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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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The experimental data encompassing surface pressure measurements, and wake surveys at static and wind-on conditions are analyzed. Cruise performance trends reflecting nacelle geometric variations, and nozzle operating conditions are presented. Details of the modeling process are included.
Precipitation assimilation poses a special challenge in that the forward model for rain in a global forecast system is based on parameterized physics, which can have large systematic errors that must be rectified to use precipitation data effectively within a standard statistical analysis framework. We examine some key issues in precipitation assimilation and describe several exploratory studies in assimilating rainfall and latent heating information in NASA's global data assimilation systems using the forecast model as a weak constraint. We present results from two research activities. The first is the assimilation of surface rainfall data using a time-continuous variational assimilation based on a column model of the full moist physics. The second is the assimilation of convective and stratiform latent heating retrievals from microwave sensors using a variational technique with physical parameters in the moist physics schemes as a control variable. We will show the impact of assimilating these data on analyses and forecasts. Among the lessons learned are (1) that the time-continuous application of moisture/temperature tendency corrections to mitigate model deficiencies offers an effective strategy for assimilating precipitation information, and (2) that the model prognostic variables must be allowed to directly respond to an improved rain and latent heating field within an analysis cycle to reap the full benefit of assimilating precipitation information. of microwave radiances versus retrieval information in raining areas, and initial efforts in developing ensemble techniques such as Kalman filter/smoother for precipitation assimilation. Looking to the future, we discuss new research directions including the assimilation
This study examines the influence of photochemical processes on tropospheric ozone distributions over the extratropical western North Pacific. The analysis presented here is based on data collected during the Pacific Exploratory Mission-West Phase B (PEM-West B) field study conducted in February-March 1994. Sampling in the study region involved altitudes of 0-12 km and latitudes of 10deg S to 50deg N. The extratropical component of the data set (i.e., 20-50deg N) was defined by markedly different photochemical environments north and south of 30deg N. This separation was clearly defined by an abrupt decrease in the tropopause height near 30deg N and a concomitant increase in total O3 column density. This shift in overhead O3 led to highly reduced rates of O3 formation and destruction for the 30-50deg N latitude regime. Both latitude ranges, however, still exhibited net O3 production at all altitudes. Of special significance was the finding that net O3 production prevailed even at boundary layer and lower free tropospheric altitudes (e.g., less than 4 km), a condition uncommon to Pacific marine environments. These results reflect the strong impact of continental Outflow of O3 precursors (e.g., NO and NMHCS) into the northwestern Pacific Basin. Comparisons with PEM-West A, which sampled the same region in a different season (September-October), revealed major differences at altitudes below 4 km, the altitude range most influenced by continental outflow. The resulting net rate of increase in the tropospheric O3 column for PEM-West B was 1-3 % per day, while for PEM-West A it was approximately zero. Unique to the PEM-West B study is the finding that even under wintertime conditions substantial column production of tropospheric O3 can occur at subtropical and mid-latitudes. While such impacts may not be totally unexpected at near coast locations, the present study suggests that the impact from continental outflow on the marine BL could extend out to distances of more than 2000 km from the Asian Pacific Rim.
Empirical guidelines for the design of minimum weight turbine rotor disk fragment containment rings made from a monolithic metal were generated by experimentally establishing the relationship between a variable that provides a measure of containment ring capability and several other variables that both characterized the configurational aspects of the rotor fragments and containment ring, and had been found from exploratory testing to have had significant influence on the containment process. Test methodology and data analysis techniques are described. Results are presented in graphs and tables.
An improved data-labeling system provides for automatic association of data products of an exploratory robot (downlink information) with previously transmitted commands (uplink information) that caused the robot to gather the data. Such association is essential to correct and timely analysis of the data products -- including, for example, association of the data with the correct targets. The system was developed for use on Mars Rover missions during the next few years. The system could also be adapted to terrestrial exploratory telerobots for which delays between commands and data returns are long enough to give rise to questions as to which commands resulted in which data returns. The main advantage of this system over prior data-labeling systems is that given a downlink data product, the uplink command and sequence hierarchy that produced it are automatically provided, and given an uplink sequence and command, the downlink data products that it produced are automatically provided.
