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All sourcesNASA NTRSDOE OSTI
NASA NTRS2001

Computational Aeroacoustic Analysis System Development

Many industrial and commercial products operate in a dynamic flow environment and the aerodynamically generated noise has become a very important factor in the design of these products. In light of the importance in characterizing this dynamic environment, Rocketdyne has initiated a multiyear effort to develop an advanced general-purpose Computational Aeroacoustic Analysis System (CAAS) to address these issues. This system will provide a high fidelity predictive capability for aeroacoustic design and analysis. The numerical platform is able to provide high temporal and spatial accuracy that is required for aeroacoustic calculations through the development of a high order spectral element numerical algorithm. The analysis system is integrated with well-established CAE tools, such as a graphical user interface (GUI) through PATRAN, to provide cost-effective access to all of the necessary tools. These include preprocessing (geometry import, grid generation and boundary condition specification), code set up (problem specification, user parameter definition, etc.), and postprocessing. The purpose of the present paper is to assess the feasibility of such a system and to demonstrate the efficiency and accuracy of the numerical algorithm through numerical examples. Computations of vortex shedding noise were carried out in the context of a two-dimensional low Mach number turbulent flow past a square cylinder. The computational aeroacoustic approach that is used in CAAS relies on coupling a base flow solver to the acoustic solver throughout a computational cycle. The unsteady fluid motion, which is responsible for both the generation and propagation of acoustic waves, is calculated using a high order flow solver. The results of the flow field are then passed to the acoustic solver through an interpolator to map the field values into the acoustic grid. The acoustic field, which is governed by the linearized Euler equations, is then calculated using the flow results computed from the flow solver.

Hadid, A.↗
NASA NTRS2021

Evaluating the Impact of Model Resolutions and Cumulus Parameterization on Precipitation in NU-WRF: A Case Study in the Central Great Plains

Regional climate models are expected to exhibit improved skill at finer spatial resolutions due to improved representation of land surface heterogeneity. However, at spatial scales between 1 to 10 km (grey scales), these improvements are often illusive due to the competing benefits from spatial resolution and cumulus parameterization. This study provides insights into the impact of model resolution and cumulus parameterization on precipitation prediction in the Central Great Plains by using an object-based evaluation method. Our results show limited improvement solely from finer resolution but larger improvement without using the cumulus scheme at a 4-kmresolution. Compared to traditional evaluation methods, the object-based analysis shows that without the cumulus scheme the spatial properties of precipitation are better represented. In contrast, all model configurations show a dry bias in precipitation days and a tendency to produce widespread precipitation but with fewer hours with precipitationwhich indicates other shortcomings in the model.

Yuqi Zhang↗
NASA NTRS2013

Hadoop for High-Performance Climate Analytics: Use Cases and Lessons Learned

Scientific data services are a critical aspect of the NASA Center for Climate Simulations mission (NCCS). Hadoop, via MapReduce, provides an approach to high-performance analytics that is proving to be useful to data intensive problems in climate research. It offers an analysis paradigm that uses clusters of computers and combines distributed storage of large data sets with parallel computation. The NCCS is particularly interested in the potential of Hadoop to speed up basic operations common to a wide range of analyses. In order to evaluate this potential, we prototyped a series of canonical MapReduce operations over a test suite of observational and climate simulation datasets. The initial focus was on averaging operations over arbitrary spatial and temporal extents within Modern Era Retrospective- Analysis for Research and Applications (MERRA) data. After preliminary results suggested that this approach improves efficiencies within data intensive analytic workflows, we invested in building a cyber infrastructure resource for developing a new generation of climate data analysis capabilities using Hadoop. This resource is focused on reducing the time spent in the preparation of reanalysis data used in data-model inter-comparison, a long sought goal of the climate community. This paper summarizes the related use cases and lessons learned.

