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NASA NTRS1994

The optical and near-infrared colors of galaxies, 1: The photometric data

We present optical and near-infrared photometry and spectroscopic redshifts of a well defined sample of 171 field galaxies selected from three high galactic latitude fields. This data set forms the basis for subsequent studies to characterize the trends, dispersion, and evolution of rest-frame colors and image structure. A subset of 143 galaxies constitutes a magnitude-limited sample to B approx. 19.9-20.75 (depending on field), with a median redshift of 0.14, and a maximum redshift of 0.54. This subset is statistically representative in its sampling of the apparent color distribution of galaxies. Thirty six galaxies were selected to have the reddest red-optical colors in two redshift intervals between 0.2 less than z less than 0.3. Photometric passbands are similar to U, B, V, I, and K, and sample galaxy spectral energy distributions between 0.37 and 2.2 micrometers in the observed frame, or down to 0.26 micrometers in the rest frame for the most distant galaxies. B and K images of the entire sample are assembled to form the first optical and near-infrared atlas of a statistically-representative sample of field galaxies. We discuss techniques for faint field-galaxy photometry, including a working definition of a total magnitude, and a method for matching magnitudes in different passbands and different seeing conditions to ensure reliable, integrated colors. Photographic saturation, which substantially affects the brightest 12% of our sample in the optical bands, is corrected with a model employing measured plate-density distributions for each galaxy, calibrated via similar measurements for stars as a function of known saturation level. Both the relative and absolute calibration of our photometry are demonstrated.

Bershady, Matthew A.↗

NASA NTRS2006

Less-Complex Method of Classifying MPSK

An alternative to an optimal method of automated classification of signals modulated with M-ary phase-shift-keying (M-ary PSK or MPSK) has been derived. The alternative method is approximate, but it offers nearly optimal performance and entails much less complexity, which translates to much less computation time. Modulation classification is becoming increasingly important in radio-communication systems that utilize multiple data modulation schemes and include software-defined or software-controlled receivers. Such a receiver may "know" little a priori about an incoming signal but may be required to correctly classify its data rate, modulation type, and forward error-correction code before properly configuring itself to acquire and track the symbol timing, carrier frequency, and phase, and ultimately produce decoded bits. Modulation classification has long been an important component of military interception of initially unknown radio signals transmitted by adversaries. Modulation classification may also be useful for enabling cellular telephones to automatically recognize different signal types and configure themselves accordingly. The concept of modulation classification as outlined in the preceding paragraph is quite general. However, at the present early stage of development, and for the purpose of describing the present alternative method, the term "modulation classification" or simply "classification" signifies, more specifically, a distinction between M-ary and M'-ary PSK, where M and M' represent two different integer multiples of 2. Both the prior optimal method and the present alternative method require the acquisition of magnitude and phase values of a number (N) of consecutive baseband samples of the incoming signal + noise. The prior optimal method is based on a maximum- likelihood (ML) classification rule that requires a calculation of likelihood functions for the M and M' hypotheses: Each likelihood function is an integral, over a full cycle of carrier phase, of a complicated sum of functions of the baseband sample values, the carrier phase, the carrier-signal and noise magnitudes, and M or M'. Then the likelihood ratio, defined as the ratio between the likelihood functions, is computed, leading to the choice of whichever hypothesis - M or M'- is more likely. In the alternative method, the integral in each likelihood function is approximated by a sum over values of the integrand sampled at a number, 1, of equally spaced values of carrier phase. Used in this way, 1 is a parameter that can be adjusted to trade computational complexity against the probability of misclassification. In the limit as 1 approaches infinity, one obtains the integral form of the likelihood function and thus recovers the ML classification. The present approximate method has been tested in comparison with the ML method by means of computational simulations. The results of the simulations have shown that the performance (as quantified by probability of misclassification) of the approximate method is nearly indistinguishable from that of the ML method (see figure).

Hamkins, Jon↗

NASA NTRS1987

In-orbit calibration adjustment of the Nimbus-7 SMMR

The procedure for converting raw antenna signals (counts) from the Nimbus-7 Scanning Multichannel Microwave Radiometer (SMMR) to microwave radiances is described. The procedure entails taking the raw data stored on TAT data tapes, applying an interim prelaunch calibration, correcting for polarization mixing, and finally adjusting the calibration so that the observations conform to model calculations of oceanic radiances. The results are stored on TCT data tapes with the same format as the TATs, i.e., the basic sampling interval of the SMMR is retained. The properties of the TCTs are compared with those of the other basic SMMR radiance data product, the CELL tapes, in which the integrated fields-of-view (IFOVs) have been averaged into cells with coarser sampling intervals and in which the prelaunch calibration is the final one used.

