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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 415 records · Page 23
All sourcesNASA NTRSDOE OSTI
NASA NTRS1999

Interim Control Module Extraction Strut Assembly

The Interim Control Module is a propulsion and attitude control module for the International Space Station developed to serve as a replacement for the Russian Service Module in the event that Russia does not deliver the hardware as expected. The hardware was developed through a joint NASA/Naval Research Laboratory program and is based on a Department of Defense payload. This paper discusses the development and testing of the Extraction Strut hardware that will be used to assist in removing the Interim Control Module from the Shuttle's payload bay.

Hansen, Chris↗
NASA NTRS1997

Improvements for Image Compression Using Adaptive Principal Component Extraction (APEX)

The issues of image compression and pattern classification have been a primary focus of researchers among a variety of fields including signal and image processing, pattern recognition, data classification, etc. These issues depend on finding an efficient representation of the source data. In this paper we collate our earlier results where we introduced the application of the. Hilbe.rt scan to a principal component algorithm (PCA) with Adaptive Principal Component Extraction (APEX) neural network model. We apply these technique to medical imaging, particularly image representation and compression. We apply the Hilbert scan to the APEX algorithm to improve results

Ziyad, Nigel A.↗
NASA NTRS1999

Juneau Airport Doppler Lidar Deployment: Extraction of Accurate Turbulent Wind Statistics

A 2 micrometer pulsed Doppler lidar was deployed to the Juneau Airport in 1998 to measure turbulence and wind shear in and around the departure and arrival corridors. The primary objective of the measurement program was to demonstrate and evaluate the capability of a pulsed coherent lidar to remotely and unambiguously measure wind turbulence. Lidar measurements were coordinated with flights of an instrumented research aircraft operated by representatives of the University of North Dakota (UND) under the direction of the National Center for Atmospheric Research (NCAR). The data collected is expected to aid both turbulence characterization as well as airborne turbulence detection algorithm development activities within NASA and the FAA. This paper presents a summary of the deployment and results of analysis and simulation which address important issues regarding the measurement requirements for accurate turbulent wind statistics extraction.

Hannon, Stephen M.↗
NASA NTRS1999

The Extraction of the NIRS Point Source Catalogs

The Near Infrared Spectrometer (NIRS) on the Infrared Telescope in Space, IRTS (a Japanese-US collaboration project), surveyed about 7% of the sky during its one month mission. In this work we extracted spectro-photometric point source (PS) data between 1.4 and 4 micron of high quality absolutely calibrated (2% flux uncertainties) and unbiased PS spectra in the near-IR. This database facilitates the study and understanding of a variety of science objectives, including stellar evolution of late type stars, determination of the Cosmic Infrared Background (CIB), and provides unprecedented faint stellar spectral calibrators. The objective of this work was to provide the community with a series of absolutely calibrated NIRS point source catalogs (PSC), with classification and association files. The catalogs will be archived at IRSA/IPAC.

Freund, Minoru M.↗
NASA NTRS2000

Information Theoretic Extraction of EEG Features for Monitoring Subject Attention

The goal of this project was to test the applicability of information theoretic learning (feasibility study) to develop new brain computer interfaces (BCI). The difficulty to BCI comes from several aspects: (1) the effective data collection of signals related to cognition; (2) the preprocessing of these signals to extract the relevant information; (3) the pattern recognition methodology to detect reliably the signals related to cognitive states. We only addressed the two last aspects in this research. We started by evaluating an information theoretic measure of distance (Bhattacharyya distance) for BCI performance with good predictive results. We also compared several features to detect the presence of event related desynchronization (ERD) and synchronization (ERS), and concluded that at least for now the bandpass filtering is the best compromise between simplicity and performance. Finally, we implemented several classifiers for temporal - pattern recognition. We found out that the performance of temporal classifiers is superior to static classifiers but not by much. We conclude by stating that the future of BCI should be found in alternate approaches to sense, collect and process the signals created by populations of neurons. Towards this goal, cross-disciplinary teams of neuroscientists and engineers should be funded to approach BCIs from a much more principled view point.

Principe, Jose C.↗
NASA NTRS2000

Automated Fluid Feature Extraction from Transient Simulations

In the past, feature extraction and identification were interesting concepts, but not required in understanding the physics of a steady flow field. This is because the results of the more traditional tools like iso-surfaces, cuts and streamlines, were more interactive and easily abstracted so they could be represented to the investigator. These tools worked and properly conveyed the collected information at the expense of a great deal of interaction. For unsteady flow-fields, the investigator does not have the luxury of spending time scanning only one 'snap-shot' of the simulation. Automated assistance is required in pointing out areas of potential interest contained within the flow. This must not require a heavy compute burden (the visualization should not significantly slow down the solution procedure for co-processing environments like pV3). And methods must be developed to abstract the feature and display it in a manner that physically makes sense.