analytics↗
NASA NTRS2000

Fractal Characterization of Multitemporal Remote Sensing Data

Scale is an "innate" concept in geographic information systems. It is recognized as something that is intrinsic to the capture, storage, manipulation, analysis, modeling, and output of space and time data within a GIS purview, yet the relative meaning and ramifications of scaling spatial and temporal data from this perspective remain enigmatic. As GISs become more sophisticated as a product of more robust software and more powerful computer systems, there is an urgent need to examine the issue of scale, and its relationship to the whole body of spatiotemporal data, as imparted in GISs. Scale is fundamental to the characterization of geo-spatial data as represented in GISs, but we have relatively little insight on how to measure the effects of scale in representing data that are acquired in different formats and exist in varying spatial, temporal and radiometric configurations. Moreover, the complexities associated with the integration of multiscaled data sets in a multitude of formats are exacerbated by the confusion of what the term "scale" is from a multidisciplinary perspective. "Scale" takes on significantly different meanings depending upon one's disciplinary background and spatial perspective which lead to substantial confusion in the input, manipulation, analysis, and output operations. Hence, we must begin to look at the universality of scale and begin to develop the theory, methods, and techniques necessary to advance knowledge on the "Science of Scale' across all disciplines that use GISs.

Quattrochi, Dale A.↗
NASA NTRS2012

Preliminary Evaluation of MapReduce for High-Performance Climate Data Analysis

MapReduce is an approach to high-performance analytics that may be useful to data intensive problems in climate research. It offers an analysis paradigm that uses clusters of computers and combines distributed storage of large data sets with parallel computation. We are particularly interested in the potential of MapReduce to speed up basic operations common to a wide range of analyses. In order to evaluate this potential, we are prototyping a series of canonical MapReduce operations over a test suite of observational and climate simulation datasets. Our initial focus has been on averaging operations over arbitrary spatial and temporal extents within Modern Era Retrospective- Analysis for Research and Applications (MERRA) data. Preliminary results suggest this approach can improve efficiencies within data intensive analytic workflows.

Duffy, Daniel Q.↗
NASA NTRS2005

NASA Remote Sensing Data in Earth Sciences: Processing, Archiving, Distribution, Applications at the GES DISC

The NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) is one of the major Distributed Active Archive Centers (DAACs) archiving and distributing remote sensing data from the NASA's Earth Observing System. In addition to providing just data, the GES DISC/DAAC has developed various value-adding processing services. A particularly useful service is data processing a t the DISC (i.e., close to the input data) with the users' algorithms. This can take a number of different forms: as a configuration-managed algorithm within the main processing stream; as a stand-alone program next to the on-line data storage; as build-it-yourself code within the Near-Archive Data Mining (NADM) system; or as an on-the-fly analysis with simple algorithms embedded into the web-based tools (to avoid downloading unnecessary all the data). The existing data management infrastructure at the GES DISC supports a wide spectrum of options: from data subsetting data spatially and/or by parameter to sophisticated on-line analysis tools, producing economies of scale and rapid time-to-deploy. Shifting processing and data management burden from users to the GES DISC, allows scientists to concentrate on science, while the GES DISC handles the data management and data processing at a lower cost. Several examples of successful partnerships with scientists in the area of data processing and mining are presented.

Leptoukh, Gregory G.↗
NASA NTRS2008

The Analysis of Image Segmentation Hierarchies with a Graph-based Knowledge Discovery System

Currently available pixel-based analysis techniques do not effectively extract the information content from the increasingly available high spatial resolution remotely sensed imagery data. A general consensus is that object-based image analysis (OBIA) is required to effectively analyze this type of data. OBIA is usually a two-stage process; image segmentation followed by an analysis of the segmented objects. We are exploring an approach to OBIA in which hierarchical image segmentations provided by the Recursive Hierarchical Segmentation (RHSEG) software developed at NASA GSFC are analyzed by the Subdue graph-based knowledge discovery system developed by a team at Washington State University. In this paper we discuss out initial approach to representing the RHSEG-produced hierarchical image segmentations in a graphical form understandable by Subdue, and provide results on real and simulated data. We also discuss planned improvements designed to more effectively and completely convey the hierarchical segmentation information to Subdue and to improve processing efficiency.