Gloersen, Per↗

DOE OSTI2022

Substructure in the stellar halo near the Sun: II. Characterisation of independent structures

In an accompanying paper, we present a data-driven method for clustering in ‘integrals of motion’ space and apply it to a large sample of nearby halo stars with 6D phase-space information. The algorithm identified a large number of clusters, many of which could tentatively be merged into larger groups. The goal here is to establish the reality of the clusters and groups through a combined study of their stellar populations (average age, metallicity, and chemical and dynamical properties) to gain more insights into the accretion history of the Milky Way. To this end, we developed a procedure that quantifies the similarity of clusters based on the Kolmogorov–Smirnov test using their metallicity distribution functions, and an isochrone fitting method to determine their average age, which is also used to compare the distribution of stars in the colour–absolute magnitude diagram. Also taking into consideration how the clusters are distributed in integrals of motion space allows us to group clusters into substructures and to compare substructures with one another. We find that the 67 clusters identified by our algorithm can be merged into 12 extended substructures and 8 small clusters that remain as such. The large substructures include the previously known Gaia-Enceladus, Helmi streams, Sequoia, and Thamnos 1 and 2. We identify a few over-densities that can be associated with the hot thick disc and host a small metal-poor population. Especially notable is the largest (by number of member stars) substructure in our sample which, although peaking at the metallicity characteristic of the thick disc, has a very well populated metal-poor component, and dynamics intermediate between the hot thick disc and the halo. We also identify additional debris in the region occupied by Sequoia with clearly distinct kinematics, likely remnants of three different accretion events with progenitors of similar masses. Although only a small subset of the stars in our sample have chemical abundance information, we are able to identify different trends of [Mg/Fe] versus [Fe/H] for the various substructures, confirming our dissection of the nearby halo. We find that at least 20% of the halo near the Sun is associated to substructures. When comparing their global properties, we note that those substructures on retrograde orbits are not only more metal-poor on average but are also older. We provide a table summarising the properties of the substructures, as well as a membership list that can be used for follow-up chemical abundance studies for example.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2016

The evolution of metallicity and metallicity gradients from z = 2.7 to 0.6 with KMOS{sup 3D}

We present measurements of the [N ii]/Hα ratio as a probe of gas-phase oxygen abundance for a sample of 419 star-forming galaxies at z = 0.6–2.7 from the KMOS{sup 3D} near-IR multi-integral field unit (IFU) survey. The mass–metallicity relation (MZR) is determined consistently with the same sample selection, metallicity tracer, and methodology over the wide redshift range probed by the survey. We find good agreement with long-slit surveys in the literature, except for the low-mass slope of the relation at z∼2.3, where this sample is less biased than previous samples based on optical spectroscopic redshifts. In this regime we measure a steeper slope than some literature results. Excluding the contribution from active galactic nuclei from the MZR reduces sensitivity at the high-mass end, but produces otherwise consistent results. There is no significant dependence of the [N ii]/Hα ratio on star formation rate at fixed redshift and stellar mass. The IFU data allow spatially resolved measurements of [N ii]/Hα, from which we can infer abundance gradients for 180 galaxies, thus tripling the current sample in the literature. The observed gradients are on average flat, with only 15 gradients statistically offset from zero at >3σ. We have modeled the effect of beam smearing, assuming a smooth intrinsic radial gradient and known seeing, inclination, and effective radius for each galaxy. Our seeing-limited observations can recover up to 70% of the intrinsic gradient for the largest, face-on disks, but only 30% for the smaller, more inclined galaxies. We do not find significant trends between observed or corrected gradients and any stellar population, dynamical, or structural galaxy parameters, mostly in agreement with existing studies with much smaller sample sizes. In cosmological simulations, strong feedback is generally required to produce flat gradients at high redshift.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2026

Opportunities and Limitations of Nuclear Magnetic Resonance Spectroscopy in Astrobiology