Haimes, Robert↗
NASA NTRS2001

Characterization of the Heat Extraction Capability of a Compliant, Sliding, Thermal Interface for Use in a High Temperature, Vacuum, Microgravity Furnace

A compliant, thermal interface material is tested to evaluate its thermal behavior at elevated temperatures, in vacuum conditions, and under varying levels of compression. Preliminary results indicate that the thermal performance of this polymer fiber-based, felt-like material is sufficient to meet thermal extraction requirements for the Quench Module Insert, a Bridgman furnace for microgravity material science investigation. This paper discusses testing and modeling approaches employed, gives of a status of characterization activities and provides preliminary test results.

Bellomy-Ezell, Jenny↗
NASA NTRS1998

Feature Extraction of Event-Related Potentials Using Wavelets: An Application to Human Performance Monitoring

This report describes the development and evaluation of mathematical models for predicting human performance from discrete wavelet transforms (DWT) of event-related potentials (ERP) elicited by task-relevant stimuli. The DWT was compared to principal components analysis (PCA) for representation of ERPs in linear regression and neural network models developed to predict a composite measure of human signal detection performance. Linear regression models based on coefficients of the decimated DWT predicted signal detection performance with half as many f ree parameters as comparable models based on PCA scores. In addition, the DWT-based models were more resistant to model degradation due to over-fitting than PCA-based models. Feed-forward neural networks were trained using the backpropagation,-, algorithm to predict signal detection performance based on raw ERPs, PCA scores, or high-power coefficients of the DWT. Neural networks based on high-power DWT coefficients trained with fewer iterations, generalized to new data better, and were more resistant to overfitting than networks based on raw ERPs. Networks based on PCA scores did not generalize to new data as well as either the DWT network or the raw ERP network. The results show that wavelet expansions represent the ERP efficiently and extract behaviorally important features for use in linear regression or neural network models of human performance. The efficiency of the DWT is discussed in terms of its decorrelation and energy compaction properties. In addition, the DWT models provided evidence that a pattern of low-frequency activity (1 to 3.5 Hz) occurring at specific times and scalp locations is a reliable correlate of human signal detection performance.

Trejo, Leonard J.↗
NASA NTRS2003

Magnetogasdynamic Power Extraction and Flow Conditioning for a Gas Turbine

An extension of the Russian AJAX concept to a turbojet is being explored. This magnetohydrodynamic (MHD) energy bypass engine cycle incorporating conventional gas turbine technology has MHD flow conditioning at the inlet to electromagnetically extract part of the inlet air kinetic energy. The electrical power generated can be used for various on-board vehicle requirements including plasma flow control around the vehicle or it may be used for augmenting the expanding flow in the high speed nozzle by MHD forces to generate more thrust. In order to achieve this interaction, the air needs to be ionized by an external means even up to fairly high flight speeds, and the leading candidates may be classified as electrical discharge devices. The present kinetic modeling calculations suggest that the use of electron beams with characteristics close to the commercially available e-beam systems (electron energy approx. 60 keV, beam current approx. 0.2 mA/sq cm) to sustain ionization in intermediate pressure, low-temperature (P = 0.1 atm, T = 300 K) supersonic air flows allows considerable reduction of the flow kinetic energy (up to 10 to 20 percent in M = 3 flows). The calculations also suggest that this can be achieved at a reasonable electron beam efficiency (eta approx. 5), even if the e-beam window losses are taken into account. At these conditions, the exit NO and O atom concentrations due to e-beam initiated chemical reactions do not exceed 30 ppm. Increasing the beam current up to approx. 2 mA/sq cm, which corresponds to a maximum electrical conductivity of sigma(sub max) approx. 0.8 mho/m at the loading parameter of K = 0.5, would result in a much greater reduction of the flow kinetic energy (up to 30 to 40 percent). The MHD channel efficiency at these conditions would be greatly reduced (to eta approx. 1) due to increased electron recombination losses in the channel. At these conditions, partial energy conversion from kinetic energy to heat would result in a significant total pressure loss (P(sub 0)/P(sub 0i) approx. 0.3). The total pressure loss can be reduced operating at the loading parameter closer to unity, at the expense of the reduced electrical power output. Raising the beam current would also result in the increase of the exit O atom concentrations (up to 600 ppm) and NO (up to 150 ppm).

Adamovich, Igor V.↗
NASA NTRS2002

Software for Improved Extraction of Data From Tape Storage

A computer program has been written to replace the original software of Racal Storeplex Delta tape recorders, which are still used at Stennis Space Center but have been discontinued by the manufacturer. Whereas the original software could be activated by a command-line interface only, the present software offers the option of a command-line or graphical user interface. The present software also offers the option of batch-file operation (activation by a file that contains command lines for operations performed consecutively). The present software is also more reliable than was the original software: The original software was plagued by several deficiencies that made it difficult to execute, modify, and test. In addition, when using the original software to extract data that had been recorded within specified intervals of time, the resolution with which one could control starting and stopping times was no finer than about a second (or, in some cases, several seconds). In contrast, the present software is capable of controlling playback times to within 1/100 second of times specified by the user, assuming that the tape-recorder clock is accurate to within 1/100 second.

