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At least 631 records · Page 35

Mercury - Thermal emission at radio wavelengths. I - 3.3- and 28-mm observed brightness temperatures and periodicities therein

The thermal radio emission from Mercury at 3.3 mm and 28 mm was measured over a period of several years, and the results of a statistical analysis of the data are reported. The disk-average brightness temperature is reported as a function of longitude, and other periodicities are reported. The range of values of the thermophysical parameters is constrained by comparing the data with models.

Epstein, E. E.↗

Modeling the interactions between the ocean and the environment for microwave radar sensing

An extensive set of X-band microwave backscatter measurements has been analyzed to determine its dependence on winds near the surface, atmospheric stability, and long-wave slopes. These radar measurements, made from a tower in the Gulf of Mexico, were performed in conjunction with an extensive set of simultaneous environmental measurements. The CW microwave system operated at an incidence angle of 45 deg, with antennas directed into winds and waves. Model functions for the radar cross section (RCS) and the modulation transfer function (MTF) are developed that depend on the geophysical variables, including wind stress. Statistical analysis shows that these models functions yield a significant smaller error when fit to the RCS data than a simple wind-speed function displays. A Taylor-series expansion of the returned power from a small area provides a unified function that demonstrates the complementary roles of wave slope and atmospheric fluctuations on both the RCS, the MTF, and the coherence. The issue of linearity of the MTF is addressed with this data set, yielding evidence that this is a valid assumption. These results have direct application to the remote sensing of the mean and fluctuating winds, and the wave spectrum with coherent and incoherent active radars.

Weissman, David E.↗

Rdesign: A data dictionary with relational database design capabilities in Ada

Data Dictionary is defined to be the set of all data attributes, which describe data objects in terms of their intrinsic attributes, such as name, type, size, format and definition. It is recognized as the data base for the Information Resource Management, to facilitate understanding and communication about the relationship between systems applications and systems data usage and to help assist in achieving data independence by permitting systems applications to access data knowledge of the location or storage characteristics of the data in the system. A research and development effort to use Ada has produced a data dictionary with data base design capabilities. This project supports data specification and analysis and offers a choice of the relational, network, and hierarchical model for logical data based design. It provides a highly integrated set of analysis and design transformation tools which range from templates for data element definition, spreadsheet for defining functional dependencies, normalization, to logical design generator.

Lekkos, Anthony A.↗

An empirical comparison of software fault tolerance and fault elimination

Reliability is an important concern in the development of software for modern systems. Some researchers have hypothesized that particular fault-handling approaches or techniques are so effective that other approaches or techniques are superfluous. The authors have performed a study that compares two major approaches to the improvement of software, software fault elimination and software fault tolerance, by examination of the fault detection obtained by five techniques: run-time assertions, multi-version voting, functional testing augmented by structural testing, code reading by stepwise abstraction, and static data-flow analysis. This study has focused on characterizing the sets of faults detected by the techniques and on characterizing the relationships between these sets of faults. The results of the study show that none of the techniques studied is necessarily redundant to any combination of the others. Further results reveal strengths and weakness in the fault detection by the techniques studied and suggest directions for future research.

Shimeall, Timothy J.↗

Determination of cloud optical depth with the multiple field of view sun photometer

An approach to determining cloud optical depth is presented which utilizes a multiple-field-of-view sun photometer, along with modeled behavior of transmittance ratios as a function of the field of view, to infer the optical depth. The data used in the analysis were collected during the FIRE Stratocumulus IFO, which took place from July 15 to 17, 1987. Values which were taken within an hour of local solar noon are presented and compared with the values computed for mu sub 0 = 1.0. The zenith angle for the measurements was between 11 and 18 deg. It is found that this method of inferring the optical depth indicates most clouds with optical depths within these limits. The measured curves have a slightly different shape than do the modeled ratios.

