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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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At least 19 records

Urban street patterns detectable from ERTS-1

The author has identified the following significant results. The major street patterns in Lincoln, Nebraska, are detectable on the January 24, 1973 ERTS MSS-4 image. To further study and identify the street patterns, a 3x Polaroid enlargement was made of the city from the image. An overlay of the enlargement was used to map the street patterns, with reference to the original image for clarity. The technique seems to be adaptable for updating standard road maps.

Morain, S. A.↗

Methylation Pattern Detection in the Genome of Bacillus Pumilus Strain SAFR-032

Bacillus pumilus SAFR-032, an endospore-forming bacterial strain that was isolated from a spacecraft assembly facility (SAFR), was investigated to determine its methylation pattern (methylome) across the genome in comparison to the previously sequenced reference genome. In addition, a version of SAFR-032 that was flown as spores for 18 months on the International Space Station (ISS) was also investigated for possible genomic changes due to long-duration ISS-flight and to determine if methylation patterns may have changed. Both the genomics and methylomics were conducted using a Nanopore MinION sequencing device. In addition to the omics investigation, the two SAFR-032 strains, ISS flown and non-ISS flown, were compared phenotypically in chamber experiments testing individual environmental insults: ionizing radiation, UV exposure, and cold desiccation (i.e. freeze drying). Results from this study inform on Planetary Protection concerns and will reveal potential DNA damage associated with long-term spaceflight and how such damage may influence survivors after being transported to an extraterrestrial environment, such as Mars.

Serda, Bianca M.↗

A Screening Method Using Pulsed-Power Combined with Infrared Imaging to Detect Pattern Defects in Bulk Metal Foil or Thin Film Resistors

Bulk metal foil and thin film resistors occasionally contain localized defects within the etched resistor pattern. Common defects of this type include in-line constrictions referred to as notches, unremoved resistor material bridges between adjacent pattern lines, and embedded non-conductive particles in the resistor material. Such defects are prone to fracture due to thermomechanical fatigue during powered operation, especially power cycling, resulting in positive resistance change and open circuit failure modes. Common screening methods of optical microscopy, short time overload power tests (e.g., 6.25x rated power for 5 seconds) and burn-in (e.g., 1.5x rated power for 100 hours) are useful, but they are not always effective at removing devices with such defects. An improved method has been developed to screen for localized resistor pattern defects. The method involves the application of brief, high power electrical pulses at a low duty cycle while inspecting the resistor with a high resolution, high speed infrared camera. The following test conditions were found to be suitable for this purpose: 6.25x rated power, 1 to 5 pulses, 50 ms pulse width and 10% duty cycle. During the power pulsing, localized constrictions in the resistor pattern are identifiable as hot spots via the infrared camera. Reject criteria can be established based on observations of hot spots. To assess its effectiveness, a total of two hundred eighty (280) surface mount foil resistors (40 each from 7 different lots) were screened using this infrared technique. The screening identified twenty-nine (29) resistors with significant hot spots in the resistor pattern. All 280 resistors were then subjected to an industry standard 10,000 hour life test at 1x rated power at 70°C with power cycled for 90 minutes on and 30 minutes off. During life testing, three resistors exhibited positive resistance change failure mode. All three failures were due to thermomechanical fatigue failure of localized bridge defects at the locations identified via infrared screening. The results of this evaluation illustrate the benefits of the pulsed-power infrared detection screening technique to identify reliability suspect foil or thin film resistors that may escape common screening methods.

screening↗

A Screening Method Using Pulsed-Power Combined with Infrared Imaging to Detect Pattern Defects in Bulk Metal Foil or Thin Film Resistors

