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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 469 records · Page 26

Software and Algorithms for Biomedical Image Data Processing and Visualization

A new software equipped with novel image processing algorithms and graphical-user-interface (GUI) tools has been designed for automated analysis and processing of large amounts of biomedical image data. The software, called PlaqTrak, has been specifically used for analysis of plaque on teeth of patients. New algorithms have been developed and implemented to segment teeth of interest from surrounding gum, and a real-time image-based morphing procedure is used to automatically overlay a grid onto each segmented tooth. Pattern recognition methods are used to classify plaque from surrounding gum and enamel, while ignoring glare effects due to the reflection of camera light and ambient light from enamel regions. The PlaqTrak system integrates these components into a single software suite with an easy-to-use GUI (see Figure 1) that allows users to do an end-to-end run of a patient s record, including tooth segmentation of all teeth, grid morphing of each segmented tooth, and plaque classification of each tooth image. The automated and accurate processing of the captured images to segment each tooth [see Figure 2(a)] and then detect plaque on a tooth-by-tooth basis is a critical component of the PlaqTrak system to do clinical trials and analysis with minimal human intervention. These features offer distinct advantages over other competing systems that analyze groups of teeth or synthetic teeth. PlaqTrak divides each segmented tooth into eight regions using an advanced graphics morphing procedure [see results on a chipped tooth in Figure 2(b)], and a pattern recognition classifier is then used to locate plaque [red regions in Figure 2(d)] and enamel regions. The morphing allows analysis within regions of teeth, thereby facilitating detailed statistical analysis such as the amount of plaque present on the biting surfaces on teeth. This software system is applicable to a host of biomedical applications, such as cell analysis and life detection, or robotic applications, such as product inspection or assembly of parts in space and industry.

Talukder, Ashit↗

New Approaches to Quantifying Transport Model Error in Atmospheric CO2 Simulations

In recent years, much progress has been made in observing CO2 distributions from space. However, the use of these observations to infer source/sink distributions in inversion studies continues to be complicated by difficulty in quantifying atmospheric transport model errors. We will present results from several different experiments designed to quantify different aspects of transport error using the Goddard Earth Observing System, Version 5 (GEOS-5) Atmospheric General Circulation Model (AGCM). In the first set of experiments, an ensemble of simulations is constructed using perturbations to parameters in the model s moist physics and turbulence parameterizations that control sub-grid scale transport of trace gases. Analysis of the ensemble spread and scales of temporal and spatial variability among the simulations allows insight into how parameterized, small-scale transport processes influence simulated CO2 distributions. In the second set of experiments, atmospheric tracers representing model error are constructed using observation minus analysis statistics from NASA's Modern-Era Retrospective Analysis for Research and Applications (MERRA). The goal of these simulations is to understand how errors in large scale dynamics are distributed, and how they propagate in space and time, affecting trace gas distributions. These simulations will also be compared to results from NASA's Carbon Monitoring System Flux Pilot Project that quantified the impact of uncertainty in satellite constrained CO2 flux estimates on atmospheric mixing ratios to assess the major factors governing uncertainty in global and regional trace gas distributions.

Ott, L.↗

Repeatability of Cryogenic Multilayer Insulation

Due to the variety of requirements across aerospace platforms, and one off projects, the repeatability of cryogenic multilayer insulation has never been fully established. The objective of this test program is to provide a more basic understanding of the thermal performance repeatability of MLI systems that are applicable to large scale tanks. There are several different types of repeatability that can be accounted for: these include repeatability between multiple identical blankets, repeatability of installation of the same blanket, and repeatability of a test apparatus. The focus of the work in this report is on the first two types of repeatability. Statistically, repeatability can mean many different things. In simplest form, it refers to the range of performance that a population exhibits and the average of the population. However, as more and more identical components are made (i.e. the population of concern grows), the simple range morphs into a standard deviation from an average performance. Initial repeatability testing on MLI blankets has been completed at Florida State University. Repeatability of five GRC provided coupons with 25 layers was shown to be +/- 8.4 whereas repeatability of repeatedly installing a single coupon was shown to be +/- 8.0. A second group of 10 coupons have been fabricated by Yetispace and tested by Florida State University, through the first 4 tests, the repeatability has been shown to be +/- 16. Based on detailed statistical analysis, the data has been shown to be statistically significant.

