SEARCH · Search NASA

Results for “Principal Component”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 415 records · Page 23

All sources NASA NTRS DOE OSTI

NASA NTRS2002

Analysis of Salinity Intrusion in the San Francisco Bay-Delta using a GA- Optimized Neural Net, and Application of the Model to Prediction in the Elkhorn Slough Habitat

The San Francisco Bay Delta is a large hydrodynamic complex that incorporates the Sacramento and San Joaquin Estuaries, the Burman Marsh, and the San Francisco Bay proper. Competition exists for the use of this extensive water system both from the fisheries industry, the agricultural industry, and from the marine and estuarine animal species within the Delta. As tidal fluctuations occur, more saline water pushes upstream allowing fish to migrate beyond the Burman Marsh for breeding and habitat occupation. However, the agriculture industry does not want extensive salinity intrusion to impact water quality for human and plant consumption. The balance is regulated by pumping stations located alone the estuaries and reservoirs whereby flushing of fresh water keeps the saline intrusion at bay. The pumping schedule is driven by data collected at various locations within the Bay Delta and by numerical models that predict the salinity intrusion as part of a larger model of the system. The Interagency Ecological Program (IEP) for the San Francisco Bay/Sacramento-San Joaquin Estuary collects, monitors, and archives the data, and the Department of Water Resources provides a numerical model simulation (DSM2) from which predictions are made that drive the pumping schedule. A problem with this procedure is that the numerical simulation takes roughly 16 hours to complete a C:~ prediction. We have created a neural net, optimized with a genetic algorithm, that takes as input the archived data from multiple stations and predicts stage, salinity, and flow at the Carquinez Straits (at the downstream end of the Burman Marsh). This model seems to be robust in its predictions and operates much faster than the current numerical DSM2 model. Because the system is strongly tidal driven, we used both Principal Component Analysis and Fast Fourier Transforms to discover dominant features within the IEP data. We then filtered out the dominant tidal forcing to discover non-primary tidal effects, and used this to enhance the neural network by mapping input-output relationships in a more efficient manner. Furthermore, the neural network implicitly incorporates both the hydrodynamic and water quality models into a single predictive system. Although our model has not yet been enhanced to demonstrate improve pumping schedules, it has the possibility to support better decision-making procedures that may then be implemented by State agencies if desired. Our intention is now to use this model in the smaller Elkhorn Slough complex near Monterey Bay where no such hydrodynamic model currently exists. At the Elkhorn Slough, we are fusing the neural net model of tidally-driven flow with in situ flow data and airborne and satellite remote sensation data. These further constrain the behavior of the model in predicting the longer-term health and future of this vital estuary.

Thompson, David E.↗

NASA NTRS1983

Medical Gas Analyzer

The Remote Monitoring System (RMS) is manufactured by Perkin Elmer Corporation. The principal component of the RMS was originally developed for spacecraft use to monitor astronaut's respiratory gases in NASA's Gemini and Apollo program. At Wishard Memorial Hospital in Indianapolis, IN, the RMS is used in operating rooms for analysis of anesthetic gases and measurement of oxygen, carbon dioxide and nitrogen concentrations. It assures that the patient undergoing surgery has the proper breathing environment.

Source record↗

NASA NTRS1982

Methane-Powered Vehicles

Liquid methane is beginning to become an energy alternative to expensive oil as a power source for automotive vehicles. Methane is the principal component of natural gas, costs less than half as much as gasoline, and its emissions are a lot cleaner than from gasoline or diesel engines. Beech Aircraft Corporation's Boulder Division has designed and is producing a system for converting cars and trucks to liquid methane operation. Liquid methane (LM) is a cryogenic fuel which must be stored at a temperature of 260 degrees below zero Fahrenheit. The LM system includes an 18 gallon fuel tank in the trunk and simple "under the hood" carburetor conversion equipment. Optional twin-fuel system allows operator to use either LM or gasoline fuel. Boulder Division has started deliveries for 25 vehicle conversions and is furnishing a liquid methane refueling station. Beech is providing instruction for Northwest Natural Gas, for conversion of methane to liquid state.

Source record↗

NASA NTRS1980

Emergency/Night Lightning

UDEC's highly efficient lighting system is finding wide acceptance among industrial and commercial firms as an energy savings means of providing emergency and night lighting. Originating from Skylab, the system consists of small high frequency fluorescent light fixtures powered by solar cells. Advantages of UDEC's lighting system stem from high reliability and high light output with very low energy drain. Principal components of system are long life fluorescent lamps operated by electronic circuitry, a sealed gelatine cell battery that needs no maintenance for eight years and a solid-state automatic battery charger. Installation of UDEC lighting in a company's six-and-a-half acre warehouse office cut the annual night lighting electric bill from $8,000 a year to $300 per year.