Bulk metal foil and thin film resistors occasionally contain localized defects within the etched resistor pattern. Common defects of this type include in-line constrictions referred to as notches, unremoved resistor material bridges between adjacent pattern lines, and embedded non-conductive particles in the resistor material. Such defects are prone to fracture due to thermomechanical fatigue during powered operation, especially power cycling, resulting in positive resistance change and open circuit failure modes. Common screening methods of optical microscopy, short time overload power tests (e.g., 6.25x rated power for 5 seconds) and burn-in (e.g., 1.5x rated power for 100 hours) are useful, but they are not always effective at removing devices with such defects. An improved method has been developed to screen for localized resistor pattern defects. The method involves the application of brief, high power electrical pulses at a low duty cycle while inspecting the resistor with a high resolution, high speed infrared camera. The following test conditions were found to be suitable for this purpose: 6.25x rated power, 1 to 5 pulses, 50 ms pulse width and 10% duty cycle. During the power pulsing, localized constrictions in the resistor pattern are identifiable as hot spots via the infrared camera. Reject criteria can be established based on observations of hot spots. To assess its effectiveness, a total of two hundred eighty (280) surface mount foil resistors (40 each from 7 different lots) were screened using this infrared technique. The screening identified twenty-nine (29) resistors with significant hot spots in the resistor pattern. All 280 resistors were then subjected to an industry standard 10,000 hour life test at 1x rated power at 70°C with power cycled for 90 minutes on and 30 minutes off. During life testing, three resistors exhibited positive resistance change failure mode. All three failures were due to thermomechanical fatigue failure of localized bridge defects at the locations identified via infrared screening. The results of this evaluation illustrate the benefits of the pulsed-power infrared detection screening technique to identify reliability suspect foil or thin film resistors that may escape common screening methods.

screening↗

A gridding approach to detect patterns of change in coastal wetlands from digital data

The conversion of land to water or water to land in the Grand Bayou wetlands area from 1972 to 1981 is evaluated on the basis of Landsat MSS band 2 and 4 images. A postclassification (land vs water) procedure is employed, and grids 1, 5, 10, 25, and 50 pixels square are superimposed on the classified data in an effort to reduce the effects of poor georegistration of the images (simulated by shifting one set of grids two pixels vertically and horizontally). The results are presented in tables, maps, and sample images and characterized in detail. Grids 5 or 10 pixels square are found to give percentage land/water change values and locations similar to those obtained in pixel-by-pixel analysis of nearly perfectly matched images.

Pelletier, R. E.↗

VLSI processors for signal detection in SETI

The objective of the Search for Extraterrestrial Intelligence (SETI) is to locate an artificially created signal coming from a distant star. This is done in two steps: (1) spectral analysis of an incoming radio frequency band, and (2) pattern detection for narrow-band signals. Both steps are computationally expensive and require the development of specially designed computer architectures. To reduce the size and cost of the SETI signal detection machine, two custom VLSI chips are under development. The first chip, the SETI DSP Engine, is used in the spectrum analyzer and is specially designed to compute Discrete Fourier Transforms (DFTs). It is a high-speed arithmetic processor that has two adders, one multiplier-accumulator, and three four-port memories. The second chip is a new type of Content-Addressable Memory. It is the heart of an associative processor that is used for pattern detection. Both chips incorporate many innovative circuits and architectural features.

NASA Program Exobiology↗

Terrestrial sedimentation impact on coral and macroalgal cover in Puerto Rico's southwest coral reefs.

The coral reefs in southwest Puerto Rico (PR) have faced coral cover reduction in the last decades due to changes in its environment that can be related to sedimentation entrance resulting from anthropogenic activities in the watershed (i.e., agriculture and urban development). The Guánica Bay and La Parguera reef platforms are two natural reserves important for recreational and fishing activities. Nonetheless, their respective coral cover has decreased dramatically. Data from a previous NASA-funded project (HICE-PR) conducted between 2014-2018 was analyzed to better understand how the terrigenous sedimentation can affect the coral reef benthic composition in Guánica Bay and La Parguera. A one-way Nested ANOVA and a Tukey's HSD analyses were applied to find differences in benthic cover composition within and among the sites and location. The preliminary results showed differences in coral cover and macroalgae cover between the platforms reefs sites. The coral cover in La Parguera was higher and averaged 11.5% compared to that of Guánica (8.6%), while the macroalgae cover followed a similar pattern. Both coral cover and macroalgae in La Parguera and Guánica varied between from 2016 to 2018 with a general trend of increased coral cover in La Parguera and increase in macroalgae in Guánica. These trends can be related to the distance to the coastline as those reefs located closer to the coastline showed a greater percentage in macroalgal cover than those located farther. Cover of macroalgae and corals at reefs located a mid-distance to the coastline varied with no definite pattern detected. These results will be further correlated with variations in water quality obtained from remotely-sensed data (patterns of chlorophyll a, total suspended sediments, vertical attenuation coefficient) to support the prediction and tracking of coral cover changes in PR's southwest region.

