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NASA NTRS1984

Acoustic structure and propagation in highly porous, layered, fibrous materials

The acoustic structure and propagation of sound in highly porous, layered, fine fiber materials is examined. Of particular interest is the utilization of the Kozeny number for determining the static flow resistance and the static structure factor based on flow permeability measurements. In this formulation the Kozeny number is a numerical constant independent of volume porosity at high porosities. The other essential parameters are then evaluated employing techniques developed earlier for open cell foams. The attenuation and progressive phase characteristics in bulk samples are measured and compared with predicted values. The agreements on the whole are very satisfactory.

Lambert, R. F.↗

NASA NTRS1984

Interferometer applications of VHF radars, part 3.6A

Using a spaced antenna setup of a VHF radar, the spatial distribution of amplitudes and phases of the radar echoes from the troposphere, stratosphere and mesosphere can be measured. Combining in a suitable analysis procedure the complex digital samples from the different receiving antennas is consistent with the radar interferometer method. In addition to the well-known parameters measured with the commonly applied Doppler and drifts methods, i.e., reflectivity and mean fluctuation velocity, the interferometer technique allows to measure the regular spectrum of the returns. This technique, which was first applied with the spaced antenna system of the SOUSY-VHF-Radar in W. Germany, as well as some first examples of results are described here. These comprise the measurements of the horizontal and vertical velocities of the mean flow as well as of turbulence structures, the aspect sensitivity and the tilt of layers from which the baroclinicity can be estimated. Particularly, results of interferometer measurements of the vertical and horizontal phase velocities and wavelengths of gravity waves in the stratosphere are displayed. The latter results are also discussed in terms of the generation and propagation of these waves.

Rottger, J.↗

NASA NTRS1984

Acoustic structure and propagation in highly porous, layered, fibrous materials

Lambert, R. F.↗

NASA NTRS1989

Shock-implanted noble gases. II - Additional experimental studies and recognition in naturally shocked terrestrial materials

The process by which ambient gases can be implanted into silicates by shocks was investigated by analyzing the noble-gas content of several experimentally and naturally shocked silicate samples. The retentivity of shock-implanted gas during stepwise heating in the laboratory was defined in terms of two parameters, namely, the activation energy for diffusion and the extraction temperature at which 50 percent of the gas is released, both of which correlate with the shock pressure. The experiments indicate that, with increasing shock pressure, gas implantation occurs through an increasing production of microcracks/defects in the silicate lattice. The degree of annealing of these defects control the degree of diffusive loss of implanted gas.

Bogard, Donald↗

NASA NTRS1990

Characteristics of AlGaAs/GaAs multiple quantum well infrared detectors

Researchers fabricated and characterized several AlGaAs/GaAs multiple quantum well infrared detectors to evaluate the ultimate performance of these devices for low infrared background applications. The detectors were designed to have a single bound state in the quantum well and the first excited state in the continuum above the AlGaAs conduction band edge. The difference in energy between the two levels, as determined by the quantum well width and aluminum mole fraction in the barrier, was chosen such that peak absorption would occur near 8 microns. The initial structures studied comprised 50 periods with 40 A well widths and 300 A Al(0.28)Ga(0.72)As barriers. The performance of these detectors are summarized. To better interpret these results and design optimized detectors, researchers modeled both the detector noise and tunneling currents. The noise model correctly predicts that multiple quantum well detectors will, indeed, exhibit noise lower than full shot noise. The tunneling current model predicts the dark current versus bias for any choice of design parameters in a multiple quantum well detector. This model predicts a substantially reduced dark current (x 10(exp 04)) for samples with 400 A barriers. To evaluate structures with thicker barriers, researchers fabricated and characterized detectors with 400 A and 500 A barriers; a comparison of detector dark currents is shown. These results are consistent with the predictions of the dark current model.

Janousek, Bruce K.↗

NASA NTRS1992

Growth and sporulation of Bacillus subtilis under microgravity (7-IML-1)

The experiment was aimed at measuring the growth and sporulation of Bacillus subtilis under microgravity. The hardware for the experiment consists of a culture chamber (15 ml) made from titanium and closed by a membrane permeable for gases but not for water. Two variants of this basic structure were built which fit into the standard Biorack container types 1 and 2 respectively. Growth of the bacteria will be monitored by continuously measuring the optical density with a built-in miniaturized photometer. Other parameters (viability, sporulation, fine structure, size distribution of cells and spores, growth kinetics, etc.) will be measured on the fixed samples and on those where metabolism was temporarily halted, respectively.

