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NASA NTRS2003

A Study of Near to Far Fields of JPL Deep Space Network (DSN) Antennas for RFI Analysis

This paper addresses the issue of calculating the gain and power distribution of DSN antennas in the Fresnel (middle zone) and Fraunhofer (far zone) as a function of the distance from the DSN antenna and the off-boresight angle. Calculating the near and mid fields of DSN antennas are of interest in the receive mode where the transmitting signals from nearby flying objects such as helicopters and airplanes transmitting in the DSN frequency range, interfere with the operation of sensitive RF receiving system of the DSN antennas, and in the transmit mode where fields from high-powered DSN antennas interfere with receivers on nearby flying objects such as helicopters or other systems. Computing the exact fields of a large DSN antenna is, in general, a very complicated and arduous task. Even far-field calculations, which are less complicated compared to near and mid zone fields, take considerable computer time. These calculations become even more involved and time-consuming in very near field and back field regions. We provide two approaches for addressing the radio frequency interference (RFI) issue. In this paper, actual fields in mid and far zones are calculated using a relatively simple formulation that is accurate enough for the purposes of RFI analysis. In a future paper, we study and develop simple reference models that provide upper limit bounds or envelopes of the far field patterns as a function of the antenna diameter and frequency, which can be used for obtaining the field at any given point in space.

aperture antennas↗

NASA NTRS2016

Earth Science Data Analytics: Preparing for Extracting Knowledge from Information

Data analytics is the process of examining large amounts of data of a variety of types to uncover hidden patterns, unknown correlations and other useful information. Data analytics is a broad term that includes data analysis, as well as an understanding of the cognitive processes an analyst uses to understand problems and explore data in meaningful ways. Analytics also include data extraction, transformation, and reduction, utilizing specific tools, techniques, and methods. Turning to data science, definitions of data science sound very similar to those of data analytics (which leads to a lot of the confusion between the two). But the skills needed for both, co-analyzing large amounts of heterogeneous data, understanding and utilizing relevant tools and techniques, and subject matter expertise, although similar, serve different purposes. Data Analytics takes on a practitioners approach to applying expertise and skills to solve issues and gain subject knowledge. Data Science, is more theoretical (research in itself) in nature, providing strategic actionable insights and new innovative methodologies. Earth Science Data Analytics (ESDA) is the process of examining, preparing, reducing, and analyzing large amounts of spatial (multi-dimensional), temporal, or spectral data using a variety of data types to uncover patterns, correlations and other information, to better understand our Earth. The large variety of datasets (temporal spatial differences, data types, formats, etc.) invite the need for data analytics skills that understand the science domain, and data preparation, reduction, and analysis techniques, from a practitioners point of view. The application of these skills to ESDA is the focus of this presentation. The Earth Science Information Partners (ESIP) Federation Earth Science Data Analytics (ESDA) Cluster was created in recognition of the practical need to facilitate the co-analysis of large amounts of data and information for Earth science. Thus, from a to advance science point of view: On the continuum of ever evolving data management systems, we need to understand and develop ways that allow for the variety of data relationships to be examined, and information to be manipulated, such that knowledge can be enhanced, to facilitate science. Recognizing the importance and potential impacts of the unlimited ways to co-analyze heterogeneous datasets, now and especially in the future, one of the objectives of the ESDA cluster is to facilitate the preparation of individuals to understand and apply needed skills to Earth science data analytics. Pinpointing and communicating the needed skills and expertise is new, and not easy. Information technology is just beginning to provide the tools for advancing the analysis of heterogeneous datasets in a big way, thus, providing opportunity to discover unobvious scientific relationships, previously invisible to the science eye. And it is not easy It takes individuals, or teams of individuals, with just the right combination of skills to understand the data and develop the methods to glean knowledge out of data and information. In addition, whereas definitions of data science and big data are (more or less) available (summarized in Reference 5), Earth science data analytics is virtually ignored in the literature, (barring a few excellent sources).

