In the further test against real biological data obtained through imaging experiments of a binary consortium (Pseudomonas fluorescens and a mutant of Escherichia coli), our model also predicted the dramatic shifts in interactions of the two organisms across different environmental contexts. Through various successful demonstrations in this work, the combined use of the agent-based model and machine learning algorithm provides a means to use new type of data - microscopic images - for extracting microbial interactions, therefore presenting itself as a useful tool for the analysis of more complex microbial community interactions.

Lee, Joon-Yong↗