For decades, Nuclear Magnetic Resonance (NMR) spectroscopy has been utilized as a powerful tool in various scientific disciplines, most prominently in chemistry, to determine molecular structures or monitor reactions. While well established in various fields, NMR applications in astrobiology are still unclear. This work aims to explore the potential of NMR in astrobiology, highlighting strengths but also weaknesses. We illustrate capabilities of NMR with two applications: (1) recently developed methods for position-specific carbon isotope analysis of complex organics; and (2) well-established tools for performing quantitative compositional analysis of complex organic mixtures. By utilizing samples relevant to astrobiology, specifically the amino acid valine and analogue mixtures of organics, we showcase that molecules retain a source dependent and distinct intramolecular carbon isotope fingerprint. We demonstrate that compositional sample analysis provides an independent and complementary line of evidence pointing towards the origin of a molecule or mixture. Together, these NMR tools have the potential to support life detection efforts, and aid in distinguishing between biotic and abiotic samples. Finally, we discuss sensitivity, detection limits, the portability of NMR, and propose how integration with mass-spectrometry techniques will be imperative to enable more targeted and comprehensive analyses relevant to astrobiology, including in-situ analysis but also sample return missions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRS2008

Analysis of Lunar Highland Regolith Samples from Apollo 16 Drive Core 64001/2 and Lunar Regolith Simulants - An Expanding Comparative Database

We present modal data from QEMSCAN(registered TradeMark) beam analysis of Apollo 16 samples from drive core 64001/2. The analyzed lunar samples are thin sections 64002,6019 (5.0-8.0 cm depth) and 64001,6031 (50.0-53.1 cm depth) and sieved grain mounts 64002,262 and 64001,374 from depths corresponding to the thin sections, respectively. We also analyzed lunar highland regolith simulants NU-LHT-1M, -2M, and OB-1, low-Ti mare simulants JSC-1, -lA, -1AF, and FJS-1, and high-Ti mare simulant MLS-1. The preliminary results comprise the beginning of an internally consistent database of lunar regolith and regolith simulant mineral and glass information. This database, combined with previous and concurrent studies on phase chemistry, bulk chemistry, and with data on particle shape and size distribution, will serve to guide lunar scientists and engineers in choosing simulants for their applications. These results are modal% by phase rather than by particle type, so they are not directly comparable to most previously published lunar data that report lithic fragments, monomineralic particles, agglutinates, etc. Of the highland simulants, 08-1 has an integrated modal composition closer than NU-LHT-1M to that of the 64001/2 samples, However, this and other studies show that NU-LHT-1M and -2M have minor and trace mineral (e.g., Fe-Ti oxides and phosphates) populations and mineral and glass chemistry closer to these lunar samples. The finest fractions (0-20 microns) in the sieved lunar samples are enriched in glass relative to the integrated compositions by approx.30% for 64002,262 and approx.15% for 64001,374. Plagioclase, pyroxene, and olivine are depleted in these finest fractions. This could be important to lunar dust mitigation efforts and astronaut health - none of the analyzed simulants show this trend. Contrary to previously reported modal analyses of monomineralic grains in lunar regolith, these area% modal analyses do not show a systematic increase in plagiociase/pyroxene as size fraction decreases.

Schrader, Christian M.↗

DOE OSTI2020

Correlative Surface Imaging Reveals Chemical Signatures for Bacterial Hotspots on Plant Roots

The rhizosphere is arguably the most complex microbial habitat on earth, comprising an integrated network of plant roots, soil and a highly diverse microbial community (the rhizosphere microbiome)1. Understanding, predicting and controlling plant-microbe interactions in the rhizosphere will allow us to harness the plant microbiome as a means to increase or restore plant ecosystem productivity, improve plant responses to a wide range of environmental perturbations, and mitigate effects of climate change by designing ecosystems for long-term soil carbon storage1. To this end, it is imperative to develop new molecular approaches with high spatial resolution to capture interactions at the plant-microbe, microbe-microbe, and plant-plant interfaces. In this work, we designed an imaging sample holder that allows integrated surface imaging tools to map the same locations of a plant root-microbe interface with submicron lateral resolutions, providing novel in vivo analysis of root-microbe interactions. Specifically, confocal fluorescence microscopy, time-of-flight secondary ion mass spectrometry (ToF-SIMS), X-ray photoelectron spectroscopy (XPS), and scanning electron microscope (SEM) were used for the first time for correlative imaging of the Brachypodium distachyon root and its interaction with Pseudomonas SW25, a typical plant growth-promoting soil bacterium. Imaging data suggest that the root surface is inhomogeneous and that the interaction between Pseudomonas and Brachypodium roots was confined to only few spots along the sampled root segments and that the bacterial attachment spots were enriched in Na- and S-related and high-mass organic species. We conclude that attachment of the Pseudomonas cells to the root surface is outcompeted by strong root-soil mineral interactions but facilitated by formation of extracellular polymeric substances (EPS).