data analytics↗

DOE OSTI2020

GPU-Based Static Data-Flow Analysis for Fast and Scalable Android App Vetting

Many popular vetting tools for Android applications use static code analysis techniques. In particular, Interprocedural Data-Flow Graph (IDFG) construction is the computation at the core of Android static data-flow analysis and consumes most of the analysis time. Many analysis tools use a worklist algorithm, an iterative fixed-point approach, to construct the IDFG. In this paper, we observe that a straightforward GPU parallelization of the worklist algorithm leads to significant underutilization of the GPU resources. We identify four performance bottlenecks, namely, frequent dynamic memory allocations, high branch divergence, workload imbalance, and irregular memory access patterns. Accordingly, we propose GDroid, a GPU-based worklist algorithm implementation with multiple fine-grained optimizations tailored to common characteristics of Android applications. The optimizations considered are: matrix-based data structure, memory access-based node grouping, and worklist merging. Our experimental evaluation, performed on 1000 Android applications, shows that the proposed optimizations are beneficial to performance, and GDroid can achieve up to 128X speedups against a plain GPU implementation.

Android security↗

NASA NTRS1994

Profile analysis of after-effects experienced during exposure to several virtual reality environments

Motion sickness symptoms are an unwanted by-product of exposure to virtual environments. This problem is not new and was reported in the early flight simulators and experiments on ego motions and vection. The cardinal symptom of motion sickness is, of course, vomiting, but this symptom is ordinarily preceded by a variety of other symptoms. In his classic studies of motion sickness conducted before and during World War II, G. R. Wendt introduced a three point scale to score motion sickness beyond a vomit/no vomit dichotomy. Later, Navy scientists developed a Motion Sickness Questionnaire (MSQ), originally for use in a slowly rotating room. In the last 20 years the MSQ has been used in a series of studies of air, sea, and space sickness. Only recently, however, has it been appreciated that symptom patterns in the MSQ are not uniform but vary with the way sickness is induced. In seasickness, for example, nausea is the most prominent symptom. In Navy simulators, however, the most common symptom is eye strain, especially when cathode ray tubes are employed in the simulation. The latter result was obtained in a survey of over 1,500 pilot exposures. Using this database, Essex scientists conducted a factor analysis of the MSQ. We found that signs and symptoms of motion sickness fell mainly into three clusters: 1) oculomotor disturbance, 2) nausea and related neurovegetative problems, and 3) disorientation, ataxia, and vertigo. We have since rescored the MSQ results obtained in Navy simulators in terms of these three components. We have also compared these and other profiles obtained from three different vitual reality systems to profiles obtained in sea sickness, space sickness, and alcohol intoxication. We will show examples of these various profiles and point out simularities and differences among them which indicate aspects of what might be called 'virtual-reality sickness'.

Kennedy, Robert S.↗

DOE OSTI2020

Metabolic Response in Patients With Post-treatment Lyme Disease Symptoms/Syndrome

Abstract Background Post-treatment Lyme disease symptoms/syndrome (PTLDS) occurs in approximately 10% of patients with Lyme disease following antibiotic treatment. Biomarkers or specific clinical symptoms to identify patients with PTLDS do not currently exist and the PTLDS classification is based on the report of persistent, subjective symptoms for ≥6 months following antibiotic treatment for Lyme disease. Methods Untargeted liquid chromatography–mass spectrometry metabolomics was used to determine longitudinal metabolic responses and biosignatures in PTLDS and clinically cured non-PTLDS Lyme patients. Evaluation of biosignatures included (1) defining altered classes of metabolites, (2) elastic net regularization to define metabolites that most strongly defined PTLDS and non-PTLDS patients at different time points, (3) changes in the longitudinal abundance of metabolites, and (4) linear discriminant analysis to evaluate robustness in a second patient cohort. Results This study determined that observable metabolic differences exist between PTLDS and non-PTLDS patients at multiple time points. The metabolites with differential abundance included those from glycerophospholipid, bile acid, and acylcarnitine metabolism. Distinct longitudinal patterns of metabolite abundance indicated a greater metabolic variability in PTLDS versus non-PTLDS patients. Small numbers of metabolites (6 to 40) could be used to define PTLDS versus non-PTLDS patients at defined time points, and the findings were validated in a second cohort of PTLDS and non-PTLDS patients. Conclusions These data provide evidence that an objective metabolite-based measurement can distinguish patients with PTLDS and help understand the underlying biochemistry of PTLDS.

Immunology↗

NASA NTRS1987

Surface inspection: Research and development

Surface inspection techniques are used for process learning, quality verification, and postmortem analysis in manufacturing for a spectrum of disciplines. First, trends in surface analysis are summarized for integrated circuits, high density interconnection boards, and magnetic disks, emphasizing on-line applications as opposed to off-line or development techniques. Then, a closer look is taken at microcontamination detection from both a patterned defect and a particulate inspection point of view.