A neural network based data analysis and decision making system to increase the autonomy of a planetary rover or similar exploratory vehicle is presented. A hierarchical series of neural networks for real time analysis of scientific images is used. The system under development emphasizes analysis of multispectral images by classifier and feature detector neural networks, to provide information on the mineral composition of a scene. A hierarchy of alternating analysis and decision making networks is being developed to allow increasingly fine scale analysis in regions of the image that are potentially important. It is noted that this system will facilitate both the selection of high priorty scientific information for transmission to earth, and the autonomous collection of rocks and soil for sample return.
Microorganisms within spacecraft have traditionally been monitored with culture-based techniques. These techniques involve growth of environmental samples (cabin water, air or surfaces) on agar-type media for several days, followed by visualization of resulting colonies or return of samples to Earth for ground-based analysis. Data obtained over the past 4 decades have enhanced our understanding of the microbial ecology within space stations. However, the approach has been limited by the following factors: i) Many microorganisms (estimated > 95%) in the environment cannot grow on conventional growth media; ii) Significant time lags (3-5 days for incubation and up to several months to return samples to ground); iii) Condensation in contact slides hinders colony counting by crew; and iv) Growth of potentially harmful microorganisms, which must then be disposed of safely. This report describes the operation of a new culture-independent technique onboard the ISS for rapid analysis (within minutes) of endotoxin and beta-1, 3-glucan, found in the cell walls of gramnegative bacteria and fungi, respectively. The technique involves analysis of environmental samples with the Limulus Amebocyte Lysate (LAL) assay in a handheld device, known as the Lab-On-a-Chip Application Development Portable Test System (LOCAD-PTS). LOCADPTS was launched to the ISS in December 2006, and here we present data obtained from Mach 2007 until the present day. These data include a comparative study between LOCADPTS analysis and existing culture-based methods; and an exploratory survey of surface endotoxin and beta-1, 3-glucan throughout the ISS. While a general correlation between LOCAD-PTS and traditional culture-based methods should not be expected, we will suggest new requirements for microbial monitoring based upon culture-independent parameters measured by LOCAD-PTS.
Calculations include drag, nonsphericity, and other perturbations. Artificial Satellite Analysis Program (ASAP) is general orbit-prediction program that incorporates sufficient orbit-modeling accuracy for mission design, maneuver analysis, and mission planning. Suitable for studying planetary orbit missions with spacecraft trajectories of exploratory (mapping) nature. Sample data included for study of drift cycle of geosynchronous station, strategy for mapping Venus by radar, frozen orbit about Mars, and repeat-ground-trace orbit. ASAP written in FORTRAN 77.
The goal of this research in to obtain infrared data on planetary atmospheres which provide information on several aspects of structure and composition. Observations include direct mission real-time support as well as baseline monitoring preceding mission encounters. Besides providing a broader information context for spacecraft experiment data analysis, observations will provide the quantitative data base required for designing optimum remote sensing sequences and evaluating competing science priorities. In the past year, thermal images of Jupiter and Saturn were made near their oppositions in order to monitor long-term changes in their atmospheres. Infrared images of the Jovian polar stratospheric hot spots were made with IUE observations of auroral emissions. An exploratory 5-micrometer spectrum of Uranus was reduced and accepted for publication. An analysis of time-variability of temperature and cloud properties of the Jovian atomsphere was made. Development of geometric reduction programs for imaging data was initiated for the sun workstation. Near-infrared imaging observations of Jupiter were reduced and a preliminary analysis of cloud properties made. The first images of the full disk of Jupiter with a near-infrared array camera were acquired. Narrow-band (10/cm) images of Jupiter and Saturn were obtained with acousto-optical filters.