Mennigmann, Horst-Dieter↗

NASA NTRS1992

Injecting asteroid fragments into resonances

We have quantitatively modeled the chance insertion of asteroid collisional fragments into the 3:1 and g = g(sub 6) resonances, through which they can achieve Earth-approaching orbits. Although the results depend on some poorly known parameters, they indicate that most meteorites and near-earth asteroids probably come from a small and non-representative sample of asteroids, located in the neighborhood of the two resonances.

Farinella, Paolo↗

NASA NTRS1995

Electromagnetic Radiation in the Plasma Environment Around the Shuttle

As part of the SAMPIE (The Solar Array Module Plasma Interaction Experiment) program, the Langmuir probe (LP) was employed to measure plasma characteristics during the flight STS-62. The whole set of data could be divided into two parts: (1) low frequency sweeps to determine voltage-current characteristics and to find electron temperature and number density; (2) high frequency turbulence (HFT dwells) data caused by electromagnetic noise around the shuttle. The broadband noise was observed at frequencies 250-20,000 Hz. Measurements were performed in ram conditions; thus, it seems reasonable to believe that the influence of spacecraft operations on plasma parameters was minimized. The average spectrum of fluctuations is in agreement with theoretical predictions. According to purposes of SAMPIE, the samples of solar cells were placed in the cargo bay of the shuttle, and high negative bias voltages were applied to them to initiate arcing between these cells and surrounding plasma. The arcing onset was registered by special counters, and data were obtained that included the amplitudes of current, duration of each arc, and the number of arcs per one experiment. The LP data were analyzed for two different situations: with arcing and without arcing. Electrostatic noise spectra for both situations and theoretical explanation of the observed features are presented in this report.

Vayner, Boris V.↗

NASA NTRS1994

Relativistic induced Compton scattering in synchrotron self-absorbed sources

We present a model of the radio emission from synchrotron self-absorbed sources, including the effects of induced Compton scattering by the relativistic electrons in the source. Order of magnitude estimates show that stimulated scattering becomes the dominant absorption process when (kT(sub B)/m(sub e) c(exp 2))Tau(sub T) greater than or approximately 1.0. Numerical simulations demonstrate that relativistic induced Compton scattering limits the brightness temperature of a self-absorbed synchroton sources to T(sub B) less than or approximately 2 x 10(exp 11) nu(exp -1/p + 3) (sub zero, 9) gamma(exp p + 2/p + 5) (sub min) K, where gamma(sub min) is the low-energy cutoff to the relativistic electron distribution with a power-law index of p. It can also significantly flatten the radio spectrum. The radio spectrum of the core of 3C 279 is well matched by a model in which stimulated scattering is important, and the additional constraint T(sub B) less than 2 x 10(exp 11)K may be important to the interpretation of the broadband spectra in variable extragalactic compact radio sources. Stimulated scattering reduces the amplitude of the radio frequency variability relative to the X-ray variability, an effect which can be detected by multiwavelength variability studies. Data for a sample of resolved compact radio cores indicate that it is inconsistent to neglect induced Compton scattering when inferring the physical parameters of the sources. The necessary generalizations to the standard synchrotron self-Compton theory are p resented.

Sincell, Mark W.↗

NASA NTRS2003

A Fast Implementation of the ISOCLUS Algorithm

Unsupervised clustering is a fundamental tool in numerous image processing and remote sensing applications. For example, unsupervised clustering is often used to obtain vegetation maps of an area of interest. This approach is useful when reliable training data are either scarce or expensive, and when relatively little a priori information about the data is available. Unsupervised clustering methods play a significant role in the pursuit of unsupervised classification. One of the most popular and widely used clustering schemes for remote sensing applications is the ISOCLUS algorithm, which is based on the ISODATA method. The algorithm is given a set of n data points (or samples) in d-dimensional space, an integer k indicating the initial number of clusters, and a number of additional parameters. The general goal is to compute a set of cluster centers in d-space. Although there is no specific optimization criterion, the algorithm is similar in spirit to the well known k-means clustering method in which the objective is to minimize the average squared distance of each point to its nearest center, called the average distortion. One significant feature of ISOCLUS over k-means is that clusters may be merged or split, and so the final number of clusters may be different from the number k supplied as part of the input. This algorithm will be described in later in this paper. The ISOCLUS algorithm can run very slowly, particularly on large data sets. Given its wide use in remote sensing, its efficient computation is an important goal. We have developed a fast implementation of the ISOCLUS algorithm. Our improvement is based on a recent acceleration to the k-means algorithm, the filtering algorithm, by Kanungo et al.. They showed that, by storing the data in a kd-tree, it was possible to significantly reduce the running time of k-means. We have adapted this method for the ISOCLUS algorithm. For technical reasons, which are explained later, it is necessary to make a minor modification to the ISOCLUS specification. We provide empirical evidence, on both synthetic and Landsat image data sets, that our algorithm's performance is essentially the same as that of ISOCLUS, but with significantly lower running times. We show that our algorithm runs from 3 to 30 times faster than a straightforward implementation of ISOCLUS. Our adaptation of the filtering algorithm involves the efficient computation of a number of cluster statistics that are needed for ISOCLUS, but not for k-means.