Plant root, Plant growth-promoting bacteria, soil,↗

DOE OSTI2017

The sami galaxy survey: revisiting galaxy classification through high-order stellar kinematics

Recent cosmological hydrodynamical simulations suggest that integral field spectroscopy can connect the high-order stellar kinematic moments h{sub 3} (∼skewness) and h{sub 4} (∼kurtosis) in galaxies to their cosmological assembly history. Here, we assess these results by measuring the stellar kinematics on a sample of 315 galaxies, without a morphological selection, using two-dimensional integral field data from the SAMI Galaxy Survey. Proxies for the spin parameter (λ{sub R{sub e}}) and ellipticity (ϵ{sub e}) are used to separate fast and slow rotators; there exists a good correspondence to regular and non-regular rotators, respectively, as also seen in earlier studies. We confirm that regular rotators show a strong h{sub 3} versus V/σ anti-correlation, whereas quasi-regular and non-regular rotators show a more vertical relation in h{sub 3} and V/σ. Motivated by recent cosmological simulations, we develop an alternative approach to kinematically classify galaxies from their individual h{sub 3} versus V/σ signatures. Within the SAMI Galaxy Survey, we identify five classes of high-order stellar kinematic signatures using Gaussian mixture models. Class 1 corresponds to slow rotators, whereas Classes 2–5 correspond to fast rotators. We find that galaxies with similar λ{sub R{sub e}}--ϵ{sub e} values can show distinctly different h{sub 3}--V/σ signatures. Class 5 objects are previously unidentified fast rotators that show a weak h{sub 3} versus V/σ anti-correlation. From simulations, these objects are predicted to be disk-less galaxies formed by gas-poor mergers. From morphological examination, however, there is evidence for large stellar disks. Instead, Class 5 objects are more likely disturbed galaxies, have counter-rotating bulges, or bars in edge-on galaxies. Finally, we interpret the strong anti-correlation in h{sub 3} versus V/σ as evidence for disks in most fast rotators, suggesting a dearth of gas-poor mergers among fast rotators.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2025

Mass Spectrometry Sample Submission Portal

Each step in the scientific process generates contextual information about the data that is important to consider when performing data integration, developing models of biological process, or training AI models. We will develop a flexible, template-driven tool that will log biological samples, capture metadata about those samples, and track the type(s) of analysis being performed by researchers providing samples for analysis by mass spectrometry.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2022

Comprehensive uncertainty quantification (UQ) for full engineering models by solving probability density function (PDF) equation

This report details a new method for propagating parameter uncertainty (forward uncertainty quantification) in partial differential equations (PDE) based computational mechanics applications. The method provides full-field quantities of interest by solving for the joint probability density function (PDF) equations which are implied by the PDEs with uncertain parameters. Full-field uncertainty quantification enables the design of complex systems where quantities of interest, such as failure points, are not known apriori. The method, motivated by the well-known probability density function (PDF) propagation method of turbulence modeling, uses an ensemble of solutions to provide the joint PDF of desired quantities at every point in the domain. A small subset of the ensemble is computed exactly, and the remainder of the samples are computed with approximation of the driving (dynamics) term of the PDEs based on those exact solutions. Although the proposed method has commonalities with traditional interpolatory stochastic collocation methods applied directly to quantities of interest, it is distinct and exploits the parameter dependence and smoothness of the dynamics term of the governing PDEs. The efficacy of the method is demonstrated by applying it to two target problems: solid mechanics explicit dynamics with uncertain material model parameters, and reacting hypersonic fluid mechanics with uncertain chemical kinetic rate parameters. A minimally invasive implementation of the method for representative codes SPARC (reacting hypersonics) and NimbleSM (finite- element solid mechanics) and associated software details are described. For solid mechanics demonstration problems the method shows order of magnitudes improvement in accuracy over traditional stochastic collocation. For the reacting hypersonics problem, the method is implemented as a streamline integration and results show very good accuracy for the approximate sample solutions of re-entry flow past the Apollo capsule geometry at Mach 30.