multilayer insulation↗

Repeatability of Cryogenic Multilayer Insulation

Due to the variety of requirements across aerospace platforms, and one off projects, the repeatability of cryogenic multilayer insulation has never been fully established. The objective of this test program is to provide a more basic understanding of the thermal performance repeatability of MLI systems that are applicable to large scale tanks. There are several different types of repeatability that can be accounted for: these include repeatability between multiple identical blankets, repeatability of installation of the same blanket, and repeatability of a test apparatus. The focus of the work in this report is on the first two types of repeatability. Statistically, repeatability can mean many different things. In simplest form, it refers to the range of performance that a population exhibits and the average of the population. However, as more and more identical components are made (i.e. the population of concern grows), the simple range morphs into a standard deviation from an average performance. Initial repeatability testing on MLI blankets has been completed at Florida State University. Repeatability of five GRC provided coupons with 25 layers was shown to be +/- 8.4% whereas repeatability of repeatedly installing a single coupon was shown to be +/- 8.0%. A second group of 10 coupons have been fabricated by Yetispace and tested by Florida State University, through the first 4 tests, the repeatability has been shown to be +/- 15-25%. Based on detailed statistical analysis, the data has been shown to be statistically significant.

multilayer insulation↗

The PetitSat Mission – Science Goals and Instrumentation

The mid- and low-latitude ionosphere is home to a variety of plasma density irregularities, including depletions (bubbles), enhancements (blobs), and small-scale scintillation. Previous studies of plasma density enhancements observed using ROCSAT data have posited that these structures are the direct result of the formation of bubbles near the geomagnetic equator. However, more recent observations from the C/NOFS satellite suggest that multiple mechanisms are responsible for forming plasma enhancements, with wave action in the ionosphere and thermosphere as a significant driver of the enhanced densities. Indeed, statistical analysis of enhancements observed from satellites resembles the statistics of Medium-Scale Traveling Ionosphere Disturbances (MSTIDs) with respect to seasonal variability and solar activity. petitSat is a CubeSat mission designed to examine the link between MSTIDs and plasma enhancements. The mission will provide in situ measurements of the plasma density, 3D ion drift, as well as ion and neutral composition. The instrument suite includes a combined retarding potential analyzer and cross-track drift meter and an ion-neutral mass spectrometer. This instrument suite will provide comprehensive information about the fluctuations in plasma, as well as changes in the neutral profile. petitSat will launch into a 51 deg inclination orbit at 400 km (consistent with an International Space Station deployment), allowing for numerous conjunctions with the Boston University All-Sky Imager network over the mission lifetime.

J. Klenzing↗

Advanced probabilistic method of development

Advanced structural reliability methods are utilized on the Probabilistic Structural Analysis Methods (PSAM) project to provide a tool for analysis and design of space propulsion system hardware. The role of the effort at the University of Arizona is to provide reliability technology support to this project. PSAM computer programs will provide a design tool for analyzing uncertainty associated with thermal and mechanical loading, material behavior, geometry, and the analysis methods used. Specifically, reliability methods are employed to perform sensitivity analyses, to establish the distribution of a critical response variable (e.g., stress, deflection), to perform reliability assessment, and ultimately to produce a design which will minimize cost and/or weight. Uncertainties in the design factors of space propulsion hardware are described by probability models constructed using statistical analysis of data. Statistical methods are employed to produce a probability model, i.e., a statistical synthesis or summary of each design variable in a format suitable for reliability analysis and ultimately, design decisions.

Wirsching, P. H.↗

Nearfield Summary and Analysis of the Third AIAA Sonic Boom Prediction Workshop C608 Low Boom Demonstrator

A summary and statistical analysis of the nearfield Computational Fluid Dynamics (CFD) submissions for the Third AIAA Sonic Boom Prediction Workshop is provided with a focus on the C608 Low Boom Flight Test Demonstrator. The C608 is more complex in terms of geometry and propulsion boundary conditions than previous workshops cases and is more representative of vehicles with lower ground loudness and the potential for lower annoyance. The nearfield signatures submitted by the participants are propagated to the ground to compute statistics of loudness measures over the vehicle sonic boom carpet. Principle component analysis is used to extract the primary variation modes. Context from previous sonic boom workshops indicates that this workshop has the lowest variation even though the case is more challenging because it is quieter and more complex. The international state-of-the-art results documented in this summary indicates that nearfield CFD variation is low enough for meaningful low-boom design and can contribute toward the discussion of replacing the prohibition of overland supersonic flight with a certification standard.