Memarsadeghi, Nargess↗

NASA NTRS2005

Spatial Scaling of Snow Observations and Microwave Emission Modeling During CLPX and Appropriate Satellite Sensor Resolution

Accurate estimates of snow water equivalent and other properties play an important role in weather, natural hazard, and hydrological forecasting and climate modeling over a range of scales in space and time. Remote sensing-derived estimates have traditionally been of the "snapshot" type, but techniques involving models with assimilation are also being explored. In both cases, forward emission models are useful to understand the observed passive microwave signatures and developing retrieval algorithms. However, mismatches between passive microwave sensor resolutions and the scales of processes controlling subpixel heterogeneity can affect the accuracy of the estimates. Improving the spatial resolution of new passive microwave satellite sensors is a major desire in order to (literally) resolve such subpixel heterogeneity, but limited spacecraft and mission resources impose severe constraints and tradeoffs. In order to maximize science return while mitigating risk for a satellite concept, it is essential to understand the scaling behavior of snow in terms of what the sensor sees (brightness temperature) as well as in terms of the actual variability of snow. NASA's Cold Land Processes Experiment-1 (CLPX-1: Colorado, 2002 and 2003) was designed to provide data to measure these scaling behaviors for varying snow conditions in areas with forested, alpine, and meadow/pasture land cover. We will use observations from CLPX-1 ground, airborne, and satellite passive microwave sensors to examine and evaluate the scaling behavior of observed and modeled brightness temperatures and observed and retrieved snow parameters across scales from meters to 10's of kilometers. The conclusions will provide direct examples of the appropriate spatial sampling scales of new sensors for snow remote sensing. The analyses will also illustrate the effects and spatial scales of the underlying phenomena (e.g., land cover) that control subpixel heterogeneity.

Kim, Edward J.↗

NASA NTRS2010

Improving the Representation of Snow Crystal Properties with a Single-Moment Mircophysics Scheme

Single-moment microphysics schemes are utilized in an increasing number of applications and are widely available within numerical modeling packages, often executed in near real-time to aid in the issuance of weather forecasts and advisories. In order to simulate cloud microphysical and precipitation processes, a number of assumptions are made within these schemes. Snow crystals are often assumed to be spherical and of uniform density, and their size distribution intercept may be fixed to simplify calculation of the remaining parameters. Recently, the Canadian CloudSat/CALIPSO Validation Project (C3VP) provided aircraft observations of snow crystal size distributions and environmental state variables, sampling widespread snowfall associated with a passing extratropical cyclone on 22 January 2007. Aircraft instrumentation was supplemented by comparable surface estimations and sampling by two radars: the C-band, dual-polarimetric radar in King City, Ontario and the NASA CloudSat 94 GHz Cloud Profiling Radar. As radar systems respond to both hydrometeor mass and size distribution, they provide value when assessing the accuracy of cloud characteristics as simulated by a forecast model. However, simulation of the 94 GHz radar signal requires special attention, as radar backscatter is sensitive to the assumed crystal shape. Observations obtained during the 22 January 2007 event are used to validate assumptions of density and size distribution within the NASA Goddard six-class single-moment microphysics scheme. Two high resolution forecasts are performed on a 9-3-1 km grid, with C3VP-based alternative parameterizations incorporated and examined for improvement. In order to apply the CloudSat 94 GHz radar to model validation, the single scattering characteristics of various crystal types are used and demonstrate that the assumption of Mie spheres is insufficient for representing CloudSat reflectivity derived from winter precipitation. Furthermore, snow density and size distribution characteristics are allowed to vary with height, based upon direct aircraft estimates obtained from C3VP data. These combinations improve the representation of modeled clouds versus their radar-observed counterparts, based on profiles and vertical distributions of reflectivity. These meteorological events are commonplace within the mid-latitude cold season and present a challenge to operational forecasters. This study focuses on one event, likely representative of others during the winter season, and aims to improve the representation of snow for use in future operational forecasts.

