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At least 487 records · Page 27

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NASA NTRS1992

Indirect myosin immunocytochemistry for the identification of fibre types in equine skeletal muscle

The histochemical ATPase method for muscle fibre typing was first described by Brooke and Kaiser in 1970. However, problems have been found with the subdivision of type II fibres using this technique. To determine whether indirect myosin immunocytochemistry using anti-slow (5-4D), anti-fast (1A10) and anti-fast red (5-2B) monoclonal antibodies with cross reactivity for type I, II and IIa fibres, respectively, in a number of species, could identify three fibre types in equine skeletal muscle, data on fibre type composition and fibre size obtained using the two different techniques were compared. Results indicate that different myosin heavy chains can coexist in single equine muscle fibres. Type I and type II fibres were identified by immunocytochemistry, but subdivision of type II fibres was not possible. Although the percentage of type I and type II fibres was not significantly different for the two techniques, a few fibres reacted with both the 1A10 and 5-4D antibodies.

NASA Discipline Musculoskeletal↗

NASA NTRS1994

MME-based attitude dynamics identification and estimation for SAMPEX

A method is described for obtaining optimal attitude estimation algorithms for spacecraft lacking attitude rate measurement devices (rate gyros), and then demonstrated using actual flight data from the Solar, Anomalous, and Magnetospheric Particle Explorer (SAMPEX) spacecraft. SAMPEX does not have on-board rate sensing, and relies on sun sensors and a three-axis magnetometer for attitude determination. Problems arise since typical attitude estimation is accomplished by filtering measurements of both attitude and attitude rates. Rates are nearly always sampled much more densely than are attitudes. Thus, the absence/loss of rate data normally reduces both the total amount of data available and the sampling density (in time) by a substantial fraction. As a result, the sensitivity of the estimates to model uncertainty and to measurement noise increases. In order to maintain accuracy in the attitude estimates, there is increased need for accurate models of the rotational dynamics. The proposed approach is based on the minimum model error (MME) optimal estimation strategy, which has been successfully applied to estimation of poorly modeled dynamic systems which are relatively sparsely and/or noisily measured. The MME estimates may be used to construct accurate models of the system dynamics (i.e. perform system model identification). Thus, an MME-based approach directly addresses the problems created by absence of attitude rate measurements.

Depena, Juan↗

NASA NTRS1957

Identification of Foreign Objects Damaging Compressor Blades in Turbojet Engines

Damage to the compressor blades of turbojet engines due to ingestion of foreign objects is a growing problem, the solution of which has been made more difficult by the large percentage of damaging materials that have remained unknown. A rapid emission spectroscopic method was devised to identify the chemical composition of these foreign objects. Results on laboratory-prepared specimens and blades from damaged engines show that the method can be utilized to determine the nature of the ingested foreign objects.

Spakowski, A E↗

NASA NTRS1988

A practical approach to object based requirements analysis

Presented here is an approach developed at the Unisys Houston Operation Division, which supports the early identification of objects. This domain oriented analysis and development concept is based on entity relationship modeling and object data flow diagrams. These modeling techniques, based on the GOOD methodology developed at the Goddard Space Flight Center, support the translation of requirements into objects which represent the real-world problem domain. The goal is to establish a solid foundation of understanding before design begins, thereby giving greater assurance that the system will do what is desired by the customer. The transition from requirements to object oriented design is also promoted by having requirements described in terms of objects. Presented is a five step process by which objects are identified from the requirements to create a problem definition model. This process involves establishing a base line requirements list from which an object data flow diagram can be created. Entity-relationship modeling is used to facilitate the identification of objects from the requirements. An example is given of how semantic modeling may be used to improve the entity-relationship model and a brief discussion on how this approach might be used in a large scale development effort.