Source record↗

NASA NTRS2003

Airframe-Jet Engine Integration Noise

It has been found experimentally that the noise radiated by a jet mounted under the wing of an aircraft exceeds that of the same jet in a stand-alone environment. The increase in noise is referred to as jet engine airframe integration noise. The objectives of the present investigation are, (1) To obtain a better understanding of the physical mechanisms responsible for jet engine airframe integration noise or installation noise. (2) To develop a prediction model for jet engine airframe integration noise. It is known that jet mixing noise consists of two principal components. They are the noise from the large turbulence structures of the jet flow and the noise from the fine scale turbulence. In this investigation, only the effect of jet engine airframe interaction on the fine scale turbulence noise of a jet is studied. The fine scale turbulence noise is the dominant noise component in the sideline direction. Thus we limit out consideration primarily to the sideline.

Tam, Christopher↗

NASA NTRS2002

The North Alabama Lightning Mapping Array: Recent Results and Future Prospects

The North Alabama Lightning Mapping Array became operational in November 2001 as a principal component of a severe weather test bed to infuse new science and technologies into the short-term forecasting of severe and hazardous weather and the warning decision-making process. The LMA project is a collaboration among NASA scientists, National Weather Service (NWS) weather forecast offices (WFOs), emergency managers, and other partners. The time rate-of-change of storm characteristics and life-cycle trending are accomplished in real-time through the second generation Lightning Imaging Sensor Data Applications Display (LISDAD II) system, initially developed in T997 through a collaboration among NASA/MSFC, MIT/Lincoln Lab and the Melbourne, FL WFO. LISDAD II is now a distributed decision support system with a JAVA-based display application that allows anyone, anywhere to track individual storm histories within the Tennessee Valley region of the southeastern U.S. Since the inauguration of the LMA there has been an abundance of severe weather. During 23-24 November 2001, a major tornado outbreak was monitored by LMA in its first data acquisition effort (36 tornadoes in Alabama). Since that time the LMA has collected a vast amount of data on hailstorms and damaging wind events, non-tornadic supercells, and ordinary non-severe thunderstorms. In this paper we provide an overview of LMA observations and discuss future prospects for improving the short-term forecasting of convective weather.

Goodman, S. J.↗

NASA NTRS2003

Jupiter Atmospheric Science with JIMO: Linking Science Objectives and Measurement Goals

Although the primary focus of the Jupiter Icy Moons Orbiter (JIMO) mission will be the characterization and study of Jupiter's icy moons, there will be opportunities throughout the mission for unprecendented observations of Jupiter. With an adaptable suite of payload instruments, the atmospheric data collected by JIMO can help to answer fundamental questions about the largest planet in our solar system that remain after (or were generated by) previous spacecraft reconnaissance (e.g. Voyager, Galileo, and Cassini). Near-IR (0.7-4 micron) spectral imaging will most likely be used to identify mineralogies and ices on the Jovian satellites by virtue of their spectral signatures. This same capability is very well tailored for studies of Jovian atmospheric dynamics and structure. Near-IR methane absorption bands allow 2-D mapping of the horizontal wind field at size scales to tens of kms, as well as the height dependence of this field above the ammonia cloud deck (700 to a few mbar), constraining current models of atmospheric vertical structure. Likewise, atmospheric ice aerosols with unique spectroscopic signatures (ammonia ice near 1.5, 2.0, and 2.8 microns and water ice between 3.0 - 3.5 microns) can be detected and mapped using spectral difference imaging or spectrally inclusive principal-component methods. Spectral imaging of the Jovian aurora via (3)H(+) emission lines between 3 - 4 microns can be used to spatially map the interplay between the satellites) Jupiter's magnetosphere, and Jupiter's atmosphere. Each of these measurements addresses one or more fundamental questions related to the energy balance in Jupiter's atmosphere. All of these tunable imaging objectives can be achieved using acousto-optic tunable filters (AOTF's), which have been used for years in ground-based observing instruments and which have been proposed for numerous planetary missions. The application of this technology to the science objectives of both the icy satellites and Jovian atmospheric components of the JIMO mission will be discussed.

