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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS2003

On Classification in the Study of Failure, and a Challenge to Classifiers

Classification schemes are abundant in the literature of failure. They serve a number of purposes, some more successfully than others. We examine several classification schemes constructed for various purposes relating to failure and its investigation, and discuss their values and limits. The analysis results in a continuum of uses for classification schemes, that suggests that the value of certain properties of these schemes is dependent on the goals a classification is designed to forward. The contrast in the value of different properties for different uses highlights a particular shortcoming: we argue that while humans are good at developing one kind of scheme: dynamic, flexible classifications used for exploratory purposes, we are not so good at developing another: static, rigid classifications used to trap and organize data for specific analytic goals. Our lack of strong foundation in developing valid instantiations of the latter impedes progress toward a number of investigative goals. This shortcoming and its consequences pose a challenge to researchers in the study of failure: to develop new methods for constructing and validating static classification schemes of demonstrable value in promoting the goals of investigations. We note current productive activity in this area, and outline foundations for more.

Wasson, Kimberly S.↗
NASA NTRS2004

Classifying Terrestrial Volcanic Alteration Processes and Defining Alteration Processes they Represent on Mars

Characterizing alteration of the rocks on Mars is difficult, but some guidelines can be made through comparison with terrestrial volcanic alteration. Subaerial volcanic activity on the Hawaiian islands and subglacial volcanic activity on Iceland have led to the formation of a variety of silicate and iron oxide-rich alteration products that may serve as models for chemical alteration on Mars. Multiple samples have been collected from palagonitized tuffs, altered pillow lavas, altered tephra, and S-rich vents for study in the lab. Variations in the kinds of alteration products have been observed depending on the sample environment. We are defining associations between the alteration products and formation conditions that can be used to provide information about environmental conditions on Mars. In particular, we are providing definitions for palagonitic, pedogenic and solfataric alteration that can be used to characterize these alteration processes.

Bishop, J. L.↗
NASA NTRS2001

Microscale Particulate Classifiers (MiPAC) Being Developed

The NASA Glenn Research Center is developing microscale sensors to characterize atmospheric-borne particulates. The devices are fabricated using MEMS (microelectromechanical systems) technologies. These technologies are derived from those originally developed in support of the semiconductor processing industry. The resulting microsensors can characterize a wide range of particles and are, therefore, suitable to a broad range of applications. This project is supported under a collaborative program called the Glennan Microsystems Initiative. The initiative comprises members of NASA Glenn Research Center, various university affiliates from the State of Ohio, and a number of participating industrial partners. Funding is jointly provided by NASA, the State of Ohio, and industrial members. The work described here is a collaborative arrangement between researchers at Glenn, the University of Minnesota, The National Institute of Standards and Technology (NIST), and the Cleveland State University. Actual device fabrication is conducted at Glenn and at the laboratories of Case Western Reserve University. Case Western is also located in Cleveland, Ohio, and is a participating member of the initiative. The principal investigator for this project is Paul S. Greenberg of Glenn. Two basic types of devices are being developed, and target different ranges of particle sizes. The first class of devices, which is used to measure nanoparticles (i.e., particles in the range of 0.002 to 1 mm), is based on the technique of Electrical Mobility Classification. This technique also affords the valuable ability of measuring the electrical charge state of the particles. Such information is important in the understanding of agglomeration mechanisms and is useful in the development of methods for particle repulsion. The second type of device being developed, which utilizes optical scattering, is suitable for particles larger than 1 mm. This technique also provides information on particle shape and composition. Applications for these sensors include fundamental planetary climatology, monitoring and filtration in spacecraft, human habitation modules and related systems, characterization of particulate emissions from propulsion and power systems, and as early warning sensors for both space-based and ter-restrial fire detection. These devices are also suitable for characterizing biological compounds such as allergens, infectious agents, and biotoxic agents.

Greenberg, Paul S.↗
NASA NTRS2007

Preliminary Considerations for Classifying Hazards of Unmanned Aircraft Systems

The use of unmanned aircraft in national airspace has been characterized as the next great step forward in the evolution of civil aviation. To make routine and safe operation of these aircraft a reality, a number of technological and regulatory challenges must be overcome. This report discusses some of the regulatory challenges with respect to deriving safety and reliability requirements for unmanned aircraft. In particular, definitions of hazards and their classification are discussed and applied to a preliminary functional hazard assessment of a generic unmanned system.