Hein, Paul F.↗

Processing parameters associated with scale-up of balloon film production

A method is set forth for assessing strain-rate profiles that can be used to develop a scale-up theory for blown-film extrusion. Strain rates are evaluated by placing four ink dots on the stalk of an extruded bubble to follow the displacements of the dots as a function of time. The instantaneous Hencky strain is obtained with the displacement data and plotted for analysis. Specific attention is given to potential sources of error in the distance measurements and corrections for these complex bubble geometries. The method is shown to be effective for deriving strain-rate data related to different processing parameters for the production of balloon film. The strain rates can be compared to frostline height, blow-up ratio, and take-up ratio to optimize these processing variables.

Simpson, D. M.↗

ACTS data center

Viewgraphs on ACTS Data Center status report are included. Topics covered include: ACTS Data Center Functions; data flow overview; PPD flow; RAW data flow; data compression; PPD distribution; RAW Data Archival; PPD Audit; and data analysis.

Syed, Ali↗

Operational Weight Estimations of Commercial Jet Transport Aircraft

In evaluating current or proposed commercial transport airplanes, there has not been available a ready means to determine weights so as to compare airplanes within this particular class. This paper describes the development of and presents such comparative tools. The major design characteristics of current American jet transport airplanes were collected, and these data were correlated by means of regression analysis to develop weight relationships for these airplanes as functions of their operational requirements. The characteristics for 23 airplanes were assembled and examined in terms of the effects of the number of people carried, the cargo load, and the operating range. These airplane characteristics were correlated for the airplanes as one of three subclasses, namely the small, twin-engine jet transport, the conventional three- and four-engine jets, and the new wide-body jets.

Anderson, Joseph L.↗

Flight Test of an Adaptive Configuration Optimization System for Transport Aircraft

A NASA Dryden Flight Research Center program explores the practical application of real-time adaptive configuration optimization for enhanced transport performance on an L-1011 aircraft. This approach is based on calculation of incremental drag from forced-response, symmetric, outboard aileron maneuvers. In real-time operation, the symmetric outboard aileron deflection is directly optimized, and the horizontal stabilator and angle of attack are indirectly optimized. A flight experiment has been conducted from an onboard research engineering test station, and flight research results are presented herein. The optimization system has demonstrated the capability of determining the minimum drag configuration of the aircraft in real time. The drag-minimization algorithm is capable of identifying drag to approximately a one-drag-count level. Optimizing the symmetric outboard aileron position realizes a drag reduction of 2-3 drag counts (approximately 1 percent). Algorithm analysis of maneuvers indicate that two-sided raised-cosine maneuvers improve definition of the symmetric outboard aileron drag effect, thereby improving analysis results and consistency. Ramp maneuvers provide a more even distribution of data collection as a function of excitation deflection than raised-cosine maneuvers provide. A commercial operational system would require airdata calculations and normal output of current inertial navigation systems; engine pressure ratio measurements would be optional.

Gilyard, Glenn B.↗

Low-Energy Study of Gamma-Ray Bursts Having Spectral Line Features

Gamma-ray bursts (GRBs) are energetic, short-duration emissions of gamma-rays. The Burst and Transient Source Experiment (BATSE) that was onboard NASA s Compton Gamma-Ray Observatory has done much to advance our understanding of GRBs. Perhaps foremost is to establish that GRBs originate from astronomical sources that exist well beyond our galaxy. Another area in which BATSE has been instrumental is to provide high-resolution data that can be used in spectral studies. Before BATSE, there were many reports of GRB spectra containing what appeared to be spectral absorption lines, whereas Briggs, after an extensive computer search of 117 bright BATSE GRBs, reported finding only one case that might be an absorption line and ten cases that might be emission lines. None of the eleven BATSE cases were definitively identified as spectral lines, and Briggs indicated reasons as to why the pre-BATSE reports should not be taken as conclusive. It remains an open question as to what these spectral-like features are, or if they are even real. The purpose of this work is, for the subset of the eleven BATSE GRBs for which low-energy data are available from two BATSE's Spectroscopy Detectors (SDs), to include these data in the spectral analysis. Such a study will provide additional constraints on the model spectral functions to better ascertain the reality of the line features. The spectral analysis program used was RMFIT. Of the six GRBs that met the selection criteria, the analysis was performed on only three of them due to a lack of time.