Drew, Daniel W.↗

NASA NTRS1973

Remote sensing in Iowa agriculture

The author has identified the following significant results. After receiving the ERTS-1 imagery, three methods of analysis of this imagery have been used. Observations noted are as follows: (1) Use of color additive and density slicing-color coding appears potentially useful for crop identification and automatic classification in Iowa for this time frame. The influence of soil association differences on the spectral response of the imagery will probably have to be taken into account for any automatic crop identification procedure to be successful. Small fields and the diversity of Iowa's cropping patterns also will cause significant problems for crop classifications. (2) The presence of high clouds and associated hazy atmospheric conditions markedly reduces the resolution of the ERTS-1 imagery. (3) Utilization of filtered 2 1/2 inch projectors is quite difficult because of multiple image registration problems. This procedure does, however, allow the interpreter to achieve image enlargement and the enhancement of response differences using two image projections.

Mahlstede, J. P.↗

NASA NTRS1975

FORTRAN Automated Code Evaluation System (faces) system documentation, version 2, mod 0

A system is presented which processes FORTRAN based software systems to surface potential problems before they become execution malfunctions. The system complements the diagnostic capabilities of compilers, loaders, and execution monitors rather than duplicating these functions. Also, it emphasizes frequent sources of FORTRAN problems which require inordinate manual effort to identify. The principle value of the system is extracting small sections of unusual code from the bulk of normal sequences. Code structures likely to cause immediate or future problems are brought to the user's attention. These messages stimulate timely corrective action of solid errors and promote identification of 'tricky' code. Corrective action may require recoding or simply extending software documentation to explain the unusual technique.

Source record↗

NASA NTRS1979

Safety hazard of aircraft icing

The problem of aircraft icing is reported as well as the type of aircraft affected, the pilots involved, and an identification of the areas where reduction in icing accidents are readily accomplished.

Mclean, J. C., Jr.↗

NASA NTRS1982

Least-squares sequential parameter and state estimation for large space structures

This paper presents the formulation of simultaneous state and parameter estimation problems for flexible structures in terms of least-squares minimization problems. The approach combines an on-line order determination algorithm, with least-squares algorithms for finding estimates of modal approximation functions, modal amplitudes, and modal parameters. The approach combines previous results on separable nonlinear least squares estimation with a regression analysis formulation of the state estimation problem. The technique makes use of sequential Householder transformations. This allows for sequential accumulation of matrices required during the identification process. The technique is used to identify the modal prameters of a flexible beam.

Thau, F. E.↗

NASA NTRS1987

Origin of northern lowland plains: Constraints from boundary morphology

The origin of the surface units of the northern lowland plains of Mars, about one third of the planet's surface, remains unclear after 20 years of analysis of spacecraft data. Hypotheses were put forward to explain the morphologies. The chief problem with constraining models of plains formation is that characterizing plains surface-forming processes is dependent upon the identification of distinctive landforms within the plains. The most commonly cited examples of distinctive morphologies found within the northern lowlands include: wrinkle ridges; small domes; giant polygons; and curvilinear ridges and ground undulations. To further constrain the processes involved, a careful analysis of boundary morphology is being conducted.

Parker, Timothy J.↗

NASA NTRS1991

A full field, 3-D velocimeter for microgravity crystallization experiments

The programming and algorithms needed for implementing a full-field, 3-D velocimeter for laminar flow systems and the appropriate hardware to fully implement this ultimate system are discussed. It appears that imaging using a synched pair of video cameras and digitizer boards with synched rails for camera motion will provide a viable solution to the laminar tracking problem. The algorithms given here are simple, which should speed processing. On a heavily loaded VAXstation 3100 the particle identification can take 15 to 30 seconds, with the tracking taking less than one second. It seeems reasonable to assume that four image pairs can thus be acquired and analyzed in under one minute.

Brodkey, Robert S.↗

NASA NTRS2017

The Diffuse Interstellar Bands: Solving a Century Old Problem

The Diffuse Interstellar Bands (DIBs) are a set of apporoximately 500 absorption bands that are seen in the spectra of reddened stars (i.e., stars obscured by the presence of interstellar clouds in their line of sight). The first DIBs were detected in the visible over a century ago. Diffuse Interstellar Bands are now detected from the near ultraviolet to the near infrared in the spectra of reddened stars spanning a variety of interstellar environments in our local, and in other galaxies. Although DIB carriers are a significant part of the interstellar chemical inventory as they account for a noticeable fraction of the interstellar extinction, the nature of their carriers is still unknown over a century after the detection of the first bands. DIB carriers are stable and ubiquitous in a broad variety of interstellar environments and play a unique role in interstellar physics and chemistry. It has long been realized that the solving of the DIB problem requires a strong synergy between astronomical observations, laboratory astrophysics and astrochemistry, quantum chemistry calculations and astrophysical modeling of line-of-sights. In this review, we'll present and discuss the current state of this perplexing problem. We'll review the progress and the failures that have been encountered in the long quest for the identification of the carriers of these ubiquitous interstellar bands.