Tilton, James C.↗
NASA NTRS2016

Soil Moisture Active Passive Mission L4_SM Data Product Assessment (Version 2 Validated Release)

During the post-launch SMAP calibration and validation (Cal/Val) phase there are two objectives for each science data product team: 1) calibrate, verify, and improve the performance of the science algorithm, and 2) validate the accuracy of the science data product as specified in the science requirements and according to the Cal/Val schedule. This report provides an assessment of the SMAP Level 4 Surface and Root Zone Soil Moisture Passive (L4_SM) product specifically for the product's public Version 2 validated release scheduled for 29 April 2016. The assessment of the Version 2 L4_SM data product includes comparisons of SMAP L4_SM soil moisture estimates with in situ soil moisture observations from core validation sites and sparse networks. The assessment further includes a global evaluation of the internal diagnostics from the ensemble-based data assimilation system that is used to generate the L4_SM product. This evaluation focuses on the statistics of the observation-minus-forecast (O-F) residuals and the analysis increments. Together, the core validation site comparisons and the statistics of the assimilation diagnostics are considered primary validation methodologies for the L4_SM product. Comparisons against in situ measurements from regional-scale sparse networks are considered a secondary validation methodology because such in situ measurements are subject to up-scaling errors from the point-scale to the grid cell scale of the data product. Based on the limited set of core validation sites, the wide geographic range of the sparse network sites, and the global assessment of the assimilation diagnostics, the assessment presented here meets the criteria established by the Committee on Earth Observing Satellites for Stage 2 validation and supports the validated release of the data. An analysis of the time average surface and root zone soil moisture shows that the global pattern of arid and humid regions are captured by the L4_SM estimates. Results from the core validation site comparisons indicate that "Version 2" of the L4_SM data product meets the self-imposed L4_SM accuracy requirement, which is formulated in terms of the ubRMSE: the RMSE (Root Mean Square Error) after removal of the long-term mean difference. The overall ubRMSE of the 3-hourly L4_SM surface soil moisture at the 9 km scale is 0.035 cubic meters per cubic meter requirement. The corresponding ubRMSE for L4_SM root zone soil moisture is 0.024 cubic meters per cubic meter requirement. Both of these metrics are comfortably below the 0.04 cubic meters per cubic meter requirement. The L4_SM estimates are an improvement over estimates from a model-only SMAP Nature Run version 4 (NRv4), which demonstrates the beneficial impact of the SMAP brightness temperature data. L4_SM surface soil moisture estimates are consistently more skillful than NRv4 estimates, although not by a statistically significant margin. The lack of statistical significance is not surprising given the limited data record available to date. Root zone soil moisture estimates from L4_SM and NRv4 have similar skill. Results from comparisons of the L4_SM product to in situ measurements from nearly 400 sparse network sites corroborate the core validation site results. The instantaneous soil moisture and soil temperature analysis increments are within a reasonable range and result in spatially smooth soil moisture analyses. The O-F residuals exhibit only small biases on the order of 1-3 degrees Kelvin between the (re-scaled) SMAP brightness temperature observations and the L4_SM model forecast, which indicates that the assimilation system is largely unbiased. The spatially averaged time series standard deviation of the O-F residuals is 5.9 degrees Kelvin, which reduces to 4.0 degrees Kelvin for the observation-minus-analysis (O-A) residuals, reflecting the impact of the SMAP observations on the L4_SM system. Averaged globally, the time series standard deviation of the normalized O-F residuals is close to unity, which would suggest that the magnitude of the modeled errors approximately reflects that of the actual errors. The assessment report also notes several limitations of the "Version 2" L4_SM data product and science algorithm calibration that will be addressed in future releases. Regionally, the time series standard deviation of the normalized O-F residuals deviates considerably from unity, which indicates that the L4_SM assimilation algorithm either over- or under-estimates the actual errors that are present in the system. Planned improvements include revised land model parameters, revised error parameters for the land model and the assimilated SMAP observations, and revised surface meteorological forcing data for the operational period and underlying climatological data. Moreover, a refined analysis of the impact of SMAP observations will be facilitated by the construction of additional variants of the model-only reference data. Nevertheless, the “Version 2” validated release of the L4_SM product is sufficiently mature and of adequate quality for distribution to and use by the larger science and application communities.