sonic boom↗

Quantitative suspended sediment mapping using aircraft remotely sensed multispectral data

Suspended sediment is an important environmental parameter for monitoring water quality, water movement, and land use. Quantitative suspended sediment determinations were made from analysis of aircraft remotely sensed multispectral digital data. A statistical analysis and derived regression equation were used to determine and plot quantitative suspended sediment concentration contours in the tidal James River, Virginia, on May 28, 1974. From the analysis, a single band, Band 8 (0.70-0.74 microns), was adequate for determining suspended sediment concentrations. A correlation coefficient of 0.89 was obtained with a mean inaccuracy of 23.5 percent for suspended sediment concentrations up to about 50 mg/l. Other water quality parameters - secchi disc depth and chlorophyll - also had high correlations with the remotely sensed data. Particle size distribution had only a fair correlation with the remotely sensed data.

Johnson, R. W.↗

GPS FOM Chimney Analysis using Generalized Extreme Value Distribution

Many a time an objective of a statistical analysis is to estimate a limit value like 3-sigma 95% confidence upper limit from a data sample. The generalized Extreme Value Distribution method can be profitably employed in many situations for such an estimate. . .. It is well known that according to the Central Limit theorem the mean value of a large data set is normally distributed irrespective of the distribution of the data from which the mean value is derived. In a somewhat similar fashion it is observed that many times the extreme value of a data set has a distribution that can be formulated with a Generalized Distribution. In space shuttle entry with 3-string GPS navigation the Figure Of Merit (FOM) value gives a measure of GPS navigated state accuracy. A GPS navigated state with FOM of 6 or higher is deemed unacceptable and is said to form a FOM 6 or higher chimney. A FOM chimney is a period of time during which the FOM value stays higher than 5. A longer period of FOM of value 6 or higher causes navigated state to accumulate more error for a lack of state update. For an acceptable landing it is imperative that the state error remains low and hence at low altitude during entry GPS data of FOM greater than 5 must not last more than 138 seconds. I To test the GPS performAnce many entry test cases were simulated at the Avionics Development Laboratory. Only high value FoM chimneys are consequential. The extreme value statistical technique is applied to analyze high value FOM chimneys. The Maximum likelihood method is used to determine parameters that characterize the GEV distribution, and then the limit value statistics are estimated.

Ott, Rick↗

Dynamics of solar filaments. III - Analysis of steady flows in H-alpha and C IV lines

A statistical analysis of intensities and radial velocities of several solar plage filaments (i.e. prominences seen on the solar disk) observed at disk center is presented. Intensity and radial (= vertical) velocity maps were derived from simultaneous 2D measurements of the H-alpha chromospheric line with the Multichannel Subtractive Double Pass spectrograph operating on the Meudon solar tower, and also obtained from 2D recordings of the C IV transition-zone line (1548 A) with the UV Spectrometer and Polarimeter aboard the Solar Maximum Mission satellite. A good correlation (around 0.5) is found between intensities in both lines, as well as between velocities. Persistent upflows are measured in both lines at the filament location. The mean vertical velocities are respectively 0.5 km/s in H-alpha and 5.6 km/s in C IV. The analysis of mass fluxes suggests that C IV upflows occur in the transition region around prominences rather than below, in the chromosphere-corona transition zone.

Schmieder, B.↗

Principle Component Analysis of AIRS and CrIS Data

Synthetic Eigen Vectors (EV) used for the statistical analysis of the PC reconstruction residual of large ensembles of data are a novel tool for the analysis of data from hyperspectral infrared sounders like the Atmospheric Infrared Sounder (AIRS) on the EOS Aqua and the Cross-track Infrared Sounder (CrIS) on the SUOMI polar orbiting satellites. Unlike empirical EV, which are derived from the observed spectra, the synthetic EV are derived from a large ensemble of spectra which are calculated assuming that, given a state of the atmosphere, the spectra created by the instrument can be accurately calculated. The synthetic EV are then used to reconstruct the observed spectra. The analysis of the differences between the observed spectra and the reconstructed spectra for Simultaneous Nadir Overpasses of tropical oceans reveals unexpected differences at the more than 200 mK level under relatively clear conditions, particularly in the mid-wave water vapor channels of CrIS. The repeatability of these differences using independently trained SEV and results from different years appears to rule out inconsistencies in the radiative transfer algorithm or the data simulation. The reasons for these discrepancies are under evaluation.