42 ENGINEERING↗

DOE OSTI2021

Mechanism Across Scales: A Holistic Modeling Framework Integrating Laboratory and Field Studies for Microbial Ecology

Over the last century, leaps in technology for imaging, sampling, detection, high-throughput sequencing, and -omics analyses have revolutionized microbial ecology to enable rapid acquisition of extensive datasets for microbial communities across the ever-increasing temporal and spatial scales. The present challenge is capitalizing on our enhanced abilities of observation and integrating diverse data types from different scales, resolutions, and disciplines to reach a causal and mechanistic understanding of how microbial communities transform and respond to perturbations in the environment. This type of causal and mechanistic understanding will make predictions of microbial community behavior more robust and actionable in addressing microbially mediated global problems. To discern drivers of microbial community assembly and function, we recognize the need for a conceptual, quantitative framework that connects measurements of genomic potential, the environment, and ecological and physical forces to rates of microbial growth at specific locations. We describe the Framework for Integrated, Conceptual, and Systematic Microbial Ecology (FICSME), an experimental design framework for conducting process-focused microbial ecology studies that incorporates biological, chemical, and physical drivers of a microbial system into a conceptual model. Through iterative cycles that advance our understanding of the coupling across scales and processes, we can reliably predict how perturbations to microbial systems impact ecosystem-scale processes or vice versa. We describe an approach and potential applications for using the FICSME to elucidate the mechanisms of globally important ecological and physical processes, toward attaining the goal of predicting the structure and function of microbial communities in chemically complex natural environments.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRS2014

WetLab-2: Tools for Conducting On-Orbit Quantitative Real-Time Gene Expression Analysis on ISS

The objective of NASA Ames Research Centers WetLab-2 Project is to place on the ISS a research platform capable of conducting gene expression analysis via quantitative real-time PCR (qRT-PCR) of biological specimens sampled or cultured on orbit. The project has selected a Commercial-Off-The-Shelf (COTS) qRT-PCR system, the Cepheid SmartCycler and will fly it in its COTS configuration. The SmartCycler has a number of advantages including modular design (16 independent PCR modules), low power consumption, rapid ramp times and the ability to detect up to four separate fluorescent channels at one time enabling multiplex assays that can be used for normalization and to study multiple genes of interest in each module. The team is currently working with Cepheid to enable the downlink of data from the ISS to the ground and provide uplink capabilities for programming, commanding, monitoring, and instrument maintenance. The project has adapted commercial technology to design a module that can lyse cells and extract RNA of sufficient quality and quantity for use in qRT-PCR reactions while using a housekeeping gene to normalize RNA concentration and integrity. The WetLab-2 system is capable of processing multiple sample types ranging from microbial cultures to animal tissues dissected on-orbit. The ability to conduct qRT-PCR on-orbit eliminates the confounding effects on gene expression of reentry stresses and shock acting on live cells and organisms or the concern of RNA degradation of fixed samples. The system can be used to validate terrestrial analyses of samples returned from ISS by providing on-orbit gene expression benchmarking prior to sample return. The ability to get on orbit data will provide investigators with the opportunity to adjust experiment parameters for subsequent trials based on the real-time data analysis without need for sample return and re-flight. Researchers will also be able to sample multigenerational changes in organisms. Finally, the system can be used for analysis of air, surface, water, and clinical samples to monitor environmental contaminants and crew health. The verification flight of the instrument is scheduled to launch on SpaceX-7 in June 2015.

quantitative PCR↗

NASA NTRS2007

Image sensor with high dynamic range linear output

Designs and operational methods to increase the dynamic range of image sensors and APS devices in particular by achieving more than one integration times for each pixel thereof. An APS system with more than one column-parallel signal chains for readout are described for maintaining a high frame rate in readout. Each active pixel is sampled for multiple times during a single frame readout, thus resulting in multiple integration times. The operation methods can also be used to obtain multiple integration times for each pixel with an APS design having a single column-parallel signal chain for readout. Furthermore, analog-to-digital conversion of high speed and high resolution can be implemented.