We have previously outlined a strategy for the detection of fossils [Storrie-Lombardi and Hoover, 2004] and extant microbial life [Storrie-Lombaudi and Hoover, 20051 during robotic missions to Mars using co-registered structural and chemical signatures. Data inputs included image lossless compression indices to estimate relative textural complexity and elemental abundance distributions. Two exploratory classification algorithms (principal component analysis and hierarchical cluster analysis) provide an initial tentative classification of all targets. Nonlinear stochastic neural networks are then trained to produce a Bayesian estimate of algorithm classification accuracy. The strategy previously has been successful in distinguishing regions of biotic and abiotic alteration of basalt glass from unaltered samples. [Storrie-Lombardi and Fisk, 2004; Storrie-Lombardi and Fisk, 2004] Such investigations of abiotic versus biotic alteration of terrestrial mineralogy on Earth are compromised by .the difficulty finding mineralogy completely unaffected by the ubiquitous presence of microbial life on the planet. The renewed interest in lunar exploration offers an opportunity to investigate geological materials that may exhibit signs of aqueous alteration, but are highly unlikely to contain contaminating biological weathering signatures. We here present an extension of our earlier data set to include lunar dust samples obtained during the Apollo 17 mission. Apollo 17 landed in the Taurus-Littrow Valley in Mare Serenitatis. Most of the rock samples from this region of the lunar highlands are basalts comprised primarily of plagioclase and pyroxene and selected examples of orange and black volcanic glass. SEM images and elemental abundances (C6, N7, O8, Na11, Mg12, Al13, Si14, P15, S16, Cll7, K19, Ca20, Fe26) for a series of targets in the lunar dust samples are compared to the extant cyanobacteria, fossil trilobites, Orgueil meteorite, and terrestrial basalt targets previously discussed. The data set provides a first step in producing a quantitative probabilistic methodology for geobiological analysis of returned lunar samples or in situ exploration.
A methodology for Hazard Extraction and Analysis of Trends (HEAT) is proposed and conducted on a data set of wildfire incident response forms, known as ICS-209-PLUS.The HEAT processes: (1) extract a set of hazards from a data set, (2) calculate hazard-relevant metrics in a primary analysis, (3) analyze trends over time in metrics using timeseries, and (4) examine potential explanations for metric trends using a secondary analysis. Hazards are extracted from narrative data in the ICS-209-PLUS based on a framework previously developed by the authors, using natural language processing. Metrics examined for each hazard include operational time to occurrence, rate of occurrence, frequency, and severity. Primary results include a taxonomy of hazards present in the data set with relevant quantitative metrics. The most frequent hazards identified are environmental and include hazardous terrain. Most hazards occur on average between 35-55% containment. Incidents with hazards tend to have a higher average severity score when compared to the average score for all incidents. Time series of the metrics and relevant predictors, including fire characteristics, fire intensity, and operations, are created to facilitate further analysis. Secondary results used to determine which factors best predict hazard frequency include a correlation matrix and regression analysis. These findings are relevant to safety for current, as well as emerging wildfire operations, and are an exploratory first step in developing historical data-driven risk assessment models.
The research activity for this first year has focussed on three distinct activities: (1) the use of an integrating sphere to improve upon the gathering of spectral data from a variety of surfaces; (2) the use of optical fiber spectrometry to determine levels of contamination from tape residues on critical bonding surfaces; and (3) an exploratory activity in the use of spectroscopic ellipsometry for the analysis of thin films of contaminants on critical surfaces has also begun.