Kelly J. Hayhurst↗
NASA NTRS1983

Method of and system for classifying emergency locating transmitters and emergency positions indicating radio beacons

During a distress call, a distress location transmitter 10 generates a high frequency carrier signal 40 that is modulated by a predetermined distress waveform characteristic 29. The classification of user associated with the distress call is identified by periodically interrupting modulation 42; user classification is determined by the repetition rate of the interruptions, the interruption periods, or both.

Wren, Paul E.↗
NASA NTRS2009

Adaptive Morphological Feature-Based Object Classifier for a Color Imaging System

Utilizing a Compact Color Microscope Imaging System (CCMIS), a unique algorithm has been developed that combines human intelligence along with machine vision techniques to produce an autonomous microscope tool for biomedical, industrial, and space applications. This technique is based on an adaptive, morphological, feature-based mapping function comprising 24 mutually inclusive feature metrics that are used to determine the metrics for complex cell/objects derived from color image analysis. Some of the features include: Area (total numbers of non-background pixels inside and including the perimeter), Bounding Box (smallest rectangle that bounds and object), centerX (x-coordinate of intensity-weighted, center-of-mass of an entire object or multi-object blob), centerY (y-coordinate of intensity-weighted, center-of-mass, of an entire object or multi-object blob), Circumference (a measure of circumference that takes into account whether neighboring pixels are diagonal, which is a longer distance than horizontally or vertically joined pixels), . Elongation (measure of particle elongation given as a number between 0 and 1. If equal to 1, the particle bounding box is square. As the elongation decreases from 1, the particle becomes more elongated), . Ext_vector (extremal vector), . Major Axis (the length of a major axis of a smallest ellipse encompassing an object), . Minor Axis (the length of a minor axis of a smallest ellipse encompassing an object), . Partial (indicates if the particle extends beyond the field of view), . Perimeter Points (points that make up a particle perimeter), . Roundness [(4(pi) x area)/perimeter(squared)) the result is a measure of object roundness, or compactness, given as a value between 0 and 1. The greater the ratio, the rounder the object.], . Thin in center (determines if an object becomes thin in the center, (figure-eight-shaped), . Theta (orientation of the major axis), . Smoothness and color metrics for each component (red, green, blue) the minimum, maximum, average, and standard deviation within the particle are tracked. These metrics can be used for autonomous analysis of color images from a microscope, video camera, or digital, still image. It can also automatically identify tumor morphology of stained images and has been used to detect stained cell phenomena (see figure).

McDowell, Mark↗
NASA NTRS2010

Propagation of New Innovations: An Approach to Classify Human Behavior and Movement from Available Social Network Data

It is interesting to observe new innovations, products, or ideas propagating into the society. One important factor of this propagation is the role of individual's social network; while another factor is individual's activities. In this paper, an approach will be made to analyze the propagation of different ideas in a popular social network. Individuals' responses to different activities in the network will be analyzed. The properties of network will also be investigated for successful propagation of innovations.

Mahmud, Faisal↗
NASA NTRS2017

Characterizing K2 Candidate Planetary Systems Orbiting Low-Mass Stars. I. Classifying Low-Mass Host Stars Observed During Campaigns 1-7

We present near-infrared spectra for 144 candidate planetary systems identified during Campaigns 1-7 of the NASA K2 Mission. The goal of the survey was to characterize planets orbiting low-mass stars, but our Infrared Telescope Facility/SpeX and Palomar/TripleSpec spectroscopic observations revealed that 49% of our targets were actually giant stars or hotter dwarfs reddened by interstellar extinction. For the 72 stars with spectra consistent with classification as cool dwarfs (spectral types K3-M4), we refined their stellar properties by applying empirical relations based on stars with interferometric radius measurements. Although our revised temperatures are generally consistent with those reported in the Ecliptic Plane Input Catalog (EPIC), our revised stellar radii are typically 0.13 solar radius (39%) larger than the EPIC values, which were based on model isochrones that have been shown to underestimate the radii of cool dwarfs. Our improved stellar characterizations will enable more efficient prioritization of K2 targets for follow-up studies.