Pangia, Michael J.↗

Simultaneous Observations of Atmospheric Tides from Combined in Situ and Remote Observations at Mars from the MAVEN Spacecraft

We report the observations of longitudinal variations in the Martian thermosphere associated with nonmigrating tides. Using the Neutral Gas Ion Mass Spectrometer (NGIMS) and the Imaging Ultraviolet Spectrograph (IUVS) on NASA's Mars Atmosphere and Volatile EvolutioN Mission (MAVEN) spacecraft, this study presents the first combined analysis of in situ and remote observations of atmospheric tides at Mars for overlapping volumes, local times, and overlapping date ranges. From the IUVS observations, we determine the altitude and latitudinal variation of the amplitude of the nonmigrating tidal signatures, which is combined with the NGIMS, providing information on the compositional impact of these waves. Both the observations of airglow from IUVS and the CO2 density observations from NGIMS reveal a strong wave number 2 signature in a fixed local time frame. The IUVS observations reveal a strong latitudinal dependence in the amplitude of the wave number 2 signature. Combining this with the accurate CO2 density observations from NGIMS, this would suggest that the CO2 density variation is as high as 27% at 0-10 deg latitude. The IUVS observations reveal little altitudinal dependence in the amplitude of the wave number 2 signature, varying by only 20% from 160 to 200 km. Observations of five different species with NGIMS show that the amplitude of the wave number 2 signature varies in proportion to the inverse of the species scale height, giving rise to variation in composition as a function of longitude. The analysis and discussion here provide a roadmap for further analysis as additional coincident data from these two instruments become available.

atmospheric tides↗

Biocene 2018 - Welcome to the Period of New Life

Biocene is the period of new life. When our descendants look back at this period in time, they will see evidence, in the geologic and electronic record, of anthropic climate change, growing population, and scarcity of resources. But they will also see the rebirth of human ingenuity as we overcame the challenges that faced us through nature-inspired exploration. The Periodic Table of Life (PeTaL) is a proposed tool and open source framework that uses artificial intelligence to aid in the systematic inquiry of biology for its application to human systems. This presentation defines the PeTaL concept and workflow. Biomimicry, biophysics, biomimetics, bionics and numerous other terms refer to the use of biology and biological principles to inform practices in other disciplines. For the most part, the domain of inquiry in these fields have been confined to extant biological models with the proponents of biomimicry often citing the evolutionary success of extant organisms relative to extinct ones. The primary objective of this paper is to expand the domain of inquiry for human processes that seek to model those that are, were or could be found in nature with examples that relate to the field of aerospace and to spur development of tools that can work together to accelerate the use of artificial intelligence in problem solving. Specifically specialized fields such as paleomimesis, anthropomimesis and physioteleology are proposed in conjunction with artificial evolution. Blockchain technology may be vital in allowing open source design tools such as PeTaL to democratize design and yet protect intellectual property. The overarching philosophy outlined here can be thought of as physiomimetics, a holistic and systematic way of learning from natural history. The backbone of PeTaL integrates an unstructured database with an ontological model consisting of function, morphology, environment, state of matter and ecosystem. Tools include text classification, thesaurus, data visualization, and analysis. Applications of PeTaL include guiding human space exploration, understanding human and geological history, and discovering new or extinct life.