Carbon dioxide (CO2) levels on ISS have typically averaged 2.3 to 5.3mm Hg, with large fluctuations occurring over periods of hours and days. CO2 has effects on cerebral vascular tone, resulting in vasodilation and alteration of cerebral blood flow(CBF). Increased CBF leads to elevated intracranial pressure(ICP), which is a factor leading to visual disturbance, headaches, and other central nervous system symptoms. Ultrasound of the optic nerve provides a surrogate measurement of ICP. Inflight ultrasounds were implemented as an enhanced screening tool for the Visual Impairment/Intracranial Pressure (VIIP) Syndrome. This analysis examines the relationships between ambient CO2 levels on ISS and ultrasound measures of the eye in an effort to understand how CO2 may be associated with VIIP and to inform future analysis of inflight VIIP data. Results as shown in Figure2, there was a large timeframe where CO2 readings were removed due to sensor fault errors(see Limitations), from June 2011 to January 2012. After extensive cleaning of the CO2 data, metrics for all of the data were calculated (Table2). Preliminary analyses showed possible associations between variability measures of CO2 and AP diameter (Figure3),and average CO2 exposure and ONSD(Figure4). Adjustments for multiple comparisons were not made due to the exploratory nature of the analysis.
Long-Term Orbit Preditor (LOP) trajectory-propagation computer program is useful tool in analysis of lifetime of orbiting spacecraft. Suitable for studying planetary-orbit missions with reconnaissance (flyby) and exploratory (mapping) trajectories. Includes sample data for study of drift cycle of geosynchronous station, strategy for radar mapping of Venus, frozen orbit about Mars, and orbit characterized by repeating ground trace. Executed faster than such programs based on Cowell's method. Written in FORTRAN 77.
Innovation in high-enthalpy facilities is fundamentally limited by the cost and risk of experimentation. New concepts for plasma control, diagnostics, facility components, and plasma-material interaction often require repeated iterations that are impractical to perform in production arcjets. As a result, promising ideas may remain unexplored or reach operational facilities only after significant development effort. ARCTRON is being developed as a rapid experimental proving ground where new ideas in plasma science, arcjet engineering, diagnostics, and material response can be conceived, tested, and quantitatively evaluated before transition to large-scale facilities. The platform combines radio-frequency (RF) and DC arc plasma generation, externally applied magnetic fields, configurable gas composition, reduced-pressure operation, laser heating, electrical biasing, and modular diagnostic access. These capabilities permit the plasma source, applied forcing, test article, and measurement configuration to be modified independently, allowing individual physical mechanisms to be isolated more readily than in a traditional test environment. One class of investigations addresses fundamental plasma-surface interaction physics. Conventional material tests often expose a specimen simultaneously to convective heating, reactive species, pressure, shear, radiation, and surface-current effects. The resulting material response may be measured accurately, while the contribution of each mechanism remains difficult to identify. ARCTRON is designed to vary these effects selectively. Plasma chemistry can be changed independently through configurable gas mixtures; magnetic fields and electrical biasing can modify charged-particle transport; laser heating can provide a non-plasma thermal input; and pressure, flow, and discharge mode can be varied over a broad operating space. This enables controlled tests of hypotheses involving surface catalycity, reactive-species transport, plasma-assisted oxidation, electromagnetic effects, shear, and the relative contributions of thermal and chemical loading. A second class of investigations enabled by this approach concerns the engineering of high-enthalpy facilities themselves. Arc-heated facilities are limited by electrode erosion, unstable arc attachment, localized heating, and damage to nozzles and other plasma-facing components. ARCTRON provides a lower-cost environment for testing concepts intended to mitigate these limitations. Candidate investigations include the use of applied magnetic fields to alter current paths and reduce plasma interaction with nozzle walls, ExB forcing to introduce controlled plasma rotation, magnetic or geometric approaches for distributing arc attachment, and alternative electrode or discharge configurations intended to reduce erosion and improve stability. Because the platform is reconfigurable, these concepts can be evaluated through repeated design--build--test cycles before they are considered for implementation in operational facilities. The platform also supports the development and validation of diagnostics that may be difficult to introduce initially into a large arcjet. Current and planned measurements include spatially resolved optical emission spectroscopy, electrostatic probes, fast imaging, pyrometry, calorimetry, laser-induced