Chanover, N. J.↗

NASA NTRS2003

Modeling the Seasonal South Polar Cap Sublimation Rates at Dust Storm Conditions

Carbon dioxide is the principal component of the Martian atmosphere and its interaction with the polar caps forms the CO2 seasonal cycle on the planet. A significant fraction of the atmospheric constituent condenses on the surface during the polar winter and sublimes back during spring. The basic aspects of the CO2 cycle have been outlined by Leighton and Murray and a number of follow-up theoretical models ranging from energy balance to general circulation models have been used to study the physical processes involved in the cycle. This paper presents a modeling study on the seasonal south polar cap subliminiation rate under dust storm conditions. Mars Global Surveyor observations are also presented.

P P Bonev↗

NASA NTRS2003

Bacterial Actins? An Evolutionary Perspective

According to the conventional wisdom, the existence of a cytoskeleton in eukaryotes and its absence in prokaryotes constitute a fundamental divide between the two domains of life. An integral part of the dogma is that a cytoskeleton enabled an early eukaryote to feed upon prokaryotes, a consequence of which was the occasional endosymbiosis and the eventual evolution of organelles. Two recent papers present compelling evidence that actin, one of the principal components of a cytoskeleton, has a homolog in Bacteria that behaves in many ways like eukaryotic actin. Sequence comparisons reveml that eukaryotic actin and the bacterial homolog (mreB protein), unlike many other proteins common to eukaryotes and Bacteria, have very different and more highly extended evolutionary histories.

Doolittle, Russell F.↗

NASA NTRS2003

CMEs, the Tail of the Solar Wind Magnetic Field Distribution, and 11-yr Cosmic Ray Modulation at 1 AU

Using a recent classification of the solar wind at 1 AU into its principal components (slow solar wind, high-speed streams, and coronal mass ejections (CMEs) for 1972-2000, we show that the monthly-averaged galactic cosmic ray intensity is anti-correlated with the percentage of time that the Earth is imbedded in CME flows. We suggest that this correlation results primarily from a CME related change in the tail of the distribution function of hourly-averaged values of the solar wind magnetic field (B) between solar minimum and solar maximum. The number of high-B (square proper subset 10 nT) values increases by a factor of approx. 3 from minimum to maximum (from 5% of all hours to 17%), with about two-thirds of this increase due to CMEs. On an hour-to-hour basis, average changes of cosmic ray intensity at Earth become negative for solar wind magnetic field values square proper subset 10 nT.

Cliver, E. W.↗

NASA NTRS1998

High Performance Parallel Architectures

Traditional remote sensing instruments are multispectral, where observations are collected at a few different spectral bands. Recently, many hyperspectral instruments, that can collect observations at hundreds of bands, have been operational. Furthermore, there have been ongoing research efforts on ultraspectral instruments that can produce observations at thousands of spectral bands. While these remote sensing technology developments hold great promise for new findings in the area of Earth and space science, they present many challenges. These include the need for faster processing of such increased data volumes, and methods for data reduction. Dimension Reduction is a spectral transformation, aimed at concentrating the vital information and discarding redundant data. One such transformation, which is widely used in remote sensing, is the Principal Components Analysis (PCA). This report summarizes our progress on the development of a parallel PCA and its implementation on two Beowulf cluster configuration; one with fast Ethernet switch and the other with a Myrinet interconnection. Details of the implementation and performance results, for typical sets of multispectral and hyperspectral NASA remote sensing data, are presented and analyzed based on the algorithm requirements and the underlying machine configuration. It will be shown that the PCA application is quite challenging and hard to scale on Ethernet-based clusters. However, the measurements also show that a high- performance interconnection network, such as Myrinet, better matches the high communication demand of PCA and can lead to a more efficient PCA execution.

El-Ghazawi, Tarek↗

NASA NTRS2000

Dimension Reduction of Hyperspectral Data on Beowulf Clusters

El-Ghazawi, Tarek↗

NASA NTRS2002

Multi-wavelength Luminosity Functions of Galaxies

Multivariate or multi-wavelength luminosity functions will reveal the interplay between star formation, chemical evolution, and absorption and re-emission of dust within evolving galaxy populations. By using principal component analysis to reduce the dimensionality of the problem, we optimally extract the relevant photometric information from large galaxy catalogs. As a demonstration of the technique, we derive the multi-wavelength luminosity function for the galaxies in the released SDSS catalog, and compare the results with those obtained by traditional methods. This technique will be applicable to catalogs of galaxies from datasets obtained by 2MASS, and the SIRTF and GALEX missions.