Biocene↗

Development of Computational Environmental Microbiome Workflows for the Laboratory and the International Space Station

Identification of microorganisms in the spaceflight environment is critical for crew health risk assessment on the International Space Station (ISS). Since 2017, nanopore sequencing technology has been used to support thein situ identification of microbial species during spaceflight. Beginning in 2018, a culture-independent, swab-to-sequencer method was implemented onboard the ISS to provide a more thorough insight of the ISS microbiome. Eliminating microbial culture enables identification of difficult-to-culture organisms, reduces risks associated with potentially pathogenic cultures, and could significantly reduce the time from sample-to-answer. However, this molecular-based approach generates large metagenomic datasets that require substantial computational resources for analysis. To process nanopore-generated sequencing data, the JSC Microbiology Laboratory established a bioinformatics workflow on Amazon EC2 under the security guidance of the NASA Science Managed Cloud Environment (SMCE).This resource allows for the development, testing, and accessing of computational tools for processing large and complex datasets. The work described here will address the downlinking of data from the ISS, the automated pipeline developed to identify targeted bacterial and fungal organisms, and the time from sampling onboard to microbial identification. The pipelines have been enhanced to address high and low biomass samples using optimization based on sample source (air, water, or surface) and type of collection (filter, colony, or swab).The resulting microbiome data can be assessed beyond microbial identifications to gain understanding toward population changes over time, potential selective environmental pressures, and evaluating correlations with a wide range of additional data sets. Metagenome analysis pipelines in development could allow for simultaneous identification of microbial species, gene function, and gene pathways present in the environment. Beyond the ground processing, the developed analysis pipeline is currently deployed onboard the ISS to allow for near real-time assessments of the ISS microbiome. This study serves as a critical foundation for exploration missions, where rapid microbiome analyses will be required.

G. Marie Sharp↗

Effects of cockpit lateral stick characteristics on handling qualities and pilot dynamics

This report presents the results of analysis of cockpit lateral control feel-system studies. Variations in feel-system natural frequency, damping, and command sensing reference (force and position) were investigated, in combination with variations in the aircraft response characteristics. The primary data for the report were obtained from a flight investigation conducted with a variable-stability airplane, with additional information taken from other flight experiments and ground-based simulations for both airplanes and helicopters . The study consisted of analysis of handling qualities ratings and extraction of open-loop, pilot-vehicle describing functions from sum-of-sines tracking data, including, for a limited subset of these data, the development of pilot models. The study confirms the findings of other investigators that the effects on pilot opinion of cockpit feel-system dynamics are not equivalent to a comparable level of added time delay, and until a more comprehensive set of criteria are developed, it is recommended that feel-system dynamics be considered a delay-inducing element in the aircraft response. The best correlation with time-delay requirements was found when the feel-system dynamics were included in the delay measurements, regardless of the command reference. This is a radical departure from past approaches.

Mitchell, David G.↗

Physics and chemistry from parsimonious representations: image analysis via invariant variational autoencoders

Electron, optical, and scanning probe microscopy methods are generating ever increasing volume of image data containing information on atomic and mesoscale structures and functionalities. This necessitates the development of the machine learning methods for discovery of physical and chemical phenomena from the data, such as manifestations of symmetry breaking phenomena in electron and scanning tunneling microscopy images, or variability of the nanoparticles. Variational autoencoders (VAEs) are emerging as a powerful paradigm for the unsupervised data analysis, allowing to disentangle the factors of variability and discover optimal parsimonious representation. Here, we summarize recent developments in VAEs, covering the basic principles and intuition behind the VAEs. The invariant VAEs are introduced as an approach to accommodate scale and translation invariances present in imaging data and separate known factors of variations from the ones to be discovered. We further describe the opportunities enabled by the control over VAE architecture, including conditional, semi-supervised, and joint VAEs. Several case studies of VAE applications for toy models and experimental datasets in Scanning Transmission Electron Microscopy are discussed, emphasizing the deep connection between VAE and basic physical principles. Python codes and datasets discussed in this article are available at https://github.com/saimani5/VAE-tutorials and can be used by researchers as an application guide when applying these to their own datasets.