macroalgal↗

The 1974 Ethiopian rift geodimeter survey

The field techniques and methods of data reduction for five successive geodimeter surveys in the Ethiopian rift valley are enlarged upon, with the considered conclusion that there is progressive accumulation of upper crustal strain, consonant with on-going rift extension. The extension is restricted to the Quaternary volcanotectonic axis of the rift, namely the Wonji fault belt, and is occurring at rates of 3 to 6 mm/yr in the northern sector of the rift valley. Although this concurs with the predictions of platetectonic analysis of the Afar triple junction, it is considered premature to endorse such a concurrence on the basis of only 5 years of observations. This is underlined by the detection of local tectonic contractions and expansions associated with geothermal and gravity anomalies in the central sector of the rift valley. There is a hint of a component of dextral slip along some of the rift-floor fault zones, both from geological evidence and from the strain patterns detected in the present geodetic surveys.

Mohr, P.↗

Improve Data Mining and Knowledge Discovery Through the Use of MatLab

Data mining is widely used to mine business, engineering, and scientific data. Data mining uses pattern based queries, searches, or other analyses of one or more electronic databases/datasets in order to discover or locate a predictive pattern or anomaly indicative of system failure, criminal or terrorist activity, etc. There are various algorithms, techniques and methods used to mine data; including neural networks, genetic algorithms, decision trees, nearest neighbor method, rule induction association analysis, slice and dice, segmentation, and clustering. These algorithms, techniques and methods used to detect patterns in a dataset, have been used in the development of numerous open source and commercially available products and technology for data mining. Data mining is best realized when latent information in a large quantity of data stored is discovered. No one technique solves all data mining problems; challenges are to select algorithms or methods appropriate to strengthen data/text mining and trending within given datasets. In recent years, throughout industry, academia and government agencies, thousands of data systems have been designed and tailored to serve specific engineering and business needs. Many of these systems use databases with relational algebra and structured query language to categorize and retrieve data. In these systems, data analyses are limited and require prior explicit knowledge of metadata and database relations; lacking exploratory data mining and discoveries of latent information. This presentation introduces MatLab(R) (MATrix LABoratory), an engineering and scientific data analyses tool to perform data mining. MatLab was originally intended to perform purely numerical calculations (a glorified calculator). Now, in addition to having hundreds of mathematical functions, it is a programming language with hundreds built in standard functions and numerous available toolboxes. MatLab's ease of data processing, visualization and its enormous availability of built in functionalities and toolboxes make it suitable to perform numerical computations and simulations as well as a data mining tool. Engineers and scientists can take advantage of the readily available functions/toolboxes to gain wider insight in their perspective data mining experiments.

Shaykhian, Gholam Ali↗

Improve Data Mining and Knowledge Discovery through the use of MatLab

Data mining is widely used to mine business, engineering, and scientific data. Data mining uses pattern based queries, searches, or other analyses of one or more electronic databases/datasets in order to discover or locate a predictive pattern or anomaly indicative of system failure, criminal or terrorist activity, etc. There are various algorithms, techniques and methods used to mine data; including neural networks, genetic algorithms, decision trees, nearest neighbor method, rule induction association analysis, slice and dice, segmentation, and clustering. These algorithms, techniques and methods used to detect patterns in a dataset, have been used in the development of numerous open source and commercially available products and technology for data mining. Data mining is best realized when latent information in a large quantity of data stored is discovered. No one technique solves all data mining problems; challenges are to select algorithms or methods appropriate to strengthen data/text mining and trending within given datasets. In recent years, throughout industry, academia and government agencies, thousands of data systems have been designed and tailored to serve specific engineering and business needs. Many of these systems use databases with relational algebra and structured query language to categorize and retrieve data. In these systems, data analyses are limited and require prior explicit knowledge of metadata and database relations; lacking exploratory data mining and discoveries of latent information. This presentation introduces MatLab(TradeMark)(MATrix LABoratory), an engineering and scientific data analyses tool to perform data mining. MatLab was originally intended to perform purely numerical calculations (a glorified calculator). Now, in addition to having hundreds of mathematical functions, it is a programming language with hundreds built in standard functions and numerous available toolboxes. MatLab's ease of data processing, visualization and its enormous availability of built in functionalities and toolboxes make it suitable to perform numerical computations and simulations as well as a data mining tool. Engineers and scientists can take advantage of the readily available functions/toolboxes to gain wider insight in their perspective data mining experiments.