Molthan, Andrew L.↗

NASA NTRS2012

Spatial Distribution of Accuracy of Aerosol Retrievals from Multiple Satellite Sensors

Remote sensing of aerosols from space has been a subject of extensive research, with multiple sensors retrieving aerosol properties globally on a daily or weekly basis. The diverse algorithms used for these retrievals operate on different types of reflected signals based on different assumptions about the underlying physical phenomena. Depending on the actual retrieval conditions and especially on the geographical location of the sensed aerosol parcels, the combination of these factors might be advantageous for one or more of the sensors and unfavorable for others, resulting in disagreements between similar aerosol parameters retrieved from different sensors. In this presentation, we will demonstrate the use of the Multi-sensor Aerosol Products Sampling System (MAPSS) to analyze and intercompare aerosol retrievals from multiple spaceborne sensors, including MODIS (on Terra and Aqua), MISR, OMI, POLDER, CALIOP, and SeaWiFS. Based on this intercomparison, we are determining geographical locations where these products provide the greatest accuracy of the retrievals and identifying the products that are the most suitable for retrieval at these locations. The analyses are performed by comparing quality-screened satellite aerosol products to available collocated ground-based aerosol observations from the Aerosol Robotic Network (AERONET) stations, during the period of 2006-2010 when all the satellite sensors were operating concurrently. Furthermore, we will discuss results of a statistical approach that is applied to the collocated data to detect and remove potential data outliers that can bias the results of the analysis.

Petrenko, Maksym↗

NASA NTRS2014

Fine Particulate Matter Predictions Using High Resolution Aerosol Optical Depth (AOD) Retrievals

To date, spatial-temporal patterns of particulate matter (PM) within urban areas have primarily been examined using models. On the other hand, satellites extend spatial coverage but their spatial resolution is too coarse. In order to address this issue, here we report on spatial variability in PM levels derived from high 1 km resolution AOD product of Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm developed for MODIS satellite. We apply day-specific calibrations of AOD data to predict PM(sub 2.5) concentrations within the New England area of the United States. To improve the accuracy of our model, land use and meteorological variables were incorporated. We used inverse probability weighting (IPW) to account for nonrandom missingness of AOD and nested regions within days to capture spatial variation. With this approach we can control for the inherent day-to-day variability in the AOD-PM(sub 2.5) relationship, which depends on time-varying parameters such as particle optical properties, vertical and diurnal concentration profiles and ground surface reflectance among others. Out-of-sample "ten-fold" cross-validation was used to quantify the accuracy of model predictions. Our results show that the model-predicted PM(sub 2.5) mass concentrations are highly correlated with the actual observations, with out-of- sample R(sub 2) of 0.89. Furthermore, our study shows that the model captures the pollution levels along highways and many urban locations thereby extending our ability to investigate the spatial patterns of urban air quality, such as examining exposures in areas with high traffic. Our results also show high accuracy within the cities of Boston and New Haven thereby indicating that MAIAC data can be used to examine intra-urban exposure contrasts in PM(sub 2.5) levels.

aerosol optical depth↗

NASA NTRS2015

Development and Execution of the RUNSAFE Runway Safety Bayesian Belief Network Model

One focus area of the National Aeronautics and Space Administration (NASA) is to improve aviation safety. Runway safety is one such thrust of investigation and research. The two primary components of this runway safety research are in runway incursion (RI) and runway excursion (RE) events. These are adverse ground-based aviation incidents that endanger crew, passengers, aircraft and perhaps other nearby people or property. A runway incursion is the incorrect presence of an aircraft, vehicle or person on the protected area of a surface designated for the landing and take-off of aircraft; one class of RI events simultaneously involves two aircraft, such as one aircraft incorrectly landing on a runway while another aircraft is taking off from the same runway. A runway excursion is an incident involving only a single aircraft defined as a veer-off or overrun off the runway surface. Within the scope of this effort at NASA Langley Research Center (LaRC), generic RI, RE and combined (RI plus RE, or RUNSAFE) event models have each been developed and implemented as a Bayesian Belief Network (BBN). Descriptions of runway safety issues from the literature searches have been used to develop the BBN models. Numerous considerations surrounding the process of developing the event models have been documented in this report. The event models were then thoroughly reviewed by a Subject Matter Expert (SME) panel through multiple knowledge elicitation sessions. Numerous improvements to the model structure (definitions, node names, node states and the connecting link topology) were made by the SME panel. Sample executions of the final RUNSAFE model have been presented herein for baseline and worst-case scenarios. Finally, a parameter sensitivity analysis for a given scenario was performed to show the risk drivers. The NASA and LaRC research in runway safety event modeling through the use of BBN technology is important for several reasons. These include: 1) providing a means to clearly understand the cause and effect patterns leading to safety issues, incidents and accidents, 2) enabling the prioritization of specialty areas needing more attention to improve aviation safety, and 3) enabling the identification of gaps within NASA's Aviation Safety funding portfolio