SMAP L4_SM↗
NASA NTRS2014

Human Performance in Simulated Reduced Gravity Environments

NASA is currently designing a new space suit capable of working in deep space and on Mars. Designing a suit is very difficult and often requires trade‐offs between performance, cost, mass, and system complexity. Our current understanding of human performance in reduced gravity in a planetary environment (the moon or Mars) is limited to lunar observations, studies from the Apollo program, and recent suit tests conducted at JSC using reduced gravity simulators. This study will look at our most recent reduced gravity simulations performed on the new Active Response Gravity Offload System (ARGOS) compared to the C‐9 reduced gravity plane. Methods: Subjects ambulated in reduced gravity analogs to obtain a baseline for human performance. Subjects were tested in lunar gravity (1.6 m/sq s) and Earth gravity (9.8 m/sq s) in shirt‐sleeves. Subjects ambulated over ground at prescribed speeds on the ARGOS, but ambulated at a self‐selected speed on the C‐9 due to time limitations. Subjects on the ARGOS were given over 3 minutes to acclimate to the different conditions before data was collected. Nine healthy subjects were tested in the ARGOS (6 males, 3 females, 79.5 +/- 15.7 kg), while six subjects were tested on the C‐9 (6 males, 78.8 +/- 11.2 kg). Data was collected with an optical motion capture system (Vicon, Oxford, UK) and was analyzed using customized analysis scripts in BodyBuilder (Vicon, Oxford, UK) and MATLAB (MathWorks, Natick, MA, USA). Results: In all offloaded conditions, variation between subjects increased compared to 1‐g. Kinematics in the ARGOS at lunar gravity resembled earth gravity ambulation more closely than the C‐9 ambulation. Toe‐off occurred 10% earlier in both reduced gravity environments compared to earth gravity, shortening the stance phase. Likewise, ankle, knee, and hip angles remained consistently flexed and had reduced peaks compared to earth gravity. Ground reaction forces in lunar gravity (normalized to Earth body weight) were 0.4 +/- 0.2 on the ARGOS, but only 0.2 +/- 0.1 on the C‐9. Discussion: Gait analysis showed differences in joint kinematics and temporal‐spatial parameters between the reduced gravity simulators and with respect to earth gravity. Although most of the subjects chose a somewhat unique ambulation style as a result of learning to ambulate in a new environment, all but two were consistent with keeping an Earth‐like gait. Learning how reduced gravity affects ambulation will help NASA to determine optimal suit designs, influence mission planning, help train crew, and may shed light on the underlying methods the body uses to optimize gait for energetic efficiency. Conclusion: Kinematic and kinetic analysis demonstrated noteworthy differences between an offloaded environment and 1‐g, as would be expected. The analysis showed a trend to change the ambulation style in an offloaded environment to a rolling‐loping walk (resembling crosscountry skiing) with increased swing time. This ambulation modification, particularly in the ARGOS, indicated that the relative kinetic energy of the subject was increased, on average, per the static body weight compared to the 1‐g condition. How much of this was influenced by the active offloading of the ARGOS system is unknown.