Molecules in Space↗

NASA NTRS1994

Improved modeling of GPS selective availability

Selective Availability (SA) represents the dominant error source for stand-alone users of the Global Positioning System (GPS). Even for DGPS, SA mandates the update rate required for a desired level of accuracy in realtime applications. As was witnessed in the recent literature, the ability to model this error source is crucial to the proper evaluation of GPS-based systems. A variety of SA models were proposed to date; however, each has its own shortcomings. Most of these models were based on limited data sets or data which were corrupted by additional error sources. A comprehensive treatment of the problem is presented. The phenomenon of SA is discussed and a technique is presented whereby both clock and orbit components of SA are identifiable. Extensive SA data sets collected from Block 2 satellites are presented. System Identification theory then is used to derive a robust model of SA from the data. This theory also allows for the statistical analysis of SA. The stationarity of SA over time and across different satellites is analyzed and its impact on the modeling problem is discussed.

Braasch, Michael S.↗

NASA NTRS1976

A spectral identification technique for adaptive attitude control and pointing of the Space Telescope

The Space Telescope is a 2.4 m class aperture optical telescope having near-diffraction-limited performance. It will be placed into earth orbit by 1980 via the Space Shuttle. The problem considered is how to achieve negligible degradation of the astronomy imaging capability (to 0.005 arc second) due to smearing by pointing motions during observations. Initially, pointing instability sources were identified and a linear stability was used to assess the magnitude of elastic body modes and to design control system compensation regions necessary for subsequent adaptive control. A spectral identification technique for this adaptive attitude control and pointing has been investigated that will alleviate requirements for comprehensive dynamic ground testing. Typical all-digital simulation results describing motions of the telescope line of sight are presented.

Teuber, D. L.↗

NASA NTRS2006

Discerning Trends in Performance Across Multiple Events

Mass Data is a computer program that enables rapid, easy discernment of trends in performance data across multiple flights and ground tests. The program can perform Fourier analysis and other functions for the purposes of frequency analysis and trending of all variables. These functions facilitate identification of past use of diagnosed systems and of anomalies in such systems, and enable rapid assessment of related current problems. Many variables, for computation of which it is usually necessary to perform extensive manual manipulation of raw downlist data, are automatically computed and made available to all users, regularly eliminating the need for what would otherwise be an extensive amount of engineering analysis. Data from flight, ground test, and simulation are preprocessed and stored in one central location for instantaneous access and comparison for diagnostic and trending purposes. Rules are created so that an event log is created for every flight, making it easy to locate information on similar maneuvers across many flights. The same rules can be created for test sets and simulations, and are searchable, so that information on like events is easily accessible.

Slater, Simon↗

NASA NTRS2014

Application of Machine Learning Algorithms to the Study of Noise Artifacts in Gravitational-Wave Data