Batchelder, J. S.↗

NASA NTRS1997

Automated navigation assessment for earth survey sensors using island targets

An automated method has been developed for performing navigation assessment on satellite-based Earth sensor data. The method utilizes islands as targets which can be readily located in the sensor data and identified with reference locations. The essential elements are an algorithm for classifying the sensor data according to source, a reference catalog of island locations, and a robust pattern-matching algorithm for island identification. The algorithms were developed and tested for the Sea-viewing Wide Field-of-view Sensor (SeaWiFS), an ocean color sensor. This method will allow navigation error statistics to be automatically generated for large numbers of points, supporting analysis over large spatial and temporal ranges.

Patt, Frederick S.↗

NASA NTRS1997

An Automated Method for Navigation Assessment for Earth Survey Sensors Using Island Targets

An automated method has been developed for performing navigation assessment on satellite-based Earth sensor data. The method utilizes islands as targets which can be readily located in the sensor data and identified with reference locations. The essential elements are an algorithm for classifying the sensor data according to source, a reference catalogue of island locations, and a robust pattern-matching algorithm for island identification. The algorithms were developed and tested for the Sea-viewing Wide Field-of-view Sensor (SeaWiFS), an ocean colour sensor. This method will allow navigation error statistics to be automatically generated for large numbers of points, supporting analysis over large spatial and temporal ranges.

Patt, F. S.↗

DOE OSTI2021

Structure Perception in 3D Point Clouds: Preprint

Understanding human perception is critical to the design of ef- fective visualizations. The relative benefits of using 2D versus 3D techniques for data visualization is a complex decision space, with varying levels of uncertainty and disagreement in both the liter- ature and in practice. This study aims to add easily reproducible, empirical evidence on the role of depth cues in perceiving structures or patterns in 3D point clouds. We describe a method to synthesize a 3D point cloud that contains a 3D structure, where 2D projec- tions of the data strongly resemble a Gaussian distribution. We performed a within-subjects structure identification study with 128 participants that compared scatterplot matrices (canonical 2D projections) and 3D scatterplots under three types of motion: rota- tion, xy-translation, and z-translation. We found that users could consistently identify three separate hidden structures under ro- tation, while those structures remained hidden in the scatterplot matrices and under translation. This work contributes a set of 3D point clouds that provide definitive examples of 3D patterns per- ceptible in 3D scatterplots under rotation but imperceptible in 2D scatterplots.

data analysis↗

DOE OSTI2022

Electrifying Road Trips to and from National Parks in the Western United States

We evaluate charging infrastructure requirement for electrified long-distance travels to/from national parks in the Western U.S. We conduct a high-resolution spatial and temporal analysis of road trips in the region, accounting for detailed travel volume and pattern, the type of electric vehicles, heterogeneous energy consumption rates depending on driving conditions, charging technology (e.g., power and speed), and charging behavior. The scope includes on-route (or way-point) charging as well as destination charging (in national parks). We estimate the locations and sizes of required charging stations in the entire Western U.S. to enable electrified road trips to/from national parks. We also examine environmental justice and energy equity aspects of projected charging infrastructure (for national parks) in the context of the overall vehicle electrification and charging infrastructure build-out.

ADVANCED PROPULSION SYSTEMS,ENERGY PLANNING, POLIC↗

DOE OSTI2020

Morphological Characters Can Strongly Influence Early Animal Relationships Inferred from Phylogenomic Data Sets