Cowley, Matthew↗
NASA NTRS2015

Spatial and Temporal Variability of Carbon Dioxide Using Structure Functions in Urban Areas: Insights for Future Active Remote CO2 Sensors

High resolution in-situ CO2 measurements were recorded onboard the NASA P-3B during the DISCOVER-AQ (Deriving Information on Surface Conditions from Column and Vertically Resolved Observations Relevant to Air Quality) Field Campaigns during July 2011 over Washington DC/Baltimore, MD; January-February 2013 over the San Joaquin Valley, CA; September 2013 over Houston, TX; and July-August 2014 over Denver, CO. Each of these campaigns have approximately two hundred vertical soundings of CO2 within the lower troposphere (surface to about 5 kilometers) at 6-8 different sites in each of the urban areas. In this study, we used structure function analysis, which is a useful way to quantify spatial and temporal variability, by displaying differences with average observations, to evaluate the variability of CO2 in the 0-2 kilometers range (representative of the planetary boundary layer). These results can then be used to provide guidance in the development of science requirements for the future ASCENDS (Active Sensing of CO2 Emissions over Nights, Days, and Seasons) mission to measure near-surface CO2 variability in different urban areas. We also compare the observed in-situ CO2 variability with the variability of the CO2 column-averaged optical depths in the 0-1 kilometer and 0-3.5 kilometers altitude ranges in the four geographically different urban areas, using vertical weighting functions for potential future ASCENDS lidar CO2 sensors operating in the 1.57 and 2.05 millimeter measurement regions. In addition to determining the natural variability of CO2 near the surface and in the column, radiocarbon method using continuous CO2 and CO measurements are used to examine the variation of emission quantification between anthropogenic and biogenic sources in the DC/Maryland urban site.

Choi, Yonghoon↗
NASA NTRS1995

A diagnostic analysis of the VVP single-doppler retrieval technique

A diagnostic analysis of the VVP (volume velocity processing) retrieval method is presented, with emphasis on understanding the technique as a linear, multivariate regression. Similarities and differences to the velocity-azimuth display and extended velocity-azimuth display retrieval techniques are discussed, using this framework. Conventional regression diagnostics are then employed to quantitatively determine situations in which the VVP technique is likely to fail. An algorithm for preparation and analysis of a robust VVP retrieval is developed and applied to synthetic and actual datasets with high temporal and spatial resolution. A fundamental (but quantifiable) limitation to some forms of VVP analysis is inadequate sampling dispersion in the n space of the multivariate regression, manifest as a collinearity between the basis functions of some fitted parameters. Such collinearity may be present either in the definition of these basis functions or in their realization in a given sampling configuration. This nonorthogonality may cause numerical instability, variance inflation (decrease in robustness), and increased sensitivity to bias from neglected wind components. It is shown that these effects prevent the application of VVP to small azimuthal sectors of data. The behavior of the VVP regression is further diagnosed over a wide range of sampling constraints, and reasonable sector limits are established.

Boccippio, Dennis J.↗
NASA NTRS2018

Investigations of Hail Damage Swaths Using Various Satellite Remote Sensing Platforms

Severe thunderstorms that bring damaging winds and large hail can cause significant damage to agricultural crops. Severe thunderstorms can cause upwards of several hundreds of millions of dollars in damage to agricultural areas. Formal ground surveys are not conducted on these areas of damage, like they are for suspected tornado damaged areas. IF ground surveys were conducted, they would likely be time and resources consuming due to their large spatial extent. Satellite remote sensing has been frequently used in identification and analysis of these hail damage swaths. Previous analysis have looked at the simple change in damaged vegetation to looking at the damage areas in satellite imagery with varying spatial resolutions. One study has even looked at the impacts that these damage swaths can have on the land surface, associated fluxes and how they affect numerical weather prediction. Previous studies have focused on using optical remote (VIS, NIR, SWIR) sensing instruments and derived indices, such as Normalized Difference Vegetation Index (NDVI) for analysis. NDVI is used to monitor the health (greenness) of the vegetation. Optical sensors however are limited by sky conditions over the areas they are imaging and certain bands are further limited by the diurnal cycle. These limitations can lead to sometimes upwards of 7 to 10 day gaps of the surface not being imaged, especially during the height of summer convection. One way to obtain more views of the surface, regardless of the sky conditions or time of day is through the use of synthetic aperture radar (SAR). SAR sensors are active instruments that transmit in the microwave portion of the EM spectrum. The surface and its characteristics will determine the amount of energy scattered back to the sensor. The SAR sensors then measure amplitude and phase of wavelength coming back from surface.