Shaykahian, Gholan Ali↗

Atmospheric scattering effects on ground-based measurements of thermospheric winds

Convergent or divergent thermospheric wind patterns detected by ground-based Fabry-Perot interferometric measurements of the Doppler shifts of atomic lines are demonstrated to occur in the presence of strong intensity gradients and a scattering atmosphere. Consideration is given to the color shifts observed when sighting to the north or the south, and a numerical model is developed to describe the wind patterns which produce the recorded shifts. An account is taken of the direct and scattered components of the brightness, with the atmosphere treated as a single scattering layer with a reflecting surface underneath. A scattering coefficient is calculated, together with the line shape of the wavelength shifts. The scattered light is demonstrated, both through simulations and measurements taken near Calgary, Alberta, to produce convergence or divergence of the color shifts, depending on the line-of-sight of the viewing.

Abreu, V. J.↗

Comparisons of neural networks to standard techniques for image classification and correlation

Neural network techniques for multispectral image classification and spatial pattern detection are compared to the standard techniques of maximum-likelihood classification and spatial correlation. The neural network produced a more accurate classification than maximum-likelihood of a Landsat scene of Tucson, Arizona. Some of the errors in the maximum-likelihood classification are illustrated using decision region and class probability density plots. As expected, the main drawback to the neural network method is the long time required for the training stage. The network was trained using several different hidden layer sizes to optimize both the classification accuracy and training speed, and it was found that one node per class was optimal. The performance improved when 3x3 local windows of image data were entered into the net. This modification introduces texture into the classification without explicit calculation of a texture measure. Larger windows were successfully used for the detection of spatial features in Landsat and Magellan synthetic aperture radar imagery.

Paola, Justin D.↗

The effect of lossy image compression on image classification

We have classified four different images, under various levels of JPEG compression, using the following classification algorithms: minimum-distance, maximum-likelihood, and neural network. The training site accuracy and percent difference from the original classification were tabulated for each image compression level, with maximum-likelihood showing the poorest results. In general, as compression ratio increased, the classification retained its overall appearance, but much of the pixel-to-pixel detail was eliminated. We also examined the effect of compression on spatial pattern detection using a neural network.

Paola, Justin D.↗

Overview of the Center for Advanced Space Propulsion

The mission of the Center for Advanced Space Propulsion (CASP), a Center for the Commercial Development of Space (CCDS), is to strengthen U.S. competitiveness in space technology, foster cooperative research with industry and government, assist industry in developing commercial products and services, and perform research in advanced space propulsion. Current areas of focus are (1) advanced chemical propulsion, including high area ratio nozzle performance, variable thrust engine performance, and spray combustion stability; (2) artificial intelligence propulsion applications, including health monitoring of rocket engines, fault pattern detection and diagnosis, and intelligent hypertext applications; (3) microgravity fluid management, including liquid storage and transfer, a subscale orbital fluid transfer experiment, and helical, two-phase flow; (4) electric propulsion, including magnetic annular arc thruster, ion thrustor, and electrostatic plasma accelerator; and (5) laser materials processing.

George W Garrison↗

Optimal Correlation Filters for Images with Signal-Dependent Noise

We address the design of optimal correlation filters for pattern detection and recognition in the presence of signal-dependent image noise sources. The particular examples considered are film-grain noise and speckle. Two basic approaches are investigated: (1) deriving the optimal matched filters for the signal-dependent noise models and comparing their performances with those derived for traditional signal-independent noise models and (2) first nonlinearly transforming the signal-dependent noise to signal-independent noise followed by the use of a classical filter matched to the transformed signal. We present both theoretical and computer simulation results that demonstrate the generally superior performance of the second approach in terms of the correlation peak signal-to-noise ratio.

Downie, John D.↗