Gardner, J. P.↗

NASA NTRS2002

Multi-Wavelength Luminosity Functions of Galaxies

Multivariate or multi-wavelength luminosity functions will reveal the interplay between star formation, chemical evolution, and ab- sorption and re-emission of dust within evolving galaxy populations. By using principal component analysis to reduce the dimensionality of the problem, I optimally extract the relevant photometric information from large galaxy catalogs. As a demonstration of the technique, I derive the multi-wavelength luminosity function for the galaxies in the released SDSS catalog, and compare the results with those obtained by traditional methods. This technique will be applicable to catalogs of galaxies from datasets obtained by 2MASS, and the SIRTF and GALEX missions.

Gardner, Jonathan P.↗

NASA NTRS2001

An Approach to Application Validation of Multispectral Sensors Using AVIRIS

High-resolution multispectral data are becoming widely available for commercial and scientific use. For specific applications, such as agriculture studies, there is a need to quantify the performance of such systems. In many cases, parameters such as GSD and SNR can be optimized. Data sets with varying GSD's for the Landsat ETM+ bands were produced to evaluate the effects of GSD on various algorithms and transformations, such as NDVI, principal component analysis, unsupervised classification, and mixture analysis. By showing that AVIRIS data can be used to simulate spaceborne and airborne multispectral platforms over a wide range of GSD, this research can be used to assist in band selection and spatial resolution specifications for new sensors and in optimization of acquisition strategies for existing multispectral systems.

Warner, Amanda↗

NASA NTRS2003

NASA Materials Related Lessons Learned

Lessons Learned have been the basis for our accomplishments throughout the ages. They have been passed down from father to son, mother to daughter, teacher to pupil, and older to younger worker. Lessons Learned have also been the basis for the nation s accomplishments for more than 200 years. Both government and industry have long recognized the need to systematically document and utilize the knowledge gained from past experiences in order to avoid the repetition of failures and mishaps. Through the knowledge captured and recorded in Lessons Learned from more than 80 years of flight in the Earth s atmosphere, NASA s materials researchers are constantly working to develop stronger, lighter, and more durable materials that can withstand the challenges of space. The Agency s talented materials engineers and scientists continue to build on that rich tradition by using the knowledge and wisdom gained from past experiences to create futuristic materials and technologies that will be used in the next generation of advanced spacecraft and satellites that may one day enable mankind to land men on another planet or explore our nearest star. These same materials may also have application here on Earth to make commercial aircraft more economical to build and fly. With the explosion in technical accomplishments over the last decade, the ability to capture knowledge and have the capability to rapidly communicate this knowledge at lightning speed throughout an organization like NASA has become critical. Use of Lessons Learned is a principal component of an organizational culture committed to continuous improvement.

Garcia, Danny↗

NASA NTRS1991

Characterization of exopolymers of aquatic bacteria by pyrolysis-mass spectrometry

Exopolymers from a diverse collection of marine and freshwater bacteria were characterized by pyrolysis-mass spectrometry (Py-MS). Py-MS provides spectra of pyrolysis fragments that are characteristic of the original material. Analysis of the spectra by multivariate statistical techniques (principal component and canonical variate analysis) separated these exopolymers into distinct groups. Py-MS clearly distinguished characteristic fragments, which may be derived from components responsible for functional differences between polymers. The importance of these distinctions and the relevance of pyrolysis information to exopolysaccharide function in aquatic bacteria is discussed.

NASA Program CELSS↗

NASA NTRS2004

Fossil Signatures Using Elemental Abundance Distributions and Bayesian Probabilistic Classification

Elemental abundances (C6, N7, O8, Na11, Mg12, Al3, P15, S16, Cl17, K19, Ca20, Ti22, Mn25, Fe26, and Ni28) were obtained for a set of terrestrial fossils and the rock matrix surrounding them. Principal Component Analysis extracted five factors accounting for the 92.5% of the data variance, i.e. information content, of the elemental abundance data. Hierarchical Cluster Analysis provided unsupervised sample classification distinguishing fossil from matrix samples on the basis of either raw abundances or PCA input that agreed strongly with visual classification. A stochastic, non-linear Artificial Neural Network produced a Bayesian probability of correct sample classification. The results provide a quantitative probabilistic methodology for discriminating terrestrial fossils from the surrounding rock matrix using chemical information. To demonstrate the applicability of these techniques to the assessment of meteoritic samples or in situ extraterrestrial exploration, we present preliminary data on samples of the Orgueil meteorite. In both systems an elemental signature produces target classification decisions remarkably consistent with morphological classification by a human expert using only structural (visual) information. We discuss the possibility of implementing a complexity analysis metric capable of automating certain image analysis and pattern recognition abilities of the human eye using low magnification optical microscopy images and discuss the extension of this technique across multiple scales.

Hoover, Richard B.↗