Yadid-Pecht, Orly↗

DOE OSTI2020

Shear strength and permeability of the cement-casing interface

Here, the shear strength and hydraulic permeability of the interface between well cement and casing was investigated using a triaxial direct shear apparatus. For the first time, these experiments provide measurements under controlled stress conditions with fluid flow measurements along the interface. The low cohesion (1.1 ± 1.1 MPa) and the high friction angle (43.4 ± 2.0°) indicates that the shear strength of the interface is provided by friction. This implies that the state of stress of the cement is critical to well integrity. The hydraulic aperture of the undamaged cement-steel samples was 6.8 ± 1.0 microns. Shear damage to the interface caused a decrease (-20 %) in hydraulic aperture for samples aged up to 1 month, and an increase (+300 %) for samples cured for two years. We performed numerical simulations to estimate the leakage potential from a carbon storage operation. This model predicts negligible leakage amounts (47 tonnes) in a shear-damaged well for the modeled injection of ~1.26 million tonnes of CO 2 . Thus, our measurements indicate that the cement-casing interface is not a significant leakage pathway in its intact or damaged state, and that shear-driven failure scenarios for this interface are not a significant risk to CO 2 storage security.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Data-Driven Computation of Probabilistic Marching Cubes for Efficient Visualization of Level-Set Uncertainty

Uncertainty visualization is an important emerging research area. Being able to visualize data uncertainty can help scientists improve trust in analysis and decision-making. However, visualizing uncertainty can add computational overhead, which can hinder the efficiency of analysis. In this paper, we propose novel data-driven techniques to reduce the computational requirements of the probabilistic marching cubes (PMC) algorithm. PMC is an uncertainty visualization technique that studies how uncertainty in data affects level-set positions. However, the algorithm relies on expensive Monte Carlo (MC) sampling for the multivariate Gaussian uncertainty model because no closed-form solution exists for the integration of multivariate Gaussian. In this work, we propose the eigenvalue decomposition and adaptive probability model techniques that reduce the amount of MC sampling in the original PMC algorithm and hence speed up the computations. Our proposed methods produce results that show negligible differences compared with the original PMC algorithm demonstrated through metrics, including root mean squared error, maximum error, and difference images. We demonstrate the performance and accuracy evaluations of our data-driven methods through experiments on synthetic and real datasets.

Athawale, Tushar↗

DOE OSTI2020

The AMUSING++ Nearby Galaxy Compilation. I. Full Sample Characterization and Galactic-scale Outflow Selection

We present here AMUSING++: the largest compilation of nearby galaxies observed with the MUSE integral-field spectrograph so far. This collection consists of 635 galaxies from different MUSE projects covering the redshift interval 0.0002 < z < 0.1. The sample and its main properties are characterized and described here. It includes galaxies of almost all morphological types, with a good coverage in its color–magnitude diagram, within the stellar mass range between 10{sup 8} and 10{sup 12} M {sub ⊙}, and with properties resembling those of a diameter-selected sample. The AMUSING++ sample is, therefore, suitable for studying, with unprecendented detail, the properties of nearby galaxies at global and local scales, providing us with more than 50 million individual spectra. We use this compilation to investigate the presence of galactic outflows. We exploit the use of combined emission-line images to explore the shape of the different ionized components and the distribution along classical diagnostic diagrams to disentangle the different ionizing sources across the optical extension of each galaxy. We use the cross-correlation function to estimate the level of symmetry of the emission lines as an indication of the presence of shocks and/or active galactic nuclei. We uncovered a total of 54 outflows, comprising ∼8% of the sample. A large number of the discovered outflows correspond to those driven by active galactic nuclei (∼60%), suggesting some bias in the selection of our sample. No clear evidence was found that outflow host galaxies are highly star-forming, and outflows appear to be found within all galaxies around the star-formation sequence.

79 ASTRONOMY AND ASTROPHYSICS↗

NASA NTRS1988

Quantitative non-destructive evaluation of porous composite materials based on ultrasonic wave propagation

Two complementary ultrasonic techniques for characterizing porosity in fiber-reinforced composite laminates are evaluated. Five uniaxial graphite-fiber/epoxy-matrix composites having a range of 1 to 8 percent volume fraction of solid glass inclusions to model porosity were investigated. In one technique, signal loss was measured in transmission mode and slope of attenuation, obtained from the first order coefficient of a two-parameter polynomial fit about the center frequency of the useful bandwidth, was used as the ultrasonic parameter to characterize the porosity. The results of these transmission mode measurements displayed a good correlation between the volume fraction of porosity and the slope of attenuation. Integrated polar backscatter was used as a second ultrasonic parameter for the characterization of the porosity in these samples. A single transducer insonified the samples and measured the resulting backscatter at a polar angle of 30 deg with respect to the normal of the sample surface with the azimuthal angles centered at 0 deg with respect to the fiber orientation (i.e., along the fibers). Integrated polar backscatter also displayed good correlation with the volume fraction of porosity.

Miller, James G.↗