There are considerable phylogenetic incongruencies between morphological and phylogenomic data for the deep evolution of animals. This has contributed to a heated debate over the earliest-branching lineage of the animal kingdom: the sister to all other Metazoa (SOM). Here, we use published phylogenomic data sets ($\sim $45,000–400,000 characters in size with $\sim $15–100 taxa) that focus on early metazoan phylogeny to evaluate the impact of incorporating morphological data sets ($\sim $15–275 characters). We additionally use small exemplar data sets to quantify how increased taxon sampling can help stabilize phylogenetic inferences. We apply a plethora of common methods, that is, likelihood models and their “equivalent” under parsimony: character weighting schemes. Our results are at odds with the typical view of phylogenomics, that is, that genomic-scale data sets will swamp out inferences from morphological data. Instead, weighting morphological data 2–10$\times $ in both likelihood and parsimony can in some cases “flip” which phylum is inferred to be the SOM. This typically results in the molecular hypothesis of Ctenophora as the SOM flipping to Porifera (or occasionally Placozoa). However, greater taxon sampling improves phylogenetic stability, with some of the larger molecular data sets ($>$200,000 characters and up to $\sim $100 taxa) showing node stability even with $\geqq100\times $ upweighting of morphological data. Accordingly, our analyses have three strong messages. 1) The assumption that genomic data will automatically “swamp out” morphological data is not always true for the SOM question. Morphological data have a strong influence in our analyses of combined data sets, even when outnumbered thousands of times by molecular data. Morphology therefore should not be counted out a priori. 2) We here quantify for the first time how the stability of the SOM node improves for several genomic data sets when the taxon sampling is increased. 3) The patterns of “flipping points” (i.e., the weighting of morphological data it takes to change the inferred SOM) carry information about the phylogenetic stability of matrices. The weighting space is an innovative way to assess comparability of data sets that could be developed into a new sensitivity analysis tool.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRS2001

High Earth Orbit Design for Lunar-Assisted Medium Class Explorer Missions

This study investigates the application of high-Earth orbit (HEO) trajectories to missions requiring long on-target integration times, avoidance of the Earth's radiation belt, and minimal effects of Earth and Lunar shadow periods which could cause thermal/mechanical stresses on the science instruments. As used here, a HEO trajectory is a particular solution to the restricted three-body problem in the Earth-Moon system with the orbit period being either 1/2 of, or 1/4 of, the lunar sidereal period. A primary mission design goal is to find HEO trajectories where, for a five-year mission duration, the minimum perigee radius is greater than seven Earth radii (R(sub E)). This minimum perigee radius is chosen so that, for the duration of the mission, the perigee is always above the relatively heavily populated geosynchronous radius of 6.6 R(sub E). A secondary goal is to maintain as high an ecliptic inclination as possible for the duration of the mission to keep the apsis points well out of the Ecliptic plane. Mission design analysis was completed for launch dates in the month of June 2003, using both direct transfer and phasing loop transfer techniques, to a lunar swingby for final insertion into a HEO. Also provided are analysis results of eclipse patterns for the trajectories studied, as well as the effects of launch vehicle errors and launch delays.

McGiffin, Daniel A.↗

NASA NTRS2018

A Dispersive Backend Design for the 'Double-Fourier' Interferometer BETTII

BETTII (Balloon Experimental Twin Telescope for Infra-red Interferometry) is designed to provide high angular resolution spectroscopic data in the far-infrared (FIR) wavelengths. The most significant limitation for BETTII is its sensitivity; obtaining spectral signal-to-noise ratio greater than 5 in less than 10 minutes requires sources greater than 13 Janskys (Jy). One possible way to improve the signal-to-noise ratio (SNR) for future BETTII flights is by reducing the spectral bandwidth post beam-combination. This involves using a dispersive element to spread out a polychromatic point source PSF (Point Spread Function) on the detector array, such that each pixel corresponds to a small fraction of the bandwidth. This results in a broader envelope of the interferometric fringe pattern allowing more fringes to be detected, and thereby improving the spectral SNR. Here we present the analysis and optical design of the dispersive backend, discussing the tradeoffs and how it can be combined with the existing design.

Dhabal, Arnab↗

DOE OSTI2024

Quantile regression-enriched event modeling framework for dropout analysis in high-temperature superconductor manufacturing

High-temperature superconductor (HTS) tapes have shown promising characteristics of high critical current, which are prerequisites for applications in high-field magnets. Due to the unstable growth conditions in the HTS manufacturing process, however, the frequent occurrences of dropouts in the critical current impede the consistent performance of HTS tapes. To manufacture HTS tapes with large scale, high yield, and uniform performance, it is essential to develop novel data analysis approaches for modeling the dropouts and identifying the related important process parameters. Conventional methods for modeling recurrent events, such as the point process, require the extraction of events from quality measurements. As the critical current is a continuous process, it may not comprehensively represent the drop patterns by transforming the time-series measurements into a set of events. Here, to solve this issue, we develop a novel quantile regression-enriched event modeling (QREM) framework that integrates the non-homogeneous Poisson process for modeling the occurrence of dropouts and the quantile regression for capturing the drop patterns. By incorporating the feature selection and regularization, the proposed framework identifies a set of significant process parameters that can potentially cause the dropouts of HTS tapes. The proposed method is tested on real HTS tapes produced using an advanced manufacturing process, successfully identifying important parameters that influence dropout events including the substrate temperature and voltage. The results demonstrate that the proposed QREM method outperforms the standard point process in predicting the occurrence of dropouts.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