Cheng, Chiu-Fu↗
NASA NTRS2003

Extraction of Qualitative Features from Sensor Data Using Windowed Fourier Transform

In this paper, we use Matlab to model the health monitoring of a system through the information gathered from sensors. This implies assessment of the condition of the system components. Once a normal mode of operation is established any deviation from the normal behavior indicates a change. This change may be due to a malfunction of an element, a qualitative change, or a change due to a problem with another element in the network. For example, if one sensor indicates that the temperature in the tank has experienced a step change then a pressure sensor associated with the process in the tank should also experience a step change. The step up and step down as well as sensor disturbances are assumed to be exponential. An RC network is used to model the main process, which is step-up (charging), drift, and step-down (discharging). The sensor disturbances and spike are added while the system is in drift. The system is allowed to run for a period equal to three time constant of the main process before changes occur. Then each point of the signal is selected with a trailing data collected previously. Two trailing lengths of data are selected, one equal to two time constants of the main process and the other equal to two time constants of the sensor disturbance. Next, the DC is removed from each set of data and then the data are passed through a window followed by calculation of spectra for each set. In order to extract features the signal power, peak, and spectrum are plotted vs time. The results indicate distinct shapes corresponding to each process. The study is also carried out for a number of Gaussian distributed noisy cases.

Amini, Abolfazl M.↗
NASA NTRS2002

Software for Improved Extraction of Data From Tape Storage

A computer program has been written to replace the original software of Racal Storeplex Delta tape recorders, which are still used at Stennis Space Center but have been discontinued by the manufacturer. Whereas the original software could be activated by a command-line interface only, the present software offers the option of a command-line or graphical user interface. The present software also offers the option of batch-file operation (activation by a file that contains command lines for operations performed consecutively). The present software is also more reliable than was the original software: The original software was plagued by several deficiencies that made it difficult to execute, modify, and test. In addition, when using the original software to extract data that had been recorded within specified intervals of time, the resolution with which one could control starting and stopping times was no finer than about a second (or, in some cases, several seconds). In contrast, the present software is capable of controlling playback times to within 1/100 second of times specified by the user, assuming that the tape-recorder clock is accurate to within 1/100 second.

Cheng, Chiu-Fu↗
NASA NTRS2002

Evidence of Spin and Energy Extraction in a Galactic Black Hole Candidate: The XMM-NEWTON/EPIC SPECTRUM of XTE 11650-500

We observed the Galactic black hole candidate XTE J1650-500 early in its fall of 2001 outburst with the XMM-Newton European Photon Imaging pn Camera (EPIC-pn). The observed spectrum is consistent with the source having been in the very high state. We h d a broad, skewed Fe Kar emission line that suggests the primary in this system may be a Kerr black hole and that indicates a steep disk emissivity profile that is hard to explain in terms of a standard accretion disk model. These results are quantitatively and qualitatively similar to those from an XMM-Newton observation of the Seyfert galaxy MCG -6-30-15. The steep emissivity in MCG -6-30-15 may be explained by the extraction and dissipation of rotational energy from a black hole with nearly maximal angular momentum or from material in the plunging region via magnetic connections to the inner accretion disk. If this process is at work in both sources, an exotic but fundamental general relativistic prediction may be confirmed across a factor of l0(exp 6) in black hole mass. We discuss these results in terms of the accretion flow geometry in stellar-mass black holes and the variety of enigmatic phenomena often observed in the very high state.

Miller, J. M.↗
NASA NTRS1999

Feature extraction of event-related potentials using wavelets: an application to human performance monitoring

This report describes the development and evaluation of mathematical models for predicting human performance from discrete wavelet transforms (DWT) of event-related potentials (ERP) elicited by task-relevant stimuli. The DWT was compared to principal components analysis (PCA) for representation of ERPs in linear regression and neural network models developed to predict a composite measure of human signal detection performance. Linear regression models based on coefficients of the decimated DWT predicted signal detection performance with half as many free parameters as comparable models based on PCA scores. In addition, the DWT-based models were more resistant to model degradation due to over-fitting than PCA-based models. Feed-forward neural networks were trained using the backpropagation algorithm to predict signal detection performance based on raw ERPs, PCA scores, or high-power coefficients of the DWT. Neural networks based on high-power DWT coefficients trained with fewer iterations, generalized to new data better, and were more resistant to overfitting than networks based on raw ERPs. Networks based on PCA scores did not generalize to new data as well as either the DWT network or the raw ERP network. The results show that wavelet expansions represent the ERP efficiently and extract behaviorally important features for use in linear regression or neural network models of human performance. The efficiency of the DWT is discussed in terms of its decorrelation and energy compaction properties. In addition, the DWT models provided evidence that a pattern of low-frequency activity (1 to 3.5 Hz) occurring at specific times and scalp locations is a reliable correlate of human signal detection performance. Copyright 1999 Academic Press.

Evoked Potentials↗