fluorescence, and absorption spectroscopy. These diagnostics are intended not merely to document a nominal operating condition, but to constrain the local plasma state and its relationship to component or material response. The modular facility geometry allows diagnostic concepts to be tested, calibrated, and compared under repeatable conditions before deployment in more demanding environments. ARCTRON is also supported by an integrated software suite. Automated control and data acquisition allow discharge parameters, gas composition, magnetic fields, diagnostic timing, and test configuration to be recorded as part of each experiment (STARDAC - Software for Testing, Analysis, Research Data, and Control). The Backend for Experiment Analysis, Storage, and Traceability (BEAST) is a database that provides the infrastructure needed to associate heterogeneous measurements with facility configuration, specimen identity, calibration state, geometry, and analysis provenance. This backend is particularly important for exploratory campaigns, in which many related configurations may be tested, and the value of an individual experiment depends on its connection to earlier and subsequent iterations. Complementary analysis capabilities, including computer-vision-based transient response measurements (arcjetCV), three-dimensional surface reconstruction (STARSCAN), and model-based Bayesian inference (SHIELD), and tomography data analysis (TOMATO, PuMA) can be incorporated when required by a specific hypothesis without becoming the focus of every campaign. The central objective of ARCTRON is therefore not to maximize heat flux or reproduce a complete flight environment. Its purpose is to reduce the cost and time required to ask consequential questions about plasma behavior, plasma-facing materials, diagnostics, and arcjet technology. By providing a controlled environment for rapid reconfiguration, mechanism isolation, quantitative measurement, and iterative engineering, ARCTRON can help mature concepts that would otherwise remain too speculative or too risky for evaluation in production facilities. The resulting knowledge can then guide the design of material models, focus test objectives in larger arcjets, reduce facility-development risk, and improve the physical basis of high-enthalpy ground testing. This work will present the ARCTRON architecture, operating modes, diagnostic suite, and digital experimental workflow. Initial experimental results from the first integrated operation of the facility will be presented, including flow characterization, power limitations, and deployment of the initial diagnostic suite. Ongoing development efforts aimed at catalycity characterization, magnetic plasma control, and advanced optical diagnostics will also be discussed, illustrating how the platform supports rapid iteration from concept to experiment.
Innovation in high-enthalpy facilities is fundamentally limited by the cost and risk of experimentation. New concepts for plasma control, diagnostics, facility components, and plasma-material interaction often require repeated iterations that are impractical to perform in production arcjets. As a result, promising ideas may remain unexplored or reach operational facilities only after significant development effort. ARCTRON is being developed as a rapid experimental proving ground where new ideas in plasma science, arcjet engineering, diagnostics, and material response can be conceived, tested, and quantitatively evaluated before transition to large-scale facilities. The platform combines radio-frequency (RF) and DC arc plasma generation, externally applied magnetic fields, configurable gas composition, reduced-pressure operation, laser heating, electrical biasing, and modular diagnostic access. These capabilities permit the plasma source, applied forcing, test article, and measurement configuration to be modified independently, allowing individual physical mechanisms to be isolated more readily than in a traditional test environment. One class of investigations addresses fundamental plasma-surface interaction physics. Conventional material tests often expose a specimen simultaneously to convective heating, reactive species, pressure, shear, radiation, and surface-current effects. The resulting material response may be measured accurately, while the contribution of each mechanism remains difficult to identify. ARCTRON is designed to vary these effects selectively. Plasma chemistry can be changed independently through configurable gas mixtures; magnetic fields and electrical biasing can modify charged-particle transport; laser heating can provide a non-plasma thermal input; and pressure, flow, and discharge mode can be varied over a broad operating space. This enables controlled tests of hypotheses involving surface catalycity, reactive-species transport, plasma-assisted oxidation, electromagnetic effects, shear, and the relative contributions of thermal and chemical loading. A second class of investigations enabled by this approach concerns the engineering of high-enthalpy facilities themselves. Arc-heated facilities are limited by electrode erosion, unstable arc attachment, localized heating, and damage to nozzles and other