NASA NTRS1982

Study of atmospheric diffusion using LANDSAT

The parameters of diffusion patterns of atmospheric pollutants under different conditions were investigated for use in the Gaussian model for calculation of pollution concentration. Value for the divergence pattern of concentration distribution along the Y axis were determined using LANDSAT images. Multispectral scanner images of a point source plume having known characteristics, wind and temperature data, and cloud cover and solar elevation data provided by LANDSAT, were analyzed using the 1-100 system for image analysis. These measured values are compared with pollution transport as predicted by the Pasquill-Gifford, Juelich, and Hoegstroem atmospheric models.

Torsani, J. A.↗

NASA NTRS2008

Dynamic Measurement of Temperature, Velocity, and Density in Hot Jets Using Rayleigh Scattering

A molecular Rayleigh scattering technique was utilized to measure time-resolved gas temperature, velocity, and density in unseeded gas flows at sampling rates up to 10 kHz. A high power continuous-wave (cw) laser beam was focused at a point in an air flow field and Rayleigh scattered light was collected and fiber-optically transmitted to a Fabry-Perot interferometer for spectral analysis. Photomultipler tubes operated in the photon counting mode allowed high frequency sampling of the total signal level and the circular interference pattern to provide time-resolved density, temperature, and velocity measurements. Mean and rms velocity and temperature, as well as power spectral density calculations, are presented for measurements in a hydrogen-combustor heated jet facility with a 50.8-mm diameter nozzle at the NASA Glenn Research Center (GRC). The Rayleigh measurements are compared with particle image velocimetry data and CFD predictions. This technique is aimed at aeronautics research related to identifying noise sources in free jets, as well as applications in supersonic and hypersonic flows where measurement of flow properties, including mass flux, is required in the presence of shocks and ionization occurrence.

Mielke, Amy F.↗

DOE OSTI2021

Exploring few and single layer CrPS 4 with near-field infrared spectroscopy

Abstract We combine synchrotron-based near-field infrared spectroscopy and first principles lattice dynamics calculations to explore the vibrational response of CrPS 4 in bulk, few-, and single-layer form. Analysis of the mode pattern reveals a C 2 polar + chiral space group, no symmetry crossover as a function of layer number, and a series of non-monotonic frequency shifts in which modes with significant intralayer character harden on approach to the ultra-thin limit whereas those containing interlayer motion or more complicated displacement patterns soften and show inflection points or steps. This is different from MnPS 3 where phonons shift as 1/size 2 and are sensitive to the three-fold rotation about the metal center that drives the symmetry crossover. We discuss these differences as well as implications for properties such as electric polarization in terms of presence or absence of the P–P dimer and other aspects of local structure, sheet density, and size of the van der Waals gap.

36 MATERIALS SCIENCE↗

NASA NTRS2009

Dynamic Measurement of Temperature, Velocity, and Density in Hot Jets Using Rayleigh Scattering

A molecular Rayleigh scattering technique is utilized to measure gas temperature, velocity, and density in unseeded gas flows at sampling rates up to 10 kHz, providing fluctuation information up to 5 kHz based on the Nyquist theorem. A high-power continuous-wave laser beam is focused at a point in an air flow field and Rayleigh scattered light is collected and fiber-optically transmitted to a Fabry-Perot interferometer for spectral analysis. Photomultiplier tubes operated in the photon counting mode allow high-frequency sampling of the total signal level and the circular interference pattern to provide dynamic density, temperature, and velocity measurements. Mean and root mean square velocity, temperature, and density, as well as power spectral density calculations, are presented for measurements in a hydrogen-combustor heated jet facility with a 50.8-mm diameter nozzle at NASA John H. Glenn Research Center at Lewis Field. The Rayleigh measurements are compared with particle image velocimetry data and computational fluid dynamics predictions. This technique is aimed at aeronautics research related to identifying noise sources in free jets, as well as applications in supersonic and hypersonic flows where measurement of flow properties, including mass flux, is required in the presence of shocks and ionization occurrence.

Mielke, Amy F.↗