The sensitivity of searches for astrophysical transients in data from the Laser Interferometer Gravitationalwave Observatory (LIGO) is generally limited by the presence of transient, non-Gaussian noise artifacts, which occur at a high-enough rate such that accidental coincidence across multiple detectors is non-negligible. Furthermore, non-Gaussian noise artifacts typically dominate over the background contributed from stationary noise. These "glitches" can easily be confused for transient gravitational-wave signals, and their robust identification and removal will help any search for astrophysical gravitational-waves. We apply Machine Learning Algorithms (MLAs) to the problem, using data from auxiliary channels within the LIGO detectors that monitor degrees of freedom unaffected by astrophysical signals. Terrestrial noise sources may manifest characteristic disturbances in these auxiliary channels, inducing non-trivial correlations with glitches in the gravitational-wave data. The number of auxiliary-channel parameters describing these disturbances may also be extremely large; high dimensionality is an area where MLAs are particularly well-suited. We demonstrate the feasibility and applicability of three very different MLAs: Artificial Neural Networks, Support Vector Machines, and Random Forests. These classifiers identify and remove a substantial fraction of the glitches present in two very different data sets: four weeks of LIGO's fourth science run and one week of LIGO's sixth science run. We observe that all three algorithms agree on which events are glitches to within 10% for the sixth science run data, and support this by showing that the different optimization criteria used by each classifier generate the same decision surface, based on a likelihood-ratio statistic. Furthermore, we find that all classifiers obtain similar limiting performance, suggesting that most of the useful information currently contained in the auxiliary channel parameters we extract is already being used. Future performance gains are thus likely to involve additional sources of information, rather than improvements in the MLAs themselves.

gravitational-wave data↗

NASA NTRS2015

Development of High-Power Hall Thruster Power Processing Units at NASA GRC

NASA GRC successfully designed, built and tested four different power processor concepts for high power Hall thrusters. Each design satisfies unique goals including the evaluation of a novel silicon carbide semiconductor technology, validation of innovative circuits to overcome the problems with high input voltage converter design, development of a direct-drive unit to demonstrate potential benefits, or simply identification of lessonslearned from the development of a PPU using a conventional design approach. Any of these designs could be developed further to satisfy NASA's needs for high power electric propulsion in the near future.

Spacecraft Power Supplies↗

NASA NTRS1988

A unified process for systems identification based on performance assessment

Many modern spacecraft are complex multi-body dynamic systems where the bodies are connected by several active control systems for pointing and isolation. Mission requirements indicate that many structural modes and possibly some nonlinear effects will require characterization. Thus, even characterization at the subsystem level will become more difficult than usual. System level characterization difficulties will be compounded by the fact that only limited ground testing will be possible on the full up system, and flight testing will be restricted by an extremely limited measurements set. The object of the present discussion is the application of matrix majorant theory to the problem of assessing dynamic system performance when knowledge of the system is uncertain. We show how majorants provide an effective tool to relate required performance output to system identification test quality in terms of residual uncertainty in input-output relations, parameter values, nonlinearities, and interactions. The underlying machinery consists of the block-norm matrix which is a nonnegative matrix each of whose elements is the norm of a block of a suitably partitioned matrix. A matrix which bounds the block-norm matrix in the sense of nonnegative matrices, i.e., element by element is known as a majorant.

Hyland, C.↗

NASA NTRS2006

Enabling the Discovery of Recurring Anomalies in Aerospace System Problem Reports using High-Dimensional Clustering Techniques

This paper describes the results of a significant research and development effort conducted at NASA Ames Research Center to develop new text mining techniques to discover anomalies in free-text reports regarding system health and safety of two aerospace systems. We discuss two problems of significant importance in the aviation industry. The first problem is that of automatic anomaly discovery about an aerospace system through the analysis of tens of thousands of free-text problem reports that are written about the system. The second problem that we address is that of automatic discovery of recurring anomalies, i.e., anomalies that may be described m different ways by different authors, at varying times and under varying conditions, but that are truly about the same part of the system. The intent of recurring anomaly identification is to determine project or system weakness or high-risk issues. The discovery of recurring anomalies is a key goal in building safe, reliable, and cost-effective aerospace systems. We address the anomaly discovery problem on thousands of free-text reports using two strategies: (1) as an unsupervised learning problem where an algorithm takes free-text reports as input and automatically groups them into different bins, where each bin corresponds to a different unknown anomaly category; and (2) as a supervised learning problem where the algorithm classifies the free-text reports into one of a number of known anomaly categories. We then discuss the application of these methods to the problem of discovering recurring anomalies. In fact the special nature of recurring anomalies (very small cluster sizes) requires incorporating new methods and measures to enhance the original approach for anomaly detection. ?& pant 0-

Srivastava, Ashok, N.↗