36 MATERIALS SCIENCE↗

Use of ERTS-1 data for regional planning in the Metropolitan Washington Council of Governments: A short brief

Land use and land use activity changes over discrete intervals of time represent basic data requirements in regional planning studies. Two examples of land use analysis required by the Council of Governments' transportation planning staff are described. Both were undertaken utilizing remote sensing imagery analysis. One study using large scale aircraft imagery developed a high degree of analytical detail and functional identification. The other, to support further detailed data base evaluation, utilizing ERTS-1 and small scale aircraft imagery, developed data identifying in more general detail major activity changes within the metropolitan region.

Mallon, H. J.↗

Spatial Correlation Function of the Chandra Selected Active Galactic Nuclei

We present the spatial correlation function analysis of non-stellar X-ray point sources in the Chandra Large Area Synoptic X-ray Survey of Lockman Hole Northwest (CLASXS). Our 9 ACIS-I fields cover a contiguous solid angle of 0.4 deg(exp 2) and reach a depth of 3 x 10(exp -15) erg/square cm/s in the 2-8 keV band. We supplement our analysis with data from the Chandra Deep Field North (CDFN). The addition of this field allows better probe of the correlation function at small scales. A total of 233 and 252 sources with spectroscopic information are used in the study of the CLASXS and CDFN fields respectively. We calculate both redshift-space and projected correlation functions in co-moving coordinates, averaged over the redshift range of 0.1 < z < 3.0, for both CLASXS and CDFN fields for a standard cosmology with Omega(sub Lambda) = 0.73,Omega(sub M) = 0.27, and h = 0.71 (H(sub 0) = 100h km/s Mpc(exp -1). The correlation function for the CLASXS field over scales of 3 Mpc< s < 200 Mpc can be modeled as a power-law of the form xi(s) = (S/SO)(exp - gamma), with gamma = 1.6(sup +0.4 sub -0.3) and S(sub o) = 8.0(sup +.14 sub -1.5) Mpc. The redshift-space correlation function for CDFN on scales of 1 Mpc< s < 100 Mpc is found to have a similar correlation length so = 8.55(sup +0.74 sub -0.74) Mpc, but a shallower slope (gamma = 1.3 +/- 0.1). The real-space correlation functions derived from the projected correlation functions, are found to be tau(sub 0 = 8.1(sup +1.2 sub -2.2) Mpc, and gamma = 2.1 +/- 0.5 for the CLASXS field, and tau(sub 0) = 5.8(sup +.1.0 sub -1.5) Mpc, gamma = 1.38(sup +0.12 sub -0.14 for the CDFN field. By comparing the real- and redshift-space correlation functions in the combined CLASXS and CDFN samples, we are able to estimate the redshift distortion parameter Beta = 0.4 +/- 0.2 at an effective redshift z = 0.94. We compare the correlation functions for hard and soft spectra sources in the CLASXS field and find no significant difference between the two groups. We have also found that the correlation between X-ray luminosity and clustering amplitude is weak, which, however, is fully consistent with the expectation using the simplest relations between X-ray luminosity, black hole mass, and dark halo mass. We study the evolution of the AGN clustering by dividing the samples into 4 redshift bins over 0.1 Mpc< z <3.0 Mpc. We find a very mild evolution in the clustering amplitude, which show the same evolution trend found in optically selected quasars in the 2dF survey. We estimate the evolution of the bias, and find that the bias increases rapidly with redshift (b(z = 0.45) = 0.95 +/- 0.15 and b(z = 2.07) = 3.03 +/- 0.83): The typical mass of the dark matter halo derived from the bias estimates show little change with redshift. The average halo mass is found to be log (M(sub halo)/M(sun))approximates 12.1. Subject headings: cosmology: observations - large-scale structure of the universe - x-rays: diffuse background - galaxies: nuclei

Yang, Y.↗

Identification of natural frequencies and modal damping ratios of aerospace structures from response data

An analysis of one and multidegree of freedom systems with classical damping is presented. Definition and minimization of error functions for each system are discussed. Systems with classical and nonclassical normal modes are studied, and results for first order perturbation are given. An alternative method of matching power spectral densities is provided, and numerical results are reviewed.

Michalopoulos, C. D.↗