Bell, Jordan R.↗
NASA NTRS1994

Thermal and albedo mapping of the polar regions of Mars using Viking thermal mapper observations: 1. North polar region

We present the first maps of the apparent thermal inertia and albedo of the north polar region of Mars. The observations used to create these maps were acquired by the infrared thermal mapper (IRTM) instruments on the two Viking orbiters over a 50-day period in 1978 during the Martian early northern summer season. The maps cover the region from 60 deg N to the north pole at a spatial resolution of 1/2 deg of latitude. The analysis and interpretation of these maps is aided by the results of a one-dimensional radiative convective model, which is used to calculate diurnal variations in surface and atmospheric temperatures, and brightness temperatures at the top of the atmospphere for a wide range of assumptions concerning aerosol optical properties and aerosol optical depths. The results of these calculations show that the effects of the Martian atmosphere on remote determinations of surface thermal inertia are more significant than have been indicated in previous studies. The maps of apparent thermal inertia and albedo show a great deal of spatial structure that is well correlated with surface features.

Paige, David A.↗
NASA NTRS1993

The Spectral Image Processing System (SIPS) - Interactive visualization and analysis of imaging spectrometer data

The Center for the Study of Earth from Space (CSES) at the University of Colorado, Boulder, has developed a prototype interactive software system called the Spectral Image Processing System (SIPS) using IDL (the Interactive Data Language) on UNIX-based workstations. SIPS is designed to take advantage of the combination of high spectral resolution and spatial data presentation unique to imaging spectrometers. It streamlines analysis of these data by allowing scientists to rapidly interact with entire datasets. SIPS provides visualization tools for rapid exploratory analysis and numerical tools for quantitative modeling. The user interface is X-Windows-based, user friendly, and provides 'point and click' operation. SIPS is being used for multidisciplinary research concentrating on use of physically based analysis methods to enhance scientific results from imaging spectrometer data. The objective of this continuing effort is to develop operational techniques for quantitative analysis of imaging spectrometer data and to make them available to the scientific community prior to the launch of imaging spectrometer satellite systems such as the Earth Observing System (EOS) High Resolution Imaging Spectrometer (HIRIS).

Kruse, F. A.↗
NASA NTRS2022

Flood Monitoring Using Enhanced Resolution Passive Microwave Data: A Test Case Over Bangladesh

Monitoring floods is a major issue in water resources management and risk mitigation, especially in the Global South. Optical and radar observations, even providing a fine spatial resolution, are still limited by cloud cover interaction or insufficient temporal resolution. On the other hand, passive microwave (PMW) sensors collect information on a daily frequency with minor cloud cover interaction, but they have been historically limited in terms of spatial resolution. Here, we evaluate the capability of an enhanced spatial resolution PMW dataset (3.125 km) in monitoring spatio-temporal evolution of flood events, focusing on a major flood event that occurred in October 2005 in Bangladesh. We apply an algorithm aimed to remove the seasonal variability of surface temperature from the PMW timeseries, exploiting the difference in emissivity between dry and water-covered pixels. We assess the capability of the algorithm in capturing flood evolution and extension through the comparison with quantities obtained from optical data collected by the Moderate Resolution Imaging Spectroradiometer (MODIS) and water level measurements. We also compare the enhanced product with the historical coarser resolution dataset by means of a variogram-based analysis to evaluate the improvements in terms of spatial representation. Finally, we evaluate the possibility to extract the water fraction within a single pixel by using an Advanced Microwave Scanning Radiometer—Earth Observing System (AMSR-E) emissivity dataset and compare the estimates with MODIS-derived water fractions. Our results show that the enhanced PMW product outperforms the coarser one when compared to flood mapped from optical data based on information content, indicating that it is possible to integrate such a product into the mapping of floods at a global scale on a daily basis.