infrared↗

Statistical and Prediction modeling of the Ka Band Using Experimental Results from ACTS Propagation Terminals at 20.185 and 27.505 GHZ

With the increase in demand for wireless communication services, most of the operating frequency bands have become very congested. The increase of wireless costumers is only fractional contribution to this phenomenon. The demand for more services such as video streams and internet explorer which require a lot of band width has been a more significant contributor to the congestion in a communication system. One way to increase the amount of information or data per unit of time transmitted with in a wireless communication system is to use a higher radio frequency. However in spite the advantage available in the using higher frequency bands such as, the Ka-band, higher frequencies also implies short wavelengths. And shorter wavelengths are more susceptible to rain attenuation. Until the Advanced Communication Technology Satellite (ACTS) was launched, the Ka- band frequency was virtually unused - the majority of communication satellites operated in lower frequency bands called the C- and Ku- bands. Ka-band is desirable because its higher frequency allows wide bandwidth applications, smaller spacecraft and ground terminal components, and stronger signal strength. Since the Ka-band is a high frequency band, the millimeter wavelengths of the signals are easily degraded by rain. This problem known as rain fade or rain attenuation The Advanced Communication Technology Satellite (ACTS) propagation experiment has collected 5 years of Radio Frequency (RF) attenuation data from December 1993 to November 1997. The objective of my summer work is to help develop the statistics and prediction techniques that will help to better characterize the Ka Frequency band. The statistical analysis consists of seasonal and cumulative five-year attenuation statistics for the 20.2 and 27.5 GHz. The cumulative five-year results give the link outage that occurs for a given link margin. The experiment has seven ground station terminals that can be attributed to a unique rain zone climate. The locations are White Sands, NM, Tampa, Fly Clarksburg, MD, Norman, OK, Ft. Collins, COY Vancouver, BC, and Fairbanks, AK. The analysis will help us to develop and define specific parameters that will help system engineers develop the appropriated instrumentation and structure for a Ka-band wireless communication systems and networks.

Ogunwuyi, Oluwatosin O.↗

Economic Storage Size Optimization for Electric Vehicle Extreme-Fast Charging Stations

En-route charging infrastructure for electric vehicles is critical to support transportation needs. These charging stations are likely to have high loads and especially sharp peak loads given fast charging capabilities needed to meet transportation schedules. In order to reduce both strain on distribution grid infrastructure and charging station operational costs, many stations are likely to employ behind the meter storage. This paper demonstrates a behind the meter storage sizing optimization that employs an open-source agent-based vehicle behavior model (BEAM) to determine the best sizing across many scenarios. This optimization and analysis is novel in that it examines how storage size impacts not only charging station cost and peak load, but also vehicle queue times. The optimization is also applied across a wide analysis region with sufficient diversity and numbers to provide novel statistical analysis of optimal sizes.

Aka, Julius↗

Preliminary analysis of hot spot factors in an advanced reactor for space electric power systems

The maximum fuel pin temperature for nominal operation in an advanced power reactor is 1370 K. Because of possible nitrogen embrittlement of the clad, the fuel temperature was limited to 1622 K. Assuming simultaneous occurrence of the most adverse conditions a deterministic analysis gave a maximum fuel temperature of 1610 K. A statistical analysis, using a synthesized estimate of the standard deviation for the highest fuel pin temperature, showed probabilities of 0.015 of that pin exceeding the temperature limit by the distribution free Chebyshev inequality and virtually nil assuming a normal distribution. The latter assumption gives a 1463 K maximum temperature at 3 standard deviations, the usually assumed cutoff. Further, the distribution and standard deviation of the fuel-clad gap are the most significant contributions to the uncertainty in the fuel temperature.

Lustig, P. H.↗

Quantiles, parametric-select density estimation, and bi-information parameter estimators

A quantile-based approach to statistical analysis and probability modeling of data is presented which formulates statistical inference problems as functional inference problems in which the parameters to be estimated are density functions. Density estimators can be non-parametric (computed independently of model identified) or parametric-select (approximated by finite parametric models that can provide standard models whose fit can be tested). Exponential models and autoregressive models are approximating densities which can be justified as maximum entropy for respectively the entropy of a probability density and the entropy of a quantile density. Applications of these ideas are outlined to the problems of modeling: (1) univariate data; (2) bivariate data and tests for independence; and (3) two samples and likelihood ratios. It is proposed that bi-information estimation of a density function can be developed by analogy to the problem of identification of regression models.

Parzen, E.↗