plasma-facing components. ARCTRON provides a lower-cost environment for testing concepts intended to mitigate these limitations. Candidate investigations include the use of applied magnetic fields to alter current paths and reduce plasma interaction with nozzle walls, ExB forcing to introduce controlled plasma rotation, magnetic or geometric approaches for distributing arc attachment, and alternative electrode or discharge configurations intended to reduce erosion and improve stability. Because the platform is reconfigurable, these concepts can be evaluated through repeated design--build--test cycles before they are considered for implementation in operational facilities. The platform also supports the development and validation of diagnostics that may be difficult to introduce initially into a large arcjet. Current and planned measurements include spatially resolved optical emission spectroscopy, electrostatic probes, fast imaging, pyrometry, calorimetry, laser-induced fluorescence, and absorption spectroscopy. These diagnostics are intended not merely to document a nominal operating condition, but to constrain the local plasma state and its relationship to component or material response. The modular facility geometry allows diagnostic concepts to be tested, calibrated, and compared under repeatable conditions before deployment in more demanding environments. ARCTRON is also supported by an integrated software suite. Automated control and data acquisition allow discharge parameters, gas composition, magnetic fields, diagnostic timing, and test configuration to be recorded as part of each experiment (STARDAC - Software for Testing, Analysis, Research Data, and Control). The Backend for Experiment Analysis, Storage, and Traceability (BEAST) is a database that provides the infrastructure needed to associate heterogeneous measurements with facility configuration, specimen identity, calibration state, geometry, and analysis provenance. This backend is particularly important for exploratory campaigns, in which many related configurations may be tested, and the value of an individual experiment depends on its connection to earlier and subsequent iterations. Complementary analysis capabilities, including computer-vision-based transient response measurements (arcjetCV), three-dimensional surface reconstruction (STARSCAN), and model-based Bayesian inference (SHIELD), and tomography data analysis (TOMATO, PuMA) can be incorporated when required by a specific hypothesis without becoming the focus of every campaign. The central objective of ARCTRON is therefore not to maximize heat flux or reproduce a complete flight environment. Its purpose is to reduce the cost and time required to ask consequential questions about plasma behavior, plasma-facing materials, diagnostics, and arcjet technology. By providing a controlled environment for rapid reconfiguration, mechanism isolation, quantitative measurement, and iterative engineering, ARCTRON can help mature concepts that would otherwise remain too speculative or too risky for evaluation in production facilities. The resulting knowledge can then guide the design of material models, focus test objectives in larger arcjets, reduce facility-development risk, and improve the physical basis of high-enthalpy ground testing. This work will present the ARCTRON architecture, operating modes, diagnostic suite, and digital experimental workflow. Initial experimental results from the first integrated operation of the facility will be presented, including flow characterization, power limitations, and deployment of the initial diagnostic suite. Ongoing development efforts aimed at catalycity characterization, magnetic plasma control, and advanced optical diagnostics will also be discussed, illustrating how the platform supports rapid iteration from concept to experiment.
Fast automated analysis of hyperspectral imagery can inform observation planning and tactical decisions during planetary exploration. Products such as mineralogical maps can focus analysts' attention on areas of interest and assist data mining in large hyperspectral catalogs. In this work, sparse spectral unmixing drafts mineral abundance maps with Compact Reconnaissance Imaging Spectrometer (CRISM) images from the Mars Reconnaissance Orbiter. We demonstrate a novel "superpixel" segmentation strategy enabling efficient unmixing in an interactive session. Tests correlate automatic unmixing results based on redundant spectral libraries against hand-tuned summary products currently in use by CRISM researchers.
A NASA grant provided support for a research project at Augsbury College, Minneapolis, Minnesota for the analysis of atomic nitrogen density data obtained by the Neutral Atmospheric Composition Spectrometer (NACS) on board the Dynamics Explorer-2 satellite. Initial funding was for an exploratory study of the feasibility of obtaining ambient densities of N from source densities of NO. Funding was continued under the Dynamics Explorer Guest Investigator Program when initial studies indicated probable success in obtaining such ambient densities. The major scientific focus of the later work was to be to characterize the behavior of N densities at high latitudes.