flood detection↗
NASA NTRS1973

Multiwire proportional chamber development

The development of large area multiwire proportional chambers, to be used as high resolution spatial detectors in cosmic ray experiments is described. A readout system was developed which uses a directly coupled, lumped element delay-line whose characteristics are independent of the MWPC design. A complete analysis of the delay-line and the readout electronic system shows that a spatial resolution of about 0.1 mm can be reached with the MWPC operating in the strictly proportional region. This was confirmed by measurements with a small MWPC and Fe-55 X-rays. A simplified analysis was carried out to estimate the theoretical limit of spatial resolution due to delta-rays, spread of the discharge along the anode wire, and inclined trajectories. To calculate the gas gain of MWPC's of different geometrical configurations a method was developed which is based on the knowledge of the first Townsend coefficient of the chamber gas.

Doolittle, R. F.↗
NASA NTRS2007

Analysis of Eddy Current Capabilities for the Detection of Outer Diameter Stress Corrosion Cracking in Small Bore Metallic Structures

The use of eddy current techniques for the detection of outer diameter damage in tubing and many complex aerospace structures often requires the use of an inner diameter probe due to a lack of access to the outside of the part. In small bore structures the probe size and orientation are constrained by the inner diameter of the part, complicating the optimization of the inspection technique. Detection of flaws through a significant remaining wall thickness becomes limited not only by the standard depth of penetration, but also geometrical aspects of the probe. Recently, an orthogonal eddy current probe was developed for detection of such flaws in Space Shuttle Primary Reaction Control System (PRCS) Thrusters. In this case, the detection of deeply buried stress corrosion cracking by an inner diameter eddy current probe was sought. Probe optimization was performed based upon the limiting spatial dimensions, flaw orientation, and required detection sensitivity. Analysis of the probe/flaw interaction was performed through the use of finite and boundary element modeling techniques. Experimental data for the flaw detection capabilities, including a probability of detection study, will be presented along with the simulation data. The results of this work have led to the successful deployment of an inspection system for the detection of stress corrosion cracking in Space Shuttle Primary Reaction Control System (PRCS) Thrusters.

Wincheski, Buzz↗
NASA NTRS1997

Planetary Aeronomy and Related Studies

Mercury atmosphere - Sprague and Hunten, in collaboration with Katharina Lodders of Washington University, proposed, mainly on cosmochemical grounds, that S atoms are an important constituent of the atmosphere (30 times more abundant than sodium). This paper has appeared in Icarus. We also suggest that condensed sulfur is an excellent candidate for the radar-bright polar caps, more plausible than water ice because the latter is only barely stable even in permanently-shadowed craters. The best prospect for detection of the vapor is through its resonance lines, a triplet near 1814 A. Mercury is too close to the Sun to be observed by any existing space telescope, but there is some prospect that the search could be made from a Shuttle-based spectrograph such as Lyle Broadfoot's USTAR. Sprague and Hunten have completed an elaborate data analysis of over 100 measurements of the Na D lines, obtained with the 61-inch telescope and our echelle spectrograph. Full account has been taken of the radiative-transfer problem that arises because the Na atmosphere is not optically thin. The output of this code is used in another program that makes an elaborate inverse interpolation in two angles and optical depth and computes the effect of the seeing (always bad for Mercury). The seeing is determined by fitting cuts across a computed image to part of the spectrum adjacent to the sodium lines, and typically ranges from slightly less than 4 arcsec to worse than 6 (diameter at l/e of a Gaussian). The final result is a list of Na abundances, with some information on spatial distribution. One particularly interesting result of further analysis is a strong abundance maximum in the morning relative to the afternoon, confirming an earlier result for potassium, based on much fewer measurements. The analysis are completed during the extension of the present grant. This work depends heavily on the Hapke parameters used to estimate the reflectance of Mercury's surface. The paper by Domingue et al. examines the credibility of the available parameters, which are derived from disk-unresolved photometry, and concludes that errors in the derived Na abundances could be as great as 30%.

Hunten, D. M.↗