Green, Lawrence L.↗

NASA NTRS2017

The Fundamental Stellar Parameters of FGK Stars in the SEEDS Survey Norman, OK 73071, USA

Large exoplanet surveys have successfully detected thousands of exoplanets to-date. Utilizing these detections and non-detections to constrain our understanding of the formation and evolution of planetary systems also requires a detailed understanding of the basic properties of their host stars. We have determined the basic stellar properties of F, K and G stars in the Strategic Exploration of Exoplanets and Disks with Subaru (SEEDS) survey from Echelle spectra taken at the Apache Point Observatory's 3.5m telescope. Using ROBOSPECT to extract line equivalent widths and Temperature Gravity microtrubulent Velocity ITerations to calculate the fundamental parameters, we have computed T(sub eff), log(g), v(sub t), [Fe/H], chromospheric activity and the age for our sample. Our methodology was calibrated against previously published results for a portion of our sample. The distribution of [Fe/H] in our sample is consistent with that typical of the Solar neighbourhood. Additionally, we find the ages of most of our sample are less than 500 Myr, but note that we cannot determine robust ages from significantly older stars via chromospheric activity age indicators. The future meta-analysis of the frequency of wide stellar and sub-stellar companions imaged via the SEEDS survey will utilize our results to constrain the occurrence of detected comoving companions with the properties of their host stars.

Strategic Exploration of Exoplanets and Disks with↗

NASA NTRS2000

Life Sciences Research in the Centrifuge Accommodation Module of the International Space Station

The Centrifuge Accommodation Module (CAM) will be the home of the fundamental biology research facilities on the International Space Station (ISS). These facilities are being built by the Biological Research Project (BRP), whose goal is to oversee development of a wide variety of habitats and host systems to support life sciences research on the ISS. The habitats and host systems are designed to provide life support for a variety of specimens including cells, bacteria, yeast, plants, fish, rodents, eggs (e.g., quail), and insects. Each habitat contains specimen chambers that allow for easy manipulation of specimens and alteration of sample numbers. All habitats are capable of sustaining life support for 90 days and have automated as well as full telescience capabilities for sending habitat parameters data to investigator homesite laboratories. The habitats provide all basic life support capabilities including temperature control, humidity monitoring and control, waste management, food, media and water delivery as well as adjustable lighting. All habitats will have either an internal centrifuge or are fitted to the 2.5-meter diameter centrifuge allowing for variable centrifugation up to 2 g. Specimen chambers are removable so that the specimens can be handled in the life sciences glovebox. Laboratory support equipment is provided for handling the specimens. This includes a compound and dissecting microscope with advanced video imaging, mass measuring devices, refrigerated centrifuge for processing biological samples, pH meter, fixation and complete cryogenic storage capabilities. The research capabilities provided by the fundamental biology facilities will allow for flexibility and efficiency for long term research on the International Space Station.

Dalton, Bonnie P.↗

NASA NTRS1976

Environmental parameters of the Tennessee River in Alabama. 1: Thermal stratification

Thermal stratification data of a transect across Wheeler Reservoir are correlated with the climatological data at the time of sampling. This portion of the Tennessee River is used as a heat sink for the effluent from the three reactor Browns Ferry Nuclear Power Plant. The transect sampling line is 1.3 miles below this point of effluence. Data are presented by weekly samplings for one year prior to plant operations. Post-operational data are presented with one reactor in operation and with two reactors in partial operation. Data gathering was terminated when the plant ceased operations. The results indicate that the effluent for partial plant operation were inconclusive. As a result, recommendations include continuing the sampling when the plant resumes operation at full capacity. Recommendations also include developing math models with the presented thermal and climatological data to be used for predicting the effluent impact in the river with varying climatological conditions and also to predict the effectiveness of the cooling towers.

Rosing, L. M.↗