Campaigns17 of the NASA K2 Mission↗
NASA NTRS2019

A Robust Vision-Based Algorithm for Detecting and Classifying Small Orbital Debris Using On-Board Optical Cameras

This study develops a vision-based detection and classification algorithm to address the challenges of in-situ small orbital debris environment classification including debris observability and instrument requirements for small debris observation. The algorithm operates in near real time and is robust under difficult tasks in moving objects classification such as multiple moving objects, objects with various movement trajectories and speeds, very small or faint objects, and substantial background motion. The performance of the algorithm is optimized and validated using space image data available through simulated environments generated using NASA Marshall Space Flight Centers Dynamic Star Field Simulator of on-board optical sensors and cameras.

Zamani, Yasin↗
NASA NTRS2020

Mark Twain National Forest Ecological Forecasting - Utilizing NASA Earth Observations to Classify Ground Cover Types in the Mark Twain National Forest

The Mark Twain National Forest (MTNF) encompasses 1.5 million acres of public land in the Ozarks region of southeastern Missouri. The industrial boom between the 1880s and 1920s had devastating effects on the shortleaf pine (Pinus echinata),Missouri’s only native pine species. The combination of fire suppression on this fire-dependent species and timber harvest of mature pine stands inhibited the development of pine seedlings and promoted the establishment of hardwood stands. Partners at the US Forest Service’s MTNF are currently involved in restoration efforts in two ranger districts, which includes removing invasive eastern red cedar (Juniperus virginiana) and prescribed burning. To expand spatial coverage for the MTNF beyond in situ observation sites, the NASA DEVELOP team analyzed land cover change from 1986 through 2019 and forecasted changes based on a ‘business-as-usual' scenario out to 2040. The team incorporated remotely sensed data from Landsat 5 Thematic Mapper (TM) and Landsat 8 Operational Land Imager (OLI) into the random trees supervised classification tool in ArcGIS Pro. This tool spectrally separated pixels into five distinct land cover classes and produced classifications for 1986 and 2019, with kappa statistics of 0.87 and 0.81, respectively. Overall, there was a net decrease in conifer and meadow land cover between 1986 and 2019 along with a net increase in water, developed, and deciduous land cover. The team used TerrSet’s Land Change Modeler to forecast land cover through 2040. Results showed an increase in coniferous land cover and a decrease in deciduous cover, indicating a high probability that current restoration efforts will produce the intended effect.

Kaitlyn Bretz↗
NASA NTRS2020

Mark Twain National Forest Ecological Forecasting: Utilizing NASA Earth Observations to Classify Ground Cover Types in the Mark Twain National Forest

The Mark Twain National Forest (MTNF) encompasses 1.5 million acres of public land in the Ozarks region of southeastern Missouri. The industrial boom between the 1880s and 1920s had devastating effects on the shortleaf pine (Pinus echinata),Missouri’s only native pine species. The combination of fire suppression on this fire-dependent species and timber harvest of mature pine stands inhibited the development of pine seedlings and promoted the establishment of hardwood stands. Partners at the US Forest Service’s MTNF are currently involved in restoration efforts in two ranger districts, which includes removing invasive eastern red cedar (Juniperus virginiana) and prescribed burning. To expand spatial coverage for the MTNF beyond in situ observation sites, the NASA DEVELOP team analyzed land cover change from 1986 through 2019 and forecasted changes based on a ‘business-as-usual' scenario out to 2040. The team incorporated remotely sensed data from Landsat 5 Thematic Mapper (TM) and Landsat 8 Operational Land Imager (OLI) into the random trees supervised classification tool in ArcGIS Pro. This tool spectrally separated pixels into five distinct land cover classes and produced classifications for 1986 and 2019, with kappa statistics of 0.87 and 0.81, respectively. Overall, there was a net decrease in conifer and meadow land cover between 1986 and 2019 along with a net increase in water, developed, and deciduous land cover. The team used TerrSet’s Land Change Modeler to forecast land cover through 2040. Results showed an increase in coniferous land cover and a decrease in deciduous cover, indicating a high probability that current restoration efforts will produce the intended effect.

DEVELOP Tech Paper↗